(University of Peradeniya, 2017-10-12) Samaranayake, D. I. J.; Samaranayake, D. L. M.
Introduction
This study is done based on a developed actuarial model of Susceptible, Infected and Recovered (SIR) compartments, which describes the transfer dynamics in an insurance contract of a given population (Abramson, 2001). The SIR model created by Kermack and McKendrick (1927) set the mathematical and theoretical foundation for these epidemic models. Further research has been done to extended thresholds of these models using advanced analytical viewpoints (Mollison, 1995; Allen and Burgin, 2000; Kaddar et al., 2011; Bhattacharya et al., 2015).
The actuarial bases of epidemic disease spread are used with the intention of how to address the financial and economic possessions of such a venture. A book written by Slud (2001) provided imperative information of insurance and life annuity contracts. Feng (2005) developed an actuarial based model for epidemiology with the intention of building a bridge between epidemiology modeling and actuarial mathematics. His theory was utilized to design insurance contracts for the Great Plague in England and SARS epidemic in Hong Kong (Feng and Garrido, 2006). This was an imperative contribution made in literature of epidemic modeling which has open the gates of another testing ground for economic and financial analysts. In the context of Sri Lanka, few studies have been done for modeling the epidemic disease spread (Briët et al., 2008; Pathirana et al., 2009) and it is even more difficult to discover an analysis centered on actuarial based models. Hence, this study provides pioneering steps to the actuarial based model building for Sri Lankan epidemic profiles.
Objectives
While putting fore steps for the actuarial based modeling in relation to the epidemic disease spread in Sri Lanka, this study intends to revisit the theory by Feng (2005) and to obtain an expanded version of it based on SIR infection which describes the transfer dynamics in an insurance contract considering the highest total case recorded epidemics in Sri Lanka.
Methodology
A simple SIR model describes the conversion between sub-populations of susceptible, infectious and those who recovered. If recovery is permanent and recovered individuals are no longer susceptible to that pathogen then SIR model can be shown as follows,
β is the infecting rate for an individual per unit time and simultaneously α is the recovering rate from the diseases per unit time. SIRS model is more general than SIR model. The only difference when compared to SIR model is defining a new parameter called f which represents the rate of recovered individuals who are again susceptible per unit time due to the temporary recovery from the infectious disease.
Actuarial mathematics concepts are used to describe the financial transactions between two parties called insurer and insured.
Equivalence Principle:
E [Present value of benefits] = E[Present value of benefits premium]
For a continuous Whole Life Insurance Policy with a unit benefit the Level Premium Payment can be determined using equivalence principle as,
Where is the actuarial present value of future benefit payments and is the actuarial present value of future premium payments. An actuarial based model has developed for the epidemiological diseases and the following equations are given for the annuity for hospitalization plan which has defined by using the whole life insurance policy. When δ is the force of interest, γ is the rate of recovering of susceptible (s) and infectious (i) compartments at time t,
The total discounted future claim:
The total discounted future premium:
The force of infection:
The force of infection:
The level premium for the unit annuity for hospitalization plan:
MATLAB statistical software and recorded epidemiological data from the official website of Epidemiological Unit, Sri Lanka are used as the materials of this study. Data were collected weekly for 40 weeks period beginning from 26th December 2015 to 30th September 2016.
Results and Discussion
Sensitivity of Level Premium Payment with respect to the parameters
Determining the level premium payment with positive benefit reserve is mainly focused when the actuarial model is developed. According to the observation of this study, there is an effect from the parameters, γ and β to determine the level premium payment.
The rates taken at a monthly basis vary from 5-7 for infecting rate and 4-6 for recovering rate. Simulation shows a simultaneous decline in the recovery rate and increase in the infecting rate leaning the level premium rates towards zero. Premium rate reaches the highest possible level when a simultaneous increase in recovery rate and improvement in infecting rate occur. Therefore, independent as well as simultaneous changes in the rates of getting infected and recovery specify the characteristics of level premium payment to be considered for a hospitalization plan. Above results were obtained while developing MATLAB simulation for the actuarial based model for SIR infectious disease developed by Feng (2005) for SARS epidemic.
Adjusting Level Premium Payment
According to retrospective approach the individual benefit reserve at time and t for the annuity for hospitalization plan with unit benefit can be formulated as follows,
However to satisfy the requirement of positivity of the benefit reserve curve, for all t > 0
Feng (2005) has found out some results by setting up δ=0 and those results do not make sense of the time value of money. Since the complexity of solving equations without neglecting the force of interest, an algorithm is defined and developed a MATLAB program through this study to calculate the minimum adjusted level premium for the hospitalization plan to satisfy the above condition. This program could be used to calculate the level premium of diseases which has a permanent immunity with the absence of Vector-Host transfer dynamics. Otherwise it will not be adequate to obtain 100 percent accuracy in results. Henceforth, it is important to identify the nature and characteristics of Sri Lankan epidemic diseases to recognize the applicability of the program developed.
Feasibility of SIR model to represent epidemics in Sri Lanka
This analysis is based on only the top 10 epidemics which have the highest number of total recorded cases for the selected period. According to the data, highest recorded number of cases is Dengue and it is 72.65 % from the total top 10 epidemic cases. This implies that the probability of being infected by Dengue for a person is very high than the other diseases. However, there are considerable percentages for the diseases called Chickenpox (6.64%), Leptospirosis (5.44 %), Dysentery (4.83 %) and Typhus (3.29 %).
There are several patterns which can be seen when constructing time plots for the above 10 diseases. Some have clear seasonal patterns (Dengue fever). Also, some have very short-term fluctuations and it is difficult to determine the length of a season (Dysentery, Meningitis and etc.). Additionally, some diseases have declining patterns (Leptospirosis, Typhus and Leishmani). However, it is a huge area to study the reasons behind those patterns. Thus, this study is focused on developing an actuarial model for epidemiological diseases spread which can be used more generally to reduce the impact of several patterns. Dengue fever only contains a clear seasonal pattern based on the data for a 40-week period. APPENDIX provides further evidence on the seasonal behavior presence with dengue epidemic with a comparison of actual data with estimated measures for a given optimal lag length of 20 weeks for each season. Therefore, dengue fever has got expected seasonal features and it appears as a testing ground to practice feasibility of the insurance contract improved at the previous section of this study.
Actuarial Based Model for Dengue Fever Spread using SIR (Vector- Host) Model
There are some questions still to be addressed through further advancements of actuarial model considering long term effects such as Vector-Host transfer dynamics embedded with epidemic disease spread. According to the data it can be estimated the length of an epidemic season for some diseases such as dengue. But the SIR model defined by neglecting the type of disease which can be transferred by a vector. Dengue fever is the major epidemic disease in Sri Lanka which is generally spread by mosquitoes. Hence it is important to expand the SIR model by including the Vector-Host transfer dynamics to find out an actuarial model for diseases such as Dengue fever. Using the same procedure carried out to obtain Result in 4.2 it can be easily shown that,
and it yields to the level premium payment which formulated for the SIR infection model without the Vector-Host transfer dynamics being same here. Hence, it is reasonable to use the MATLAB program developed earlier through this study to calculate the minimum adjusted level premium for the hospitalization plan for Dengue fever.
Actuarial Model using SIRS Model
Moreover, other diseases have consisted of very short-term fluctuations and it is difficult to determine the length of the epidemic period. Also some people can be infected by the same disease more than once for the considered time period. On other hand, usually an insurance contract is drawn up for annum or a period of six months and it is rarely possible to adjust it with the epidemic season. Hence, the transformation within compartments for a long term can be described more generally using SIRS model than SIR model. But SIRS model is expressed using Delay Differential Equations and this study was not focused on simulating that model.
Conclusion and Policy Implications
This study is done based on a developed actuarial model of SIR infection which describes the transfer dynamics in an insurance contract in a given population. At the initial stage, we satisfied key assumptions and observed that the rate of infecting is positively related and the rate of recovering is negatively related to the level premium payment. Further, we developed a MATLAB program to calculate the minimum adjusted level premium for a hospitalization plan. Secondly this study obtained expanded models for the basic model to eliminate some problems which occurred such as the Vector-Host relationship due to unsatisfied assumptions for real data. It is reasonable to expand the SIR model by including Vector-Host transfer dynamics to find out an actuarial model for Dengue fever, as it can be estimated for the length of an epidemic season for Dengue for the sample period. Results show that there is no impact from Vector-Host to determine the level premium payment. Finally, we suggest the SIRS infection model with delayed differential equations as an appropriate solution which arises as a result of difficulties to identify seasonal patterns clearly for other diseases.
References
Bhattacharya, P., Paul, S., and Choudhury, K. S. (2015). Different Types of Epidemic Models and their Characteristic Behaviour by using Matlab. Journal of Interdisciplinary Mathematics, 18(5), p. 569-592.
Feng, R. H. (2005). Epidemiological models in actuarial mathematics (Doctoral dissertation, Concordia University).
Feng, R., and Garrido, J. (2006). Application of Epidemiological Models in Actuarial Mathematics. Soa. Org. 15(1), 1-29. Retrieved from http://www.soa.org/research/ARCH07v41n1_XIV.pdf.
Kermack, W. O., and McKendrick, A. G. (1927). A contribution to the mathematical theory of epidemics. In Proceedings of the Royal Society of London, Series A. 115(772), p. 700-721.
Slud, E. V. (2012). Actuarial mathematics and life-table statistics. Chapman and Hall/CRC.
Appendix
Time Series Plots for Epidemiological Data
(University of Peradeniya, 2017-10-12) Wanniarachchi, S. Minonshika
Introduction
Financial stability is an important component in the global economy and plays a key role in maximizing real economic gains. This proves the continuous efforts taken by the international regulatory bodies to minimize the adverse effects due to the economic and financial crisis in 2007/2008. The Bank for International Settlements – Central Banker’s Bank, located in Basel, Switzerland produced new set of banking regulations to avoid – at least minimize – the danger of another financial and economic crisis. The Basel Committee on Banking Supervision (BCBS) is an international financial regulatory body which was established in 1974 to structure the global banking risks by formulating guidelines and regulations relating to credit, capital, markets and operations. As an operational practice to overcome the effects of financial crisis, the Basel Committee collectively discussed and came up with a set of agreements. Its first accord issued in 1988 which named as Basel I and an updated version was published in 2004 as Basel II (Buddhipala, 2017). Basel III introduced in 2011 by reforming Basel II regulations to strengthen the global capital and liquidity rules with the goals of promoting more resilient banking sector. Capital adequacy, Liquidity Management, Risk Management and Market Discipline are the four major components that has been regulated in the Basel III. According to Bank of International Settlements, lack of quality and quantity of the capital base was one of the main influential factors for the financial crisis. This resulted, the credit losses come out from retained earnings (a part of bank’s tangible common equity base), inconsistency in the definition of capital across economies and lack of disclosure (Bank of International Settlements, 2016. Therefore, Basel Committee on Banking Supervision clearly defined the "Total Regulatory Capital" through Basel III accords as Tier one capital: Going-concern capital and Tier two capital: Gone- concern capital.
International regulatory bodies introduced a concept of "Systematically Important Banks" to regulate financial bodies effectively with more control, which represents a financial institution whose unmanageable failure, because of its size, complexity and systemic interconnectedness, would lead significant disruption to the wider financial and economic system. Domestic and Global are the two types of systematically important banks where the banks which are limited their operations within the originated country called domestic while the banks which provide a wide range of international coverage through branches defined as global. Existing researches recognized the impact of implementing Basel III in developed economies such as USA, Japan and European Union, but cannot be satisfied with the assessments carried out on local banking system. This research considered the domestic systematically important banks since the global systematically important banks carry out operations here are not originated in Sri Lanka.
Objectives
Assess the capital adequacy measurements of Basel III within the domestic systematically important banks and to identify the emerging challenges in implementing Basel III capital adequacy regulations when moving further.
Methodology
The capital adequacy ratio consists of three main ratios namely, Tier one capital ratio (Core capital ratio), Total capital ratio and Common equity ratio, defined as follows.
< equity ratio>
A comparative ratio analysis of six Domestic Systematically Important Banks (DSIBs) been conducted using the secondary data from the respective annual reports for the period of 2011-2016.All six DSIBs in Sri Lanka namely Bank of Ceylon, Peoples’ Bank, Sampath Bank, Commercial Bank, Hatton National Bank and Seylan Bank will be assessed in this empirical research. These six DSIBs represent 75 % of the commercial bank assets, 63 % of the banking sector assets and 36 % of the entire financial system’s assets(Central Bank of Sri Lanka, 2013).
Results and Discussion
The Central Bank of Sri Lanka divided the banking sector by assigning an asset threshold of LKR 500 billion to regulate the financial intermediary system in a sophisticated manner. Table 1 illustrates the set targets which should be met in given time frames in order to satisfy Basel III capital adequacy regulations.
(a) Tier one capital ratio is the proportion of tier one capital to risk weighted assets of the bank which has Basel III threshold of 4.5 % to 6 % at the end of 2016. As shown in figure 1, all six domestic systematically important banks in Sri Lanka are in satisfactory level when meeting the core capital requirements of Basel III. Two state banks managed to continue stable capital ratio while Seylan, Sampath and Hatton National banks report slight decline in their capital ratio over the considered time period. Commercial bank is maintaining fairly high and stable capital ratio comparing to its' competitors.
(b) Total Capital ratio, is the ratio between total capital base and the risk weighted assets of the bank which the minimum requirement of Basel III accords is 8 %. The total capital ratios of domestic systematically important banks in Sri Lanka are also reports a satisfactory level. Figure 2 illustrates the behavior of total capital ratios of considered DSIB’s and there we can clearly see The Hatton National Bank has sudden incline in capital ratio after three years of downturn by reporting 15.3 % in 2016.
(c) Common capital ratio provides the fraction between common capital to risk weighted assets, but most of the banks did not clearly differentiate common equity from core capital in their calculations which they publish in annual reports. Even all domestic systematically important banks pay their attention to clearly publish tier one capital ratio and total capital ratio, lack of data on common equity ratio created a challenge in this data analysis. Basel III accords require minimum 5 % common equity ratio without capital conservation buffer in 2016. This must be increased up to 8.5 % by domestic systematically important banks by 1st January 2019.
Conclusion and Policy Implications
As per the evidences drown from the research it can be conclude that all the domestic systematically important banks in Sri Lanka could manage to meet the international capital adequacy requirements drawn by Basel III accords, in terms of tier one (core) capital ratio and total capital ratio. Lack of proper disclosure created a challenge to assess the level of implementation on common equity ratio. In addition to the findings drawn from the analysis, prevailing literature emphasizes several challenges emerged with new Basel III accords. Increased capital and liquidity requirements may limit the options to raise additional tier one capital with small equity market in Sri Lanka (25 % of GDP) comparing to other Asian economies such as India (70 % of GDP) and Thailand (88 % of GDP). Another challenge may arise is uncommon usage of convertible structures to claim additional tier one capital in future stages in Basel III implementation. Further investments on IT infrastructure and on data architecture will be needed in terms of fulfilling disclosing requirements assigned by Basel III and the local financial regulatory bodies and commercial banks should pay attention on these challenges when moving further.
References
Bank for International Settlements, 2015. International Regulatory Framework for Banks (Basel III). [Online] Available at: http://www.bis.org/bcbs/basel3.htm [Accessed 3 February 2016].
Buddhipala, N., 2017. What You Need to Know about Basel III and Sri Lankan Banks. [Online] Available at: http://echelon.lk/home/what-you-need-to-know-about-basel-iii-and-sri-lankan-banks/ [Accessed 06 September 2017].
Central Bank of Sri Lanka, 2016. Capital Requirements under Basel III. [Online] [Accessed August 2017].
Fitch Rating Lanka Ltd., 2012. The Sri Lankan Banking Sector Special Report. [Online] Available at: http//:www.fitchratings.lk [Accessed 16 March 2016]
(University of Peradeniya, 2018-11-09) Herath, S.; Ranabahu, A.; Harvie, C.
Introduction
Micro, Small and Medium Enterprises (MSMEs) play a critical role in economic development in the Asia-Pacific region specifically in countries such as Vietnam, Indonesia, Sri Lanka and Cambodia (Nguyen and Wolfe, 2016). Usually, businesses with 1 to 249 employees are categorised as MSMEs (Kushnir et al., 2010). However, the size of MSMEs varies across countries (ibid) and, even within a country, there are variations in terms of business size, type and distribution of industries. For example, to be classified as an MSME in Sri Lanka, there should be 1 to 199 employees (industry and construction sector), 1 to 74 employees (services sector), or 1 to 34 employees (trade sector) (Department of Census and Statistics, 2015).
Apart from the size differences, MSMEs are also clustered into different areas. For example, in Sri Lanka, apparel-based enterprises are concentrated in Colombo (ibid) and jewellery-making businesses are clustered in the Central and Southwest districts (Dasanayaka and Sardana, 2015). In addition, there are differences in the availability of services across districts. For example, the number of licenced commercial bank branches and outlets varies across districts with the highest located in Colombo (900 outlets) and the lowest in Mullaitivu (29 outlets) (Central Bank of Sri Lanka, 2018). Similarly, access to infrastructure such as road network, public transport, telephone, electricity and internet facilities, and proximity to commodity and raw material markets vary across districts and these disparities may influence MSME performance.
Moreover, provincial councils in Sri Lanka have legislative power over a variety of matters including agriculture, education, health, housing, local government, planning, road transport and social services (Parliament Secretariat, 2015). Some of the central government laws also permit provincial amendments – for example, the law on co-operative societies states that the councils of nine provinces are entitled to enact their own statutes (GTZ ProMis & LMFPA-Lanka Microfinance Association, 2010). These result in legislative differences across provinces which could influence the operation of SMEs. To sum up, some of the MSME performance differences are location-based and issues affecting MSMEs according to the location can only be captured in research by using spatially representative samples.
Objectives
This abstract explains a survey sampling strategy developed for a research project to select manufacturing MSMEs that are representative of location- based performance variations. The project focuses on efficiency performance of Sri Lankan manufacturing MSMEs, ascertaining key explanatory factors contributing to this, emphasising financial and locational aspects. An innovative conceptual framework is applied to measure firm efficiency and its determinants through integrating firm, entrepreneur, business environment, cultural and locational characteristics. The empirical analysis utilises the latest empirical techniques to measure technical efficiency.
The sampling strategy is designed to achieve an inclusive sample of manufacturing MSMEs by considering distances from MSMEs to the capital city, province and district in which the MSMEs are located, and local business conditions measured via number of MSMEs in localities. The survey targets a stratified sample of 500 manufacturing MSMEs.
Methodology
Below, we discuss two different methods that were considered to achieve a spatially representative survey sample to capture the diversities in regional MSMEs. The stepwise process reflects Sri Lanka‘s administrative structure that includes provinces, districts, divisional secretariats, and Grama Niladari (GN) divisions (Figure 1).
The first step took into account provinces in which the firms are located as different provinces encapsulate the location in terms of proximity to the capital city Colombo. This is important not only because Colombo is the shipping hub of Sri Lanka but also it concentrates the best infrastructure and technology, and the largest commodity markets in the country. The latter is particularly important given that 99.8% of products produced by small firms and 83% by medium firms are sold within the country compared to only 44.5% domestic sales by large firms (World Bank, 2011). Hence, we included all nine provinces in our sampling strategy.
In the second step, we used Department of Census and Statistics data on non-agriculture establishments to develop two options to select districts:
1) Option 1: One district within each province was selected taking into account the ratio of manufacturing MSMEs. The aim here was to select a district that is closely synonymous with the ratio of manufacturing MSMEs of each province. This resulted in nine districts.
2) Option 2: Districts were classified into inner, middle and outer districts depending on their proximity to Colombo (<75 kms, 75< and <150 kms, >150 kms). Then, districts were ranked based on their population density and MSME density, and the districts with largest differences in terms of 'population density > MSME density‘ and 'population density < MSME density‘ were identified for each region (i.e. inner, middle and outer regions). The aim here was to select districts with different business environments (i.e. 'low population – high MSMEs‘ versus 'high population – low MSMEs‘). This resulted in six districts.
Then, we used the same ratio of manufacturing MSMEs to select the DS divisions. Approaches A and B ensure the business environments in those DSs represent the relevant district norms. As Fig. 1 illustrates, this sampling method generated four strategies to identify a representative sample. Finally, we considered practical aspects such as project timeline, budget and the availability of interviewers in finalising the DSs from which the MSMEs to be selected. Businesses registered with the DSs will be used as a guide to identify MSMEs.
Conclusion
The contribution of Micro, Small and Medium Enterprises (MSMEs) to the national economy is growing in many countries. These firms also provide livelihoods to many, particularly providing a springboard for upward mobility to those in low-income groups and in rural areas. Whilst MSME growth has been identified as a solution to growing inequalities in many regions, there are significant challenges that constrain the development of these firms. A number of them are of locational/spatial nature – e.g. access to finance, markets and suppliers, infrastructure, technology, business networks, support services, skilled labour, legislation relevant to businesses and competition. A spatially inclusive sample of MSMEs is required to examine these diverse issues. Drawing on a recent project on SME performance in Sri Lanka, this abstract presents a method to populate a sample of MSMEs representing diversities associated with proximity to the capital city, administrative regions and the local business environment. This sampling strategy emphasises that a spatially representative sample of MSMEs is crucial for investigating a wide-range of issues associated with those firms in urban and rural settings.
The expected outcomes of the project include an assessment of the key challenges for manufacturing MSMEs in Sri Lanka, identification of empirically grounded MSME development policy measures of economic and social benefit to Sri Lanka, regionally tailored MSME development strategies and general lessons benefiting MSME sectors in other regional economies. Capturing the locational/spatial disparities is particularly useful within a policy agenda that aims to achieve inclusive growth because MSMEs in remote and lagging regions may require additional support to improve their businesses. A wide range of policy instruments will need to be considered taking into account different challenges experienced in different areas to help promote spatial equity and inclusivity in the MSME sector. Once the locations of interest are identified for the survey, we relied on business registries held at divisional secretariats to obtain contact details of MSMEs. This is perhaps the only available dataset that provides relatively complete information about individual MSMEs. As a limitation of this research however this approach only captures the formal sector (i.e. registered MSMEs). Considering the relatively large informal sector in developing countries, future research should consider sampling methods that incorporate informal MSMEs.
References
Dasanayaka, S. W. S. B. and Sardana, G. D. (2015). Development of small and medium enterprises through clusters and networking: A comparative study of India, Pakistan and Sri Lanka International Journal in Economics and Business Administration, 3, 84-108.
Department of Census and Statistics.(2015). Non-agriculture economic activities in Sri Lanka - Economic census 2013/2014: Listing Phase. Colombo; Sri Lanka.
Kushnir, K., Mirmulstein, M. L. & Ramalho, R. (2010). Micro, Small, and Medium Enterprises Around the World: How Many Are There, and What Affects the Count? : World Bank / IFC.
Nguyen, S. & Wolfe, S. (2016). Determinants of successful access to bank loans by Vietnamese SMEs: New evidence from the Red River delta. Journal of Internet Banking and Commerce, 21, 1-23.
(University of Peradeniya, 2017-10-12) Nagarajah, N.; Ranasinghe, K.; Kavitharan, S.
Introduction
Climate change is happening and is felt deeply globally. Sri Lanka is already facing the adverse impacts of climate change in the form of droughts, unprecedented and rising temperature, floods, unseasonal rain, and coastal erosion. As a small island nation, Sri Lanka falls into the UNFCCC and IPCC's category of 'vulnerable' Small Island nations which are under serious threat from various climate change impacts, such as sea level rise and severe floods and droughts (Climate Change Secretariat, 2014). These threats are considered to have significant negative consequences on various sectors within Sri Lanka (Athukorala, 2015).
Sri Lanka is a negligible contributor to global warming. However, as a nation, we are highly vulnerable to the impacts of climate change. Sri Lanka has ratified the United Nations Framework Convention on Climate Change (UNFCC) in November 1993 and became a party to the Kyoto Protocol in 2002. The national Climate Change Policy of Sri Lanka aims to sensitize and make aware the communities periodically on the country’s vulnerability to climate change and to enhance knowledge on the multifaceted issues related to climate change in the society and build their capacity to make prudent choices in decision- making.
A number of research were done in Sri Lanka on the different causes of climate change. However, there is little literature to understand Sri Lankans’ awareness about climate change to determine if they act as responsive citizens to their share of emissions. According to Margaret Gardner, “in the next 55 years the greatest threat to Sri Lanka will be from climate change. Sri Lanka is particularly vulnerable to rising sea levels and weather-related disasters have the potential to set back any gains made in agriculture, fisheries and even services such as tourism” (Fernando, 2017). This paper helps to determine the success of using the environment valuation methods as a pragmatic approach to monitor the ‘nationally determined contributions’.
Objective
The objective of this paper is to understand people’s awareness on climate change and its impact, to investigate the relationship between household income and the level of awareness on climate change and to investigate the demand for climate change mitigation action by their willingness to pay to compensate their emissions and damages to the environment.
Methodology
The survey was done from May to June 2017 by gathering primary data using a semi-structured questionnaire in both local languages as well as an online survey. The respondents represented different age groups, gender, education status and income levels. 120 respondents from 15 districts consisted of farmers, government and non-government employees, school children, self-employed and unemployed. They are between the ages of 15 to 67. 87 % represent rural sector and 13 % represent urban sector. Also 55 % of the respondents are females. The secondary data on climate change was gathered from on-line sources.
Average imputation and common-point imputation are being used to fill the missing vital data. These methodologies analyses the association between categorical variables. Microsoft Excel and Minitab were used to obtain an accurate assessment of relationships, and possible contradictions found in the data by generating graphs, charts, cross tabulation and descriptive statistics. The contingent valuation method was applied in this study by asking the respondents for their Willingness to Pay (WTP) to offset their contribution to climate change and damages to the environment.
Results and Discussion
People’s awareness on climate change and its impact
In our sample 99 % of the respondents have stated that they are aware of the concept of climate change irrespective of gender, age, educational background, income level or their locality. Among those who are aware of climate change 41 % had come to know through media, 35 % have felt it and 14 % have heard it from other people. The survey indicate that 14.5 % respondents thought climate change was caused only by humans, while 9.6 % thought it happens naturally. 75 % of the respondents indicated that the cause for climate change is both by human and natural reasons.
When the respondents were asked to rate top three environmental issues; first rated issue was deforestation with 93 %, second highest was extreme weather conditions i.e. rains and droughts (82.5 %). Third rated with 75 % was water pollution. Findings also reveal how respondents conceptualize climate change; while majority of them interpret it as the rise in temperature and global warming, droughts, heavy rains, irregular rain patterns and floods, others interpret it as storms and strong winds, strange weather patterns, irregular climate, rise in sea water level, spread of diseases, Tsunami, disturbance to natural cycle, presence of Elnino and Lanino, failed agriculture and change in harvest patterns. While few relate it with melting of glaciers, depletion of Ozone layer and GHG emissions. Likewise, people’s beliefs about air pollution, factory / vehicle emissions, deforestation, and unplanned development are also again a way of anchoring climate change. The survey finding also indicated that the respondents are aware that the prevailing climatic conditions are impacts of climate change. Majority of the respondents felt that drought, floods and global warming are impacts of climate change; 36 %, 26 % and 25 % respectively.
The relationship between household income and the level of awareness on climate change
Results indicate there is no relationship between household income and the level of awareness on climate change (figure 1). Of those who are aware of climate change 28.3 % are very low, 28.3 % are middle, 24 % are average and 7.5 % are upper class income earners. 93 % of people agree that climate change is a common problem for everyone. Again, their income level and answers do not show any relationship. However, 39 % involved in farming strongly agree that climate change to be a common issue.
When judgments of other issues are solicited, climate change is invariably not the highest or most important priority for many people. Only 17 % of the respondents believed that environment was a pressing issue in Sri Lanka. Environmental problems were rated seventh place of ten other current problems given. Understanding people’s perceptions as contributors for the climate change is an important indicator of awareness. It is evidence that 90 % of people believe they contribute to climate change in some way. Of the respondents, 48 % are females and 48 % are involved in farming. Comparing it with the level of income, 28 % of very low-income holders, 20.8 % of average and 23 % of middle income earners believed that they are contributing to the climate change (figure 2). Neither gender, age, education nor income level or if farmer or not suggest a correlation.
The demand for climate change mitigation action by their willingness to pay to compensate the damage caused by them to the environment.
The respondents were introduced to a hypothetical fund called ‘Green Future’ which will be exclusively used for tree planting to compensate for the anthropogenic effects. The respondents were asked for their WTP for the fund and if they were willing, the maximum amount they can contribute annually. Further, 78 % of the respondents were willing to pay for the green future fund and out of them 42.5 % were females and 40.8 % were advanced level students and 15 % of them were graduates. The youth are sensitive to the climate change and proactive to make an action. A correlation cannot be observed between income level and peoples’ WTP. Approximately 22 % of those who were not willing to pay, stated their reason as their income being low or them willing to spend the money on other things. Further, 83 respondents stated a maximum amount they are willing to contribute annually to offset their emissions and harm to the environment. The amount ranged between Rs. 50 to Rs. 12,000. Out of those who are willing to pay and who earn more than Rs. 1,000.00 monthly income; people are willing to contribute 0.69 % (on an average) of their monthly income for the ‘Green Future’ program. Their average annual contribution in rupees amounts to Rs. 2,154.
Conclusion and Policy Implications
Sri Lankan’s awareness on climate change is in satisfactorily high level. Media is the main source people had come to know about climate change. The way people have described climate change varied from bringing out real-time examples, to attempts for text-book definitions. Placed among other problems country currently faces, their ranking for the environment as a topic was towards the lower side.
There is no relationship between Sri Lankan’s awareness level on climate change and their income. The conclusion holds still with the farmers and non-farmers responses. 78 % of the respondents were willing to pay for a hypothetical fund that will be used for replanting trees. Of the people who are able to pay, and have suggested an amount, it is about 0.69 % of their monthly income and annually it will amount to Rs. 2,154.41. Despite high awareness level, when it comes to action, the youth are keen to express climate change and even ready to take action. As a recommendation, the respondents suggest that Sri Lankans have to change the lifestyles to reduce energy consumption in order to address climate change.
References
Athukorala, W. (2015). Education, Attitudes and Agricultural Biodiversity: An Application of Randomised Control Method. Sri Lanka Journal of Economic Research, 3(1): 115-132.
Climate Change Secretariat - Ministry of Environment and Renewable Energy, Sri Lanka. 2014. Technology Needs Assessment and Technology Action Plans for Climate Change Adaptation.
Ministry of Environment Sri Lanka. 2010. National Climate Change Adaptation Strategy for Sri Lanka 2011 – 2016.
United Nations. 1992. United Nations Framework Convention on Climate Change.
Fernando L. 2017. Sri Lankan Guardian. Why so much of flooding and natural disasters? [online] Available at: https://www.slguardian.org/2017/06/why-so-much-of-flooding-and-natural-disasters/ [Accessed 02 July 2017]
(University of Peradeniya, 2017-10-12) Dissanayake, D. M. D. K.; Dorabawila, S. S. K. B. M
Introduction
The employees of every country can be identified as formal sector and informal sector employees. In most of the developing countries’ the predominant sector is the informal sector. Sri Lankan national definition of the informal sector states that an institute is informal if there is no registration of the institute under the employees’ provident fund and/or Inland Revenue Department, no formal accounts maintained and the number of regular employees less than 10 (DCS, 2017). Employees of the informal sector have to face many difficulties. Currently, there is no formal mechanism established for the informal sector pay and benefits schemes in Sri Lanka.
Aruntilaka (2004) states that the market forces decide that wages of the informal sector of Sri Lanka. A study by Gunatilaka (2008) shows that the ability to earn in this sector can change according to the area of employment. These statements confirm the research by Saget in 2006on wage in the informal economy in Brazil, India, Indonesia and South Africa for Sri Lanka as well. According to Banerjee (2014) the wages of the informal sector should be decided through the trade liberalization policies. Cho and Cho (2011) deduce that the gender wage gap of the informal sector as the worst.
Objectives
This research examines the functionality of the existing informal structures used in determining informal sector wages in Sri Lanka and compares the available structures with the existing systems in other countries. Based on the above country comparison results, this study proposes essential factors to be incorporated in determining a methodology for a fair wage for daily informal sector workers, acceptable for Sri Lanka.
Methodology
This study is based on primary data and secondary data. A total sample of 108 employees and employers were selected from the informal sector from Anuradhapura and Mullaitivu districts by using multistage sampling in 2016. Sample consisted of 54 employers and 54 employees with a representation from agricultural (36), industry (36) and service (36) sectors. Two separate questionnaires were administered among employers and employees to collect the primary data and the secondary data were collected from publish documents from several institutions. For the data analysis, descriptive method and multiple regression estimation were used.
Results and Discussion
According to the National Minimum Wages Act No. 3 of 2016, for the first time in the country, a mandatory national minimum daily wage of Rs. 400 was fixed payable to all workers by all employers in the country. The daily wages between the two districts differ by sector and gender (given in figure 1.1). In the agricultural sector the daily wage in Anuradhapura is 49 % higher than Mullaitivu. The average overall daily wage is 191 % higher than national minimum daily wage of 2016. Lowest average female daily wage (Rs. 833) is also 9 7% higher. There is a considerable variation by district compared to the national minimum daily wage.
A multiple regression model was used to determine the factors that affect the daily wage of the employee. Five separate regression models were estimated for the surveyed data (One for each district, Employees, Employers and overall sample- given in Table 1). According to overall sample regression results, districts, gender, labor supply demand, wage of nearby areas, hours of work, experience, service sector and agriculture sector had a statistically significant impact in determining informal sector wages. Besides that, for Anuradhapura district number of working hours, experience, wage of nearby areas, labor supply and demand, gender and additional benefits determine the wages of the informal sector. For Mullaitivu, wage of the nearby areas, labor supply and demand, gender and service sector had an impact on a workers’ daily payment. Among the variables significant for Mullaitivu, only service sector variable was not among the significant variables for Anuradhapura district. According to regression results of this study, different factors influence the daily wage levels in each district. The level of education and age of the employee had no impact on wage in the informal sector employment.
This research studied informal sector wage determination structures of several countries in the world (Brazil, India, Indonesia and South Africa). The study found that the countries use different criteria to determine the level of informal sector daily wage. These countries had used criteria such as occupation, power to form groups, collective agreements and social security benefits. In most of the countries, the informal sector wage is determined based on various characteristics of the locality such as the districts and states. Furthermore, some labor regulations, such as the minimum wage in Sri Lanka are applicable to formal as well as the informal sector jobs. However, since there is no contractual binding (This can have positive impact on the salary and the other benefits of informal sector worker.) between the employers and employees in the informal sector, there is no mechanism to go for litigation. And also this study found informal sector employees can be divided mainly into two categories as casual workers and seasonal workers. The employers and employees lack knowledge on the wages and other benefits.
Conclusion and Policy Implications
This study identifies a set of essential factors to be considered in determining the informal sector minimum daily wage for informal sector worker in Sri Lanka. Policy makers must take into account the following factors such as district/state of the employment, industry of employment, wage of nearby areas, labor supply and demand and gender in determining the informal sector wage. Based on these identified, influencing factors, the government can introduce a mechanism to determine the informal sector wage, new saving systems, insurances, pension systems for informal sector. The employers and employees must be well-informed about their expected daily wage and other benefits. There are some labor regulations that are formally constituted, equally for both the formal and informal sector jobs. However, when implemented there are areas that require policy makers’ attention to rectify possible short-comings that can impede the benefits to the informal sector workers.
References
Gunathilaka, R. 2008. Informal Employment in Sri Lanka: Nature , Probability of Employment and Determinants of Wage. http://www.researchgate.net
Hohberg, M. and Lay, J. 2015. The Impact of Minimum Wages on Informal and Formal Labour Market Outcomes : Evidence form Indonesia. IZA Journal of Labor & Development, 4:14
Labour Force Survey-Department of Census and Statistics. 2017. http://www.statistics.gov.lk
Saget, C. 2006. Wage Fixing in the informal economy: Evidence from Brazil, India, Indonesia and South Africa. Conditions of Work and Employment Series No. 16
(University of Peradeniya, 2017-10-12) Chandrasiri, K. A. D. S.
Introduction
Dengue is a vector borne arbo viral disease and it is transmitted by two mosquito species namely Aedes aegyptii and Aedes albopictus. Dengue virus is named as DENV and it belongs to the genus flavivirus in family flaviviridae. It has 4 antigenically different serotypes, DENV1, DENV2, DENV3, and DENV4. Infection with a single DENV serotype leads to long-term immunity against that particular serotype, however, not against the other serotypes. Therefore, prior infection with a single serotype of DENV only provides a homotypic protection (Sirisena 2013).
All serotypes of DENV have been seen in Sri Lanka for more than five decades and their distribution has not changed significantly in the last 30 years. Although the Sri Lankan population had been exposed to DENV for a long time, the severe forms of DENV infection (DHF and dengue shock syndrome (DSS)) were very rare before 1989. There was an island-wide epidemic of DF associated with DENV serotypes 1 and 2 from 1965 to 1968. This epidemic caused 51 DHF cases and 15 deaths.5 DENV-1 and DENV-2 were isolated from the outbreaks in 1965 and 1966 (Sirisena 2013).
The disease is seen in tropical countries and the burden of disease has increased by 30-fold over the past 50 years (Ebi 2016). By 2017, this is the most concerned public health issue in Sri Lanka. The reported numbers of cases have increased gradually and the increment is 840.5 % since 2002 through 2016. There are various numbers of reasons for this including urbanization, climate change, and poor waste management. 57 years have passed since Sri Lanka started to experience Dengue but 2017 is the year that recorded the highest numbers of patients and it’s only for 6 months.
Numbers of studies have already been undertaken to investigate the various aspects of the link between climate change and the spread of dengue fever in different countries Rigau-Perez et al. (1998) observed that high humidity is favorable for increased dengue disease transmission, hatching and activities of mosquito vectors. According to findings of Tun - Lin et al. (2000) development rates of Aedes aegpti eggs, larvae, pupae, increased with increased temperature. Their findings are similar to observations of Rueda et al. (1990). Cyclical nature and seasonal increase of dengue disease was studied Reiter (2001) and he found a condition between climatic changes and disease occurrence. It is clear that dengue transmission is influenced by several factors related to households, individual and environmental. Similar findings were made by Hoeck et al. (2003) who observed that monsoon rains in neighborhood areas increased the population of mosquitoes. According to Sukri et al. (2003) as well as Wilder - Smith and Gubler (2008) ideal conditions for dengue fever transmission were stated to be enhanced by high population density of both humans and mosquitoes. While Siqueira-Junior et al. (2008) reported that spatial distribution of dengue cases depended on the community status of individuals, additional factors such as demographic density, population motility and sanitation contributed to the spread of mosquitoes and dengue incidence.
The above review of the previous studies shows that these studies have only provided limited information on the disease pattern. Accordingly, it is obvious that more conceptual and theoretical work is needed to develop a better understanding of this field.
Objectives
The objective of this study is to analyze the seasonal pattern of Dengue in Sri Lanka. There are numbers of diseases which show seasonal pattern ranging from childhood diseases such as measles, chicken pox and faeco-oral infections to vector-borne diseases such as Leptospirosis and Dengue (Grassly et al. 2006). Only a few numbers of research papers could be found on this subject. Therefore, it is important to study the epidemiological dynamics of a disease in terms of planning control strategies.
Methodology
Nationally accepted data on reported dengue cases and population were used as secondary data in this study. As far as the data on Dengue reported cases are concerned, monthly as well as biweekly reported numbers were used and they were categorized based on districts and MOH (Medical Officer of Health) areas. The data were analyzed using Excel to evaluate the spatial distribution and the relationship with population variables. Various charts and graphs are used to describe the relationships between variables as well as the disease prevalence across the year and districts.
This study used two type of data. They are reported dengue cases and population data. The data on reported dengue cases used in this article were retrieved from the information published by the Epidemiology unit of Sri Lanka ministry of health. Those are freely available in their official website(www.epid.gov.lk). Population data which are used while preparing this article were taken from the official website of the Department of census and statistics of Sri Lanka (www.statistics.gov.lk). The data on reported dengue cases from January 2002 to June 2017 were used to analyse of this study.
Results and Discussion
Dengue fever is an infectious tropical disease caused by the denguevirus and it is transmitted by several species of mosquito that breed under different climate situations(Athukorala, 2016). Infection with a different type increases the risk and there is no available vaccine, to prevention reducing the habitat and the number of mosquitoes and limiting exposure to bites. According to the WHO report (2012) approximately 2.5 billion people, two fifths of the world's population is now at risk from dengue and estimates that there may be 50 million cases of dengue infection worldwide every year. The disease is now endemic in more than 100 countries.
As far as the reported dengue cases since 2002 in Sri Lanka are concerned, it is noteworthy that there is an increasing trend over the time. There were 8,931 cases in 2002 and it was increased up to 55,150 by 2016. The difference is 46,219 and it was 517.5 % increment. More steep increment is observed in 2009 and it was 35,095 cases island’s cumulative. The dengue cases were increased by 20,055 and the increment is 57.14 % from 2009 to 2016. More intensive increment can be observed from 2009 to 2016 and more in 2017 making cumulative cases 83,997 only till June.
There is distinctive pattern of dengue disease throughout the year. This is generally equal in almost every year. There are two dengue case peaks in a year while no zero case months. One peak is in June/ July while other peak is in December/ January. This characteristic “W" pattern is evidenced in every year from 2012 and this is clearly seen in monthly average of dengue cases in Sri Lanka. The height of the peaks is becoming increased over the years. Usually the middle year peak is higher than the early/end year peak but this pattern was differed in 2013 and 2015 making the early/end year peak higher. There is a slight difference of peak month between months in district level case analysis. But the general pattern can be observed in almost all districts.
The cause for this phenomenon might include several factors includingclimate change and the virulence of the causative agent. More researches are needed to solve this problem. There is a strong relationship between cumulative dengue cases and population density in district level analysis. Every year, Colombo district records the highest numbers of cases and it has a population density of 3330 people’s per km² in 2001 census which is the highest of the island. Interestingly this trend can be observed in every district.
Conclusion and Policy Implications
Dengue represented a significant economic burden on the communities. It can result in loss of lives, considerable expenses to the family for the hospitalization and care of the patient, in addition to travel costs, loss of work among patients and their career, considerable expenses to ministry of health and local government authorities for mosquito control activities and disruption of health care services and economics, including loss of tourism revenue. Government in Sri Lanka allocate over Rs. 300 million as the direct cost of control measures for dengue in each year.
Dengue has a distinctive disease pattern over the time. This is similar in almost every year. Characteristic “ W “ pattern is observed with two peaks. There is a strong relationship between dengue numbers of cases and population density in district level. Reason for these characteristics should be analyzed furthermore and more research are needed.According to the result of this study it is clear that the selection of high risk areas for dengue transmission should be based on population density rather than the reported numbers of cases. A threshold value should be assigned in terms of risk area selection and it will be helpful in dengue prevention programs. The threshold values can be decided up to Divisional secretariat level and it needs more expertise researches.
A study of this nature helps develop a program for changing peoples’ behavior with the changes of climate in any country while minimizing the social cost of climate change. The overall findings of this research will help implement policies to reduce spread of dengue related diseases that is increasingly posing a major challenge in the health sector in the country. The results of the study will provide an opportunity to make necessary policies that provide incentives to reduce of spreading dengue related diseases at the household and district level which generate regional as well as global benefits in the future.
References
Athukorala, W. 2016. Estimating the health cost of climatic change related diseases: A case of Dengue in Sri Lanka. Unpublished Report. Department of Economics and Statistics, University of Peradeniya.
Alberini, A. and A. Krupnick . 1998. Air Quality and Episodes of Acute Respiratory Illness in Taiwan Cities: Evidence from Survey Data. Journal of Urban Economics, 44(1): 68-92.
Hopp, M.J. and Foley, J.A. 2001.Global – scale relationships between climate and the dengue fever vector, Aedes aegypti. Climate Change, 48,441-463.
Lowe. R., Bailey, T.C., Stephenson, D.B., Graham. R., Coelho, C.A.S., Carvalho, M. and Barcellos. C. 2011. Spatio-temporal modeling of climate-sensitive disease risk: towards an early warning system for dengue in Brazil. Computers and Geosciences 37, 371–381.
(University of Peradeniya, 2018-11-09) Vinayagathasan, T.; Ramesh, R.
Introduction
A substantial amount of literature shows that higher levels of education and literacy are more likely to decrease corruption, and such literature clearly establishes the relationship between education and corruption from a global perspective (Charron and Rothstein, 2016; Truex, 2011; Anduiza et al. 2013; Caillier 2010). Though Sri Lanka has a high rate of literacy and participation in school education, there is still a high degree of corruption in public and political institutions (Transparency International -TI, 2014, 2016; Trust Survey Report, 2015). Thus, the research problem is: ―Why does education have a positive impact on decreasing corruption in some countries, not in others, in this case Sri Lanka? Against this backdrop, this paper seeks to explain why the level of education seems to have a low level of impact in decreasing corruption in Sri Lanka using TI data over of the period of 1996 to 2016.
Our argument and the contribution of this paper is that, at the individual level, education can only have a positive effect on corruption when institutional quality is sufficiently high (anti-corruption bodies, law enforcement agencies, courts, other public institutions) and they uphold the key principles of quality of government such as impartiality, fairness, rule of law and effectiveness. Otherwise, the effect of education on corruption becomes negligible. This calls into question the view that simply increasing the years of schooling and literacy and time spent in school are less likely to have a positive impact on decreasing corruption.
There is enough evidence to believe from the Northern European countries along with Singapore, Hong Kong, New Zealand and Australia that the higher the level of education, the lower the level of corruption. Some empirical studies demonstrate that more educated people show less accepting attitudes across the range of corrupt behaviors (Truex, 2011). The evidence from Nepal shows that more educated Nepalese are generally less accepting of corrupt behavior (Truex, 2011). Further, it has been argued that better educated citizens are more likely to complain to government authorities about the misconduct of officials which helps increase the quality of government operations and reduces corruption which in turn has a positive effect on social trust (Charron and Rothstein, 2016:60).
Objective
Based on the above empirical and theoretical evidence, we pose a simple question in this paper: ―How far and to what extent does the level of education impact on decreasing corruption, and how do educated, well- informed and critical citizens react to a political system with low-quality institutions, a system with high levels of corruption?
Methodology
This study employs annual data of Sri Lanka over the period 1996 2016. The variables and corruption equation in this paper is in the spirit of Asongu (2012) and the equation is given below:
where, education index2, set of other regressors such as GDP growth rate (GDPGR), consumer price index , trade openness , regulatory quality and rule of law , : corruption perception index3, and white noise error term. As found in existing studies on corruption, we control for economic prosperity (in terms of GDPGR), trade openness and inflation. Data for CPI is collected from the Transparency International database; GDPGR, OPEN and INF were extracted from the World Bank‘s World Development Indicator database, whereas ROL and RQ were obtained from the World Governance Indicator database.
Auto Regressive Distributed Lag (ARDL) co-integration bound testing procedure developed by Pesaran et al. (2001) was employed to investigate the equation (1). Once we confirmed the co-integrating relationship between the variables via bound testing technique, then we adapted error correction version of the ARDL model to examine the short run relationship and long run adjustment between the variables. ADF and PP unit root test methods were used to test the order of integration of variables. Akaike Information Criterion (AIC) was adapted to determine the optimal lag length of each series.
Results and Discussion
Both ADF and PP unit root test technique confirmed that GDPGR is I(0) while all other variables are I(1). AIC advocated the use of ARDL (1, 1, 0, 1, 1, 1, 1) model to estimate the parameter. Bound testing approach confirmed that there is a co-integrating relationship between the variables since we reject the null hypothesis of no cointegration as test statistics are greater than critical value at 5% level of Significance (See the Table 1 below).
Since we confirmed the cointegrating relationship between the variables through the Bounds test, we then estimated the long run relationship among the variables via the ARDL model, and the results are given in Table 2 below.
According to the results EDUI has a significant and positive impact on corruption, which implies that, in the case of Sri Lanka, when the level of education increases, it is more likely to increase the CPI, which is the indication for decreasing corruption. As expected by theory and most of the existing empirical studies (e.g., Charron and Rothstein, 2016; Truex, 2011; Anduiza et al. 2013; Caillier 2010), this finding demonstrates that a higher level of education helps to control corruption in Sri Lanka. Similarly, as theory and some of the existing empirical studies indicate, GDPGR tends to mitigate corruption in the long run (e.g., Asongu and Jellal, 2013; Asongu, 2013a, Asongu, 2013b). This study also indicates that although strict ROL principles are less likely to help reduce corruption, it is also evident that if the government upholds high quality in institutional regulation (RQ) it enables the government to control corruption. This shows that controlling corruption is closely linked with efficient and effective regulation of public institutions adhering to quality of government principles in which ROL plays a significant role. The message is very clear, that is, in developing countries, low regulatory quality opens up avenues for various forms of corruption and malpractices in public institutions than that of ROL.
However, inflation and trade openness do not have a statistically significant impact in decreasing corruption in the long run. Moreover, the selected ARDL model passes all the diagnostic testing such as normality of the error term, no heteroscedasticity, no serial correlation and no omitted variable(s) and also CUSUM test confirmed the stability of the selected model.
According to Table 3, as in theory and some of the existing empirical studies, EDUI, GDPGR, INF and RQ have a positive impact on CPI in the short run. That is, an increase in the level of education, GDP growth rate, inflation and high regulatory quality, are more likely to increase the corruption perception index which is the signal for low level of corruption. However, this impact is not statistically significant. Even though, ROL and OPEN affect the CPI negatively, the effect is not statistically significant. This could be because, when we take some measures to control corruption, it takes substantial time to provide results, and therefore, these regressors may not have a significant impact in controlling corruption in the short run.
Conclusion
The selected ARDL model passes the diagnostic test and the stability test. The results of the Wald test imply that there exists a co-integrating relationship between the variables under considered in this study. Thus, the higher the level of education, the more it supports fighting against corruption in the long run, but not in the short run. GDPGR and RQ appear supportive in controlling corruption in the long run whereas GDPGR and RQ do not have a significant impact on corruption in the short run even though they are positively correlated with CPI as expected. OPEN and INF do not affect CPI significantly both in the long and short run. These findings imply the significance of maintaining high quality in regulating public institutions inline with the quality of government principles such as impartiality, fairness,rule of law and effectiveness. Further, it suggests the necessity of institutional reforms to ensure institutional quality at all levels, which is a precondition to decrease corruption, as the evidence shows in the case of less corrupt or non-corrupt countries. Further, this study addresses policy makers on how education and corruption are interrelated, and thereby advocates relevant policies and programs to control corruption through the educational system in the long run.
References
Asongu, S. A., (2012). On the effect of foreign aid on corruption, Economics Bulletin, 32(3): 2174-2180.
Asongu, S. A., and Jellal, M., (2013).On the channels of foreign aid to corruption, Economics Bulletin, 33(3): 2191-2201.
Asongu, S.A, and Nwachuku, J. C., (2016).The Role of Lifelong Learning in Political Stability and Non-violence: Evidence from Africa, Journal of Economic Studies: Forthcoming.
Lalountas, D.A., Manolas, G.A., and Vavouras, I.S. (2011). Corruption, globalization and development: How are these three phenomena related? Journal of Policy Modeling, 33: 636-648.
Pesaran, M. H, Shin, Y & Smith, R. (2001).Bound testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16, 289-326.
Truex, R. (2010). Corruption, attitudes, and education.survey evidence from Nepal. World Development, 39(7): 1133-1142.
(University of Peradeniya, 2018-11-09) Prasanna, R. P. I. R.; Ranathilaka, M. B.
Introduction
In the early 1980s, the IMF and the World Bank advocated that the government of Sri Lanka undertake market-oriented policy reforms in the economy, including in the agricultural sector, under the Structural Adjustment Program (SAP). The main argument made was that government operations in agricultural marketing (input and output markets) are not effective and efficient, and do not promote the interests of farmers and consumers. Farmers in Sri Lanka's main paddy producing areas complain of difficulties in selling their paddy harvest due to failures in the government paddy purchasing mechanism. Through the market-oriented policy reforms in agriculture, it was expected to increase market competition and thereby increase producer prices (producer welfare) and stimulate agricultural growth and income. With this policy reform, the significance of the Paddy Marketing Board (PMB) and Multi-Purpose Cooperative Societies (MPCS) in paddy marketing was reduced due to the competition from the private sector (Prasanna, 2006). For example, during the 1980s, the open market price of paddy exceeded the guaranteed price, rendering the government paddy purchasing institutions as financially unviable (Weerahewa, 2004).
The studies cited numerous reasons for the widening gap between producer price and consumer price, and thereby poor earnings from paddy farming. Among these reasons, the oligopolistic nature of traders and smaller involvement of the government sector in paddy marketing activities are the decisive reasons (Prasanna, 2006). Hence, today, paddy farming has become an economically unviable sector, leading to indebtedness among the farmers (Irshard & Thiruchelvam, 2006), and the government has to spend more on subsidy programs and other supportive programs to protect the paddy sector due to its importance concerning national food security; it provides approximately 50% of the daily calorie intake of households with 45% of per capita protein requirements, and livelihoods of many farmers. At present, from over 1.8 million paddy farmers, the majority of small-scale farmers own less than 1 ha. of land and are primarily dependent on rice farming. In this context, it is questionable whether the nature of the paddy market structure is a matter of poor earnings of paddy farming.
Objectives
The main objective of this paper is to study the nature of the problem of poor earnings of paddy farming, paying particular attention to the paddy marketing channel in the major colonization schemes in Sri Lanka. The study will focus on the following points: 1) Analysis of cost and income of paddy farming, 2) Examination of the nature of the paddy marketing channel, 3) Analysis of the effects of the existing paddy marketing structure on farmers‘ production and marketing conditions, and 4) Suggesting ways to correct paddy marketing problems by empirically conceptualizing the paddy marketing problems, solutions, and challenges.
Methodology
In order to deal with the research subject, data for analysis was drawn from two field surveys—farmer survey and survey on traders in paddy marketing channel—in the Huruluwewa Major Colonization Scheme (HMCS) area in January / February 2018. The HMCS was selected for the study as it is one of the main paddy producing areas of the North Central Province in Sri Lanka. A pre-tested, semi-structured questionnaire was employed in each survey to gather data on the socioeconomic background of paddy farmers, paddy production, characteristics of paddy marketing channel, and nature and functions of participants in paddy marketing channel. One hundred and ten (110) farmers in the right-bank and left-bank of the HMCS were selected for the study by giving equal probability to all farm households in sampling. In addition, 20 traders in the paddy marketing channel, officers in the government paddy purchasing centers in the area, and leaders of farmer organizations were interviewed to gather data on the paddy marketing channel in the area. The collected data were analyzed using a descriptive statistical method.
Results and Discussion
The analysis of average cost and income of paddy farming in the survey area shows that farmers earn a net income of Rs. 12,989 per acre by spending Rs. 42,575. As the average farm size in the area is 1.8 acres, the total net income of average farmers in the scheme is Rs. 23,380. Mean Selling Price of paddy in the concerned season of the study was Rs. 39 and only 47 farmers could sell their produce at the above mean price. However, the distribution of farmers‘ net income revealed that 37 (33.6%) farmers did not receive the deserved positive net income. Moreover, the study identified a positive relationship between farm productivity and per acre normalized profit. The results further designate a negative relationship between farm size and paddy productivity, indicating declining farm productivity when farmers increase the land scale of farming. This finding contradicts with other studies that encourage farmers to increase the land scale to get economies of scale. The possible reasons explained by the farmers for the negative relationship between farm size and productivity are water management issues at the field level frequently faced by the farmers due to drought, and the problems of irrigation water management by the Irrigation Department at the scheme, and the prevailing labor shortage.
Several village-level collectors were reported in one village. The capacity of storage facilities of interviewed collectors at the village level varied from 11,000 kg to 200,000 kg. Most of them had zero transportation cost because usually, the farmers transport their harvest from farm to assembler's place. Most collectors had their own small stores, and some had concrete compounds for drying the wet paddy. However, the collectors do not hold the collected paddy for a long time, and 80 percent of them kept 50 cents from each kilogram as their profit. They usually find the capital for buying paddy by their own capital or savings, pawning jewelry or registration certificates of their vehicles and obtaining a short-term loan from the banks.
The main feature of the channel is the hierarchical relationship between participants in the marketing channel based on the market. It shows that the paddy market in the area is dominated by a few large-scale traders directly via their agents, who find the required paddy procurement finance from large-scale traders and indirectly through village-level assemblers. At the village level, 67% and 15% of farmer products are channeled through village-level collectors and agents of large-scale traders, and a proportion of 80% and 100% of assembled products are then shipped to large-scale traders by the village level collectors and agents of large-scale traders respectively. The government purchasing mechanism has only purchased 7% of production in the area, from which, 80% have been directed to the large- scale traders, particularly during off-season. Thus, it indicates that 74.2% of the products sold by the farmers is handled by a few large-scale traders, particularly in the region. This assembled paddy by the large-scale traders is ungraded and unprocessed; thus, they undertake marketing functions— finance of paddy procurement, transportation, storage, processing, rice distribution, and price determination at the farm level. The interviews with village-level collectors revealed that they had to dispatch their assembled paddy to large-scale traders because generally they are provided with price information with an assured forward market. Thus, it is posited that there are only a few buyers or there is an oligopolistic market structure for paddy in the survey area since a significant proportion of farmer products is handled by only a few traders in the NCP.
The results also showed that 63 (57.2%) farmers are selling their harvest before eight weeks (between A and B) after harvesting (or before the next cultivation season) at a price below the average. The pressing concern of this matter is that this leads to lower income in paddy farming (even a loss). As depicted in Figure 1, there are 16 (14.5%) farmers in the negative net income region because of selling the harvest at the harvesting period, even though their farm productivity is above the mean productivity in the area. The study identified causes that influence paddy farmers to sell their harvest in between the harvesting time and the beginning of next cultivation season. Less financial capability to cover the cost of production within a cultivated season and the debt trap laid by the village-level paddy collectors are the critical factors which limit farmer movement to a higher price region in certain seasons.
Conclusions
The primary aim of this study was to investigate the nature of the paddy marketing structure in one of the main colonization schemes in Sri Lanka, to understand whether it explains poor earnings of paddy farming. The study results indicated that paddy farmers do not derive adequate net income from paddy farming, and a majority of farmers sell their harvest at the harvesting period at the lowest price; this does not support them to cover the cost of production adequately. Further, the oligopolistic market structure in the paddy marketing in the area was revealed by the study as few large-scale traders handle 74.2% of farmers‘ production. The lower financial capability of the farmers to cover variable costs of paddy farming and pre-modern economic characteristics of the paddy marketing channel have created a space for large-scale traders to grab the farmers‘ production at a minimum price during the harvesting period. Farmers do not receive any service from these traders regarding price information, input supply, credit provisions, or assured market for them at a reasonable price. The study found small involvement of the government in paddy marketing and zero involvement of farmer organizations and agricultural cooperatives in paddy marketing activities, though they provide agricultural extension services, inputs (managing the government subsidy programs), irrigation water management, and other farm-related services.
In conclusion, it is evident that the market-oriented policy reforms have not led to improved market competition in paddy marketing and enhancement of the welfare of paddy producers in the scheme. Thus, immediate measures should be taken to address the marketing-related issues faced by the farmers in main paddy growing areas of the country.
References
Irshard, A. & Thiruchelvam, S. (2006). Socioeconomic Issues and Conservation Related Attitudes of Farmers in the Gambirigaswewa Cascade Tank Area. Peradeniya, Postgraduate Institute of Agriculture, Peradeniya.
Prasanna, R. (2006). Time to Rethinking Sri Lankan Agricultural Policy: An Analysis of the Sri Lankan Paddy Sector. Economic Review, pp. 26- 31.
Senanayake, S. & Premarathna, S. (2016). An Analysis of Paddy/Rice Value Chain in Sri Lanka, Colombo: University of Colombo.
Weerahewa, J.(2004). Impact of Trade Liberalization and Market Reforms on the Paddy/Rice Sector in Sri Lanka, Washinton DC: International Food Policy Research Institute
(University of Peradeniya, 2018-11-09) Madadeniya, M. G. C. N.; Sivarajasingham, S.
Introduction
Trade is generally identified as a key engine of economic growth and welfare. Therefore, countries around the world continuously attempt to develop trade relationships with each other. Sri Lanka has signed many of its trade agreements with other SAARC (South Asian Association for Regional Cooperation) countries. In addition to the South Asian Free Trade Agreement (SAFTA) and bilateral trade agreements with India and Pakistan, another FTA is expected to be signed with Bangladesh. Apart from its continuing interest in trading with SAARC countries, Sri Lanka is also exploring possibilities for trade beyond SAARC. In fact, the country is currently more interested in developing its bilateral trade relationships with ASEAN (Association of the Southeast Asian Nations) countries. Sri Lanka‘s first ever FTA with an ASEAN member was signed in January 2018, with Singapore. It is also planning to sign trade agreements with three other ASEAN countries which are Indonesia, Malaysia and Thailand. Hence, this paper aims to analyse whether it is trade with SAARC or trade with ASEAN which can promote economic growth in Sri Lanka.
Few studies have focused on the impact of trade with SAARC and ASEAN on economic growth in Sri Lanka. Almost all of those studies are descriptive and there is hardly any empirical study conducted on the particular issue. Most of the researchers recommend that under the current economic and political circumstances, trading with other countries is better for economic growth in Sri Lanka than trading with SAARC members. Bandara and Yu (2001) find that unilateral liberalisation would benefit South Asian countries much more than preferential liberalisation. Weerakoon and Wijayasiri (2001) show that the technology, investment and trade needs of Sri Lanka are more closely aligned to those of its East Asian neighbours than to Bangladesh, Bhutan, Nepal or the Maldives. Ali and Talukder (2009) find that, with an insignificant share in world trade and persistent high levels of tariff barriers, the gains from free trade arrangements in the South Asian region are likely to be minimal. They highlight the possibility that small countries may lose and large countries may gain from an FTA in such a region. However, they emphasize the importance of exposure to a regional market for an economy in order to expand market size, gain economies of scale and increase the competitiveness of domestic firms.
Certain studies have emphasized that developing trade relationships with India is important for Sri Lanka to gain access to Southeast Asia. Weerakoon and Perera (2014) show that Sri Lanka can benefit from greater connectivity with South and Southeast Asia by pursuing closer economic integration with its neighbours. They argue that Sri Lanka should expand the current bilateral free trade agreement with India because many of the country‘s competitors in the Asian region have gained access to markets through such beneficial deals. Bhattacharyay (2014) also shows that integrating India - and through India other major South Asian economies such as Bangladesh, Pakistan, and Sri Lanka - to the South East Asian production network will create win-win situations for both regions. Through this, it is expected to reduce the excessive dependence of South Asia on advanced countries in the West. However, this leads to a new question whether the small countries in South Asia will then start to depend on India.
Objectives
Accordingly, the two objectives of this study are to analyse the growth contribution of SAARC-Sri Lanka trade and ASEAN-Sri Lanka trade, and thereby draw policy implications of the findings.
Methodology
There is hardly any empirical study on the growth contribution of trade with SAARC and ASEAN for Sri Lanka. Therefore, this study has attempted to provide a foundation to conduct an empirical analysis on the particular issue.
This study conducted a time series analysis on the impact of trade with SAARC and ASEAN on economic growth in Sri Lanka, during 1990-2016. In constructing the model, the Neo-classical growth accounting equation was used, which explains what part of growth in total output is due to growth in different factors of production. Neo-classical growth theory shows that the output of an economy is determined by three factors, which are capital, labour and technology. Considering trade as another determinant of economic growth, the following regression model was constructed.
where LNGDP is the log of real GDP, LNGCF is the log of real gross capital formation, LFPR is the labour force participation rate, SAARC is the log of total trade with SAARC (due to the lack of data, Bhutan and Nepal were excluded), ASEAN is the log of total trade with ASEAN (due to the lack of data, Brunei, Cambodia and Laos were excluded), ε is the error term and the subscript t indicates time. All the variables are relevant to Sri Lanka and secondary data were collected from two online databases which are World Development Indicators and ARIC Integration Indicators.
Augmented Dickey Fuller and Philips Perron unit root tests were used to check whether the variables are stationary. Schwarz criterion was used as the model selection criterion. Auto Regressive Distributed Lag (ARDL) Bounds Testing approach was used to study the long run equilibrium relationship between variables. ARDL Error Correction Model was estimated to study the short run relationship between variables. The level of significance considered in the analysis is 5 percent. Diagnostic Tests were conducted to check whether the results are robust. The tests conducted are, Jarque-Bera test to check whether the residuals are normally distributed, Lagrange Multiplier (LM) test to detect serial correlation among residuals, Breusch-Pagan- Godfrey test to detect heteroscedasticity in the model, Ramsey RESET test to check whether the model is specified correctly. Cumulative Sum (CUSUM) test and Cumulative Sum Squares (CUSUMSQ) test to check the stability of the model.
Results and Discussion
After confirming that there is cointegration among variables in the model through the ARDL bounds test, ARDL long run and short run estimations were derived. Accordingly, trade with SAARC as well as with ASEAN has a positive and significant impact on the GDP of Sri Lanka in the long run. When trade with SAARC increases by 1 percent, the GDP of Sri Lanka increases by 13.6 percent, ceteris paribus. When trade with ASEAN increases by 1 percent, the GDP of Sri Lanka increases by 8.9 percent, ceteris paribus. However, in the short run, trade with SAARC has a negative impact on Sri Lanka‘s GDP. When trade with SAARC increases by 1 percent, GDP decreases by 2.3 percent in the short run, ceteris paribus. In the short run, trade with ASEAN has a positive impact on Sri Lanka‘s GDP only at 10 percent level of significance. Gross capital formation has a positive and significant impact on the GDP of Sri Lanka both in the long run and short run. However, labour force participation rate has no impact on the GDP of Sri Lanka either in the long run or short run. The Error Correction Term which is negative and significant shows that the model is stable in the long run and there is long run causality. GDP growth moves back to the equilibrium path and the disequilibrium error is corrected by 38% each year following an exogenous shock. All the diagnostic tests proved that there are no diagnostic errors in the model and that the results are robust.
According to the findings, trading with both SAARC and ASEAN promotes economic growth in Sri Lanka in the long run. It should be noted that in 2016, SAARC accounted for 10 percent of Sri Lanka‘s exports and 22 percent of the country‘s imports. ASEAN accounted for only 3 percent of Sri Lanka‘s exports and 15 percent of the country‘s imports. However, Sri Lanka‘s trade with SAARC is mainly dominated by India. In 2016, India accounted for around 72 percent of Sri Lanka‘s exports to SAARC and 90 percent of its imports from SAARC. In fact, India is Sri Lanka‘s largest origin of imports after China. But Sri Lanka imports from Singapore, Malaysia, Thailand and Indonesia more than from any SAARC country except for India. Further, Bangladesh, Maldives and Singapore each accounts for around 1 percent of Sri Lanka‘s exports. Thus, India should have played a significant role behind the impact of trade with SAARC on economic growth in Sri Lanka. Among ASEAN countries, Singapore has the largest effect on Sri Lanka‘s trade.
Conclusion
This study followed Neoclassical growth theory in a time series analysis conducted to address the problem, ‘which is better for economic growth in Sri Lanka, trade with SAARC or trade with ASEAN?, considering the period from 1990 to 2016. The main objectives of the study were to analyse the growth contribution of SAARC-Sri Lanka trade and ASEAN-Sri Lanka trade, and thereby draw policy implications of the findings. The results showed that both ways of trading promote economic growth in Sri Lanka in the long run. Therefore, Sri Lanka should expand its trade with countries in both regions in order to reap growth benefits in the long run. In fact, the country should improve its trade relationships with India and Singapore.
It is likely that trading with SAARC promotes economic growth in Sri Lanka, especially because of free trade agreements with India and Pakistan. However, although with no trade agreements signed during the period considered, trade with ASEAN has also contributed significantly to economic growth in Sri Lanka. Given that ASEAN is a region with some high income economies with a considerable population and exporting high technology products, this region can have more growth potential than SAARC. Therefore, it can be concluded that Sri Lanka‘s FTAs with ASEAN countries can be beneficial for the future economic growth in the country. However, policy makers should make sure that the prospective agreements are designed so as to give the maximum possible benefit to Sri Lanka.
References
Ali, E. and Talukder, D. K. (2009). Preferential trade among the SAARC countries: Prospects and challenges of regional integration in South Asia. Joaag, 4(1): 47-59.
Bandara, J. S. and Yu, W. (2003). How desirable is the South Asian Free Trade Area? A quantitative economic assessment. The World Economy, 26(9):1293-1323.
Bhattacharyay, B. (2014). Prospects and Challenges of Integrating South and Southeast Asia. International Journal of Development and Conflict, 4(2014): 40-66.
Weerakoon, D. and Perera, N. (2014).The Role of Sri Lanka in Enhancing Connectivity between South Asia and Southeast Asia‘. ADBI Working paper series, No. 487.
Weerakoon, D. and Wijayasiri, J. (2001).Regional Economic Cooperation in South Asia: A Sri Lankan Perspective. IPS Research Studies: International Economic Series, No.6.
(University of Peradeniya, 2018-11-09) Hassan, Y. A.; Kankanamge, A.
Introduction
Global electricity demand doubled between 1990 and 2016, outpacing other fuels, and is set to grow at twice the pace of energy demand as a whole in the next 25 years (IEA 2018). In addition a recent world wide shift towards digital society, electrification in the transportation sector, expansion of business, and urbanization are some common reasons in many countries that has influenced the electricity demand growth (Athukorala and Wilson, 2010). This high electricity consumption is of concern in developing countries where a high growth rate of electricity consumption is expected. An interesting case in research and policy issues is whether aggregate electricity consumption, which is considered as a proxy for energy consumption, can forecast non energy variables. Lack of this understanding could result in misguiding long run investment decisions in the electricity sector. Such causes will lead to periodic power shortages which are common to developing countries (Athukorala and Wilson, 2010).
At the global scale the electricity sector attracts more investment than oil and gas combined at present (IEA 2018). Under such circumstances it is important to improve our understanding on the link between electricity demand growth and economic growth. This link which appears to have a generic effect indeed varies across countries. The existing literature provides ample evidence on variation in this relationship across countries (Ozturk and Bilgili, 2015). We believe it is important to re-investigate the issue following the recent advances in time series estimation technique with a focus on structural breaks in the data generating process. Besides methodological differences such variations in the above relationship could be attributed to complementary effects of the power sector with others in the economy.
Objective
In this study we empirically investigate the relationship between electricity consumption and economic growth of Sri Lanka by incorporating structural breaks into the models. Such analysis could add a different dimension to this debate because allowing for structural breaks is important given that during the period considered the economy has experienced several shocks, all of which have potentially caused a break in economic growth and or electricity consumption.
Methodology
This study used annual time series data of the Sri Lankan economy from 1971-2015. The data was obtained from World Bank Development Indicators. All variables are converted to natural logs prior to analysis. The multivariate framework includes real GDP in billions of constant 2010 US dollars, real gross fixed capital formation (K) in billions of constant 2010 U.S dollars, real domestic investment, real Foreign Direct investment, total labour force (L) in millions and electric power consumption (ELC) defined in kilowatt hours. In this paper, we measure n as growth rate of labour force, g is the rate of technology growth and δ is the rate of depreciation. We further set (g+δ)at the rate of 0.05 because we notice it is a match with the available data in Sri Lanka. The use of Gross Capital Formation as a proxy for capital stock is standard in the energy literature.
To examine the relationship between electricity consumption (ELC) and economic growth (GDP) we use an augmented production function in which output is expressed as a function of capital, labour and electricity consumption. We further segregate capital into domestic capital (DI) and foreign direct investment (FDI). This is to capture the relationship between external financing and economic growth. In our analysis, we apply the Granger Causality approach developed by Toda and Yamamoto (1995) to ascertain the direction of causality between electricity consumption and economic growth.
Results and Discussion
We used the LM unit root test with one break. Interestingly there are two variables for which the unit root null is rejected and the break in the intercept is significant at 10 percent level or better. To determine the presence of long- run equilibrium relationship between economic growth and its determinants we applied the multivariate Johnasen (1998) cointegration test. The results of Johansen cointegration tests or Trace statistics rejects the null of r ≤ 0 but cannot reject r ≥ 1 and also, the Lmax statistics rejects the null of r=0 but fails to reject r=1 at 5% level of significance. Even though we find that electricity consumption and economic growth in Sri Lanka are cointegrated, it does not confirm the direction of causality. For this reason, we implemented the TYDL causality test proposed by Toda and Yamamoto and Dolado-Lutkepohl (1995) approach to verify the direction of causality. We use the popular VAR modeling to infer the direction of causality among the variables in the model. The VAR model is just a special case of the AR models where we have more than one equation. The model suggests that electricity consumption Granger cause GDP growth but GDP growth does not Granger cause electricity consumption. However this does not imply that electricity consumption is not important for economic growth in Sri Lanka but rather that electricity consumption only has a minimal effect on economic growth.
The results of this study have many policy implications. Variations in the regulatory environment in the electricity sub-sector, linkages and complementarities between sectors would result in country wide heterogeneity between energy consumption and economic growth. Thus we suggest that one needs to carefully consider the country specific effects particularly when the study uses country wide pooled data.
Conclusion
This paper contributes to the debate on electricity consumption and economic growth. For this purpose, recent developments in unit root tests considering structural breaks have been applied to investigate the relationship between electricity consumption and growth in Sri Lanka. The results indicate a unit root process in electricity consumption. The implication of the finding is that shocks on the demand side will be effective. Thus demand management policies such as block pricing, taxation, financial incentives and subsidies essentially have flattened the demand for electricity. The results further revealed that there exists a stable relationship between economic growth and electricity consumption. We found that generally electricity consumption, FDI and capital stock positively affect economic growth.
References
Amarawickrama, H. and Hunt, L. (2008). Electricity demand for Sri Lanka: A time series analysis. Energy,(33): 724-739.
Apergis, N. 2016. Environmental Kuznets curves: New evidence on both panel and country-level CO2 emissions. Energy Economics,(54): 263-271.
Athukorala, W. P. P. A. & Wilson, C. (2010). Estimating short and long- term residential demand for electricity: New evidence from Sri Lanka. Energy Economics, 32: S34-S40.
Dilaver, Z. & Hunt, L. C. (2011). Industrial electricity demand for Turkey: A structural time series analysis. energy Economics, 33: 426-436.
Ozturk, I. & Bilgili, F. (2015). Economic growth and biomass consumption nexus: Dynamic panel analysis for Sub-Sahara African countries. Applied Energy, 137: 110-116.
(University of Peradeniya, 2018-11-09) Dovleac, L.; Brătucu,T. O.; Brătucu, G.; Chițu, I. B.
Introduction
This paper includes an analysis of Romanian students‘ opinions regarding the main values associated with the subjective well-being concept. A deeper understanding of subjective well-being among the young Romanian population leads to the development of a more sustainable society where individuals, organisations and policy makers are able to make better decisions. The Organization for Economic Cooperation and Development (OECD) (2015) measures subjective well-being considering: material condition (income and wealth, jobs and earnings, work-life balance, housing, environmental quality) and quality of life (health status, education and skills, social connections and personal security). Well-being is tightly connected to the concept of sustainability. In measuring a country‘s sustainability, the Sustainable Society Index is based on human, environmental and economic well-being (Sustainable Society Foundations, 2012). The sustainability of well-being is reflected in the need to preserve four types of capital: natural, human, social and economic (OECD, 2015). The research on youth well-being is quite limited and the authors considered it essential to conduct a more in-depth analysis about this age group. Inside the European Union, Romania has one of the highest percentages of young people willing to emigrate for improving their quality of life - 30% (Sandu et al., 2014). The research results are valuable by adding to the international framework the perspective of the young population from Romania, a South-Eastern European country with a different approach of the topic from other countries. The research problem is to understand the meaning of subjective well-being for these students, to identify the most cherished values and to analyse if there is a different perception between males and females regarding this matter.
Objectives
The aim of this paper is to present the results of a survey which quantifies the Romanian students‘ opinions about the most important values of subjective well-being and their role for creating a sustainable society.
Methodology
To achieve the objective, the authors conducted a quantitative marketing research involving 1122 students (aged 18-35) from 10 Romanian universities. The authors collected the data during December 2016 and January 2017 using an online questionnaire. The sample was built using multistage sampling based on geographical area, university size, faculty profile and the study level. So, inside the sample 55% of respondents are Bachelor‘s students, 35% - Master‘s students and 10% - PhD Students. The sample structure includes 68.5% females and 31.5% males. The research variables were selected based on several studies which identified the factors that substantiate the well-being of the young generation; satisfaction regarding personal fulfilment, interpersonal relationships at job and during their free time, finding a sense in life and happiness, health, education, social relationships and environment, finding a stable job and professional satisfaction (Fabbrizzi et al, 2016). The data collected was analysed using the statistical software SPSS 17.
Results and Discussion
Inside this study, the Romanian students were asked to rank 10 values associated with the well-being concept. Overall, the students have mentioned happiness as being the most important value of subjective well-being followed by freedom and outdoor activities. An analysis by gender shows that there is a difference of perspective. The females ranked the values exactly as mentioned above – happiness, freedom and outdoor activities. The males made a different ranking: personal income, happiness, freedom. One explanation could be the desire of men to support their family, bringing material wealth.
Further, the sources of happiness were identified in this study. The majority of the respondents mentioned family as being the major source of happiness. In second place, males mentioned personal income, compared to females who chose career. In third place both males and females mentioned their friends as being an important well-being value. Young people under the age of 25 need friends with the same concerns to provide mutual support. The study results show that freedom is a well-being value which also generates happiness. The meaning of freedom is shown in Table 2.
A person considers herself free when he can take action according to his desires or in the absence of constraints. The study‘s results in the table below show that the freedom of decision is the first sense given to freedom by 46.1% of males and 49% of females. Freedom of speech is the second meaning of freedom cherished by 16.9% males and 24.6% females.
The third important subjective well-being value mentioned by respondents is the time spent on outdoor activities. The results of the study show that students spend an average of 10.37 hours per week in nature (Table 3).
The analysis of age groups shows that although it would be expected for younger students to spend more time outdoors (due to the fact they have more free time), the results show something different. The students aged 26- 35 are those who spend the highest amount of hours outdoor – an average of 13.63 hours/week.
Conclusion
The youth population represent a valuable resource for each country‘s development and Romanian institutions need to make an effort in order to create a safe and promising environment. Considering the high percentage of youth willing to leave the country for a better life (30%) and the most important well-being values resulting from this study, the authors suppose that the Romanian young generation is not satisfied with the level of happiness and freedom and the amount of free time spent on outdoor activities. Based on this study results, all the responsible parties could apply measures in order to encourage the young generation to remain in the country. Through such analyses, the government could achieve a better understanding of how to use the resources on activities and policies which provide the biggest well-being benefits for citizens (Cloutier et al, 2013). If youth are given more opportunities to have a meaningful experience they would be more likely to remain inside the country building a sustainable society. Romanian institutions should create long term strategies for supporting this generation because its current well-being will influence the future well-being of an entire nation.
References
Cloutier, S., Larson, L., and Jambeck, J.(2013). Are sustainable cities "happy" cities? Associations between sustainable development and human well-being in urban areas of the United States. Environment, Development and Sustainability.16(3): 633-647.
OECD.(2015). How's Life? 2015 Measuring Well-being, OECD Publishing. [pdf] OECD.
Sustainable Society Foundations.(2012). Measuring wellbeing and progress towards sustainability [pdf] Available at: http://ec.europa.eu/environment/beyond_gdp/download/factsheets/bg dp-ve-ssi.pdf.
Fabbrizzi, S., F., Maggino, N., Marinelli, S., Menghini, Ricci, C.(2016). Sustainability and Well-being: The Perception of Younger Generations and their Expectations. Agriculture and Agricultural Science Procedia, 8: 592-601.
Introduction
Among various dimensions of inequalities and exclusion such as gender, religion, region, race and ethnicity, caste and class continue to be the two most important components of the stratification debate in India (Deshpande, 2000; Thorat, 2013; Patankar, 2015; Bhowmik, 1992). There is a vast literature that highlights the central role that caste and class play in fostering and sustaining the process of social exclusion of a major section of the population in the economic, political and cultural spheres (Nayak, 2012; Patankar, 2015; Thorat, 2013; Vakulabharanam 2010).
The Indian economy has experienced rapid growth since the 1990s; a rapid, and to large extent sustained growth for most years since the late 1980s. The literature has discussed two contradictory views about the evolution of caste and class dynamics during the decades of high growth. On one hand, the benign view suggests that the process of liberalization and economic growth has been able to create an inclusive socio-economic environment where caste boundaries and class hierarchies have been diluted (Hnatkovska, 2011; Panini, 1996; Hnatkovska et al, 2012). However, in contrast to this benign view, there exists a voluminous literature that argues that the overall growth process has been exclusionary and inequalizing, i.e., some sections of the society have been able to reap the benefits of economic growth and advancement while some have been kept out of its purview. The SC‘s and ST‘s still have low socio-economic indicators and there has been persistent inter-group inequality in terms of income and consumption, as well as in terms of access to education, healthcare, and better employment opportunities (Baru et al, 2010; Deshpande, 2000; Thorat and Mahamalik, 2006; Deshpande, 2008; Madheswaran and Attewall, 2007; Nambissan, 1996).
On the other hand, there are a number of studies in the literature that have discussed the existence of class based inequalities in India. Using an ″occupation based″ class-schema specifically designed for the Indian case, these studies suggest that there is significant inequality of opportunity in India. There is also considerable intergenerational persistence, especially in low skilled and low paying jobs. It has also been suggested that caste plays a significant role in determining the patterns of social mobility. Occupational mobility is lower for depressed castes as compared to upper castes. There has been a persistence of the fact that very few lower caste people are to be found in the high status jobs at the top of occupational hierarchy compared to the upper castes (Kumar, Heath and Heath, 2002; Vakulabharanam, 2010; Motiram and Singh, 2012; Kumar, Heath and Heath, 2002a).
Some studies have suggested using the ″intersectionality″ framework to analyse the inter-connection or association between caste and class (Bhowmik, 1992; Kumar, 2010). However, in economics, there has been no explicit empirical work in terms of caste and class employing the intersectionality framework. Though there have been few empirical studies that try to analyse the caste-class relationship and the change in their interaction over time, they mainly provide evidence of the condition or status of caste-class relationship during their period of analysis. The literature fails to address the underlying mechanisms that result in persisting caste and class based inequalities or are the driving force behind the observed patterns of change. Since caste origins have been historically tied to specific occupations, these studies mainly use an ″occupation-based class schema″ to determine the intergenerational mobility patterns. They however do not take into account other dimensions of caste and class that shape the socio-economic ″status″ and social experiences of people belonging to specific caste groups and class origins.
Objective
The objective of this study is to examine the empirical association between caste and class in times of economic growth. It also tries to enquire into the nature of the relationship between these two, i.e., to see if caste and class are just two inter-dependent forces or they mutually reinforce each other. This analysis then seeks to understand the importance of caste and class origins and their ″interaction″ in determining the social mobility patterns in India in the most recent times of growth. In an attempt to understand the above dynamics, this study tries to address the following question: Does the prevailing caste/class hierarchies necessarily imply that an individual of a particular caste group will always end up in a specific class position, with a specific set of opportunities, choices, and economic life chances? Or during the recent period of high economic growth the relationship between caste and class and their role in determining the life chances of the individual has been diluted?
Methodology
The analysis concentrates on the period 1999-2012 (the most recent decade of high economic growth), given that this period is covered by the comprehensive, disaggregated household level data from National Sample Survey Organisation (NSSO), comprising of the following four rounds – 55th round (1999-2000), 61st round (2004-2005), 66th round (2009-2010), and 68th round (2011-2012). The data set used for the study is not a panel. It is an independently pooled crossection data for four time points. In order to convert the nominal values into real values, the consumer price index (CPI) for the year 2006 of rural workers has been used in the rural areas and that of industrial workers has been used in the urban areas.
To define caste, the generally accepted contemporary caste classification by the Government of India has been used, where the population is divided into four broad groups: Scheduled Caste (SC), Scheduled Tribe (ST), Other Backward Classes (OBC), and General or Forward Castes. Class, on the other hand, has been defined in various ways in different strands of literature. Here, following the tradition of classical political economy (i.e., in the tradition of Smith, Malthus, Ricardo, and Mill, and their critique by Marx), I define class in a specific way – in terms of the position of an individual or a group of individuals within the process of production, appropriation and distribution of value added in the economy. In the urban sector classes can be broadly divided into the following four categories: self-employed (those who control the process of production, are involved in the actual labour and also are the recipients/claimants of their final produce), workers (those who actually perform the physical labour but cannot claim the final produce), professionals and managers (who perform a supervisory role in the labour process) and non-class/non-economic (those who are not involved in any economic activity as well as are not actively available for work such as students, pensioners, rentiers, disabled, remittance recipients etc.). There are intrinsic differences between people working in the manufacturing and services sector. Once this distinction is accounted for, the class of self- employed can be further divided into six sub classes namely own account worker in manufacturing and own account worker in services, employer in manufacturing and employer in services, and unpaid family worker in manufacturing and unpaid family worker in services. The working class can be divided into two composite classes, namely regular and casual workers in manufacturing and regular and casual workers in services. Thus, in the urban sector the detailed classification consists of 10 class positions.
The rural sector is first categorised into agriculture and non-agriculture at the broadest level. The agriculture sector can be further split into two broad categories namely the landed and the landless. Based on the amount of land owned, the landed category can be further subdivided into four classes- rich farmer, middle farmer, small farmer and marginal farmer/tenant. These four groups together constitute the faming/peasant class. Those who are landless but still work in agriculture, as they primarily derive their livelihood from it, are referred to as agricultural workers. The non-agricultural sector consists of non-agricultural workers, the rural professionals (e.g. government officials) and the non-agriculture self-employed. As in the urban areas, a section of the rural population falls into the non-class/non-economic category. The agricultural workers and the non-agricultural workers together comprise of the working class. The non-agriculture self-employed class can be further subdivided into six categories (as discussed above). Thus, the detailed classification in the rural sector comprises of 14 class positions.
The above mentioned classes are defined using information about household characteristics, usual principal activity, particulars of the individual members of the household, occupational data obtained from National Classification of Occupations (NCO-2004) and the industrial classification codes obtained from National Industrial Classification (NIC-2004).
In order to track the evolution of the interdependence of caste and class over time, regression analysis has been used. Since caste and class both are categorical variables, a multinomial logit framework has been employed where class is the dependent variable and caste is one of the explanatory variables. It is important to note that the focus of the analysis is not to use economic growth as an explanatory variable, since growth doesn‘t impact the caste identity12 and class position of an individual, and is also not impacted by them. However, it has been argued in the literature that there has been an expectation or hope that rapid growth and process of economic liberalization and modernisation may lead to dilution of the rigid caste boundaries and class hierarchies, thereby resulting in an improvement in the socio-economic outcomes of the depressed and excluded sections of the society (Hnatkovska et.al, 2012; Vaid, 2012). Hence, in the analysis, the attempt is to capture the caste and class dynamics by analysing the period which is the most recent decade of high economic growth.
A whole host of factors which might influence the class position of an individual have been controlled for. These include education, gender, monthly per capita expenditure (mpce), and state, which captures whether an individual resides in a less advanced (backward) or a developed state. All these variables are categorical in nature, except for mpce which is a continuous variable. First, a regression with explained set of controls is carried out which describes how the changes in each of these variables are affecting the class position of the individual. However, in order to capture the impact of caste over time, an interaction term has been added in the second regression.
Results and Discussion
The multinomial logit estimation seeks to explain the relative probability of an individual ending up in a particular class position given his caste and attributes set. Labour and regular or casual workers (which represent the working class) serve as the base category in the rural and urban areas respectively. The coefficients of the multinomial logit model obtained from the analysis are significant and have the expected signs. The relative probability of SC‘s and OBC‘s belonging to the peasant class than in the labour class is 76% and 28% lower as compared to general category (controlling for all the other variables). Over the entire period of analysis the relative probability of an individual belonging to the peasant class rather than being in the working class has gone up by approximately 11% in the rural areas. The relative odds of being rural professionals or self-employed in non- agriculture sector rather than working as labour are much lower for ST‘s, SC‘s and OBC‘s relative to Others. Specifically, the relative odds of ST‘s and SC‘s being self-employed than working as labour are about 75% and59% lower as compared to Others. However, the probability of SC‘s being rural professionals than working as labour in 2011-12 relative to general category in 1999-2000 has increased by approximately 32%. This effect is captured by the interaction term. In the urban areas as well there is a similar trend. The relative probability of ST‘s, SC‘s and OBC‘s being professionals or self-employed than being regular or casual worker is much lower as compared to Others (after controlling for all the other variables). The probability of ST‘s and SC‘s being self-employed than being regular or casual workers in 2011-12 relative to Others in 1999-2000 has decreased by 40% and 18% respectively.
Conclusion
Caste and class continue to be two major components of economic and social stratification in India. They play a crucial role in strengthening and sustaining the process of social exclusion. Though there have been some improvements over the period of analysis in terms of movement across class positions, caste still appears to be influential in determining an individual‘s class position. Although there has been some dilution of the caste and class hierarchies during this period of high economic growth, the change has not been significant enough as had been hoped. Both the rural and urban areas have witnessed similar trends but the magnitude of the change is very different. Policies formulated need to take into account the differences in the rural and urban areas.
References
Kumar, S., Heath, A. and O.Heath. (2002). Determinants of social mobility in India. Economic and Political Weekly, 37 (29): 2983-2987.
Kumar, S., Heath, A. and Heath, O. (2002).Changing Patterns of Social Mobility: Some Trends over Time. Economic and Political Weekly, 37 (40): 4091-96.
Motiram, S., and Singh, A. (2012). How close does the apple fall to the tree? Some evidence on intergenerational occupational mobility from India. WIDER Working Paper (2012/101), WIDER, Helsinki.
Vakulabharanam, V.(2010). Does Class Matter? Class Structure and Worsening Inequality in India. Economics and Political Weekly, XLV (29): 67-76.
Hnatkovska V., Lahiri, A., and Paul S. (2012).Castes and labor mobility. American Economic Journal: Applied Economics, 4(2): 274-307.
(University of Peradeniya, 2017-10-12) Thahara, A. F.; Vinayagathasan, T.
Introduction
In recent decades a vast number of studies have focused on the link between exchange rates (ER) and different causal factors. The ER is one of the most crucial macroeconomic factors in the emerging and transition economies. It affects public debt, inflation, trade and other economic activities. The ER has long been thought to have significant impact on the import and export of goods and services. Therefore, ER is expected to stimulus the price of those products that are traded. Shaheed (2015) concludes that external debt, debt service payment and foreign reserves have a positive impact on ER in the long run. Although, most of the economies currently facing issue of currency depreciation, which makes the trade balance and balance of payment (BOP) favorable and moves towards the surplus and boosts the country’s economy. However, the situation of Sri Lanka is totally different that it. Even though, Sri Lanka has experienced continuous currency depreciation since 1977, it has recorded that the deficits in the trade balance and BOP. The one way of solving the budget deficit (BD) or BOP problem is to allow the currency depreciation. Another ways are to use internal and external sources of deficit financing. Since Sri Lanka faces difficulties in accumulating the internal sources, the demand for external sources of deficit financing has been increased. As a result, external debt of the country has increased. On the contrary, BOP deficit and BD tend to decrease the foreign reserves (FR). The currency depreciation leads to increase the value of interest rate than the real value. As a result, real value of debt servicing will be higher than value of debt.
The significant number of existing literature identified a positive relationship between exchange rate and external debt (e.g., Alam and Taib, 2013; Awan et al.> 2015; Shaheed et al., 2015; Draz and Ahmed, 2015). However, the quantitative assessment of the relationship between ER and external debt is inadequate and limited in the context of Sri Lanka. Thus, this study attempts to fill this gap by investigating the ER and external debt nexus in the context of Sri Lanka.
Objectives
The main objective of this research is to identify relationship between exchange rate and external debt in the long run and in the short run.
Methodology
Annual data of Sri Lanka over the period of 1977-2015 has been used in this study. The data of exchange rate (ER), external debt (ED), foreign reserve (FR), budget deficit (BD), and debt service payment (DSP) were extracted from annual reports of Central Bank of Sri Lanka (CBSL) and consumer price index (CPI) was collected from the World Development Indicator (WDI) data base. Further, political instability (PI) and exchange rate regime (ERR) were used as dummy variables. All the variables, except PI and ERR, are transformed in to natural logarithm. ADF and PP unit root test methods were adapted to test that the series are not containing I(2) variables. Akaike Information Criterion (AIC) is applied to determine the optimal lag length of each series. Following the empirical literature in determinants of ER, we develop the long-run relationship between the variable as below:
(Equation -1)
where, is a white noise error term, t = 1, 2, …, T.
The Engel Granger method and Johansen method requires that the all of the variables in equation (1) should be integrated in same order and the error term should be integrated in order zero in order to form the long run relationship. However, if variables in equation (1) have different order, that is I(1) and I(0) we can use new co-integration method which was developed by Pesaran et al., (2001). This procedure, also known as autoregressive distributed lag (ARDL) approach to co-integration. The ARDL co-integration bound testing procedure is given by equation (2):
(Equation -2)
where, refers to the long run coefficients; is the vector of explanatory variables with lag one; and refers to the short run dynamic coefficients, denotes the vector of explanatory variables with lag and is the white noise error term.
The equation (2) can be further transformed as in equation (3) to accommodate the error correction term with one period lagged :
(Equation -3)
where, γ speed of adjustment, which should have statistically significant and negative sign to support the co-integration between the variables, (symbol> pure random error term.
To investigate the existence of long-run relationships between the variables, bound testing procedure is used, which is based on the F-test (Wald test). The F-test is actually a test of the hypothesis of no co-integration among the variables () against the existence of cointegration among the variables () in equation (2). Finally, we used Granger causality test to determine the direction of the causality between the variables.
Results and Discussion
The results of ADF and PP unit root test indicate that the variables are integrated in order zero (LER, LBD and LED) and order one (LCPI, LFR and LDSP). AIC advocated that to use ARDL (1, 0, 1, 2, 1,1) model for this analysis. The long-run results of the corresponding ARDL (1, 0, 1, 2, 1, 1) model are presented in Table 1 below:
As expected to the theory and most of the existing literature (e.g., Saeed et al., 2012; Awan et al., 2015; Draz and Ahmed, 2015) ED, BD, CPI and FR (at 10 %) have positive and statistically significant relationship with ER in the long run, whereas, DSP affects the ER negatively in the long run. At the same time BD and CPI have significant (10 % level of significance) and positive impact on ER in the short run while other variables do not affect significantly.
The Lagrange Multiplier (LM) test of autocorrelation advocates that the residuals are not serially correlated. According to the Jarque-Bera (JB) test, the null hypothesis of normally distributed residuals cannot be rejected. The Breusch-Pagan-Godfrey (BPG) test of heteroscedasticity suggests that the disturbance term in the equation is homoscedastic. The Ramsey RESET test result confirms that there is no specification error in the estimated model (See Table 1, Panel C above). The CUSUM plots lie between the lower and upper critical bounds at the 5 % level of significance, which confirms the stability of the parameters. The result of Wald test confirms that there is long run relationship between ER and other variables under considered in this study since we reject the null hypothesis of no cointegration among the variables due to the computed F-statistics (3.92) greater than the upper bound critical value (3.79) at 5 % level of significance (The both results of stability and the Wald test are not presented here due to concerning the page limit).
Next, the results of short run dynamic and long run adjustment coefficients are estimated using Equation (3), which is presented in Table 2. The ECM model passed all the diagnostics tests (see Table 2, Panel B below). Panel A of Table 2 reports the short run dynamics coefficient estimates of ARDL-ECM. Accordingly, as expected, one period lagged value of ER and one and two period lagged value of CPI have positive and significant impact on ER in the short run whereas one period lagged value of FR has negative and significant impact on it. Further, ECT(-1) carries an expected negative sign, which is highly significant, indicating that, there should be an adjustment toward steady state line in the long run one period after the exogenous shock. That is, about 19.4 % of the disequilibrium in the ER is offset by short-run adjustment in each period.
Finally, Granger causality test detected only unidirectional causality that stemming from FR to ER and DSP to ER in the long run (The results are not shown here due to space constraint).
Conclusion and Policy Implications
This study concludes that the both cointegration approach to ARDL and error correction version of ARDL passed all the diagnostics and the stability test. The Wald test confirms that the variables are cointegrated. The CPI affects the ER positively and significantly in the long run and in the short run. ED, BD, and FR have positive and significant impact on ER in the long run while DSP has negative affect on it. But, lagged value of FR negatively affects the ER in the short run. Further, this model confirms that whole system can get back to long run steady state line at the speed of 19.4 % in each year one period after the exogenous shocks. In sum, the government of Sri Lanka should take necessary action to reduce the BD, ED and CPI in order to bring the economy well off.
References
Awan, R. U., Anjum, A., and Rahim, S. 2015. An Econometric Analysis of Determinants of External Debt in Pakistan. British Journal of Economics, Management and Trade. 5(4): 382-391.
Draz, M. U. and Ahmed, F. 2015. External Debts and Exchange Rates of Oil-Producing and Non-Oil-Producing Nations: Evidence from Nigeria and Pakistan. Journal of Advance Management Science. 3(1): 8-12.
Pesaran, M. H., Shin, Y, and Smith, R. J. 2001. Bounds Testing Approaches to the Analysis of Level Relationships, Journal of Applied Econometrics, 16: 289-326.
Saeed, A., Awan, R. U., Sial, H. M. R., and Falak, S. 2012. An Econometric Analysis of Determinants of Exchange Rate in Pakistan. International Journal of Business and Social Science. 3(6): 184-196.
Shaheed, Z. S., Sani, I. E., and Idakwoji, B.O. 2015. Impact of Public External Debt on Exchange Rate in Nigeria. International Finance and Banking. 2(1):15-26.
(University of Peradeniya, 2017-10-12) Paranamana, G. P.; Ranjith, J. G. Sri
Introduction-
Although the government involvement in economic development has been substantially high in Sri Lanka, the investment has been highly dominated by the private sector accounting for 20 % of GDP on average over the proceeding decades. It apparently indicates that the fiscal policy and budget deficit is conducive for thriving private sector businesses. Hence public sector spending may have helped in developing infrastructure and work force development for encouraging private investment. With this move, fiscal policy influences the macro economy through a number of ways; it changes the level and composition of aggregate demand, changes aggregate supply and influences national savings and investments (through expenditure and taxation). As an emerging economy Sri Lanka and its government expenditures show the directions to develop productive investments and human capital infrastructure through the government economic policy packages. However, this field of study in economics have no clear policy direction given and highly debatable over the experience of different contexts (Biza, et. al., 2013; Rathnasekara, 2016). With this background, this research therefore focuses on empirical study on how budget deficit and fiscal policy of the country effect on private investment maintaining macroeconomic stability to achieve sustainable growth. This study attempts to investigate whether there is an empirical relationship between budget deficit and private investment. We consider two types of investment: Domestic Private Investment and Foreign direct investment.
Objectives
The main objective of this study is to assess the policy effectiveness of the government in achieving high and sustainable economic growth in compliance with fiscal consolidation effort.
The secondary objectives are to investigate the determinant factors of private investment and also to examine whether there is a crowding out or in effect between budget deficit and private investment.
Methodology
The empirical model constructed for this study is based on the regression model by Samwel (2016) that used for his study regarding the Tanzanian economy. We have modified that model by adding new variables suitably to conduct our study. We took log difference for all variables.
Where PI refers to Private investment which can be divided into two, those are DPI and FDI (Domestic Private Investment and Foreign Direct Investment respectively as a ratio of GDP); CPI refers to Consumer Price Index, ER refers to Exchange rate (LKR per $) and BD refers to Budget deficit. There is no surplus value for the relevant period. So we consider only absolute value of BD defined as a ratio of GDP. This study covers time period of 1990 to 2015. The relevant data were collected from annual Reports of Central bank of Sri Lanka.
At the first step of the estimation procedure, ADF test and Phillip Peron tests were used to check the stationary of data. Johansen co-integration test was used to identify the long-run relationship and also VECM was used to identify both short-run and long-run relationship as well as long-run equilibrium among the variables.
Results and Discussion
Unit root test revealed that all variables were non-stationary at the initial level, but stationary at the First difference. According to lag length criteria, AIC and HQ criteria were selected 2 lags. LR, FPE and SC criteria were selected 1 lag. Most criteria were selected in 1 lag. So lag length test suggested 1 lag. Johnsen co- integration trace test has detected co-integration relationship for both model which implies that there is a long -run relationship, long -run speed adjustment and short-run relationship are examine using Vector Error Correction Model.
The Equation 3`and 4 show long-run relationship:
According to above results, all variables are significant at the 5 % significant level at the long-run. Therefore, this results show that government fiscal deficit positively impact on domestic investment and also on foreign direct investment. For instance, when BD increases in 1 %, DPI increases in 5.27 % and also FDI increases in 1.03%. As it similar to the findings of literature, (Coban and Tugcu, 2015) the empirical estimation results of our model reveals that there is a long-term relationship between private investment and its determinants specified in the model. Also it clearly shows that government budget has been favourable for investment.
Since Error Correction term of the both models are significant and negative the long-run adjustment relationship can be identified related to PI and FDI (See Table 2). According to Equation 1 speed adjustment is -0.59 which means that after an external shock, domestic private investment moves, from short-run to long-run steady state after one year. And also According to equation 2, speed adjustment is 1.57 means that after an external shock, foreign direct investment moves from short-run to long-run steady state after one year.
According to above results there is no significant relationship among the variables at the short-run consider about DPI. However, Last year FDI and Current year FDI has positive significant relationship.
Conclusion and Policy Implications
The empirical results indicate that budget deficits have been favourable for both domestic and foreign direct investment in the long-run. Also budget deficits are favourable for foreign direct investment at the short-run. Under the current fiscal policy the government spends more on improving public welfare, physical and social infrastructure development. These expenditures will have a tremendous positive impact on investment potentials in Sri Lanka. And also, government established BOI and tax reduction and concessions have made an optimistic view for investors. Therefore, current phase of fiscal policy stance is conducive for foreign investment in the short-run and long-run. Also we can say that although there is a crowding out effect on domestic private investment in the short-run, the current fiscal policy has a crowding in effect on domestic private investment in the long-run
References
Central Bank of Sri Lanka, Annual Reports for the years 1990-2015. Colombo: Sri Lanka.
Rathnasekara, H. 2016. Does Private Domestic Investment Crowd Out Foreign Direct Investment (FDI) in Sri Lanka? Evidence from Multivariate Vector Error Correction Model’. 26th Asian Economic Symposium, pp. 23-38.
Samwel, M. 2016. Do Budget Deficit Crowds Out Private Investment: A case of Tanzanian Economy? International Journal of Business and Management, 11(6): 183-189.
(University of Peradeniya, 2018-11-09) Mayoshi, R. M. M.; Sri Ranjith, J. G.
Introduction
Creating self-employment opportunities is a way of improving the socio economic status of a country‘s rural economy. There are enough natural resources to create self-employment businesses in rural area such as lands and raw materials. Therefore, especially rural people in Sri Lanka pay attention towards self-employment. Many rural inhabitants in Sri Lanka are self-employed (International Labour Organization, 2014). In general, successful self-employment contributes to increased production, income and eventually, the eradication of rural poverty. In Sri Lankan, self-employment is a way of creating a larger space in the job market to promote work opportunities for the unemployed people. Gindling and Newhouse (2014) (cited in. De Mel et al, 2010) find most workers in developing countries to be self-employed. During the period 1991 to 2013 the percentage of self-employed in total employment increased yearly. In 1991, percentage of self-employed in total employment was 37.60 and 46.30 in 2013 (International Labour Organization, 2014).
In this research, we have attempted to identify the education, training and experience affecting the success of rural self-employed individuals and trends of self-employment. Nature of self-employment activities can be categorized into two parts; viz. non-farm and farm self-employment (Trends in non-farm self-employment activity for rural women, 2004). The majority of rural people in Sri Lanka engage in non-farm self-employment activities such as sweets production; producing and selling of spices; producing incense sticks, soap, wicks, handicraft productions, and bakery foods; services of beauty and hair cutting saloons; fashion designing, dress making and tailoring etc. Examples of farm self-employment are cultivation of mushrooms, flowers, vegetables and fruits, and animal production that are related to agriculture.
The literature provides information as to what factors affect the success of self-employed individuals. According to Robinson and Sexton (1994) self- employment success was measured by monthly income and education, training, experience, developed technology, age of self-employer and gender. The results indicate that education, training, and experience mainly affect the success of self-employment among rural inhabitants. Timothy (1995) finds that the self-employed are highly educated individuals often possessing financial resources. In 2009 Macieire analysed the impact of self- employment experience on income. The results indicate that experience and earnings from self-employment have a positive relationship and this quality of self-employment tends to be crucial for the success of a business.
Objective
The main objective of this study is to analyse the effects of training, experience and education of self-employed individuals on the success of having rural self-employment in Sri Lanka. Secondary objectives include, identifying the nature of self-employment activities and the major problems which are faced in the self-employment in rural inhabitants.
Methodology
A sample of 30 self-employed people living in the Ambalantota Divisional Secretariat in Hambantota was selected using a simple random sampling method. Questionnaire interviews were used to collect primary data. The study uses descriptive analysis and the Multiple Regression Model and uses the success of self-employment as the dependent variable (Y): self-employment success was measured by monthly income. The multiple linear regression model is specified as follows.
Yᵢ = β₀ + β₁Xᵢ + β₂X₂ᵢ + β₃X₃ᵢ + β₄X₄ᵢ + β₅X₅ᵢ + β₆D₁ᵢ + β₇D₂ᵢ + β₈D₃ᵢ + uᵢ
X₁- Monthly savings from self-employment (Rs.)
X₂- Numbers of family workers engaged in the business
X₃- Experience (numbers of years)
X₄- Age of self-employed
X₅- Education (numbers of years).
There are three qualitative variables that have been included in the multiple regression model as dummy variables. D₁ is usage of machine, use = 1, otherwise 0, D₂ is vocational training of the self-employed, yes = 1, no = 0. D₃ is Gender of the self-employed, male = 1, otherwise = 0.
Results and Discussion
The results of the multiple regression model show that R² is 0.97. The estimation results show the overall regression model to be significant at the 5% significance level and that the overall goodness of fit is high. It indicates that the independent variables used explain about 97% of the success of self- employment. Moreover, the results indicate that there are a number of key significant factors such as savings, number of family workers engaged in the business, education, experience, training, usage of machine and gender affecting the success of self-employment; which are statistically significant at 5% and 10% confidence levels. Technology tends to be significant at the 10% confidence level. Age of self-employed is not significant at 5% and 10% confidence levels.
According to the analysis, 27% of the sample is engaged in farm self- employment activities and 73% is engaged in non-farm self-employment activities. The results also indicate demographic factors such as age, gender and family background, human capital and experience and economic factors affect the likelihood of being self-employed in the country‘s rural economy. As per the results, 53% of the sample is female self-employed and 47% is male. The highest proportion of self-employed is found between the ages of 24-30. This research has discovered three major problems in the self-employment of rural inhabitants, which are, difficulties of registering their business, difficulties of getting loans from government and private sector, and insufficient infrastructure in the rural area. According to the sample data, 53% of the sample is not registered business and 47% is registered business. Using the five point Likert-scale, difficulties of getting loan from government and private sector is 80% of the sample and 53% of the sample indicates that infrastructure is not sufficient in rural area.
Conclusion
The results indicate that education, training and experience tend to be crucial for the success of self-employment among rural inhabitants. Savings from self-employment, number of family workers engaged in the business, education, experience, training and being a female self-employed are the main factors affecting high income earnings and that tend to make rural self- employment successful. This research has also discussed three major problems in rural self-employment; viz. difficulties in registering their business, difficulties of getting loans from government and private sector, and insufficient infrastructure in rural area. Therefore, the government and private sector should take necessary actions to supply sufficient infrastructure facilities like transport, communication, credit facilities and marketing facilities. Marketing facilities help to find suitable markets for their produce without any losses. Also the rural self-employed should be encouraged to produce more using their resources and should take action to distribute their production around the country. Further studies are needed to assess psychological and social factors that affect the success of rural self- employment.
References
Bates, T. (1995).Self-employment Entry Across Industry. Journal of Business Venturing. 10(4): 481-498.
Gindling, T.H. and N, David.(2014). Self-employment in the developing World‘. World Development. 56: 313-331.
Macieira, M.H.C. (2009). The Determinants of Self-employment.Dissertation to Obtain the Degree of Master in Industrial Engineering and Management, University of Lisboa, Portugal.
Robinson, P.B. and Sexton, E.A. (1994).The Effect of Education and Experience on Self-employment Success. Journal of Business Venturing. 9(2): 141-156.
(University of Peradeniya, 2017-10-12) Arachchi, A. Janaki Imbulana; Banda, O. G. Dayarathna
Introduction
At the economic development, process economist has commonly considered that industrial sector has been a leading sector in the economy. Because industrial sector provides the main contribution to economic development process through produces goods and services, value addition for agriculture products, foreign exchange earnings by export, increase in employment, etc. Sri Lanka as a low middle-income country, the manufacturing sector is a primary component within the industrial sector. According to the Central Bank report in 2016 manufacturing sector contributed 15.2 % of GDP in Sri Lanka. At the same time, many official economic and social reports provide evidence that small and medium scale industries have been providing major proportion from above contribution. Therefore it is important to keep considerable attention on small and medium scale industry in Sri Lanka to achieve economic development goal.
There are many academic works which examine about the growth of SMEs internationally. Afande (2015) identified that access to credit, firm age and level of education of firm’s owner effect positively and significantly on the growth of small-scale manufacturing industry. According to the Yasuda (2005) investigates the relationship between firm’s growth and size of the firm, firm’s age and firm’s behavior in Japanese manufacturing firms. And also Pherson (1994) identified the negative relationship between firm’s growth and firm’s age. Heshmati (2001) examined the relationship between the size, age and growth rate of firms is for a large sample of micro and small firms in Sweden. However, while concentrating on local studies, Dayarathna-Banda and Sri-Ranjith (2014) examined the relationship between characteristics of entrepreneur and success of small business. Varothayan (2013) examined six factors namely financial, management, marketing, technology, infrastructure and government regulation that influence the performance of SMEs. Lingesiya (2012) studied the factors which to indicate the business performance of small-scale industries. In this study he identified that customer satisfaction with managing change, growth at business and income level, growth in profitability, growth in turnover, growth in a number of employees are the main indicators of the business’s growth.
Performance of small-scale industries, the growth of industry and performance of industry are completely different concepts. When we referred Sri Lanka’s research works on small-scale manufacturing industry, there is a lack of studies in the area growth of small-scale manufacturing industry. Therefore, the purpose of this study is to examine the growth of small-scale manufacturing industries.
Objectives
The objectives of this study are to identify the growth of small-scale manufacturing industry in Sri Lanka and to examine impact of access to credit, firm’s age, level of education of firm’s owner, gender of firm’s owner, vocational training of firm’s owner and technology applied in firm on growth of small-scale manufacturing industry.
Methodology
According to the research objectives, we used both primary and secondary data for the analysis of this study. The primary data were collected through questionnaire. The primary data was gathered in this study using a sample of 60 small-scale manufacturing firms selected through random sampling method in kuliyapitiya DS division. The secondary data was extracted from annual reports of the Central Bank of Sri Lanka and registries in kuliyapitiya DS division office. The study applied a multiple regression model using OLS techniques. I have developed my model based on Afande (2015). The model is given below.
ᵞᵢ = ᵝₒ+ᵝ₁ᵝ₁ᵢ+ᵝ₂ ᵡ₂ᵢ+ ᵝ₃ᵡ₃ᵢ+ ᵝ₄ᴰ₁ᵢ +ᵝ₅ᴰ₂ᵢ+ᵝ₆ᴰ₃ᵢ+ᵘᵢ
Where u is the random error term.
We considered firm growth (Y), access to credit (X₁), firm’s age (X₂), level of education of firm’s owner (X₃), dummy variables were used for gender of firm’s owner (D₁), vocational training of firm’s owner (D₂), technology applied in firm (D₃) there, D₁ takes the value 1 if firm’s owner is male, 0 if firm’s owner is female, and D₂ takes the value 1 if firm’s owner received vocational training, 0 otherwise and D₃ takes the value 1 if firm used new technology, 0 otherwise.
Results and Discussion
According to the survey, the firm profit was used to measure the growth of small-scale manufacturing industry. In order to measure the growth rate, we used firm profit both of 2014 and 2015 years. We categorized them according to the growth rate. That results are depicte in Figure 1.
According to the result in Figure 1, all firms have maintained considerable growth rate. Most of the firms in the sample obtained between 10 %-15 % growth rate at considering the time period. However, some firms obtained 35 % level growth rate but some firms obtained 5 % growth rate.
To estimate above-mentioned multiple regression 60 observations were employed. The estimates show that overall multiple regression model is significant at 5 % confidence level and the overall fitness as the R² value is equal to 0.7279, It indicates that the independent variables used to explain about 73 % variation in growth of the small-scale manufacturing industries in the sample. The results show that there is a significant positive relationship between access to credit and growth of Small scale industries. It implies that provision of credit facilities effect to increase the growth of these firms. However, evidence showed that 50 % of small-scale industries did not use credit due to many reasons such as ignorance, dislike, institutional problems and so on. It was also identified short-term (2 or 3 days) repayments loans between some small-scale businessmen and suppliers of inputs and purchases. This has been a powerful factor for each of them.
According to results, it shows that gender of firm’s owner positively significant at 5 % level. Further evidence shows that male-owned 80 % of Small scale industries in the sample. It may happen due to nature of small-scale industries in this area. The few of them received specific training from government and non- government organizations. It helps them to improve both quality and quantity of particular products. Especially it improved their compatibility with homogeneity products. According to the literature review, it shows that adoption of new technology helps to increase labor productivity of small-scale industries. Further increase of labor productivity makes surplus which helps to the capital accumulation of this sector. the results of this study show that the technology applied in the firm is positively significant at 5 % level. Even though modern technology improves productivity and increased the profit of small-scale industries in the area, more than 57 % of firms have used traditional technology for their production activities. It was also found that firm age and level of education of firm’s owner displayed positive relationship but not significantly. Majority of firm’s owners passed GCE (O/L) or (A/L) level but it does not help them to increase the growth of firms. These kinds of education systems will not provide vocational training, which will help to improve the productivity of a firm.
Conclusion and Policy Implications
Small-scale manufacturing industries face working capital difficulties to conduct their business. They seek to obtain loans as a solution to the capital shortfall. But only 50 percent of the sample has obtained credit from the formal sector. They obtain a short-term loan from private sector especially input suppliers and businessmen. This situation may affect negatively to their profit and growth of small-scale industries. Therefore, credit facilities under a low-interest rate from the formal sector could make a positive impact on the growth of small-scale industries. Therefore, government and formal private sector credit institutions have a significant role to develop small-scale industries in the rural areas.
According to the study results, male-owned small-scale industries have relatively higher growth rate compared to female-owned ones. Further small-scale industries that were included in this sample characteristically non-female owned industries. It implies that unutilized female entrepreneurs in the rural sector and need to introduce suitable industries with necessary guidelines and training.
The study was revealed that the owners of small-scale manufacturing industries were given vocational training in their business activities and these training programs positively effect on the growth of the industry. The study is recognized that most of the small-scale entrepreneurs who included in the sample have been conducting their production activities using their own experiences, which they learned from parents or their inborn abilities. It is important government and non-government agencies intervention to facilitate formal training and consultancy programmers for small-scale producers, which is positively impact on the growth of these industries.
According to the result, most of the small-scale industries in the sample use traditional technology. That technology is a labor-intensive manufacturing process. Further, it was observed that according to the nature of these industries they compel to use conventional technology. However, in comparison with conventional technology, the industries which use modern technology have been able to produce higher amount within the particular time period and higher quality products. Therefore, the introduction of suitable and practical new technology related with these small-scale industries will help to improve productivity and increased the profit of small-scale industries in the area.
References
දයාරත්න -බණ්ඩා, ඕ .ජි. (2013). කුඩා කර්මාන්ත සංවර්ධනය - ගැටලු හා ව්භවතා. කැලණිය: විද්යාලංකාර මුද්රණාලය.
Afande, F. O. 2015. Factors influencing growth of small and microenterprises in Neirobi central Business District. An international peer-reviewed journal.9:104-134.
Dayarathna-Banda, O. G. and Sri Ranjith, J.G. 2014.Deteminants of success of small business: A survey-based study in kuliyapitiya divisional secretariat of Sri Lanka. International Journal of Business and Social Research.4(6):38-50.
Pherson, M. A. 1996.Growth of micro and small enterprises in southern Africa. Journal of Development Economics. 48: 253-277.
Yasuda, T. 2005. Firm Growth, Size, Age and Behavior in Japanese Manufacturing’. Small Business Economics. 24(1): 1-15.
(University of Peradeniya, 2017-10-12) Priyatharsiny, S.
Introduction
Exchange rate is a fundamental macroeconomic variable that has various impacts on balance of payments as well as other macroeconomic variables (Odili, 2014). Exchange rate plays a major role in the international economic integration because all nations are not hold autarky equilibrium so they are holding an international economic relation with other countries (Oladipupo and Onataniyohuwo, 2011). Exchange rate refers to the price of one currency in terms of another foreign currency. Sri Lanka’s exchange rate policy has gradually evolved from a fixed exchange rate regime in 1948 to an independently floating regime by 2001. Sri Lanka, which followed a managed floating exchange rate regime with crawling bands since 1977, shifted to an independently floating exchange rate regime in January 2001 due to the strong need of maintaining a large stock of international reserves (Central Bank o Sri Lanka, 2016).
The exchange rate is a key determinant of balance of payments (BOP) of the country (Oladipupo and Onataniyohuwo, 2011). Balance of Payments is a balance of international monetary transactions engaged in during a specific period of time; government, residents and non-residents individuals and institutions in the rest of the world can be involved in such transactions. In Sri Lanka, the current crisis in the BOP of the country is fundamental weaknesses in the structure and performance of the economy over a period of time. Sri Lanka faces the BOP crisis again because current account balance remains stable but the financial account weakened with the resumption of capital out flows, inability to attract foreign investments and the country’s net international foreign reserves fell short of the target and deficit trade balance which lead BOP crisis in Sri Lanka. A sound economic and financial policy is imperative to resolve the current crisis of BOP; therefore, in this study test whether exchange rate is an adoptable variable to remove this imbalance BOP situation from the country.
There are number of empirical studies have been carried out the impact of exchange rates on BOP, although with mixed results. Ahmad et al. (2014) and Odili (2014) estimated the impact of exchange rate on the BOP by using auto regressive distributed lag (ARDL) and they found exchange rate has a statistically significant and positive impact on BOP in the long-run as well as short run. However, Ontaniyohuo and Onataniyohuwo (2011) found the result which is contradictory with Ahmad et al and Odili. Iyoboyi and Muftan (2014) confirmed a long-term relationship with associated variables and bidirectional causality between BOP and other variables employed. In Sri Lanka, Alawattage (2002) examined the effectiveness of exchange rate policy of Sri Lanka and he found that there is a long-run relationship between trade balance and the real effective exchange rate.
According to the Sri Lankan data, it is difficult to identify the clear relationship between exchange rate and budget deficit. This motivated to do the quantitative assessment between these variables since the quantitative assessments between these variables are inadequate and limited in the Sri Lankan context. Therefore, this study attempts to fill this gap by investigating the impact of exchange rate on BOP position in Sri Lanka.
Objectives
The main objective of this study is to empirically analyze the impact of exchange rate depreciation on BOP in Sri Lanka.
Methodology
There are two main theories explained the behavior of exchange rate (Olidi, 2011). First, aspect of elasticity approach to BOP and exchange rate relationship is the Marshall-Lerner condition. Elasticity states that devaluation helps to improve BOP deficits of a country by increasing its exports and reducing its imports. When the sum of price elasticity of demand for exports and imports in absolute terms is equal to unity, depreciation has no effect on the BOP situation will remain unchanged where: is the demand elasticity of exports and is the demand elasticity for imports. The sum of price elasticity is greater than unity; depreciation will improve balance of payments () . On the other hand, if the sum of price elasticity is less than unity, depreciation will worsen on the balance of payment because which increase the burden of the balance of payment deficits (). Second, monetary approach focuses on both the current and capital accounts of the BOP (Ontaniyohuo and Onataniyohuwo (2011). In this approach also indicates the depreciation leads to correct the BOP imbalance situation. Another thought is the IS-LM model, suggest depreciation is theoretically expected to have positive effect on export and it would reduce import (Iyoboyi and Muftan, 2014).
In this study has been used the time series data gathering from World Bank and Central Bank Reports spanning from 1978 to 2015. We employed the data of balance of payment (BOP), current account (CA), exchange rate (ER), inflation (INF), lending interest rate (LIR), real gross domestic product (RGDP), inflation of USA (INFUS) and lending interest rate of USA (LIRUS). Following general specification of theoretical framework was developed by Fedderke (2002) and it was expanded by Vinayagathasan and Priyatharsiny (2017) adopted to examine the above objective.
Where, is the white noise error term. Auto Regressive Distributed Lag (ARDL) co-integration technique developed by Pesaran et al. (2001) was adapted to examines the above equation. Once we confirmed the co-integrating relationship between the variables using bound testing method, then we employed error correction version of ARDL model to examine the short run relationship and long run adjustment between the variables.
Results and Discussion
The both ADF and PP unit root test approaches confirmed that none of the variables are I(2). Akaike information criterion (AIC) suggested that to use ARDL (2, 2, 2, 0, 1, 2, 0, 0) model for this analysis. Our ARDL bound testing model passes the all the diagnostic testing (see Panel B in Table 1 below).
The CUSUM test concludes that the model is stable and result of Wald test suggests that there exist co-integrating relationships between the variables under considered in this study . As expected to the theory and some of the existing studies (Ahmad et al, 2014; Odili, 2014 and Iyoboyi and Muftan, 2014), the ARDL bound testing results found that ER has positive and significant impact on BOP in the long-run. Whereas CA affect positively and significantly on BOP in the long run, which implies that positive and higher balance of CA will bring BOP surplus to domestic economy but RGDP affect negatively and significantly on BOP which implies increasing RGDP encourage to rely on imports more and reduce the export activities because of the feeling of enough income (see Panel A in Table1). The error correction version of ARDL model also passes the all the diagnostic testing (see Panel B in Table 2 below) and the stability test.
CA, ER and LIRUS in current values have a positive impact on BOP and CA in lag 2, ER in lag 1, LIR in current and RGDP in current, lag 1 and 2 affect BOP negatively in the short run (see Panel A in Table 2). As expected, the coefficient of ECT is significant and negative implies that the dependent variable can get back to long run steady state line at the speed of 99.2 % in each year one period after the exogenous shocks.
Conclusion and Policy Implications
The both co-integration bound testing approach and the error correction version of ARDL model passes the all the diagnostic test and the stability test. Our results of Wald test imply that long-run (LR) co-integrating relationship exists between the variables. ER has positive and significant impact on BOP in the short run (current value) as well as in the LR while GDP has a negative and significant impact on BOP in the short run (current, lagged 1 and 2) as well as in the LR (It followed the results of Ahmad et al, 2014; Odili, 2014 and Iyoboyi and Muftan, 2014). Further this model confirms that dependent variable can get back to long run steady state line at the speed of 99.2 % in each year one period after the exogenous shocks. In sum, this study confirms that the exchange rate depreciation improves the BOP (reduce the BOP deficit) of Sri Lanka. Sri Lanka relies on the exchange rate depreciation it can reduce the crisis of expanding BOP deficit. In sum, this study confirms that the exchange rate depreciation improves the BOP (surplus) of Sri Lanka. Sri Lanka relies on the exchange rate depreciation it can reduce the crisis of expanding BOP deficit.
References
Ahmad, N., Ahmed, R.R., Khoso, I., Palwishah, R., I. Raza, U. 2014. Impact of Exchange Rate on Balance of Payment: An Investigation from Pakistan. Research Journal of Finance and Accounting. 5:13.
Alawattage, U. P. 2002. Exchange rate, competitiveness and balance of payments performance. Central Bank of Sri Lanka Staff Duties. 34, 63–91.
Central Bank of Sri Lanka. 2016. Exchange Rate and Economic Impact of Depreciation. Economic Research Department: Central Bank of Sri Lanka. Online: www.cbsl.gov.lk
Pesaran, M. H., Y. Shin, and R. J. Smith. 2001. Bounds testing approaches to the analysis of level relationships. Journal of applied econometrics 16(3): 289-326.
Vinayagathasan, T. and Priyatharsiny, S. 2017. Impact of Interest Rate on Foreign Direct Investment in Sri Lanka: An Empirical Analysis. International Conference on the Humanities and the social sciences (ICHSS): University of Peradeniya - 267-271.
(University of Peradeniya, 2018-11-09) Brătucu, T. O.; Brătucu, G.; Chițu, I. B.; Dovleac, L.
Introduction
In many countries around the world, women‘s opportunity to build a career and to access management positions is strongly related to the society‘s mentality. Different studies show that women do not succeed in advancing to top management positions, although education and job experience do not differentiate them from men (Beeson and Valerio, 2012). Eurostat data (2017) shows that, although women represent almost half of the employees in the European Union (EU), only 35% of them are in management positions. Among the obstacles to advancement are: structural obstacles (like the role assigned by society), family responsibilities, institutional mind-sets (masculine corporate culture, lack of company equality policies etc.) and individual mind-sets (lack of role models for women) (Barsh and Yee, 2012; ILO, 2015).
Global studies show that women‘s presence in the labor market is increasingly significant for economic growth and business development (Kuhlmann et al., 2017). In this context, the authors identified the research problem as one of analysing the particularities of the Romanian young generation‘s mentality related to women‘s career opportunities. The originality of the research comes from the authors‘ idea to identify the perspective of Romanian students on the topic considering them the new generation of employees who could change the present situation. The findings of this study can fill the literature gap by bringing new information on the topic considering the particular case of Romania, a developing country inside the European Union.
Objectives
The research objective is to analyse the mentality of the Romanian young population related to women‘s efforts on building a remarkable career by identifying the students‘ opinions regarding the chances of women‘s integration in the labor market and their access to leading positions.
Methodology
To achieve the objective, the authors conducted a quantitative marketing research (a survey) involving a very large sample of 1122 students (aged 18- 35) from 10 Romanian universities. The authors collected the data during December 2016 and January 2017 using an online questionnaire posted on Google Drive platform. The sample was built using multistage sampling based on 4 criteria: geographical area, university size, faculty profile and the study level. 55% of respondents are Bachelor‘s students, 35% - Master‘s students and 10% - PhD Students. The sample structure includes 68.5% females and 31.5% males. The data collected was analysed using the statistical software SPSS 17.
Results and Discussion
The most important variables analysed in this study are: the barriers faced by female students in applying for a job, the essential skills and competencies for being employed, women‘s chances of becoming leaders and the essential attributes for women to have in order to access management positions. The most important barrier for Romanian students in looking for a job is the lack of professional experience, followed by the gap between theory (from academic courses) and practice, mentioned by a third of respondents. An important barrier mentioned mostly by female students is gender discrimination. This fact confirms the fact that in Romania, as in the European area, young women still have more difficulties to be employed than young men (ILO, 2015).
The following figure shows the students‘ opinions on the skills considered essential in order to have a good job. The females consider that elements like teamwork skills, a strong theoretical background and IT skills help a person to have a good job, and these opinions are different from the male perspective.
In the last 10 years, at the European level many actions empowering women to a larger access at managing positions became more visible, in various fields previously reserved for men. This research shows that in Romania the hope that women can become leaders is very small. Therefore, according to Table 1, only 5.7% of the respondents give women a greater than 75% chance to become leaders.
According to the study, the attributes considered a must for women to have a chance at a management career are: motivation and perseverance, professional skills and gender equality inside the organisation. The following figure shows that a woman with the highest chance to become a leader must have a variety of skills and competences. A high percentage (28.3%) considers that the ability of teamwork is essential for a leader. Also, 13.2% consider it essential to know foreign languages, 11.3% consider that it is necessary to have a solid theoretical background. Equal percentages of respondents (7.5%) mention IT skills and practical skills.
Conclusion
The research results show that in Romania women face more barriers than men in finding a job and an important reason is gender discrimination. The women interested in building a career and achieving management positions face a difficult path, the main obstacle being the conservative and obsolete mentality of the society, even for the young generation. The small trust of young generation in women becoming leaders could be the result of the traditional education, where the woman is prepared for different roles in life compared to men. The research results show that in Romania are gender deep-rooted stereotypes that define women‘s and men‘s roles inside the community also for the young generation. For a future balanced Romanian society it is important that the individuals change their mentality. The first step can be done in the educational environment where teachers should explain the benefits of gender equality. The research results show the employers that an important part of young women still felt discriminated at job interviews. So, employers need to realize is the fact that gender is not an indicator of competence. The decision to recruit, train and promote young people (women and men), must be always based on criteria linked to skills and behavior. In conclusion, gender stereotypes should be forgotten, corporate cultures should be shaped and really implemented and the lack of measures should be solved in order to give real chances to women to add value to the economy and society.
References
Beeson, J., and Valerio A.M.(2012). The executive leadership imperative: A new perspective on how companies and executives can accelerate the development of women leaders. Business Horizons, 55: 417-425.
ILO (2015).Women in Business and Management.Gaining Momentum. [online] Available at: [Accessed 15 March 2018].
Kuhlmann, E., Ovseiko, P.V., Kurmeyer, C., Lobos, K. G., Steinböck, S., von Knorring, M., Buchan, A. M. and Brommels, M. (2017). Closing the gender leadership gap: a multi-centre cross-country comparison of women in management and leadership in academic health centers in the European Union. Human Resources for Health, 15: 2.
(University of Peradeniya, 2017-10-12) Ashfaque, Ismail
Introduction-
It is woeful that in Pakistan the most crucial aspect of well-being is also the most neglected. Discussions around health policy in Pakistan’s 70-year history have received little or no space in the agenda of any government – civil or military - that has taken over. While specific health related crises such as the spread of polio and child deaths in the tend to take the media by storm, a meaningful debate around the causes actually spurring such abysmal health services is appallingly absent. The indifference of Pakistan’s government to health is reflected in the fact that a measly 0.9 % of the GDP is spent on health with only a third of that being allocated to public sector health services, leaving the public availing these services from the private sector primarily through out-of-pocket payments.
This apathy is evident in health indicators such as to name a few, the infant mortality is sky-rocketing to 66 per 1,000 births as opposed to 38 in India or a mere 8 in Sri Lanka and life expectancy in the nation for women is 67 years as compared to 73 in Bangladesh and 78 in Thailand. However, while these numbers speak volumes about the dismal quality of healthcare provided in Pakistan, they also remind us that behind these facts and figures lie heart-wrenching stories of countless lives that were ruined and cut short due to health facilities lacking the necessary care. Information failure, lack of accountability, miserly and mismanaged government funding and readiness on part of healthcare providers coupled with poor training amongst other deep-rooted problems are responsible for the dreadful condition of the country’s healthcare sector. After extensive research though we have deduced information failure as being the primal cause behind a great proportion of the problems that the healthcare sector faces and therefore our research aims to focus on solutions addressed specifically to overcome it (Malkani, 2016).
A systematic literature review being drawn from various sources has helped us analyze the major themes plaguing the health sector as a result of information failure. Assuming their prominence from the frequency of times they were mentioned in our sources along with the significance of their impact, we have narrowed down these themes and selected two to focus on for the purpose of this paper:
• Mismanaged Data Collection and Record-Keeping
• Staff Absenteeism
Keeping in special consideration the deep-rooted problems common to both the general concerns plaguing the healthcare sector and our specific areas of focus, our paper aims to expand beyond the traditional methods of physical contact with patients to the virtual platforms of e-Health as proposed solutions to correct information failure. E-health systems entail many sub-facilities including telemedicine, tele-education, telematics for improved management of healthcare and research, giving access to improved access and quality of healthcare. Both biblical and new models of healthcare are globally serving the masses side by side, with the latter pulling forward in most developed and developing societies alike, but in Pakistan the concept of e-Health is still relatively alien. Computer based health information systems are becoming the order of the day but their spread in Pakistan is still limited.
Objectives-
The main objective of this study is to identify the relationship between information failure and poor health services in Pakistan. It also will investigate whether information communication technology (ICT) can fill the gap in the future.
Methodology-
After a stringent evaluation of the sources used based on the credibility of their database (journal/website/newspaper), we compiled and analyzed data from several studies. We evaluated the methods of how ICT could be used to improve the health systems in Pakistan, and how the health system lacks behind in the country and developed policy recommendations based on the literature used in the report.
Results and Discussion-
The World Health Organization (WHO) has listed Pakistan as one of the fifty-seven countries with a critical deficiency in its Human resources for health (HRH) (MLHW 102). The problem of health workforce deficiency is two-pronged. Firstly, there is no specific department dedicated to HRH within the ministry of health, and along with the inadequate training programs and unrevised health curriculums, health force that is being produced is simply not competent enough.With an absence of a department whose specific function is to monitor the workforce, ‘slackers’ take advantage of the information failure resulting from the fact that they have to meet low standards of accountability and do not take their public-sector duties seriously. Secondly, in Sindh alone, 35.7 percent of public-sector doctors are absent from their workplace during normal working hours (Agboatwalla and Niazi, 2010). This proportion is higher amongst rural regions as compared to urban regions.
A cause of inefficiency in itself, absenteeism further abates the efficient delivery of public health services within the country by presenting a dual obstacle- not only does absenteeism translate into leakage in budgetary allocations as absence of health workers entails that budgetary allocations do not reach the beneficiaries; but absenteeism also leads to poor health service delivery due to unavailability of health personnel (Agboatwalla and Niazi, 2010).
Therefore, without the correction of information failure and a way forward being devised to improve standards of accountability and monitoring, increasing spending on the health sector is futile. Chaudhury et al. (2011) study staff attendance in health facilities in Bangladesh, Ecuador, India, Indonesia, Peru and Uganda to find that some common themes persist across countries such as generally higher absence rates in poorer regions, higher absence rates amongst higher-ranking and more powerful providers (such as the doctors), and higher absenteeism amongst men as compared to women. They also observe low evidence of financial incentives decreasing absenteeism, and instead find greater evidence that infrastructure plays a crucial role in increasing staff attendance.
We have identified the efficient keeping of medical records as a high-threat problem to Pakistan’s healthcare institution due to the fact that record-keeping is a government’s administration’s basic tool. With records that are accurate and up-to-date, viable information is provided and this lays the foundation for future decision making and planning. A structured and effective medium to maintain records is needed such that it coordinates the care the patient receives in every department that they have received treatment in; with this not only serving the purpose of the patient receiving higher quality healthcare due to the staff having access to a complete medical history but also with the records providing evidence for the hospital’s accountability for its actions and perhaps also direction for future medical research.
In line with new policies emphasizing better health care services including Millennium Development Goals, the Pakistan Government has introduced a series of federally funded vertical and horizontal programs such as Lady Health Worker Programme, Expanded Programme on Immunization, National Maternal and Child Health Programme and Tuberculosis and HIV/AIDS Control Programme. Mismanaged record keeping is not only a consequence of information failure but also a cause of it. The purpose of this section is to highlight how important it is to carry out efficient and structured record keeping by ensuring that the information failure it both entails and creates is overcome, so as to not only record medical information of patients during consultation accurately leading to proper diagnosis and treatment but also for the successful execution of any health-related initiative.
Conclusion and Policy Implications-
This report has discussed two major problems in the health sector that are caused by poor information which have often been given secondary importance in the literature on health policies. Firstly, ICT could significantly improve the condition of record keeping in Pakistan, which is a high-threat problem to the healthcare institution of Pakistan. An efficient record keeping system could improve the treatment the patient receives and also provide more informed directions for future research. The use of Electronic Health Records (EHRs) would significantly improve the record keeping system and provide quick and accurate medical information. Secondly, poor management and information flow results in stock unavailability in the pharmacies. An investment into an IT based management system could improve the budgeting and forecasts for the future, which would balance the levels of supply of different medicines. A more informed higher-level management would improve the accountability of the corruption and inefficiencies of the lower level workers.
References-
Afzal, U. and A. Yousuf. 2013. The State Of Health In Pakistan: An Overview. The Lahore Journal of Economics, 18. 233-247.
Agboatwalla, M. and T. A. Niazi. 2010. To Assess the Extent Of Absenteeism I N The Health Sector In Pakistan. Transparency and Accountability Project the Brooking Institution-WA
Ahmed, J. and B. Shaikh. 2008.. An All Time Low Budget for Healthcare in Pakistan. Journal of the College of Physicians and Surgeons Pakistan, 18(6):388-91.
Banerjee, Abhijit V., Duflo, E. and R.l Glennerster.2008. Putting A Band-Aid on a Corpse: Incentives For Nurses in the Indian Public Health Care System. Journal of the European Economic Association 6(2-3): 487-500.
(University of Peradeniya, 2017-10-12) Bandara, Praveena B.; Gunewardena, Dileni
Introduction
Sri Lanka’s Arts graduates have the lowest employment rate among graduates of the Sri Lankan (public) higher education system (Graduand employability census, 2012) and the problem of unemployment among Arts graduates has been persisting for the past few decades and has been the subject of much debate. The issue has been examined through the perspectives of students, the university system, and the private sector and government (as potential employers). Many studies point to structural unemployment, as the cause of the issue. A tendency on the part of the government to resolve the issue by hiring arts graduates is said to have led to more problems such as under-employment and relatively low salaries. Therefore, current solutions look to the private sector and require graduates to make themselves more ‘employable’ by acquiring skills required by the private sector, such as I.C.T and English language skills (Ariyawansa, 2011).
In the neo-classical model of human capital, engaging in education is seen as a form of investment in human capital where benefits accrue in the long term, in the form of higher earnings. Furthermore, the neo-classical human capital model elaborates that, irrespective of investments in human capital, different levels of innate ability of individuals will be translated into different levels of productivity at the work place. Here ability is defined in relation to the demands of employment and therefore could mean physical strength or intellectual capabilities. Alternatively, there is also the idea that education performs a signaling function (Arrow, 1973), where educational attainment of prospective candidates may not necessarily have a direct relationship to productivity, but nevertheless acts as a signal of ability to interested employers. Accordingly, employers will therefore use education as a screening device as they believe it reflects innate ability.
Hanushek (1995) builds on the idea of education production functions which is similar to a (physical) production function relating inputs to outputs. Hence an education production function shows that student outcomes – schooling attainment (usually measured as years of schooling) or schooling achievement (reflected in a score in a standardized test or examination), depends on a multitude of input factors that affect student learning. A study by Harmon et al. (2011) with regard to the Irish tertiary education system, analyzes the relationship between socio-economic status and student outcomes at university level. The study analyses student outcomes (performance in their degree program) as a function of parental socio-economic status, prior educational attainment, characteristics of the institution and course attended and characteristics of the student (gender, age, personality measures, etc).
Recent studies in education, particularly by James Heckman, indicate that a variety of outcomes are determined not just by years of schooling, but also by cognitive and non-cognitive skills (Heckman et al. 2006). The latter include not just technical skills or “employability” skills like English and Information Technology, but also socioemotional skills sometimes known as personality traits. Kautz et al. (2014) argue that these are malleable, and therefore should be considered skills that can be acquired rather than traits that cannot be changed.
We argue, that the (low) initial (entry level) ability of arts/humanities undergraduates is a significant constraint in ensuring high performance outcomes at university level, leading to a problem where the majority of students are not competent enough to secure themselves jobs (especially in the private sector) upon leaving the university. We follow Harmon et al.’s (2011) approach, to explore the link between initial ability of students’ (at the point of entering the faculty of arts), their socio-economic status, and their outcomes of academic achievement. We include in the analysis the effect of personality traits, also known as non-cognitive skills, on student outcomes. The results of this study provide an indication of whether the faculties of Arts of Sri Lankan universities (as proxied by the University of Peradeniya) are absorbing the right input to ensure an output of a higher quality – an employable graduate.
Objectives
The primary objective of this study is to identify the nature of the relationship between the GPA (outcome) and the Z – Score received at A/L as a measure of initial ability. Secondary objectives included, identifying the effect of the socioeconomic background of a student on performance at university level and ascertaining the impact of socioemotional skills or personality traits on academic performance of a student.
Methodology
The model is a form of an education production function. The left-hand side variable is student outcome and the right-hand side variables are student inputs. Variable definitions are provided in Table 1.
Student outcome = f (Entry requirement, S.E.S, Personality traits)
CGPAi = α + β (Zi) + θ(MNYEi) + χ(FNYEi) + Ϟ(GGY) + φ(SOC) + λ(Oi) + γ(Ci) + ρ(Ei) + κ(Ai) + ω(Ni) + εi
Here the student outcome is the current grade point average of a student, which is dependent on, the entry requirement - the Z-score, the number of years of education of the father and mother (included as two separate variables) is used as a proxy for a students’ socio-economic status and the personality test scores of the big five personality traits. The scores were computed and standardized to facilitate comparison. Additionally dummy variables for the area of specialization were included as well.
Primary data was obtained from 60 students specializing in the areas of Economics, Geography and Sociology from the Faculty of Arts University of Peradeniya, through a questionnaire designed for the purpose of the study, which collected information on the variables listed in Table 1. Measures of socioemotional skills were obtained from questions based on the survey instrument of the STEP Skills Measurement Surveys – World Bank (2014). Students were selected using a random stratified sampling method, where subject specializations formed the strata. Sub-samples of students were randomly selected where class lists provided the complete listing of all students within the strata.
Results and Discussion
The results show that Z-score is significant at 10 % level of confidence, father’s number of years of education is significant at 1%, dummy variable for Geography is significant at 0.1%, personality traits of conscientiousness and agreeableness both are significant at 5% level of confidence. A change in the Z-score of a student by one point has a positive effect of 0.242 points on the CGPA, which is equivalent to 80 % of the interval between letter grades including + or – (for example, a B is 3.0 while B+ is 3.3) while an increase in the father’s number of years of education by one year increases the CGPA by 0.0312 points.
The performance of a student specializing in Geography is 0.354 points. less than of a student specializing in Economics. The performance of students specializing in Sociology and Geography are a class (second upper vs. second lower) below the performance of students specializing in Economics. For example the average Z-score of a student specializing in Geography is 1.72 and their average CGPA is 3.11 vs. the average Z-score of a student specializing in Economics is 1.76 and their average GPA is 3.48). Therefore it can be said that there is a tendency for students to be segregated into departments according to initial ability, where some departments absorb more able students than others. This may be a point of concern as a lack of distribution of students according to ability among the fields of specialization may mean that there is a chance of graduates specializing in a particular field being prone to unemployment than others. This may also be reflected in the claim that some programs within arts faculties lack quality.
Additionally, Conscientiousness has a negative effect on performance where a student who is more conscientious will lose 0.0888 points for having such a disposition while agreeableness is rewarded by the addition of 0.0737 points into their CGPA. Conscientiousness is defined as “the tendency to be organized, responsible, and hardworking” the fact that not only are hard-working students not rewarded but that they are penalized, as pointed out by the regression analysis should be a point of concern.
It is observed that the Z-score cut off point for the Arts stream fluctuated around 1.3 points for decades. This was the case till 2014, when the cut-off point for the Faculty of Arts of the University of Colombo, started to pick up and stood at 1.7 in 2015. A similar development can be observed for the University of Peradeniya (1.6) in 2015 as well. There are signs of other universities following this trend (Sri Jayawardanapura 1.5) but as of now the cut-off point to enter the arts faculty of most other universities lies between 1.1-1.3. Given the results of this study a continuation of this trend of advancing of the standard is a welcome development. Furthermore, raising the quality of education received by school level students may contribute in producing more competent students. Drawing from the neo-classical model of human capital, it can be deduced that better learned parents are also higher earners (investment in human capital is made with the aim of maximizing life time earnings potential). Therefore, the results also imply that children of richer parents perform better.
Conclusion and Policy Implications
The Z-score cut-off point depicts the average performance of the cohorts of students entering into different universities. Currently, there is a large variation in the Z-scores (cut-off points) of students entering into the Arts Faculties of the public universities. Thus, when considering the policy implications of this study, given the positive relationship between the two variables, it is advisable to take steps to reduce the large variation in the standard of admittance into the Faculty of Arts, by raising the standard up to a common higher standard acceptable by all universities.
The current variation in the cut-off points of Z score maybe attributed to the variation in quality between degree programs offered by universities. Thus steps need to be taken to reduce the drastic difference in the acceptable standards between universities by standardizing degree programs. Also, raising the standard of admittance cannot be done exogenously; artificially setting a higher standard will not be beneficial to either the universities or the students. What is needed is an endogenous increase in the standard of performance of students engaging in education through the arts stream at the school level (Advanced Level class).The results of the study also indicate a positive relationship between parental educational achievement and the child’s performance.
References
Ariyawansa, R. G. 2011. Employability of Graduates of Sri Lankan Universities. Sri Lankan Journal of Human Resource Management, 1(2), 91–104.
Delaney, L., Harmon, C., and Redmond, C. 2011. Parental education, grade attainment and earnings expectations among university students. Economics of Education Review, 30(6), 1136–1152. http://doi.org/10.1016/j.econedurev.2011.04.004
Hanushek, E. 2007. Education Production Functions. Palgrave Encyclopedia
Ramanayaka A, Jayarathne I, Ramayadevipriya Y, Perera K .2012). Graduand employability census 2012. Ministry of Higher Education.