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, 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, 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.
(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.
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Truex, R. (2010). Corruption, attitudes, and education.survey evidence from Nepal. World Development, 39(7): 1133-1142.
Introduction
The importance of the agrarian sector has long been debated in development theory. The sector not only serves as a pool of surplus labor, but also provides food security to the economy, employment while industry is at its nascent stage, raw-materials to fledgling industry and a source of demand for the industrial sector‘s products (Karunarathna, 2014). However, the Indian agricultural sector has been reeling under socio-economic distress over the past two decades. Agricultural output growth in the 1980s was 3.19% and it fell to 1.58% in the 1990s. Per capita availability of arable land has experienced a fast decline in the recent past, falling from more than .2 hectares per person in 1980s to less than .15 hectares per person. The productivity rates for all major crops; wheat, paddy, pulses etc., have been falling. The same period has also witnessed incidence of suicides among farmers. The toll has reached about three lakh farmers. With agriculture providing only 14% of the national GDP, roughly 50% of the population depends directly or indirectly on the sector.
Against this background, it becomes important to study the changing role of the agriculture sector when confronted with structural transformation. Structural transformation in its core also means changing inter-sectoral linkages over time. Empirically, in the context of India a number of studies have focused on explaining the trend of these linkages. Mathur (1990) concluded that agricultural growth is a necessary condition but not a sufficient condition for industrial growth. There are various non-agricultural factors like power, transport infrastructure, institutional finance, etc. that are important for the growth of industry. Kanwar (2000) studied cointegration of different sectors in a multivariate autoregressive framework and found that growth in agriculture, infrastructure and services sector affect income generation in the manufacturing sector, while the reverse is not true. Sastry et al (2003) using the input-output tables found that agriculture still plays a significant role in determining the overall growth of the economy through its linkages with other sectors. Kaur et al (2009) used both input-output tables and co-integration analysis and found that agriculture exhibits strong demand linkages with the industry sector, while the industry sector‘s demand dependence on agriculture has weakened since the 1990s. Further, through cointegration analysis they find strong long-run equilibrium among primary, secondary and tertiary sectors.
Objective
The Agriculture Sector is thought to be the initial reservoir of resources until other sectors start producing a surplus of their own for re-investment. Transfer of surplus from one sector to another happens through exchange where the exchange can either happen in a free market or can be mediated by the government. However, it is argued that over time the industrial sector diversifies beyond agro-based industries. Further, with the opening up of the economy domestic sectors form important linkages with the foreign sector thereby affecting domestic sectoral inter-dependence (Thirlwall, 1986; Vogel, 1994). Our hypothesis is that over time, the agriculture sector‘s exchange either in quantity or in value with other sectors has become weak, which has exacerbated the distress. If the people in the agriculture sector are not able to generate enough value for their commodities so they can reap enough surplus for investing in the next cycle then surely they will be left to subsist with minimum means.
Methodology
Data is obtained from the Data Book for Planning Commission prepared by Central Statistical Organisation of India. This provides time series data from 1950 to 2014 on GDP at factor cost for the sectors; agriculture, industry, manufacturing and services at constant 2004-05 prices.
We apply causality test in a bivariate framework on the long time series data based on Granger (1969). According to Granger (1969) the notion of causality is based on the assumption that the future cannot cause the past. Consider a bivariate VAR model with two variables, Xt and Yt, where both Xt and Yt are two stationary stochastic processes. In such a framework, Xt is said to Granger cause Yt if we are able to make better forecasts of Yt with all the information available than if the information independent of Xt had been used. To test the causality relationships following model is used.
Toda and Yamamoto (1995) present a lag-augmented approach to rectify the non-standard Wald statistic. The T-Y approach ensures that the asymptotic distribution is valid regardless of the order of cointegration and is immune to lag selection tests. Instead of the VAR (p) in the above equations, they estimate an augmented VAR (p+d) model, where d is the order of integration. For most macroeconomic data, the order of integration is 1, so d=1 in most cases. Further, a non-parametric test based on Heimstra Jones (1994) improved upon by Diks and Panchenko (2005, 2006) is applied. Apart from bivariate VAR, multivariate VAR is also applied. It tests the conditional independence of the variables with critical values based on asymptotic theory. The test can be run for a multivariate case where, under the null the conditional distribution of Z given (X, Y) = (x, y) is the same as the conditional distribution of Z given only Y = y.
Results and Discussion
The analysis was started at a broader level to test the causality between agriculture sector and non-agriculture sector as a whole. The non-agriculture sector includes the industry sector, which, in turn includes manufacturing and infrastructure, and the services sector. As can be observed, our results tell us that there is uni-directional causality from non-agriculture towards agriculture. In other words, growth in the non-agriculture sector GDP Granger causes growth in the agriculture sector GDP. Further, the non-agriculture sector was broken down into its component parts and the same analysis was run. As it turned out, no test projected significant results for the individual sectors. Since, the data on national GDP already includes the data on agricultural growth, so there could be a feedback from the agriculture sector to itself. There could be a problem of double counting of the agriculture data.
1990 served as a period of tectonic structural change for the economy. Based on this we break our period of analysis into two: before and after the reforms. A uni-directional linkage was observed between the agriculture sector GDP and the industry sector GDP; i.e. growth in industry sector GDP Granger causes growth in the agriculture sector GDP. So, the causality running from national GDP to agriculture can be explained through this link between industry and agriculture.
Parametric tests make quite rigid assumptions about the density functions of the time-series data. Moreover, they assume that the relationship between variables is linear in nature. We are unable to reject the null hypothesis of non-causality. There could be a case where the presence of a third variable might be affecting results. Hence, Multivariate non-Parametric causality tests were also performed, which control for the presence of the third variable. As can be observed, once the restrictions were removed and more variables were added, the results changed completely. The agricultural sector‘s growth has followed a variable path over the years (Twelfth Five Year Plan, 2013). This erratic behavior in the output growth of the agriculture sector could have been normalized due to the restrictions that were placed on the parameters of the first test. However, once restrictions are removed the causality is no longer sustained. The literature on inter-sectoral linkages has argued that growth in agriculture is linked to growth in non-agriculture. However, we have found no evidence to support the argument that the growth of the sectors is inter-dependent.
Conclusion
The theory on economic development, and growth models have consciously or inadvertently talked about the linkages between different sectors of the economy. Our focus in this study has been to explore the linkages between the two sectors i.e. agriculture and industry. If the framework of growth follows a pattern of a feedback, from within and externally imported from other sectors, then our understanding is that this relationship can help us recognize the reasons why the individual sectors are suffering from lower growth. To begin with, we initiated the study by developing a macro picture of the situation and how it has evolved over the years. We ran a series of parametric and non-parametric tests. However, our results from non- parametric tests have completely overturned these conclusions. When we loosen the strict assumptions of parametric tests on our data of 63 years, the models show us that no long-term relationship exists between the sectors. Even if it did exist, it was not sustained over the years. Both our conclusions give us new information that is different from the results of our academic contemporaries who have undertaken similar studies. Through similar and less robust techniques they have concluded that agriculture still plays an important role in economic development and there is feedback from agriculture to other sectors. However, that has not been the case in our study.
On the contrary, our results, from parametric tests, show the causality runs from the other sectors towards the agrarian sector. This understanding when juxtaposed with the current predicament of the agrarian sector is quite ironic. The lack of inter-dependence of the sectoral growth rates means that the sectors have been financing their own growth over the years. Given that the agriculture sector employs around 50% of the population with limited ability to trade with other sectors and small employment elasticity of the non-agricultural sector, agriculture sector does not generate enough value for investing in the next cycle of production. This leaves the sector at the mercy of banking and insurance companies whose presence in the rural areas has also diminished in the last two decades. India has followed an unbalanced growth strategy with focus on the industrial sector and currently, the service sector. Over the last two decades the agriculture sector has witnessed a falling rate of public investment. The decoupling of growth means that investment and growth are not trickling down from the modern industrial sector and public investment in the agriculture sector needs to be revived to bring the sector out of distress.
References
Adelman, I. (1984). Beyond Export-Led Growth. World Development, 12 (9): 937-949.
Diks, C. and V. Panchenko.(2006). A new statistic and practical guidelines for nonparametric Granger causality testing. Journal of Economic Growth and Control. 30: 1647-1669.
Kaur, G. and Sanjib, B. and R. Rajesh. (2009). An empirical investigation on the Inter-sectoral linkages in India, Reserve Bank of India Occasional Papers, 30 (1): 29-72.
Karunarathna, M. (2014).Estimating technical efficiency of vegetable farmers in Anuradhapura district in Sri Lanka. Sri Lanka Journal of Economic Research.2(2): 55-67.
Thirlwall, A.P. (1986).A General Model of Growth and Development on Kaldorian Lines, Oxford Economic Papers, New Series, 38 (2): 199- 219.
Sastry, D. V. S., Balwant, S., Kaushik, B. and N. K. Unnikrishnan (2003) Sectoral Linkages and Growth Prospects: Reflections on the Indian Economy, Economic and Political Weekly, 38 (24): 2390-2397.
(University of Peradeniya, 2018-11-09) Tofan, M. Ș.; Brătucu, G.; Chițu, I. B.; Dovleac, L.
Introduction
There is a wide variety of health systems around the world, with many organizational histories and structures as nations. By default, each country has to create and develop health systems according to its needs and resources, although common principles are found in almost all health systems. Since 2000, more and more initiatives have been taken at the international level to strengthen national sanitary systems. Given this scope, it is necessary to have a clear and unrestricted vision of national health systems that could generate new global health developments (Handler et al. 2001).
Globalization works with mechanisms that influence each other, such as market liberalization, integration policies and institutions, the emergence of new technologies and international rules (Eșanu 2012). At the theoretical level, each country has resources available if it is effectively prioritized. A study conducted by the European Commission in 2013 reveals that 73% of Romanians consider that the health services do not have the expected quality, while the average of those dissatisfied with the quality of medical services at the European Union level is 27%. Due to deficiencies of sanitary systems, it is important to focus on primary and family medicine, accessible to those with low and very low income (World Health Organization and the World Bank 2017). There are a variety of reasons why people's needs are not satisfied, such as: services have too high rates, the distance to the unit/physician is too long (making them inaccessible), the waiting list is too long (appointments are hard to get).
Economic redistribution, as well as increased democratization of the processes associated with economic decision-making and the means of reproduction of social institutions, would lead to the development of the economy and health. The latter includes educational facilities, healthcare services and social services that could allow new generations to prevent serious or incurable diseases (Benatar et al. 2011). The health system in Romania has a very large gap compared to countries such as the Czech Republic, Poland, Greece, Bulgaria (EU Member States), but national development policies and strategies also aim at reducing this gap by: investing in the sanitary public system, implementing screening programs for incurable diseases, developing partnerships between private health clinics and EU health funds. Also, the importance of globalization could be seen through the development of partnerships between the national health system and other countries in order to treat Roman patients.
The death rate due to cancer in the European Union was 1,036 deaths per 100,000 inhabitants in 2015, with the highest death rates being Bulgaria (1,660 deaths per 100,000 inhabitants), followed by Romania (1,530 deaths per 100,000 inhabitants) (Eurostat 2018). In Romania, in 1995 there were 36,673 new cases of tumor-based illnesses, and in 2016 the number of new cases reached 98,856. In terms of tumor-based deaths, in 1995, 37,359 people died of oncological diseases, and in 2016 the number of deaths reached 51,803.
The research problem is the analysis of statistics about the Romanian health system compared to the international ones regarding population access to treatment, education, screening programmes, in order to identify some solutions for catching up with the globalization of health system. The originality of the research comes from the authors‘ idea to identify the situation of Romania in comparison with the European Union in terms of healthcare and breast cancer statistics. This comparison was made taking into consideration the fact that Romania is a developing country which needs worthy models in order to protect its population‘s health.
Objectives
The paper aims to present the statistics on the Romanian public and privatehealthcare system and how health access can be difficult for some parts of the population. The research objective is to analyse health inequalities (access to healthcare, income) and how the lack of health education affects the statistics of breast cancer in the case of Romanian women. The purpose of these analyzes is to see the opportunities of the Romanian health system offered by globalization.
Methodology
To achieve the objective, the authors conducted a descriptive marketing research in order to present the bond between globalization and the Romanian health system in terms of breast cancer statistics and inequalities in access of healthcare because of the migration of human resources and the lack of primary health in the entire country. The lack of health education can lead to much higher spending for the state budget, making it much easier to prevent than to treat. This study is based on secondary data analysis. The data used for the analysis are obtained from the Romanian National Institute of Statistics and from Eurostat (statistical office of the European Union).
Results and Discussion
In Romania, the evolution of the healthcare system is closely linked to medium and long-term economic development. Differences between areas in terms of the access and quality of healthcare services presents a gap that can only be recovered with well-established policies. The fragility of health system earnings has been seen as a response to economic, political and social changes and instability in recent years (Sen and Bonita 2011). Meanwhile, the private medical services market in Romania grows with about 10% per year and it was estimated in 2016 at over 700 million euro. In recent years, in Romania, the number of private health service providers has increased, largely due to the poor quality of public health services, outdated endowments, and equity of services. The public health system has a lot of gaps, not from the point of view of the physicians who provide services, but because of lack of a unitary health system.
According to Romanian National Institute of Statistics, at the end of 2016 there were 367 public hospitals, 187 private hospitals and 3 public hospitals with private areas. In 2007, there were 22 private hospitals in Romania, so their number increased more than eight times in ten years, while the number of public hospitals fell from 425 in 2007 to 366 in 2016. Romanians tend to choose a private hospital at the expense of a public hospital in the urban areas. The following chart is based on the Institute's data:
The European Commission's Working Paper "Investing in Health" shows that the health of the population also affects economic prosperity (European Union, 2018). Education has an essential role to play in preventing various diseases, and especially in understanding the strategies used to promote campaigns. Education includes components such as: patient education, school education, mass media, health communication (Nutbeam 2000). All these concepts are closely linked to globalization and adaptation to the highest standards of population health. In the last few years, public authorities have shown a growing concern to provide quality health services and the increase in health budgets has exacerbated the need for information and by default the research on the accessibility, quality and cost of providing good health services (Enăchescu 2007).
In fact, Romania is ranked the penultimate place in Europe as regards the percentage of the female population that has breast-controlled at least once in life and the last place in terms of the number of women who have performed a test at least once in their life in order to prevent cervical cancer. The study conducted by the European Union in 2012 is still valid today because in 2018 Romania is among the last three EU member states that have not yet implemented a national breast cancer screening program (Figure 2).
The consequence is the mortality rate caused by this disease in Romania which is 36%, higher than the European average (29%). In Romania, in 2017, 21 new cases of breast cancer are detected daily, and breast cancer is the main cause of female mortality in Romania (at every 3 hours a woman dies from this disease). However, the big health problems faced in the whole world demonstrate that the state of healthcare concern is still at the beginning.
Conclusion
The research results show that Romania does not currently have policies and strategies geared towards the real evolution of the healthcare system. Globalization in the health field can have a positive influence on the reduction of cancer mortality rates, thanks to facilitating the exchange of information and best practices used globally. More than 9000 women are diagnosed with breast cancer annually in Romania, 33% of them are diagnosed in stage IV, when options therapies are minimal. Breast cancer in Romania is the oncological disease with the most victims among women.
Sanitary education can help to create patterns that can describe the symptoms that can lead to breast cancer, understand the importance of prevention and apply good practice in this field. All these efforts would help the country's evolution and then remove health gaps and help the country align with global health policies. Another key issue is the medical staff, globalization being a factor that has led to a migration of the necessary human resources (which is a reason of the difficult access to healthcare), due to the unsatisfactory incomes in Romania, as well as the difficult working conditions. In poorly developed or in developing countries, even if the population had access to medical services, they would not afford the medication needed to treat serious diseases such as cancer. In order not to get into that impasse, prevention and education are very important. The research results show that Romania has an urgent need to implement a breast cancer screening program. Such screening programs can lead to very important results and can help in decreasing the funds needed to treat a breast cancer discovered in the advanced stage, precisely by early detection.
In conclusion, globalization can be used to the advantage of health systems with the help of policies and strategies created by the profile of each country because targeted populations are not similar in terms of attitudes and behaviors.
References
Handler A, Issel M and B. A.Turnock.(2001). Conceptual framework to measure performance of the public health system. A.J. of Public Health, 91(8): 1235–1239.
Eșanu, A. (2012). The concept of "global health" from the perspective of globalization, Chișinău: CEP Medicina. Current public health issues and management, (2):553-557.
Benatar, S., Gill S. and I. Backer. (2011). Global Health and the Global Economic Crisis, American Journal of Public Health, 101(4): 646– 653.
Sen, K., Bonita, R. (2011) Global health status: two steps forward, one step back, The Lancet, 365(9229): 579-582.
Nutbeam, D. (2000) Health literacy as a public health goal: a challenge for contemporary health education and communication strategies into the 21st century, Health Promotion International, 15(3).
(University of Peradeniya, 2018-11-09) Kumara, T.; Sevatkodiyon, N.; Abeyweera, G.
Introduction
Remittances play an increasingly important role in developing countries, particularly in the economies of South Asia. Sri Lanka is one of the economies that receive a high value of international remittances in the Asian region. There is a growing interest on studying how remittances are spent and to find out whether its usage affects economic development. The inflow of remittances to Sri Lanka is increasingly contributing to the rapid growth of the country‘s GDP which was 9% (CBSL, 2015). The exchange rate was also depreciating significantly in the past couple of years increasing the domestic monetary value of remittances. There are three main arguments on the use of international remittances in household expenditure. Randazzo and Piracha (2014) state that the remittance receiving households may perceive the international remittances as transitory income, compensatory income or as just another source of income, and as a result the expenditure pattern may depend on the nature of perception.
Remittances are a key element in identifying the net impact of international migration on the country of origin. In Sri Lanka‘s national accounts, workers remittances are treated as a component of national savings. There is a growing interest on how remittances are spent and whether the use of remittances may have an impact on the economic development of the country. Although there are several studies on remittance to Sri Lanka from international migration such as Samaratunge et al, (2012) and Prabal and Ratha (2012), little is known of the impact of international remittances on household expenditure patterns in the recent past.
The existing literature provides contradictory arguments on the way remittances are perceived by the remittance receiving households. For example, Samaratunge et al, (2012) and Chami et al. (2005) consider it as compensatory income whilst Mahapatro et al. (2015) and Tabuga (2008) suggest it is transitory income, and Randazzo and Piracha (2014), as well as Adams, Jr. (2005) argue that it is just another source of income. Hence, the objective of this research is to analyze the impact of international remittances on household expenditure patterns in Sri Lanka and thereby generate policies for effective use of international remittances in Sri Lanka.
Objectives
International migration in Sri Lanka is in an increasing trend over the past two decades and international remittances follow the same. Sri Lanka is one of the leading economies in the South Asian region with a rapid growth in foreign workers‘ remittances. The existing literature argues that international remittance significantly affects the expenditure patterns of the households. In this context, this paper examines the impacts of international remittance on the household expenditure patterns in Sri Lanka and investigates how remittances are utilized by the remittance receiving households. The main objective of the study is to analyze the relationship between the international remittances and the total household expenditure disaggregated by food, non-food, and liquor, drugs and tobacco expenditure.
Methodology
The study was conducted using secondary data collected from the Household Income Expenditure Survey (HIES, 2012/13). The HIES data is collected as a year-long sample survey conducted in 12 consecutive monthly rounds, covering all 25 Districts. The study uses Ordinary Least Squares (OLS) as one of the main analytical techniques, while the Propensity Score Matching (PSM) method is applied to overcome the possible selection bias due to the endogeneity in the household receipt of remittances generated by OLS. This problem was highlighted in Yang (2005). To deal with this issue, expenditure behavior of households receiving remittances should be compared with that of similar households without migrants while controlling for the endogeneity of migration choices and thereby, remittances. Therefore, the study employs the PSM method as an alternative approach. International remittance to the household was the dependent variable and age of the household head, highest education in the family, household size, land size, employment status, and wage income were the major independent variables included. Working-Lesser Model was taken as the major theoretical model for the analysis.
Results and Discussion
The inflow of international remittances is increasing over the years. In 2013, the remittances received from international migration by the households was Rs.6.4 billion or 8.64% of the country‘s GDP and in 2015 it was Rs.6.98 billion, amounting to 9% of the GDP (CBSL,2015). Therefore, it is important to explore what changes this increasing amount of remittances makes on the consumption pattern of the households. Average consumption of a household in Sri Lanka in the survey year was Rs. 41,587 while average consumption of a remittance receiving household and non-remittance receiving household was Rs. 45,738 and 41,322 respectively. This shows that on average a remittance receiving household spends more than the amount spent by the non-remittance receiving receiving household.
The analysis in the paper is mainly based on OLS regression and Propensity Score Matching (PSM) method. After controlling for the other variables, OLS estimates suggested that compared to a non-remittance receiving household, a remittance receiving household spends more than Rs. 7000 which was statistically significant at 99 %. Further, it showed that remittance receiving households spend more on non food expenditure. OLS analysis also suggested that education and household size has a positive statistically significant effect on household consumption.
PSM analysis showed that the coefficient of the average treatment effect of the treated is 8287.69. This implies that the households who are receiving international remittances spend approximately Rs. 8288 more than households who do not receive international remittances. Furthermore, the analysis found that the households who receive international remittance spend more than Rs. 1212.47 on food, compared to households that do not receive international remittances. Importantly the results generated by using PSM analysis confirmed that, compared to the households not receiving remittances, households which receive international remittances spend more on non-food items such as durable goods, healthcare, education and investments and they spend less on food,and liquor, drugs and tobacco. The coefficient of the expenditure on non-food was Rs. 4442.6 which is strongly supported by Mahapatro et al. (2015), Adams, Jr (2006) and Tabuga (2008) which found that households who received remittances spend on investment activities and less on consumption. The households with similar characteristics of receiving remittances are compared using PSM technique. The study used the nearest neighbor matching method to estimate the average treatment effect on the dependent variable. However, the study suggests that there is no relationship between international remittance and household expenditure on liquor, drugs and tobacco. This could be due to migration of male (male household‘s heads) member(s) of the family.
< Table 1: Estimated coefficients using PSM and OLS analysis>
Conclusion
International remittance has become an important foreign currency earning source in Sri Lanka and can potentially play a significant role. The analysis showed that international remittances have a stronger impact on household expenditure; especially the expenditure on non-food items (durables). But, receiving remittance does not have any statistically significant impact on expenditure on liquor and tobacco. The OLS and PSM estimates generated similar results. Therefore, the study confirmed that the international remittance receiving households tend to spend more on investment goods while spending less on food items and alcohol. As the international remittances increase the expenditure on non food and non alcohol items, the study recommended that entrepreneurs should be given more opportunities to attract investment from the families with international remittances.
References
Adams, R.H. (2005). Remittances, Household Expenditure and Investment in Guatemala. Policy Research Working Paper. Work Bank.
Randazzo, T. and M. Piracha. (2014). Remittances and Household Expenditure Behaviour in Senegal, IZA Discussion Paper No. 8106, Germany.
Samaratunge, P., Jayaweera, R. and N. Perera. (2012). Impact of Migration and Remittances on Investment in Agriculture and Food Security in Sri Lanka. Institute of Policy Studies of Sri Lanka, Colombo.
Tabuga, A.D. (2008). International Remittances and Family Expenditure Patterns: The Philippines' Case. Philippine Journal of Development, 35(2).
Yang, D. (2008). International Migration, Remittances and Household Investment: Evidence from Philippine Migrants‘ Exchange Rate Shocks. The Economic Journal, 118(528)
(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) 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) Shrestha, R. N.
Introduction
A high youth unemployment rate as well as a high labor migration rate in Nepal has caused much debate in recent times both in policy circles and academia. Migration is in an increasing trend and unemployment trend is largely the same. Annual Household Survey of 2013 showed that the unemployment rate was 3.3 percent whereas time-related unemployment was 13.4 percent and labor underutilization rate was about 27.8 percent. This depicts the problem of unemployment and underemployment in Nepal‘s labor market (CBS, 2015). If we look for the corresponding figures for youth (age15-29), the unemployment rate is 19.2 percent and if we consider the relaxed definition of unemployment, this figure reaches 28.9 percent (Serrière, 2014). The youth unemployment rate is even higher among the highly educated.
The labor market in Nepal is characterized by a large informal sector within a low productivity agriculture based economy. The problem of underemployment, inadequate earnings and skill mismatch are features of the employed in Nepal. Afram and Del Pero (2012) point to rigid labor market regulations and unionization as obstacles to job creation and the hiring of workers through formal contracts. Lower productivity in the agriculture sector and lower wage rates are pushing youth to seek alternative employment options. Labor migration has emerged in a great way as the means of securing employment. Those youth who are employed are also mostly employed in informal sectors with little or no social protection (Serrière, 2014). Like in other developing countries, the youth in Nepal take a long time to get "decent jobs" and the issue of youth (un)employment has been incorporated in the National Youth Policy 2010. The lack of "desirable" employment (in terms of employment opportunities and well- remunerated jobs), (real or perceived) low returns to education, desire for family‘s economic well-being, etc. are often cited as the main reasons for migration (Sijapati et al. 2017). Though Nepal is predominately an agricultural economy, reluctance to work in the (subsistence) agriculture sector and considering it as "dirty job" is another reason which has both promoted unemployment and migration among youths in Nepal (Gartaula et al. 2012). Since agriculture in Nepal is a subsistence livelihood it may not fulfill the aspirations of the young. While there is high unemployment among youth in Nepal, enterprises looking for employees find difficulties in finding applicants with the right skills and competencies (Serrière, 2014). In this way, the problem of (un)employment and youth migration in Nepal are interlinked.
Objectives
In this paper, we examine determinants of work-related migration intentions among the youth in Nepal. This paper examines their willingness to move for work and its relation with labor market indicators for both employed and unemployed youth. Both employment and unemployment are not homogenous categories. Employment rate or unemployment rate alone cannot explain variability in labor market conditions. We explore how specific labor market situations may affect migration aspirations. Using intention data has certain advantages. First, studies have shown that intended migration is a predictor of actual migration though there are exceptions. Second, intention data should be seen as potential migration rather than actual migration and this gives the mirror image of the future prospects of the country.
Methodology
We use data from the School-to-work-transition (SWTS) survey for Nepal conducted by the International Labour Organization (ILO) in 2013, covering 15-29 year-olds. The survey contains information on various aspects of labour market conditions, history of economic activities and perceptions and aspirations of youth. The survey is nationally representative and the sample size is 3584. We use a sub-sample of 1932 from 3584 including only those youths who are either employed or available for work (relaxed unemployment). Those who are still in education or undergoing training and not seeking to work are not included in the analysis. We apply survey weights to make it nationally representative. We also employ multinomial logistic regression to analyze the various determinants of the work-related youth migration intentions. We analyze a baseline model for the whole sample including both employed and unemployed youths and two separate analyses for the employed and unemployed youths.
Results and Discusstion
The focus was on effects of labor market conditions on migration intentions. Our analysis highlighted the importance of employment status (in terms of (un)employment as well as quality of (un)employment) in migration intentions. The result shows that gender plays a significant role in explaining migration intentions. Females have a lower intention for migration as compared to males. This result mirrors the real migration trends where most of the migrants are male. Income level of household is significant for internal migration only. Those who are poor are more likely to migrate internally. Those having an education at or below primary level have a higher intention of international migration as compared to those having secondary level education. Youths in rural area mostly intend to migrate internally whereas youths in urban areas have higher aspirations for international migration.
Compared to employed youth, unemployed youth show higher aspirations for migrating both internally and internationally. Employed youth can be categorized into two groups: those transited and those who are still in transition. Unemployment is also categorized as unemployed and inactive. This shows that youths having temporary or unsatisfactory employment (not transited) are more likely to have higher migration intentions as compared to those having stable employment. This highlights the importance of quality of employment in explaining migration trends in Nepal. This demands further analysis on the indicators quality of employment. We have extended analysis to employed and unemployed youths separately.
Youths employed in informal employment are more likely to have higher migration intentions as compared to those employed in formal employments. Similarly, those working as employees are more likely to have higher migration intentions. This indicates the bleak labor market prospects. Youths who want to change their employment see migration as the feasible option indicating problem in local labor market prospects. Youths in agriculture sectors are more likely to have international migration aspirations compared to those employed in the service sector. Similarly, youths having higher level of skills have a higher intention of international migration indicating ―brain-drain‖. Poor labor market prospects are not able to hold skilled labor in the domestic labor market.
Youths who are not in the labor market and who have a preference for a minimum income level (below which they don‘t work) have higher aspirations for international migration. Similarly, those who have applied for jobs before but are unemployed till now are more likely to have aspirations for both internal and international migration. This, again, portrays the poor local labor market conditions. Demand side constraints in finding jobs have significant effects on determining internal migration.
Conclusion
Our analysis highlights that there is significant role played by quantity as well as quality of labor market conditions in explaining the present migration trend in Nepal. Though intention/aspirations data do not directly explain the real migration situation, it gives an indication of the potential problems in the domestic labor market. Quality of employment matters in explaining migration aspirations. So, focusing on employment alone without focusing on the quality of employment cannot explain the migration pattern in Nepal. Informal employment in informal sectors is constraining youths to realize their potentials and aspirations. One probable problem is the low income as compared to their potential level. The overall bleak labor market prospects in Nepal are compelling youths to migrate in search of jobs both domestically and internationally. Though our analysis is only of push factors and does not consider pull factors of migration, we can sufficiently conclude that the push factors in terms of poor labor market conditions is causing migration in Nepal.
References
Afram, G. G. and A. S. Del Pero. (2012). The labor market in Nepal. In Nepal’s Investment Climate. TheWorld Bank: 171–187.
Van Dalen, H.P., Groenewold, G. and J. J. Schoorl. (2005). Out of africa: what drives the pressure to emigrate? Journal of Population Economics, 18(4): 741–778.
Ryan, P. (2001). Theschool-to-worktransition: a cross-national perspective. Journal of economic literature, 39(1): 34–92.
Serrière, N. (2014). Labour market transitions of young women and men in Nepal, Employment Policy Department, International Labour Office, Geneva, Switzerland.
Van Mol, C. (2016). Migration aspirations of European youth in times of crisis. Journal of Youth studies, 19(10): 1303–1320.
(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) 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, 2018-11-09) Sethy, S. K.; Goyari, P.
Introduction
Financial inclusion is emerging as a new model of economic growth that plays a major role in eliminating poverty from the country. Financial inclusion is a priority for the country in terms of economic growth and it enables a reduction of the gap between the rich and the poor. In the current scenario financial institutions are the robust pillars of progress, economic growth and development of the economy.
Financial inclusion is defined as the process of ensuring access of financial services timely and adequately, and credits where needed by vulnerable groups such as weaker sections and low income groups at an affordable cost (C. Rangarajan Committee, 2008). The different financial services include access to savings, loans, insurance, payments and remittance facilities offered by the formal financial system. This aspect of financial inclusion is of vital importance in providing economic security to individuals and families (Kelkar, 2014). From this, we can know that inclusive financial sector development makes two complementary contributions to poverty alleviation – (i) it drives economic growth faster which indirectly reduces poverty and inequality, and (ii) by creating appropriate, affordable, financial services for poor people, it can improve their welfare and living standards.
In India, many people are not considered for fair treatment either by the social institutions or by the financial institutions. The concept of financial inclusion can be traced back to the year 1904 when the co-operative movement took root in India. It gained momentum in 1969 when 14 major commercial banks of the country were nationalized and the lead bank scheme was introduced shortly thereafter. Financial sector inclusion is a very important component of inclusive growth because poverty, deprivation and other socio-economic problems can arise due to financial exclusion. The existing literature on measuring financial inclusion has not been too comprehensive and the present research makes an effort towards the construction of a new financial inclusion index of Indian states for a more inclusive policy on Financial Inclusion.
Objectives
In the light of these above motivations and background, the specific objectives of the present study are: (i) to explore the current status of microfinance in India (ii) to understand the present status of India‘s financial inclusion by applying the financial inclusion index (FII).
Methodology
With the rising interest in financial inclusion among policymakers, a multiplicity of financial inclusion indicators has been developed. This study is also constructing a Financial Inclusion Index (FII). To construct an index, this study first calculates a dimension index for every dimension of financial inclusion. Steps are explained below.
Where, wᵢ = weight attached to the dimension i, 0 ≤ wᵢ ≤ 1
Aᵢ = Actual value of dimension i, mᵢ = Minimum value of dimension i, Mᵢ = Maximum value of dimension i, and dᵢ = Dimensions of financial inclusion i. Formula (1) confirms that 0 ≤ wᵢ ≤ 1 and here, n dimensions of financial inclusion are represented by a point X = (1, 2, 3…). The point 0 = (0, 0, 0…0) represents the point indicating the worst situation and point W = (1, 2, 3 …) represents an ideal situation. Here, both the worst point 0 and the ideal point W are the important factors to calculate an index for countries and states which indicate the position of financial inclusion. If the distance is larger between X and 0, then it represents higher financial inclusion and similarly if the distance is lower between X and 0, then it represents lower financial inclusion.
In the formula (2) for financial inclusion index (FII), X₁ indicates average of the Euclidian distance between X and 0. Higher value of X₁ implies more financial inclusion. In Formula (3), for FII, X₂ indicates inverse Euclidian distance between X and W and similarly, higher value of X₂ corresponds to be higher financial inclusion. The formula (4) is the simple average of X₁ and X₂. Depending on the value of FII, states are divided into three categories such as:
i. 0.5
Table 1 and Fig.1 show the state-wise FII in 2011. From the data given in the table, it is quite evident that Kerala (0.4116) has secured first rank in FII followed by Goa (0.4016), Delhi (0.356), Punjab (0.33), Tamil Nadu (0.3279) and West Bengal (0.31). These states are categorized under the medium financial inclusion (0.3 < FII < 0.5). There is no state under the high financial inclusion. Madhya Pradesh (0.1066) has secured the last rank in FII among all other states in India. A state with low financial inclusion requires an increase in banking penetration, more availability of banking services and above all usages of the banking system. Even medium financial inclusion performing states essentially means that there is lot to be done to improve the position.
From Table 1, percentage of household using banking services is the highest in Himachal Pradesh (89.1) followed by Goa (86.8), Uttarakhand (80.7), Delhi (77.7) and Kerala (74.2). The percentage of households using banking services is very low in Assam (44.1) in comparison to other states. Moreover, there is need of a comprehensive financial inclusion plan for India as a whole along with region specific inclusion plans. Till now financial inclusion has not yielded the desired results but no doubt it is playing a significant role and is working on the positive side.
Conclusion
The paper examined the financial inclusion by applying the Financial Inclusion Index (FII) for Indian states. The FII was computed for 22 states of India, using data for indicators of three dimensions such as banking penetration, availability of banking services and usage of the banking system. On the basis of the range of index, states were grouped into three categories, namely, high financial inclusion, medium financial inclusion and low financial inclusion. Kerala ranked at the top of FII followed by Goa, Delhi, Punjab, Tamil Nadu etc. and Madhya Pradesh came at the bottom. Out of 22 states, there was no state under the high financial inclusion category. Kerala, Goa, Delhi, Punjab, Tamil Nadu and West Bengal come under the medium financial inclusion category and all other states are under the low financial inclusion category, indicating the need for further development on financial inclusion measures. More opening of no-frill bank accounts is not the purpose or the end of financial inclusion while formal financial institutions must gain the trust and goodwill of the poor (Sharma and Kukerja, 2013).
The SHGs-Bank linkage programme has been promoting microfinance facilities to ensure financial inclusion. It facilitates extending financial services to unbanked disadvantaged section of society. It is also found in the analysis that the number of SHGs positively endorses financial inclusion. The policies of financial inclusion may not be yielding the expected results but the measures adopted by the governments must be speeded up in every state, particularly to those regions where FII is low.
References
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Introduction
It is important to analyze the impact of tax revenues on economic growth due to the fact that the state uses fiscal policy as an instrument to control the economy. A country‘s tax system is one of the determinants of other macroeconomic indices such as economic growth, public debt, fiscal deficit and inflation. Likewise, the macroeconomic status of a country has a major bearing on its tax structure. Specifically, there exists a relationship between the level of economic growth and development and the tax structure. Indeed, it has been argued that the level of economic development has a very strong impact on a country‘s tax base (Musgrave, 1969). Currently, Sri Lanka‘s fiscal and taxation system is at a critical juncture. While overall GDP as well as per capita income have been steadily increasing, total government revenue and tax revenue have been decreasing over time (Amirthalingam, 2013). The total revenue collection for the year, amounting to Rs.641,547 million shows an increase of Rs.81,124 million or 14.47% over that of the previous year. It amounted to a 38.02% contribution to total Government Revenue and 5.42% to GDP of the year (Department of Inland Revenue, 2016).
Domestic conflict in the north and the east of the country has severely affected Sri Lanka‘s economic growth. It can be seen that during the 1970s, per capita GDP growth was on average 5.6 percent and due to the civil war in the 1980s it fell down to only 1.6 percent. However, in spite of the impacts of civil war, economic growth has improved during the 1990s and later. Per capita GDP growth was on average 4 percent during the 1990s and in 2007 it was 4.9 percent and then decreased to -1.5% in 2001 due to the ethnic conflict. However it was recorded as 7.3% in 2013. But GDP growth in 2016 was 5.4 percent (Central Bank of Sri Lanka, 2016).
There is a problem in Sri Lanka which is, tax revenue as a percentage of GDP has continuously declined. Direct taxes (mainly income taxes) as a percentage of GDP remained at an average of 2.5 per cent during 1990-2016 (Central Bank of Sri Lanka, 2016). It shows that the decline in the tax ratio is clearly due to a decline of indirect taxes as a percentage of GDP. There are two issues here. On the one hand, Sri Lanka could not prevent the declining trend of indirect tax revenue as a percentage of GDP, and on the other hand the country could not enhance the direct tax revenue as a percentage of GDP with a view to offsetting the decline of indirect tax revenue as a percentage of GDP.
The theoretical literature suggests that taxes have a negative effect on economic growth (Athukorala and Karunarathna, 2004). Thus, high tax rates diminish economic growth. The reason for this is that higher rates may be more distortionary and hence impact growth negatively while lower rates may generate revenues that are spent in productive ways. However, the empirical literature suggests both direct and inverse relationship between tax burden and rates of growth. Mashkoar et al. (2010) examine the association among tax revenues and the speed of economic growth, for Pakistan by taking annual data from 1973 to 2008 and applying an ARDL approach. Findings show that a high rate of direct taxes would augment real economic growth. Taha et al. (2011) examine the causal relationship between these two variables, both in the short run and the long run. Results show that there is a unidirectional connection between economic growth and tax revenues. In the Sri Lankan context there is no empirical study regarding the dynamic relationship between tax revenue and economic growth. Therefore, this study is intended to fill the study gap to help fiscal policy making in Sri Lanka.
Objective
The objective of the study is to examine the impact of tax revenue on economic growth of Sri Lanka.
Methodology
Annual data of Sri Lanka over the period of 1990-2016 have been used in this study. The data of LNRGDP (Real Gross Domestic Product) is a dependent variable, real GDP growth was bring into play as a substitute (proxy) for economic growth. It was collected from annual reports of the Central Bank of Sri Lanka (CBSL). LNTTR (total tax revenue) is a combination of direct and indirect taxes, PSE is school enrollment, secondary (gross), IMP represents imports of goods and services, FDI is foreign direct investment(net), CMD are customs and other import duties, LAF is Labour force participation (total), and were extracted from the World Development Indicator (WDI) database of the World Bank. Endogenous growth models developed by Barro (1990), Mendosa, Milesi-Ferreti and Asea (1997) predict that fiscal policy can affect the level of product and long run economic growth. Thus, we construct a regression model based on the above mentioned endogenous growth model. Model estimation begins with the analysis of the order of integration of each variable using Augmented Dickey Fuller (ADF) and Philips-Perron (PP) unit root tests for this analysis. The co-integration test was conducted using the Johansen approach to test for long run relationship between variables. The model can be described as:
The following error correction model (ECM) was employed to test for the short-run relationship between variables.
where, Ψ = αβ’. α : is the (7x1) vector of speed of adjustment co-efficient, β’ : (1x7) vector of co-integrating coefficients and
is a vector of endogenous variables, is the lagged value of the variables and is the white noise error term.
Results and Discussion
Based on the ADF and PP unit root tests, all variables of this study are stationary at level form. Therefore, this result also suggests that all eight variables are integrated in the same order, i.e. I(1). Once we established the order of integration, the study process requires the estimation of the long-run relationships among the variables included. However, before estimating this relationship we need to identify the optimal lag length of the model. Using VAR model, all the lag length selection criteria except AIC suggest the use of one lag as optimal lag length. Therefore, we included one lag in our model. Trace test statistics identified one co-integrating relation in the system of equations at 5% level of significance since we reject null hypothesis at rank 0 but we failed to reject null hypothesis at rank 1. Following equation shows the long run relationship of the Model.
As shown in Equation 3, the results of all variables are significant at 5% level of significance in the long-run. Total tax revenues have a negative relationship with economic growth, while labour force, foreign direct investment, customs and other import duties, school enrollment and imports have a positive link with economic growth. Due to a one percent increase in total tax revenues, economic growth would be reduced by 1.11 percent in the long run. A negative and significant error correction coefficient (-0.016) of LNRGDP reveals that 1.6 % disequilibrium is corrected each year which implies that Real GDP growth moves downward towards long run equilibrium path.
Table 1 shows the short-run negative relationship between RGDP growth and Total Tax Revenue. And also foreign direct investment, customs and other import duties and import have a positive impact on Real GDP growth. But other variables (LNLAF, LNSEE) do not have a significant impact on economic growth in the short run in models.
Conclusion
The major intention of this research is to investigate the association, involving total tax revenue and economic growth, over the period 1990- 2016, in both long and short run. Total tax revenues have a negative and significant effect on economic growth in the long run. Due to a one percent increase in total taxes, economic growth would decrease by 1.113 percent. In the short run, total taxes revenue has a positive impact on economic growth.
There is also a need to augment the tax base/network and setting good precedence with improved tax administration. Therefore the research results show that total taxes have a negative impact on economic growth. Due to weaknesses in tax revenue administration, the level of tax collection continues to be lower than optimal in Sri Lanka (Waidyasekera, 2004). This could be the reason for negative impact of total tax revenue on economic growth. Political favoritism, political influence, and a lack of a clear cut political rationale on taxation have also adversely affected the tax revenue potential (Amirthalingam, 2010). Thus, special attention needs to be given by the government in order to promote RGDP growth rate and fiscal consolidation by reforming tax policy.
References
Athukorala, W. and K.M.R. Karunarathna. (2004). The Impact of foreign direct investments on economic growth: evidence from Sri Lanka. Sri Lanka Economic Journal, 5(2): 97-134.
Arisoy, I., and I. Unlukaplan. (2010). Tax Composition and Growth in Turkey: An Empirical Analysis. International Research Journal of Finance and Economics, 59: 50-61.
Brasoveanu, L. O., and I.Brasoveanu.(2008). Thecorrelation between fiscal policy and economic growth.Theoretical and Applied Economics, 7(524): 19-26.
Keho, Y. (2011). Tax structure and economic growth in Cote d‘Ivoire: Are some taxes better than others? Asian Economic and Financial Review, 1(4): 226-235.
Mashkoor, M., Yahya, S. and S. A. Ali. (2010). Tax revenue and economic growth: An empirical analysis for Pakistan. World Applied Science Journal, 10(11): 1283-1289.
(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.