(University of Peradeniya, 2017-10-12) Arachchi, A. Janaki Imbulana; Banda, O. G. Dayarathna
Introduction
At the economic development, process economist has commonly considered that industrial sector has been a leading sector in the economy. Because industrial sector provides the main contribution to economic development process through produces goods and services, value addition for agriculture products, foreign exchange earnings by export, increase in employment, etc. Sri Lanka as a low middle-income country, the manufacturing sector is a primary component within the industrial sector. According to the Central Bank report in 2016 manufacturing sector contributed 15.2 % of GDP in Sri Lanka. At the same time, many official economic and social reports provide evidence that small and medium scale industries have been providing major proportion from above contribution. Therefore it is important to keep considerable attention on small and medium scale industry in Sri Lanka to achieve economic development goal.
There are many academic works which examine about the growth of SMEs internationally. Afande (2015) identified that access to credit, firm age and level of education of firm’s owner effect positively and significantly on the growth of small-scale manufacturing industry. According to the Yasuda (2005) investigates the relationship between firm’s growth and size of the firm, firm’s age and firm’s behavior in Japanese manufacturing firms. And also Pherson (1994) identified the negative relationship between firm’s growth and firm’s age. Heshmati (2001) examined the relationship between the size, age and growth rate of firms is for a large sample of micro and small firms in Sweden. However, while concentrating on local studies, Dayarathna-Banda and Sri-Ranjith (2014) examined the relationship between characteristics of entrepreneur and success of small business. Varothayan (2013) examined six factors namely financial, management, marketing, technology, infrastructure and government regulation that influence the performance of SMEs. Lingesiya (2012) studied the factors which to indicate the business performance of small-scale industries. In this study he identified that customer satisfaction with managing change, growth at business and income level, growth in profitability, growth in turnover, growth in a number of employees are the main indicators of the business’s growth.
Performance of small-scale industries, the growth of industry and performance of industry are completely different concepts. When we referred Sri Lanka’s research works on small-scale manufacturing industry, there is a lack of studies in the area growth of small-scale manufacturing industry. Therefore, the purpose of this study is to examine the growth of small-scale manufacturing industries.
Objectives
The objectives of this study are to identify the growth of small-scale manufacturing industry in Sri Lanka and to examine impact of access to credit, firm’s age, level of education of firm’s owner, gender of firm’s owner, vocational training of firm’s owner and technology applied in firm on growth of small-scale manufacturing industry.
Methodology
According to the research objectives, we used both primary and secondary data for the analysis of this study. The primary data were collected through questionnaire. The primary data was gathered in this study using a sample of 60 small-scale manufacturing firms selected through random sampling method in kuliyapitiya DS division. The secondary data was extracted from annual reports of the Central Bank of Sri Lanka and registries in kuliyapitiya DS division office. The study applied a multiple regression model using OLS techniques. I have developed my model based on Afande (2015). The model is given below.
ᵞᵢ = ᵝₒ+ᵝ₁ᵝ₁ᵢ+ᵝ₂ ᵡ₂ᵢ+ ᵝ₃ᵡ₃ᵢ+ ᵝ₄ᴰ₁ᵢ +ᵝ₅ᴰ₂ᵢ+ᵝ₆ᴰ₃ᵢ+ᵘᵢ
Where u is the random error term.
We considered firm growth (Y), access to credit (X₁), firm’s age (X₂), level of education of firm’s owner (X₃), dummy variables were used for gender of firm’s owner (D₁), vocational training of firm’s owner (D₂), technology applied in firm (D₃) there, D₁ takes the value 1 if firm’s owner is male, 0 if firm’s owner is female, and D₂ takes the value 1 if firm’s owner received vocational training, 0 otherwise and D₃ takes the value 1 if firm used new technology, 0 otherwise.
Results and Discussion
According to the survey, the firm profit was used to measure the growth of small-scale manufacturing industry. In order to measure the growth rate, we used firm profit both of 2014 and 2015 years. We categorized them according to the growth rate. That results are depicte in Figure 1.
According to the result in Figure 1, all firms have maintained considerable growth rate. Most of the firms in the sample obtained between 10 %-15 % growth rate at considering the time period. However, some firms obtained 35 % level growth rate but some firms obtained 5 % growth rate.
To estimate above-mentioned multiple regression 60 observations were employed. The estimates show that overall multiple regression model is significant at 5 % confidence level and the overall fitness as the R² value is equal to 0.7279, It indicates that the independent variables used to explain about 73 % variation in growth of the small-scale manufacturing industries in the sample. The results show that there is a significant positive relationship between access to credit and growth of Small scale industries. It implies that provision of credit facilities effect to increase the growth of these firms. However, evidence showed that 50 % of small-scale industries did not use credit due to many reasons such as ignorance, dislike, institutional problems and so on. It was also identified short-term (2 or 3 days) repayments loans between some small-scale businessmen and suppliers of inputs and purchases. This has been a powerful factor for each of them.
According to results, it shows that gender of firm’s owner positively significant at 5 % level. Further evidence shows that male-owned 80 % of Small scale industries in the sample. It may happen due to nature of small-scale industries in this area. The few of them received specific training from government and non- government organizations. It helps them to improve both quality and quantity of particular products. Especially it improved their compatibility with homogeneity products. According to the literature review, it shows that adoption of new technology helps to increase labor productivity of small-scale industries. Further increase of labor productivity makes surplus which helps to the capital accumulation of this sector. the results of this study show that the technology applied in the firm is positively significant at 5 % level. Even though modern technology improves productivity and increased the profit of small-scale industries in the area, more than 57 % of firms have used traditional technology for their production activities. It was also found that firm age and level of education of firm’s owner displayed positive relationship but not significantly. Majority of firm’s owners passed GCE (O/L) or (A/L) level but it does not help them to increase the growth of firms. These kinds of education systems will not provide vocational training, which will help to improve the productivity of a firm.
Conclusion and Policy Implications
Small-scale manufacturing industries face working capital difficulties to conduct their business. They seek to obtain loans as a solution to the capital shortfall. But only 50 percent of the sample has obtained credit from the formal sector. They obtain a short-term loan from private sector especially input suppliers and businessmen. This situation may affect negatively to their profit and growth of small-scale industries. Therefore, credit facilities under a low-interest rate from the formal sector could make a positive impact on the growth of small-scale industries. Therefore, government and formal private sector credit institutions have a significant role to develop small-scale industries in the rural areas.
According to the study results, male-owned small-scale industries have relatively higher growth rate compared to female-owned ones. Further small-scale industries that were included in this sample characteristically non-female owned industries. It implies that unutilized female entrepreneurs in the rural sector and need to introduce suitable industries with necessary guidelines and training.
The study was revealed that the owners of small-scale manufacturing industries were given vocational training in their business activities and these training programs positively effect on the growth of the industry. The study is recognized that most of the small-scale entrepreneurs who included in the sample have been conducting their production activities using their own experiences, which they learned from parents or their inborn abilities. It is important government and non-government agencies intervention to facilitate formal training and consultancy programmers for small-scale producers, which is positively impact on the growth of these industries.
According to the result, most of the small-scale industries in the sample use traditional technology. That technology is a labor-intensive manufacturing process. Further, it was observed that according to the nature of these industries they compel to use conventional technology. However, in comparison with conventional technology, the industries which use modern technology have been able to produce higher amount within the particular time period and higher quality products. Therefore, the introduction of suitable and practical new technology related with these small-scale industries will help to improve productivity and increased the profit of small-scale industries in the area.
References
දයාරත්න -බණ්ඩා, ඕ .ජි. (2013). කුඩා කර්මාන්ත සංවර්ධනය - ගැටලු හා ව්භවතා. කැලණිය: විද්යාලංකාර මුද්රණාලය.
Afande, F. O. 2015. Factors influencing growth of small and microenterprises in Neirobi central Business District. An international peer-reviewed journal.9:104-134.
Dayarathna-Banda, O. G. and Sri Ranjith, J.G. 2014.Deteminants of success of small business: A survey-based study in kuliyapitiya divisional secretariat of Sri Lanka. International Journal of Business and Social Research.4(6):38-50.
Pherson, M. A. 1996.Growth of micro and small enterprises in southern Africa. Journal of Development Economics. 48: 253-277.
Yasuda, T. 2005. Firm Growth, Size, Age and Behavior in Japanese Manufacturing’. Small Business Economics. 24(1): 1-15.
(University of Peradeniya, 2017-10-12) Thahara, A. F.; Vinayagathasan, T.
Introduction
In recent decades a vast number of studies have focused on the link between exchange rates (ER) and different causal factors. The ER is one of the most crucial macroeconomic factors in the emerging and transition economies. It affects public debt, inflation, trade and other economic activities. The ER has long been thought to have significant impact on the import and export of goods and services. Therefore, ER is expected to stimulus the price of those products that are traded. Shaheed (2015) concludes that external debt, debt service payment and foreign reserves have a positive impact on ER in the long run. Although, most of the economies currently facing issue of currency depreciation, which makes the trade balance and balance of payment (BOP) favorable and moves towards the surplus and boosts the country’s economy. However, the situation of Sri Lanka is totally different that it. Even though, Sri Lanka has experienced continuous currency depreciation since 1977, it has recorded that the deficits in the trade balance and BOP. The one way of solving the budget deficit (BD) or BOP problem is to allow the currency depreciation. Another ways are to use internal and external sources of deficit financing. Since Sri Lanka faces difficulties in accumulating the internal sources, the demand for external sources of deficit financing has been increased. As a result, external debt of the country has increased. On the contrary, BOP deficit and BD tend to decrease the foreign reserves (FR). The currency depreciation leads to increase the value of interest rate than the real value. As a result, real value of debt servicing will be higher than value of debt.
The significant number of existing literature identified a positive relationship between exchange rate and external debt (e.g., Alam and Taib, 2013; Awan et al.> 2015; Shaheed et al., 2015; Draz and Ahmed, 2015). However, the quantitative assessment of the relationship between ER and external debt is inadequate and limited in the context of Sri Lanka. Thus, this study attempts to fill this gap by investigating the ER and external debt nexus in the context of Sri Lanka.
Objectives
The main objective of this research is to identify relationship between exchange rate and external debt in the long run and in the short run.
Methodology
Annual data of Sri Lanka over the period of 1977-2015 has been used in this study. The data of exchange rate (ER), external debt (ED), foreign reserve (FR), budget deficit (BD), and debt service payment (DSP) were extracted from annual reports of Central Bank of Sri Lanka (CBSL) and consumer price index (CPI) was collected from the World Development Indicator (WDI) data base. Further, political instability (PI) and exchange rate regime (ERR) were used as dummy variables. All the variables, except PI and ERR, are transformed in to natural logarithm. ADF and PP unit root test methods were adapted to test that the series are not containing I(2) variables. Akaike Information Criterion (AIC) is applied to determine the optimal lag length of each series. Following the empirical literature in determinants of ER, we develop the long-run relationship between the variable as below:
(Equation -1)
where, is a white noise error term, t = 1, 2, …, T.
The Engel Granger method and Johansen method requires that the all of the variables in equation (1) should be integrated in same order and the error term should be integrated in order zero in order to form the long run relationship. However, if variables in equation (1) have different order, that is I(1) and I(0) we can use new co-integration method which was developed by Pesaran et al., (2001). This procedure, also known as autoregressive distributed lag (ARDL) approach to co-integration. The ARDL co-integration bound testing procedure is given by equation (2):
(Equation -2)
where, refers to the long run coefficients; is the vector of explanatory variables with lag one; and refers to the short run dynamic coefficients, denotes the vector of explanatory variables with lag and is the white noise error term.
The equation (2) can be further transformed as in equation (3) to accommodate the error correction term with one period lagged :
(Equation -3)
where, γ speed of adjustment, which should have statistically significant and negative sign to support the co-integration between the variables, (symbol> pure random error term.
To investigate the existence of long-run relationships between the variables, bound testing procedure is used, which is based on the F-test (Wald test). The F-test is actually a test of the hypothesis of no co-integration among the variables () against the existence of cointegration among the variables () in equation (2). Finally, we used Granger causality test to determine the direction of the causality between the variables.
Results and Discussion
The results of ADF and PP unit root test indicate that the variables are integrated in order zero (LER, LBD and LED) and order one (LCPI, LFR and LDSP). AIC advocated that to use ARDL (1, 0, 1, 2, 1,1) model for this analysis. The long-run results of the corresponding ARDL (1, 0, 1, 2, 1, 1) model are presented in Table 1 below:
As expected to the theory and most of the existing literature (e.g., Saeed et al., 2012; Awan et al., 2015; Draz and Ahmed, 2015) ED, BD, CPI and FR (at 10 %) have positive and statistically significant relationship with ER in the long run, whereas, DSP affects the ER negatively in the long run. At the same time BD and CPI have significant (10 % level of significance) and positive impact on ER in the short run while other variables do not affect significantly.
The Lagrange Multiplier (LM) test of autocorrelation advocates that the residuals are not serially correlated. According to the Jarque-Bera (JB) test, the null hypothesis of normally distributed residuals cannot be rejected. The Breusch-Pagan-Godfrey (BPG) test of heteroscedasticity suggests that the disturbance term in the equation is homoscedastic. The Ramsey RESET test result confirms that there is no specification error in the estimated model (See Table 1, Panel C above). The CUSUM plots lie between the lower and upper critical bounds at the 5 % level of significance, which confirms the stability of the parameters. The result of Wald test confirms that there is long run relationship between ER and other variables under considered in this study since we reject the null hypothesis of no cointegration among the variables due to the computed F-statistics (3.92) greater than the upper bound critical value (3.79) at 5 % level of significance (The both results of stability and the Wald test are not presented here due to concerning the page limit).
Next, the results of short run dynamic and long run adjustment coefficients are estimated using Equation (3), which is presented in Table 2. The ECM model passed all the diagnostics tests (see Table 2, Panel B below). Panel A of Table 2 reports the short run dynamics coefficient estimates of ARDL-ECM. Accordingly, as expected, one period lagged value of ER and one and two period lagged value of CPI have positive and significant impact on ER in the short run whereas one period lagged value of FR has negative and significant impact on it. Further, ECT(-1) carries an expected negative sign, which is highly significant, indicating that, there should be an adjustment toward steady state line in the long run one period after the exogenous shock. That is, about 19.4 % of the disequilibrium in the ER is offset by short-run adjustment in each period.
Finally, Granger causality test detected only unidirectional causality that stemming from FR to ER and DSP to ER in the long run (The results are not shown here due to space constraint).
Conclusion and Policy Implications
This study concludes that the both cointegration approach to ARDL and error correction version of ARDL passed all the diagnostics and the stability test. The Wald test confirms that the variables are cointegrated. The CPI affects the ER positively and significantly in the long run and in the short run. ED, BD, and FR have positive and significant impact on ER in the long run while DSP has negative affect on it. But, lagged value of FR negatively affects the ER in the short run. Further, this model confirms that whole system can get back to long run steady state line at the speed of 19.4 % in each year one period after the exogenous shocks. In sum, the government of Sri Lanka should take necessary action to reduce the BD, ED and CPI in order to bring the economy well off.
References
Awan, R. U., Anjum, A., and Rahim, S. 2015. An Econometric Analysis of Determinants of External Debt in Pakistan. British Journal of Economics, Management and Trade. 5(4): 382-391.
Draz, M. U. and Ahmed, F. 2015. External Debts and Exchange Rates of Oil-Producing and Non-Oil-Producing Nations: Evidence from Nigeria and Pakistan. Journal of Advance Management Science. 3(1): 8-12.
Pesaran, M. H., Shin, Y, and Smith, R. J. 2001. Bounds Testing Approaches to the Analysis of Level Relationships, Journal of Applied Econometrics, 16: 289-326.
Saeed, A., Awan, R. U., Sial, H. M. R., and Falak, S. 2012. An Econometric Analysis of Determinants of Exchange Rate in Pakistan. International Journal of Business and Social Science. 3(6): 184-196.
Shaheed, Z. S., Sani, I. E., and Idakwoji, B.O. 2015. Impact of Public External Debt on Exchange Rate in Nigeria. International Finance and Banking. 2(1):15-26.
(University of Peradeniya, 2017-10-12) Hadi, Abdul
Introduction
The subject of inequality, more specifically economic inequality has been on the forefronts of election speeches. However, what seems to be evidently missing from such public discourses is a comprehensive solution to it. Society is pillared upon decisions illustrated through policies, laws and economic choices, that either strengthen the welfare of the community or debilitate it. By allowing economic inequality to metastasize rampantly, Pakistan is embarking on a path of socio-economic destruction that may be irreparable if urgent policy measures aren't enacted immediately.
So why does economic inequality matter? Aren’t inequalities inherited akin to genes and sometimes good for the functioning of the society? And what could the federal government possibly do in mitigating the inequality in Pakistan? First of all, we begin by defining the crux of our proposition – economic inequality. Economic inequality comprises of three parts - income inequality, wealth inequality and pay inequality, however, we would focus more on the former two in this paper. Income inequalities refer to the disparities in income not limited to the money received through pay, but all money received through employment whereas wealth inequality refers to the disparities in the amount of financial assets, stocks, bonds and property etc. Rampant income and wealth inequalities could very well transform into other inequalities such as education, health, gender, ethnicity in the long-run. This can be corroborated quite explicitly in Balochistan which has the lowest income/capita of the country and where in towns like Dera Bugti, female literacy rates are hardly 0.06 %. The situation perjorates since future generations are simply unable to break free of this inequality trap. According to a recent report by Oxfam (Burki, Memon and Mir), children born in income-poor families in Pakistan in the year 2010- 2011 are less likely than those born in the year 1994-1995 to break their poverty trap and move into the middle-class category. Dr. Hafiz Pasha, a former finance minister suggests that this has primarily been due to the underreporting of income for tax evasion. Gaping inequalities has corrupted politics, thwarted potential, fueled crime, stifled social mobility and hindered economic growth in Pakistan in the last few decades.
Objectives
Given the sheer increase in gaping economic inequalities and their diffused effects on other social indicators in Pakistan, it becomes imperative for the State to become a major player in the fight against inequality. This paper tries to establish this by advocating for a more robust, progressive and inclusive fiscal policy. In order to establish our case, we will first try and understand the reasons behind economic inequality in Pakistan. Then we will examine the current fiscal policy in practice in Pakistan and then suggest an alternative mechanism for achieving the goal of reducing economic inequality in a more efficient way.
Methodology
The methodology undertaken is purely secondary in nature. Papers and statistics taken from government statistics bureaus and research think tanks will form the main crux for our arguments. The Pakistan Economic Survey 2014-2015 was reviewed and thoroughly analyzed. News reports were also studied and analyzed to ensure the accuracy of the data.
Results and Discussion
According to the Pakistan Economic Survey and other reports, the reasons for Pakistan’s hitherto situation can be traced back in history. The so-called establishment in Pakistan consisting of the coalition of military and democratic governments has ensured that since independence the country remains a ‘security state' rather than a ‘developmental state'. Albeit, military tenures were focused on paradigms of rapid growth and the reliance on the ‘trickle-down’; nevertheless, they paradoxically remained the ones with the highest inequality. Estimates show that in Pakistan, Rs. 33 goes to the top 1 % for every Rs.100 worth of commodities generated and a mere Rs. 3 goes to the bottom 3%. Clearly the ‘trickle down’ theory is dubious and it’s about time we start thinking about inverting the pyramid.
Examining the fiscal terrain of Pakistan with more scrutiny, we find that the allocation of assets is the most unequal when it comes to agricultural land. About two third of the Pakistani population resides in rural areas, it follows that the primary source of income for such people is through agriculture related activities. However, a recent study revealed that the top 1 % of farmers own as much as 22 % of farmland, 41 % of the tractors and 28 % of the tube wells. Despite agriculture dominating Pakistan’s GDP, the sector has remained sufficiently under- taxed amounting up to just Rs. 1 billion for all four provinces combined. As a matter of fact, the maximum punishment for not filing agricultural tax returns is a hefty fine of just Rs. 1000 (Pasha, 2017).
Possessing enormous political power and close ties with the government, the rich have successfully managed to evade taxes to ensure that the beneficiaries of growth hitherto were the ones with the most capital. These groups enjoy wide-ranging exemptions and concessions, low tax rates and can engage in tax evasion with a degree of impunity, frequently in connivance with a corrupt tax administration. This has engendered in a low tax-to-GDP ratio of around 8.5 % (2014) that is extremely low relative to other countries in the region.
Let’s now also understand the composition of tax revenues in the country. Instead of direct taxation, the government has persistently focused on indirect taxes to finance its expenditures. Not only has this failed to circumscribe the exorbitant income sources of the rich but has targeted the poor segments of society via an increase in the general prices of essential commodities, especially food.
Tax evasion has resulted in forgone revenue of approximately Rs. 500 billion for Pakistan which could otherwise have been utilized for the public good (Oxfam, 2017). When compared with its neighbor India where 1 in 40 people file tax returns, Pakistan’s figures are estimated to be around 1 in 260. In fact, only 1/4th of the total population actually files returns and the total number of taxpayers has declined over the past 6 years, worsening the fiscal deficit. As Oliver Holmes acclaimed ‘taxes are the price we pay for a civilized society’, Pakistan’s government needs to redesign its taxation policy to further the cause of inclusive growth and reducing the economic inequities in the population.
Given the distorted tax system of Pakistan, a large fiscal deficit could be in theory be acceptable. Unfortunately, the statistics point towards the contrary. Due to inadequate receipts, not only is expenditure on public services abated, but the allocation of spending remains quite skewed. Spending on health and education, one of the cardinal tenets of social capital narrowly make 15 % of the total expenditure, and the expenditure on health is only one-third of the expenditure on education. Combined expenditure on social services approached 3 % of the GDP in 2012-2013. The realization that social expenditure on social services seems to be side lined by the federal government. Equally important is the establishment of a robust mechanism of social protection to safeguard the marginalized from their financial woes. Targeted programmes such as direct cash transfers or unemployment have received little attention in the past. The primary cash transfer programs include but are not limited to the Zakat, Bait-ul-Maal and the Benazir Income Support Programme (through which a monthly stipend of Rs. 1000 is transferred to the families of lower income classes). The system of Zakat transfers seems pretty obsolete given the current demands of this time. Similarly, the Bait-ul-Maal responsible for targeting the poor is constructed at the district level with no independently verifiable criteria for maintaining or updating the list of beneficiaries. Renewed interest in social protection in the form of the Benazir Income Support Programme, the Punjab Food Security Programme and the recently developed Khushal Fund is also under scrutiny since only one fourth of the beneficiaries actually receive the funds (Gazdar).
Conclusion and Policy Implications
A fiscal policy should be designed in a way such that it is inclusive - that is, it benefits every Pakistani so that each party gets it deserved share of the economic pie and also sustainable so that future generations could benefit from its outcomes. On the taxation side, a number of steps can be possibly undertaken to increase tax revenue in a fair and equitable manner. Many advanced economies such as the Scandinavian countries have achieved their redistributive objectives more efficiently via the progressivity of their tax and transfer systems by augmenting marginal tax rates for higher income groups and exempting taxes for lower income groups.
In order to make the progressivity and inclusiveness of taxes yield results, the funds need to be spent in a way to target economic inequality both in the short and long run. Firstly, the government needs to do away with a myriad of price subsidies and supply it with direct cash transfers to poor households. Funding the development of better educational institutions from progressive taxation for low-income groups needs to be one of the top priorities of the expenditure side, particularly at the primary schooling level. Another proposition is the initiation of a comprehensive package of health insurance to provide adequate healthcare for every citizen of the country at subsidized prices, especially the poor. A recent report emphasizes the importance of a fiscally sustainable, publicly financed basic health package covering essential health care, which would disproportionally benefit the poor since they would do away with unproductive precautionary health saving (Jamison). Finally, analogous to a system of means-tested cash transfers, a system of non-contributory social pensions could be enacted with progressive tax receipts that provide a flat pension to the country’s senior citizens.
All in all, despite some of the inherent limitations of fiscal policy in Pakistan, it is the most optimal tool at the government’s disposal to achieve redistributive goals. Inequalities reflect the hierarchies of power, and both tend to produce and reproduce their privileged positions regardless of the force of intellectual and ethical arguments against its unacceptable manifestations. Indeed, inequality and economics are a complicated science, we never know whether fiscal policy would help achieve our objectives, however, the longer we wait, the more problems it will yield.
References
Ahmed, S., Ahmed V. and C. O. Donoghue .2011. Reforming indirect taxation in Pakistan: A macro-micro analysis, Journal of Tax Research 9(2), pp. 153-74.
Abid, B., Memon, R. and M. Khalid. 2015. Multiple inequalities and policies to mitigate inequality traps in Pakistan. Oxfam.
Drèze, J. and A. Sen .2013. An Uncertain Glory: India and its Contradictions, London: Allen Lane.
Government of Pakistan. 2014. Economic Survey of Pakistan, Ministry of Finance.
(University of Peradeniya, 2017-10-12) Samaranayake, D. I. J.; Samaranayake, D. L. M.
Introduction
This study is done based on a developed actuarial model of Susceptible, Infected and Recovered (SIR) compartments, which describes the transfer dynamics in an insurance contract of a given population (Abramson, 2001). The SIR model created by Kermack and McKendrick (1927) set the mathematical and theoretical foundation for these epidemic models. Further research has been done to extended thresholds of these models using advanced analytical viewpoints (Mollison, 1995; Allen and Burgin, 2000; Kaddar et al., 2011; Bhattacharya et al., 2015).
The actuarial bases of epidemic disease spread are used with the intention of how to address the financial and economic possessions of such a venture. A book written by Slud (2001) provided imperative information of insurance and life annuity contracts. Feng (2005) developed an actuarial based model for epidemiology with the intention of building a bridge between epidemiology modeling and actuarial mathematics. His theory was utilized to design insurance contracts for the Great Plague in England and SARS epidemic in Hong Kong (Feng and Garrido, 2006). This was an imperative contribution made in literature of epidemic modeling which has open the gates of another testing ground for economic and financial analysts. In the context of Sri Lanka, few studies have been done for modeling the epidemic disease spread (Briët et al., 2008; Pathirana et al., 2009) and it is even more difficult to discover an analysis centered on actuarial based models. Hence, this study provides pioneering steps to the actuarial based model building for Sri Lankan epidemic profiles.
Objectives
While putting fore steps for the actuarial based modeling in relation to the epidemic disease spread in Sri Lanka, this study intends to revisit the theory by Feng (2005) and to obtain an expanded version of it based on SIR infection which describes the transfer dynamics in an insurance contract considering the highest total case recorded epidemics in Sri Lanka.
Methodology
A simple SIR model describes the conversion between sub-populations of susceptible, infectious and those who recovered. If recovery is permanent and recovered individuals are no longer susceptible to that pathogen then SIR model can be shown as follows,
β is the infecting rate for an individual per unit time and simultaneously α is the recovering rate from the diseases per unit time. SIRS model is more general than SIR model. The only difference when compared to SIR model is defining a new parameter called f which represents the rate of recovered individuals who are again susceptible per unit time due to the temporary recovery from the infectious disease.
Actuarial mathematics concepts are used to describe the financial transactions between two parties called insurer and insured.
Equivalence Principle:
E [Present value of benefits] = E[Present value of benefits premium]
For a continuous Whole Life Insurance Policy with a unit benefit the Level Premium Payment can be determined using equivalence principle as,
Where is the actuarial present value of future benefit payments and is the actuarial present value of future premium payments. An actuarial based model has developed for the epidemiological diseases and the following equations are given for the annuity for hospitalization plan which has defined by using the whole life insurance policy. When δ is the force of interest, γ is the rate of recovering of susceptible (s) and infectious (i) compartments at time t,
The total discounted future claim:
The total discounted future premium:
The force of infection:
The force of infection:
The level premium for the unit annuity for hospitalization plan:
MATLAB statistical software and recorded epidemiological data from the official website of Epidemiological Unit, Sri Lanka are used as the materials of this study. Data were collected weekly for 40 weeks period beginning from 26th December 2015 to 30th September 2016.
Results and Discussion
Sensitivity of Level Premium Payment with respect to the parameters
Determining the level premium payment with positive benefit reserve is mainly focused when the actuarial model is developed. According to the observation of this study, there is an effect from the parameters, γ and β to determine the level premium payment.
The rates taken at a monthly basis vary from 5-7 for infecting rate and 4-6 for recovering rate. Simulation shows a simultaneous decline in the recovery rate and increase in the infecting rate leaning the level premium rates towards zero. Premium rate reaches the highest possible level when a simultaneous increase in recovery rate and improvement in infecting rate occur. Therefore, independent as well as simultaneous changes in the rates of getting infected and recovery specify the characteristics of level premium payment to be considered for a hospitalization plan. Above results were obtained while developing MATLAB simulation for the actuarial based model for SIR infectious disease developed by Feng (2005) for SARS epidemic.
Adjusting Level Premium Payment
According to retrospective approach the individual benefit reserve at time and t for the annuity for hospitalization plan with unit benefit can be formulated as follows,
However to satisfy the requirement of positivity of the benefit reserve curve, for all t > 0
Feng (2005) has found out some results by setting up δ=0 and those results do not make sense of the time value of money. Since the complexity of solving equations without neglecting the force of interest, an algorithm is defined and developed a MATLAB program through this study to calculate the minimum adjusted level premium for the hospitalization plan to satisfy the above condition. This program could be used to calculate the level premium of diseases which has a permanent immunity with the absence of Vector-Host transfer dynamics. Otherwise it will not be adequate to obtain 100 percent accuracy in results. Henceforth, it is important to identify the nature and characteristics of Sri Lankan epidemic diseases to recognize the applicability of the program developed.
Feasibility of SIR model to represent epidemics in Sri Lanka
This analysis is based on only the top 10 epidemics which have the highest number of total recorded cases for the selected period. According to the data, highest recorded number of cases is Dengue and it is 72.65 % from the total top 10 epidemic cases. This implies that the probability of being infected by Dengue for a person is very high than the other diseases. However, there are considerable percentages for the diseases called Chickenpox (6.64%), Leptospirosis (5.44 %), Dysentery (4.83 %) and Typhus (3.29 %).
There are several patterns which can be seen when constructing time plots for the above 10 diseases. Some have clear seasonal patterns (Dengue fever). Also, some have very short-term fluctuations and it is difficult to determine the length of a season (Dysentery, Meningitis and etc.). Additionally, some diseases have declining patterns (Leptospirosis, Typhus and Leishmani). However, it is a huge area to study the reasons behind those patterns. Thus, this study is focused on developing an actuarial model for epidemiological diseases spread which can be used more generally to reduce the impact of several patterns. Dengue fever only contains a clear seasonal pattern based on the data for a 40-week period. APPENDIX provides further evidence on the seasonal behavior presence with dengue epidemic with a comparison of actual data with estimated measures for a given optimal lag length of 20 weeks for each season. Therefore, dengue fever has got expected seasonal features and it appears as a testing ground to practice feasibility of the insurance contract improved at the previous section of this study.
Actuarial Based Model for Dengue Fever Spread using SIR (Vector- Host) Model
There are some questions still to be addressed through further advancements of actuarial model considering long term effects such as Vector-Host transfer dynamics embedded with epidemic disease spread. According to the data it can be estimated the length of an epidemic season for some diseases such as dengue. But the SIR model defined by neglecting the type of disease which can be transferred by a vector. Dengue fever is the major epidemic disease in Sri Lanka which is generally spread by mosquitoes. Hence it is important to expand the SIR model by including the Vector-Host transfer dynamics to find out an actuarial model for diseases such as Dengue fever. Using the same procedure carried out to obtain Result in 4.2 it can be easily shown that,
and it yields to the level premium payment which formulated for the SIR infection model without the Vector-Host transfer dynamics being same here. Hence, it is reasonable to use the MATLAB program developed earlier through this study to calculate the minimum adjusted level premium for the hospitalization plan for Dengue fever.
Actuarial Model using SIRS Model
Moreover, other diseases have consisted of very short-term fluctuations and it is difficult to determine the length of the epidemic period. Also some people can be infected by the same disease more than once for the considered time period. On other hand, usually an insurance contract is drawn up for annum or a period of six months and it is rarely possible to adjust it with the epidemic season. Hence, the transformation within compartments for a long term can be described more generally using SIRS model than SIR model. But SIRS model is expressed using Delay Differential Equations and this study was not focused on simulating that model.
Conclusion and Policy Implications
This study is done based on a developed actuarial model of SIR infection which describes the transfer dynamics in an insurance contract in a given population. At the initial stage, we satisfied key assumptions and observed that the rate of infecting is positively related and the rate of recovering is negatively related to the level premium payment. Further, we developed a MATLAB program to calculate the minimum adjusted level premium for a hospitalization plan. Secondly this study obtained expanded models for the basic model to eliminate some problems which occurred such as the Vector-Host relationship due to unsatisfied assumptions for real data. It is reasonable to expand the SIR model by including Vector-Host transfer dynamics to find out an actuarial model for Dengue fever, as it can be estimated for the length of an epidemic season for Dengue for the sample period. Results show that there is no impact from Vector-Host to determine the level premium payment. Finally, we suggest the SIRS infection model with delayed differential equations as an appropriate solution which arises as a result of difficulties to identify seasonal patterns clearly for other diseases.
References
Bhattacharya, P., Paul, S., and Choudhury, K. S. (2015). Different Types of Epidemic Models and their Characteristic Behaviour by using Matlab. Journal of Interdisciplinary Mathematics, 18(5), p. 569-592.
Feng, R. H. (2005). Epidemiological models in actuarial mathematics (Doctoral dissertation, Concordia University).
Feng, R., and Garrido, J. (2006). Application of Epidemiological Models in Actuarial Mathematics. Soa. Org. 15(1), 1-29. Retrieved from http://www.soa.org/research/ARCH07v41n1_XIV.pdf.
Kermack, W. O., and McKendrick, A. G. (1927). A contribution to the mathematical theory of epidemics. In Proceedings of the Royal Society of London, Series A. 115(772), p. 700-721.
Slud, E. V. (2012). Actuarial mathematics and life-table statistics. Chapman and Hall/CRC.
Appendix
Time Series Plots for Epidemiological Data
Introduction
Pakistani females have long contributed significantly less than their male counterparts in the labour force. This lack of female labour force participation greatly cuts down the active labour available at Pakistan’s disposal and adversely affects its economic growth, gender equality and standards of living as about 58 % of female headed household in Pakistan live below the poverty line compared to 49 % of male headed households. (Encyclopedia of Women and Islamic Cultures: Family, Body, Sexualit, Volume 3). Intuitively, the 77.85 % (Labour Force Survey 2013) of women being out of Pakistan’s workforce, can be attributed to the long standing problem of patriarchy which restricts the access of women to productive resources.
Ever since Mincer’s pioneering study in 1962 which attempted to reinterpret labour supply by accounting for lifetime variables and the resulting conclusions that family income had no effect on the wife’s demand for leisure and that a women’s fertility is a major determinant of her labour supply, other researchers took it upon themselves to research in depth into the newly emerging field of female labour force participation which became evident after the suffragette movement. Shah (1976) examined the effects of socio-economic and demographic variables on labour force in all four provinces and concluded a positive relationship between marital status, literacy ratio, and LFP. A negative association was found between LFP and child-women ratio along with an inverse relation with nuclear family type. Shah then in 1986 attempted to observe changes in the role of women against Pakistan’s development using Panel data ranging from 1951 to 1981. The study concluded that the strict observance of purdah and the number of durable goods available, along with the level of husband’s own education level greatly limited female labour force participation. Kozel and Alderman (1990) made use of the OLS regression and Tobit model to determine the factors which affect labor force participation and supply decisions in urban areas of Pakistan. Rashed,Lodhi and Chisti (1989) examined Female labour supply determinants using a Probit model and only just focusing on Karachi. Both studies concluded a positive relationship between LFP and regressors : education levels and expected increase in wages. Presence of male members in the household found to decrease the likelihood of women working.
Ibraz (1993) studies on factors determining female work force participation based on the Rawalpindi district found religious and cultural views to discourage females from working such as observance of purdah and strict gender segregation, as these hindrances confine women to their private domains whereas Malik (1994) found variables such as age of the women, education and dependency ration to be insignificant in the determination of female labour supply but found there to be a positive relation between predicted male wage and female work force participation rate.
Objectives
This paper will aim to add to the richness of the existing literature by considering women’s own characteristics comparing not only the married with the unmarried but considering FLFP for the divorced and the widowed too along with a host of other variables. Our study will also be distinct in that it is using the actual labour force specific data from LFS 2012-13, which most other studies in this area have failed to use instead opting for Integrated household Surveys and PSLM to name a few.
Our first hypothesis is: women’s characteristics have no impact on their female labour force participation. Apart from this, we will be taking into account the fact that most women in Pakistan are dependent on the males of their household and face considerable constraints when it comes to them working outside of home. They are allowed to work only when the male is for some reason unable to do so or can’t find employment. Hence we will be evaluating the effects of properties related to the head of the household on the work participation rate of women: Second Hypothesis is: head of household’s characteristics have no impact on FLFP. Our third hypothesis focuses on whether the fertility of the women along with regional differences resulting from the women’s residence being in the urban or rural area has any impact on FLFP and if it makes a difference if the head of the household is a female. Then the third hypothesis is: household characteristics have no effect on FLFP in Pakistan.
For the purpose of testing these hypotheses, we will be using Labour Force Survey 2012-13, the labour participation rate in which is nearly equivalent (32.8 %, 32.9 %) and the gender-area wise rates congruent. Augmented participation rates seem to be curving downwards with most of the employed being classified as employees followed closely by own account workers (Pakistan Bureau of Statistics-LFS12-13).
Methodology
It is often the case that economists are faced with a dichotomous dependent variable which takes the value 1 if it’s one part of the binary and 0 otherwise. For such models, OLS and other standard estimators are deemed to be inappropriate due to the limited or qualitative nature of the dependent variable. And because this study inculcates within itself a dependent variable FLFP which takes the value 1 if the women is currently involved in economic activity for profit either on farms, shops, as employee, employer, and other modes of employment and 0 otherwise, we will be turning towards Probit model for estimation of our regressors and their due effect on FLFP.
The Probit model is based on the underlying latent variable FLFP where:
FLFP = F(Women own characteristics-WCH; Head of household characteristics-HHHC; Household characteristics-HC)
Instead of directly observing FLFP, we have assigned it a binary variable which is 1 if the woman in the sample is engaged in any form of economic activity as defined above and 0 otherwise. The residual value given above, εi, can be seen to represent any sampling errors that may have occurred and any misrepresentation of information on part of our sampling units. It is assumed to be normally distributed with mean 0 and constant covariance. Accordingly, we will be estimating three probit equations, one with a focus on urban areas of Pakistan, one focusing on the rural areas of Pakistan.
Results and Discussion
Results of the Table 1 provides us with standard probit parameters with their asymptotic t-statistics in parentheses, while Table 2 gives the predicted probabilities. We will be making use of Table 2 (predicted probabilities) for greater accuracy ad to account for the fact that other variables are more often than not never null but rather are at levels of which we have taken the average. Established relationships (signs) of all three results are the same. It can be seen that age has a positive impact on Female Labour Force Participation when Pakistan is taken as a whole and when separate regressions are run for rural and urban areas. A one unit or a one-year increase in age of the woman can result in 3.6 %, 2.8 % and 2.6 % increase in labour participation in Pakistan, Urban and Rural areas respectively. On the other hand, AGEsq i-e the squared of ages indicate a negative relationship with FLFP in all three cases intuitively due to the falling mental prowess of humans as they age.
Marital Status is another significant factor which determines whether women are allowed to work in Pakistan or not. The three sub groups of marital status, married, divorced and widowed, are being measured against the base group of unmarried women. We can see that a woman getting married decreases her chances of working by 21 % in Pakistan, rural and urban area following the same trend, however, the chances of a divorcee to work in rural areas increases in contrast to urban area and Pakistan in general. The variable indicating the divorcees is, however, insignificant in relation to FLFP. Widowship follows the same trend as being married, due to the religious obligations of women being confined in their houses for a fixed period of time and the societal stigma attached to widows working. This variable is insignificant too but results in relatively smaller decrease in FLFP as compared to being married, most likely due to the widows having to work to satisfy their basic needs and wants after the passing of their husbands. Education(Primary, Secondary and High) is positively related to FLFP in all three incidence and establishes itself as a strong determinant of women economic participation for profit as apart from these values being statistically significant, secondary and higher education increase the probability of women working in Pakistan by quiet a lot i-e 30 % and 52.4 % respectively. Primary education, though has a positive effect on FLFP, is deemed insignificant in urban areas where strict competition and the education spiral moves the employers to favour those who are highly educated whereas in Rural areas, primary education is significant at 5 % sig.level but leads to a mere 3.8 % increase in females working. Secondary and higher education statistics in rural areas: 14.5 % and 48.1 % respectively, however, indicate a substantial increase in the probability of women working than those who are not educated up to these levels. We have discussed Women’s own characteristics up till now, however, due to the long standing patriarchal mind-set that prevails in Pakistan, a majority of women are made to follow the decisions of their male counterparts who may or may not only allow their female relatives to work, but rather whose own characteristics can have a profound impact on whether the wife, a daughter, a sister or the mother works. Hence, we have included the properties of the men of the households who in Pakistan are considered head of the family.
Unlike the females themselves, higher the age of Head of household (men) , the lesser the incidence of women working in Pakistan(rural and urban) although the parameter for urban area is insignificant. Similarly, higher the education level of a man, higher the probability of a woman not working. This may be due to an illiterate male head having lower prospects of a job and a good one at that and hence the woman working to help with the finances of the house. We can observe decreasing FLFP by a bigger ratio as the head passes the education levels of primary, secondary and high in Pakistan: from a 2 %(insignificant) decrease in FLFP from the male head being primary educated to a 7.3 % decrease in FLFP if the male head gains higher education.
An unusual finding though comes in the form of a positive, significant relationship between FLFP and the employment status of the male head which also clash with the estimates of the probit equation in table one. Predicted probabilities indicate the probability of women working actively in the labour force to increase if either the male head is an employer, an employee and or self-employed by 13.1 %, 51.9 % and 31.3 % in Pakistan while the probability of the woman working decreases if the male head is an unpaid family worker. In contrast to this, the probit coefficients indicate a decrease in women working if the male head is an employer of sorts or self-employed in Pakistan. This in itself is contradictory to the estimates of urban and rural probit coefficients which indicate a positive relation between FLFP and the male head being employed. Marginal Effects follow the path of the predicted probabilities. A deviation from this unusual trend is in urban areas where if the male head is an employer in an enterprise or self- employed, owning his own business, then FLFP decreases. It is difficult to explain this anomaly. The remaining two variables referring to Household Characteristics indicate a higher probability of women working in the workforce if they are the Head of the households by 46.8 %, 22.3 % and 42.5 % in Pakistan, urban and rural areas respectively. As head of the household, they are likely responsible for bringing in the required income to satisfy the basic needs of the house. On the other hand, greater the number of dependent children who the women, as tradition requires them to, have to look after, lower their economic activity for profit in all three instances.
Conclusion and Policy Implications
In order to identify the factors that determine female labour force participation, this paper has made use of the Probit model to account for dependent binary variable and have used Labour Force Survey 2012- 13 to adequately use data collected with the view of discerning the workforce position of Pakistan. 3 sets of independent variables were used to explain FLFP; Women’s own characteristics, Head of Household Characteristics, and Household characteristics and their results declared. The low participation rate amongst females of Pakistan can be attributed to disruption in their education due to marriage, domestic duties and household discriminatory views. These factors do not only mean that employers offer them lower wages to account for their transient position but due to women’s own high reservation wages and lower demand for their labour, a discouraging framework is established for them to work. However, taking into account the evolving state of female labour force participation over the decades, it is clear that female population can now greatly alter the path of development and provide third world countries such as Pakistan much needed human capital which can go on to increase national income. However, the relationship between participation and economic growth is not as straightforward as it seems because a lot goes into the decision-making process of a woman deciding to work. It is these factors that this paper has analysed to better equip development economists on the policies which target women specifically and aim to increase FLFP. Beyond the standard labour force statistics, policy makers should ensure that women are provided equal educational facilities as this one factor can increase the probability of a woman entering the workforce manifold.
An alternative to educational facilities, is providing vocational training pertaining to established industries in Pakistan so that women are not left behind men when it comes to labour force participation. Emphasis should be placed on the education of young girls so that they don’t drop out, rather complete higher levels of education and make use of better employment opportunities. Apart from education, a change in mind set is needed such that the males of the household, along with the females, are made aware of women’s rights and their ability to work and work effectively. The stigma around any female working needs to be removed and wider options of fields should be made available to them for equal dispersion of gender across occupations. With about half of Pakistan’s population consisting of females, obstacles on their path to work will hinder the country’s development. In order to ease the burden of domestic responsibilities, government can establish care centres to look after children while mothers work.
References
Berndt, E. 1996. The practice of econometrics. New York: Addison Wesley Longman Publishing Co.
Mahmood, A. 2005. Pakistan Society of Development Economists, Export Competitiveness and Comparative Advantage of Pakistan's Non-Agricultural Production Sectors: Trends and Analysis. PIDE.
Naqvi, Z. and Shahnaz, L. 2002. How do women decide to work in Pakistan?. The Pakistan Development Review, pp.Part II: 495- 513.
Todaro, P. and Kuznets, S. 1990. Economic Development, the Family, and Income Distribution: Selected Essays. Population and Development Review, 16(1): .176.
(University of Peradeniya, 2017-10-12) Sifani, M.F.; Rajeswaran, T.
Introduction
Trade liberalization is the removal or reduction of restrictions or barriers on the free exchange of goods between nations. This includes the removal or reduction of both duties and surcharges and non-tariff obstacles like licensing rule, quotas and other requirements (Hamad et al. 2014). Many high income countries follow the path of trade liberalization policy to protect their market, competitive with other countries and to achieve their goal fast (Jayatissa 1991).
Trade openness has been continuously increasing after trade liberalization policy introduced in Sri Lanka in 1977 and Sri Lanka is the first country to open up the economy in South Asia. In addition to that Sri Lanka started to move forward in direction of intra-regional and international trade by liberalizing its trade policies to some extent. Many researchers (Manni and Afzal, 2017; Kassim and Lanre, 2013) have analyzed the relationship between trade liberalization and the economic growth all over the word, and some in Sri Lanka using different approaches. However the quantitative assessment of impact of trade liberalization on export in the context of Sri Lanka is limited. Therefore, this study attempts to fill this gap.
Objectives
The main Objective of this study is to examine the impact of trade liberalization on export of Sri Lanka since 1977.
Methodology
We used annual time series secondary data covering the period 1977- 2015 to analyze the objective of this study. The data of export, foreign direct investment, nominal exchange rate, foreign income (America’s GDP), openness and consumer price index (It is using for price of exports) were obtained from word development indicators data base on the World Bank. All the data was transformed in to natural logarithm form to reduce the heteroskedasticity
ADF, PP and KPSS unit root test is applied to check stationarity properties of the time series data. Akaike Information Criterion (AIC), Schwarz Information Criterion (SC), Sequential modified LR tests statistics are adapted to determine the optimal lag length. The number of co-integrating relationship is examined using Johansen co-integration approach which is described as below,
Where, lnEX: Export as a dependent variable in natural log, lnFDI: foreign direct investment in natural log, lnOPNN: openness in natural log, lnCPI: consumer price index in natural log, lnGDPus: foreign income in natural log, lnNER: nominal exchange rate in natural log and is the white noise error and t refer the period of time. We used Error Correction Model (ECM) to identify the short run relationship as well as long run adjustment of the modelwhich is given below
Where, Π=αβ′. α : is the ( 6×1) vector of speed of adjustment co-efficient, β′: (1×6) vector of co-integrating coefficients, vector of dependent variables, lagged value of and : white noise error term. We used STATA software to analysis the model.
Results and Discussion
According to the unit root test results, all three unit root tests confirmed that all variables are stationary at their first difference. Sequential modified LR tests statistics is suggested to use one lag as optimal lag length. The Trace Statistic of Johansen co-integration technique detected one co-integrating relation in the system of equation at 5 % level of significance. Following equation shows the long run relationship of Model.
This results shows that FDI,CPI and OPENN has a significant effect on EX at 1 % significance level and ER and GDPus does not has a significant effect on EX at any significant level. FDI has negative and significant long run relationship with EX and CPI ad OPENN have positive and significant long run relationship with EX. Many research support to our results (Onafowora and Owoye, 1998; Santos-Paulino, 2002)].
Table 1 shows the results of long run adjustment of the Error Correction Model. According to the results of the coefficient of speed of adjustment of our dependent variable export is negative as expected but which is not statistically significant. It means that the external shock do not bring the model to the steady state line significantly in the long run. Because there are many countries trying to catch the world market so, if Sri Lankas’ exports affect by external shock, other country will catch the Sri Lankas’ place. Therefore, external shock does not bring the model to the steady state line significantly in the long run.
Table 2 shows the results of short run relationship between the variables. According to the results the value of intercept 0.094 shows that the export value when the other variables are constant. There is no any short run relationship is identified between export and last year value of the variables.
Conclusion and Policy Implications
This study examines the impact of trade liberalization on export in Sri Lanka. The all three unit root test results confirmed that all the variables are stationary at their first difference of logarithm. Sequential modified LR tests statistics is suggested one lag as optimal lag length. Johansen co-integration technique detected one co-integrating relationship between the variables which is used in this study. The co- integration results confirmed that EX has positive and significant relationship with CPI and OPENN while negative and significant relationship with FDI in the long run. According to the co-integration model long run relationship if openness increase by one percentage Export will increase by 0.99 percentage. Based on the findings, trade openness has significant and positive effect on export of Sri Lanka so, if Sri Lanka wants to increase the export Sri Lankan government should use openness as a policy tool.
References
Hamad, M. M., Mtengwa, B.A. and Babiker, S. A. 2014. The Impact of Trade Liberalization on Economic Growth in Tanzania.International Journal of Academic Research in Business and Social Sciences. 4(5): 514-532.
Jayatissa, R. A. 1991. Economic Liberalisation and Export Growth. Sri Lankan Economic Journal. 6(2): 68-87.
Onafowra, O. A. and Owoye, O. 1998. Can Trade Liberalization Stimulate Economic Growth in Africa. World Development. 26(3): 497-506.
Pacheco-Lopez, P. 2005. The Effect of Trade Liberalization on Exports, Imports, the Balance of Trade, and Growth: The Case of Mexico. Journal of Post Keynesian Economics. 27(4): 595 - 619.
Santos-Paulino, A. U. 2002. Trade Liberalisation and Export Performance in Selected Developing Countries. The Journal of Development Studies. 39(1): 140-164.
(University of Peradeniya, 2017-10-12) Dissanayake, D. M. D. K.; Dorabawila, S. S. K. B. M
Introduction
The employees of every country can be identified as formal sector and informal sector employees. In most of the developing countries’ the predominant sector is the informal sector. Sri Lankan national definition of the informal sector states that an institute is informal if there is no registration of the institute under the employees’ provident fund and/or Inland Revenue Department, no formal accounts maintained and the number of regular employees less than 10 (DCS, 2017). Employees of the informal sector have to face many difficulties. Currently, there is no formal mechanism established for the informal sector pay and benefits schemes in Sri Lanka.
Aruntilaka (2004) states that the market forces decide that wages of the informal sector of Sri Lanka. A study by Gunatilaka (2008) shows that the ability to earn in this sector can change according to the area of employment. These statements confirm the research by Saget in 2006on wage in the informal economy in Brazil, India, Indonesia and South Africa for Sri Lanka as well. According to Banerjee (2014) the wages of the informal sector should be decided through the trade liberalization policies. Cho and Cho (2011) deduce that the gender wage gap of the informal sector as the worst.
Objectives
This research examines the functionality of the existing informal structures used in determining informal sector wages in Sri Lanka and compares the available structures with the existing systems in other countries. Based on the above country comparison results, this study proposes essential factors to be incorporated in determining a methodology for a fair wage for daily informal sector workers, acceptable for Sri Lanka.
Methodology
This study is based on primary data and secondary data. A total sample of 108 employees and employers were selected from the informal sector from Anuradhapura and Mullaitivu districts by using multistage sampling in 2016. Sample consisted of 54 employers and 54 employees with a representation from agricultural (36), industry (36) and service (36) sectors. Two separate questionnaires were administered among employers and employees to collect the primary data and the secondary data were collected from publish documents from several institutions. For the data analysis, descriptive method and multiple regression estimation were used.
Results and Discussion
According to the National Minimum Wages Act No. 3 of 2016, for the first time in the country, a mandatory national minimum daily wage of Rs. 400 was fixed payable to all workers by all employers in the country. The daily wages between the two districts differ by sector and gender (given in figure 1.1). In the agricultural sector the daily wage in Anuradhapura is 49 % higher than Mullaitivu. The average overall daily wage is 191 % higher than national minimum daily wage of 2016. Lowest average female daily wage (Rs. 833) is also 9 7% higher. There is a considerable variation by district compared to the national minimum daily wage.
A multiple regression model was used to determine the factors that affect the daily wage of the employee. Five separate regression models were estimated for the surveyed data (One for each district, Employees, Employers and overall sample- given in Table 1). According to overall sample regression results, districts, gender, labor supply demand, wage of nearby areas, hours of work, experience, service sector and agriculture sector had a statistically significant impact in determining informal sector wages. Besides that, for Anuradhapura district number of working hours, experience, wage of nearby areas, labor supply and demand, gender and additional benefits determine the wages of the informal sector. For Mullaitivu, wage of the nearby areas, labor supply and demand, gender and service sector had an impact on a workers’ daily payment. Among the variables significant for Mullaitivu, only service sector variable was not among the significant variables for Anuradhapura district. According to regression results of this study, different factors influence the daily wage levels in each district. The level of education and age of the employee had no impact on wage in the informal sector employment.
This research studied informal sector wage determination structures of several countries in the world (Brazil, India, Indonesia and South Africa). The study found that the countries use different criteria to determine the level of informal sector daily wage. These countries had used criteria such as occupation, power to form groups, collective agreements and social security benefits. In most of the countries, the informal sector wage is determined based on various characteristics of the locality such as the districts and states. Furthermore, some labor regulations, such as the minimum wage in Sri Lanka are applicable to formal as well as the informal sector jobs. However, since there is no contractual binding (This can have positive impact on the salary and the other benefits of informal sector worker.) between the employers and employees in the informal sector, there is no mechanism to go for litigation. And also this study found informal sector employees can be divided mainly into two categories as casual workers and seasonal workers. The employers and employees lack knowledge on the wages and other benefits.
Conclusion and Policy Implications
This study identifies a set of essential factors to be considered in determining the informal sector minimum daily wage for informal sector worker in Sri Lanka. Policy makers must take into account the following factors such as district/state of the employment, industry of employment, wage of nearby areas, labor supply and demand and gender in determining the informal sector wage. Based on these identified, influencing factors, the government can introduce a mechanism to determine the informal sector wage, new saving systems, insurances, pension systems for informal sector. The employers and employees must be well-informed about their expected daily wage and other benefits. There are some labor regulations that are formally constituted, equally for both the formal and informal sector jobs. However, when implemented there are areas that require policy makers’ attention to rectify possible short-comings that can impede the benefits to the informal sector workers.
References
Gunathilaka, R. 2008. Informal Employment in Sri Lanka: Nature , Probability of Employment and Determinants of Wage. http://www.researchgate.net
Hohberg, M. and Lay, J. 2015. The Impact of Minimum Wages on Informal and Formal Labour Market Outcomes : Evidence form Indonesia. IZA Journal of Labor & Development, 4:14
Labour Force Survey-Department of Census and Statistics. 2017. http://www.statistics.gov.lk
Saget, C. 2006. Wage Fixing in the informal economy: Evidence from Brazil, India, Indonesia and South Africa. Conditions of Work and Employment Series No. 16
(University of Peradeniya, 2017-10-12) Paranamana, G. P.; Ranjith, J. G. Sri
Introduction-
Although the government involvement in economic development has been substantially high in Sri Lanka, the investment has been highly dominated by the private sector accounting for 20 % of GDP on average over the proceeding decades. It apparently indicates that the fiscal policy and budget deficit is conducive for thriving private sector businesses. Hence public sector spending may have helped in developing infrastructure and work force development for encouraging private investment. With this move, fiscal policy influences the macro economy through a number of ways; it changes the level and composition of aggregate demand, changes aggregate supply and influences national savings and investments (through expenditure and taxation). As an emerging economy Sri Lanka and its government expenditures show the directions to develop productive investments and human capital infrastructure through the government economic policy packages. However, this field of study in economics have no clear policy direction given and highly debatable over the experience of different contexts (Biza, et. al., 2013; Rathnasekara, 2016). With this background, this research therefore focuses on empirical study on how budget deficit and fiscal policy of the country effect on private investment maintaining macroeconomic stability to achieve sustainable growth. This study attempts to investigate whether there is an empirical relationship between budget deficit and private investment. We consider two types of investment: Domestic Private Investment and Foreign direct investment.
Objectives
The main objective of this study is to assess the policy effectiveness of the government in achieving high and sustainable economic growth in compliance with fiscal consolidation effort.
The secondary objectives are to investigate the determinant factors of private investment and also to examine whether there is a crowding out or in effect between budget deficit and private investment.
Methodology
The empirical model constructed for this study is based on the regression model by Samwel (2016) that used for his study regarding the Tanzanian economy. We have modified that model by adding new variables suitably to conduct our study. We took log difference for all variables.
Where PI refers to Private investment which can be divided into two, those are DPI and FDI (Domestic Private Investment and Foreign Direct Investment respectively as a ratio of GDP); CPI refers to Consumer Price Index, ER refers to Exchange rate (LKR per $) and BD refers to Budget deficit. There is no surplus value for the relevant period. So we consider only absolute value of BD defined as a ratio of GDP. This study covers time period of 1990 to 2015. The relevant data were collected from annual Reports of Central bank of Sri Lanka.
At the first step of the estimation procedure, ADF test and Phillip Peron tests were used to check the stationary of data. Johansen co-integration test was used to identify the long-run relationship and also VECM was used to identify both short-run and long-run relationship as well as long-run equilibrium among the variables.
Results and Discussion
Unit root test revealed that all variables were non-stationary at the initial level, but stationary at the First difference. According to lag length criteria, AIC and HQ criteria were selected 2 lags. LR, FPE and SC criteria were selected 1 lag. Most criteria were selected in 1 lag. So lag length test suggested 1 lag. Johnsen co- integration trace test has detected co-integration relationship for both model which implies that there is a long -run relationship, long -run speed adjustment and short-run relationship are examine using Vector Error Correction Model.
The Equation 3`and 4 show long-run relationship:
According to above results, all variables are significant at the 5 % significant level at the long-run. Therefore, this results show that government fiscal deficit positively impact on domestic investment and also on foreign direct investment. For instance, when BD increases in 1 %, DPI increases in 5.27 % and also FDI increases in 1.03%. As it similar to the findings of literature, (Coban and Tugcu, 2015) the empirical estimation results of our model reveals that there is a long-term relationship between private investment and its determinants specified in the model. Also it clearly shows that government budget has been favourable for investment.
Since Error Correction term of the both models are significant and negative the long-run adjustment relationship can be identified related to PI and FDI (See Table 2). According to Equation 1 speed adjustment is -0.59 which means that after an external shock, domestic private investment moves, from short-run to long-run steady state after one year. And also According to equation 2, speed adjustment is 1.57 means that after an external shock, foreign direct investment moves from short-run to long-run steady state after one year.
According to above results there is no significant relationship among the variables at the short-run consider about DPI. However, Last year FDI and Current year FDI has positive significant relationship.
Conclusion and Policy Implications
The empirical results indicate that budget deficits have been favourable for both domestic and foreign direct investment in the long-run. Also budget deficits are favourable for foreign direct investment at the short-run. Under the current fiscal policy the government spends more on improving public welfare, physical and social infrastructure development. These expenditures will have a tremendous positive impact on investment potentials in Sri Lanka. And also, government established BOI and tax reduction and concessions have made an optimistic view for investors. Therefore, current phase of fiscal policy stance is conducive for foreign investment in the short-run and long-run. Also we can say that although there is a crowding out effect on domestic private investment in the short-run, the current fiscal policy has a crowding in effect on domestic private investment in the long-run
References
Central Bank of Sri Lanka, Annual Reports for the years 1990-2015. Colombo: Sri Lanka.
Rathnasekara, H. 2016. Does Private Domestic Investment Crowd Out Foreign Direct Investment (FDI) in Sri Lanka? Evidence from Multivariate Vector Error Correction Model’. 26th Asian Economic Symposium, pp. 23-38.
Samwel, M. 2016. Do Budget Deficit Crowds Out Private Investment: A case of Tanzanian Economy? International Journal of Business and Management, 11(6): 183-189.
(University of Peradeniya, 2017-10-12) Pushpakumara, G. G. D.; Dissanayake, D. M. T. G. C. H.
Introduction
Throughout the history of Sri Lanka, the islanders have practiced eco- friendly farming. We can trace the history of eco-friendly farming practices from the era of kingship as the farming was the main livelihood and farming related activities embedded to the culture and religious beliefs. The saying “ ගමයි පන්සලයි වැවයි දාගැබයි ” summarizes how much farming, culture and the religion was embedded together.
As an island nation with adequate natural resources Sri Lanka is being able to practice organic farming and sustainable eco-friendly agricultural practices. The farmer friendly weather with tanks, rivers, scattered all over the island with religious belief of optimum use kept farming a peaceful livelihood(Warnakulasooriya and Athukorala, 2016) . With the arrival of the open economy and embracing the green revolution, the farmers found interest in high yield crop varieties which demand inorganic fertilizers, and pesticides.
By focusing only on high yield the farmers have lost some of the key expectations, outcomes, and ethics of environmental friendly agriculture and excess use of fertilizers, pesticides, and technologies created health issues among consumers. Having popular media started to discuss the consequences of inorganic farming there is a rising trend among the consumers that they seek organic food, in order to be healthy and stay away from Non-Communicable Diseases (NCD) like Kidney failures, cancer etc.
Objectives
The objectives of this performance are to, discover the attitude and awareness of the consumer about the organic food and identify the needs of organic farmers to meet the market demand with quality products.
Methodology
This research was performed with the primary data collection from 48 individuals by means of a questionnaire survey among randomly selected 04 farmers, from Badulla and Monaraagala districts to get information about the supply and demand, and expectations during the period of June 2017. 04 established organic food sellers were interviewed at their respective outlets and the randomly selected 40 consumers at the same were interviewed on their consent.
The questionnaire for consumers collected the data on awareness on cultivation environment, type of fertilizers use, certification procedure, assurance, and their willingness to pay. The questionnaire for the farmer’s collected the data on their education, capacity, revenue, challenges and opportunities and rewards they wish to have. Food seller’s questionnaire collected the data of market demand, certification, challenges, strategies and pricing. Finally, the raw data was gathered in a Microsoft Excel spreadsheet and the frequency and percentage was calculated for further analysis.
Results and Discussion
The awareness on the harmful effects of chemicals present in food is increasing among the consumers. The trend towards purchasing organic food is growing among people. Some of the prominent motivating factors to purchase organic foods include environmental concern, health concern and lifestyle, product quality and subjective norms. Given this background, we first investigate the descriptive statistics of the survey.
The age categories of the consumers revels the purchasing power of the consumers as well as their willingness to pay. The consumers below age 30 has less purchasing power compare to other age categories. Also the data analysis shows that those who are above age 31 are having higher income and high profiles. On the other hand above age 31 categories are health conscious compare to below age 30 consumers.
The data of consumer’s actual awareness on organic food they consumed was collected and analyzed. Hence, the analysis tells that the type of awareness determines the quality of the awareness and rightreasons to demand organic food.
The farmers’ age and education seems to have a relationship with their level of satisfaction of the return and the interventions done by the organic food selling organizations. Also, the farmer’s ability in supply the demand of the organizations also depends on the age and education.
The summary of the survey with individual farmers shows that 13 % of them would like to have training and workshops in organic farming including costing, budgeting, planning with training on leadership, marketing and organic farming. 37 % of them would like the food selling organizations to assist them in organic food certification whereas 50 % of the farmers would like to have all the training, workshops with assistance in getting certification.
Conclusion and Policy Implications
The results reveal that consumers are not well aware of the essential ingredients in organic farming. It is recommended to have detail documentary / short video clips at both outlets and social media to give a better awareness. In order to meet the market demand, produce quality food and maximize the profit it is recommended for organic food selling organizations to capacitate the registered farmers with training and workshop in the area of strategic planning, value chain analysis, and supply chain management through visual media and exposure visits to successful farmlands.
References
Alvares, C., V. Shiva, and S. Ismail 1999. The Organic Farming Reader. India: Other India Press.
Beharrel, B. and J.H. Macfie. 1991. Consumer Attitudes to Organic Foods. British Food Journal 93(2): 25-30.
Guthman, J. 2000. Raising organic: An agro-ecological assessment of grower practices in California. Agriculture and Human Values, 17(3): 257-266.
Haas, G. 2006. The Organic Agriculture Approach in Organic Agro Expertise. www.agroexpertise.de
Lohr, L. 1998. Implications of Organic Certification for Market Structure and Trade. American Journal of Agricultural Economics 80(5):1125-1129.
Piyasiri, A.G.S.A., and A. Ariyawardana. 2002. Market Potentials and Willingness to Pay for Selected Organic Vegetables in Kandy. Sri Lankan Journal of Agricultural Economics 4(1):108-119.
Warnakulasooriya, H. U. and W. Athukorala. 2016. Productive efficiency of rice farming under rain-fed conditions in Gampaha and Kalutara Districts of Sri Lanka. Sri Lanka Journal of Food and Agriculture, 2(1): 51-64.
(University of Peradeniya, 2017-10-12) Thilanka, H. R. A. C.; Ranjith, J. G. Sri
Introduction
Government debt can be considered as one of the major sources for financing the government operational activities under the fiscal policy. If borrowed funds are used for long-term development it may lead to have higher returns. However, if borrowings are not efficiently utilized it may have detrimental impacts on the long-term economic development. Borrowings from domestic banking sources may affect interest rate and then the ability to access loanable funds for private sector may discourage. Also, a huge amount of debt service payment impedes the flowing resources towards economic development and broadening the fiscal deficit. Sri Lankan experience shows the accumulation of large public debt and recorded an increasing trend in both foreign and domestic debt over the last few decades. As a result, the economy has been led to a macroeconomic instability (Sanderatne, 2011). After significant changes happen in monetary policy with introducing liberalization economic policy in 1977, along with domestic debt foreign debt also increased for the purpose of development activities and to face the difficulties of the balance of payment. Then, total public debt was 68.6 as a percentage of GDP by 1977 and it increased up to 103.3 in 2001 with the economic recession and in 2015 domestic debt was 44.3 percent and foreign debt was 31.7 percent (Central Bank of Sri Lanka, 2015). Sanderatne (2011) reported that, along with public debt, large debt servicing cost, growing fiscal deficit, limited and low level of revenue and big losses on public enterprises so have caused further borrowings by the government. Along with the government sector, the private sector which holds a major role of the economy can be affected through the increasing debt which may impede the availability of resources for the private sector.
With the end of civil war in 2009, investment has become one of dynamic forces leading the country to well-equipped economy through infrastructure. In order to contribute to the economic development of the country, private sector also has tended to hold a significant portion of the total investment. In 2014, private investment was 22.9 as a percentage of GDP, but public investment was only 6.8 as a percentage of GDP (CBSL, 2014). Hence, it is clear that both private and public investments are not at the sufficient level in order to accelerate the economic growth and development. Crowding-out effect is one of the main scenarios which can be used to explain how public debt affects private investment. Under the Ricardian Equivalence view there would be no crowding-out of private investment when the government borrows money. In contrast, Neo-Classical School shows that increases in budget deficits cause increases in interest rates. Thus, budget deficits "crowd-out" private spending since the private sector borrows less at high interest rates (Carassco, 1998). Keynesian economists argued that public investment crowds-in private investment because of the multiplier effect (Saeed et al., 2006).
When public investment increases aggregate demand increases and then it causes more motivations for private investment. Along with this theoretical back ground many researchers have focused their attention towards examining the crowding-out effect. A study conducted by Akomolafe et al. (2015) using Johnasen Co-integration test and Vector Error Correction Model (VECM) shows that domestic debt crowds-out domestic investment in both short-run and long-run while external debt crowds-in domestic investment in the long-run. In contrast, Apere (2014) pointed out in his study, domestic debt has a linear and positive impact on private investment while external debt has a U-shaped impact on private investment in Nigeria. According to a study conducted by Dayrathna-Banda and Priyadarshanee (2013) there is no financial crowding-out effect of fiscal expansions in Sri Lanka because of accommodative monetary policy. With this theoretical and empirical back ground, it is worthwhile to examine that whether there is a crowding-out effect of public debt on private investment in Sri Lankan economy. Since the lack of consistency in conclusions, further research on this problem will help to provide clear policy directives for economic development.
Objectives
The primary objective of this study is to identify whether public debt crowds out/in the private investment through both domestic and foreign public debt in Sri Lanka. Secondary objective is to emphasize the importance of public debt management to increase the private investment.
Methodology
The theoretical framework constructed by Akomolafe et al. (2015) which considered public debt crowds out/in private investment using an econometric model (Johnasen Co-integration test and Vector Error Correction Model) has been modified appropriately to address this research problem regarding the Sri Lankan context including Debt Servicing Payments, Domestic Credit to Private Sector and Political Stability as new variables.
Where PI is the Private Investment as a percentage of GDP, EXD is the External Debt as a percentage of GDP, DD is Domestic Debt as a percentage of GDP. GDP is the Growth Rate of Gross Domestic Product, INT is the Real Interest Rate, DSP is the Debt Service Payment as a percentage of GDP, DCP is the Domestic Credit to Private Sector as a percentage of GDP, PLS is the Political Stability, ε is the error term, t is the time period (1988-2015). Data were extracted from annual reports of Central Bank of Sri Lanka and Ministry of Finance. Johenson Co-integration and Vector Error Correction Model were used to investigate the crowding out/in effect. Before doing these tests, ADF test and PP test are used to test the stationary property of time series data.
Results and Discussion
According to above mentioned two unit root tests, all variables are stationary at their first difference, suggesting that they are integrated in order one [1(1)]. Then, to examine the lag length SIC, LR, FPE, AIC and HQ criteria were used. As SIC criterion suggested that no lag length and other criteria suggested that one lag length, one lag length was used for other tests. Then, Johanson Co-integrating test was done to ensure that whether there is a long-run relationship between variables. According to this test, two co-integrating equations are identified at 5 % significant level which implies that there is a long-run relationship between variables. In order to identify the nature of the long-run relationship Johanson Co-integration technique is adapted and long-run adjustment and short-run relationship are examined using Vector Error Correction Model. According to co-integrating results, the long-run relationship between the variables is shown in Equation 2. Only significant variables were included into the estimated model which is given as below.
As shown in Equation 2, the results of all variables are significant at 5 % level of significance in long-run. Since the primary objective of this study is to identify the crowding out/in effect using both external and domestic public debt, the impact of both kinds of debt on private investment was observed. When domestic debt increases by 1 % of GDP private investment decreases by 0.261 % of GDP and whe external debt increases by 1 % of GDP private investment decreases by 0.255 % of GDP. Then, it is clear that public debt crowds out the private investment in long run. By supporting to this effect interest rate negatively affects the private investment in long-run according to above results.
Since Error Correction term of the model is significant and negative the long-run adjustment relationship can be identified related to private investment. This result shows that speed of adjustment is 0.56 which means that after an external shock, private investment moves from short-run disequilibrium to long-run steady state with speed of 0.56 in each year. And also, as domestic debt variable is significant at 1 percent and positive long-run adjustment relationship exists between domestic debt and private investment.
Conclusion and Policy Implications
The empirical results indicate that both domestic and foreign debt crowd-out private investment in long-run, but not in the short-run. Also domestic credit to private sector and debt servicing payment positively affect the private investment in long-run. Furthermore, political stability seems to associate closely for the volatility of private investment in short run showing that private investment responses instantly for the instabilities in the economy. The results of this study can be contributed for policy making considering the impact of public debt on private investment. Hence, the government should make maximum effort to manage public debt appropriately in order to mitigate the pressure on interest rate. Also measures should be taken to improve revenue through appropriate tax policy reforms and using of non-bank borrowings in the long-run.
References
Akomolafe, K. J. Bosede, O. Emmanuel, O. and Mark, A. 2015. Public Debt and Private Investment in Nigeria. American Journal of Economics. 5(5): 501-507.
Akram, N. 2013. Empirical Examination of Debt and Growth Nexus in South Asian Countries. Asia-Pacific Development Journal. 20(2): 29-48.
Apere, T. O. 2014. The Impact of public Debt on Private Investment in Nigeria: Evidence from Nonlinear Model. International Journal of Research in Social Sciences.4(2):130-138.
Sanderatne, N. 2011. The Growing Debt Burden. The Sunday Times, 3 July 2011
(University of Peradeniya, 2017-10-12) Chandrasiri, K. A. D. S.
Introduction
Dengue is a vector borne arbo viral disease and it is transmitted by two mosquito species namely Aedes aegyptii and Aedes albopictus. Dengue virus is named as DENV and it belongs to the genus flavivirus in family flaviviridae. It has 4 antigenically different serotypes, DENV1, DENV2, DENV3, and DENV4. Infection with a single DENV serotype leads to long-term immunity against that particular serotype, however, not against the other serotypes. Therefore, prior infection with a single serotype of DENV only provides a homotypic protection (Sirisena 2013).
All serotypes of DENV have been seen in Sri Lanka for more than five decades and their distribution has not changed significantly in the last 30 years. Although the Sri Lankan population had been exposed to DENV for a long time, the severe forms of DENV infection (DHF and dengue shock syndrome (DSS)) were very rare before 1989. There was an island-wide epidemic of DF associated with DENV serotypes 1 and 2 from 1965 to 1968. This epidemic caused 51 DHF cases and 15 deaths.5 DENV-1 and DENV-2 were isolated from the outbreaks in 1965 and 1966 (Sirisena 2013).
The disease is seen in tropical countries and the burden of disease has increased by 30-fold over the past 50 years (Ebi 2016). By 2017, this is the most concerned public health issue in Sri Lanka. The reported numbers of cases have increased gradually and the increment is 840.5 % since 2002 through 2016. There are various numbers of reasons for this including urbanization, climate change, and poor waste management. 57 years have passed since Sri Lanka started to experience Dengue but 2017 is the year that recorded the highest numbers of patients and it’s only for 6 months.
Numbers of studies have already been undertaken to investigate the various aspects of the link between climate change and the spread of dengue fever in different countries Rigau-Perez et al. (1998) observed that high humidity is favorable for increased dengue disease transmission, hatching and activities of mosquito vectors. According to findings of Tun - Lin et al. (2000) development rates of Aedes aegpti eggs, larvae, pupae, increased with increased temperature. Their findings are similar to observations of Rueda et al. (1990). Cyclical nature and seasonal increase of dengue disease was studied Reiter (2001) and he found a condition between climatic changes and disease occurrence. It is clear that dengue transmission is influenced by several factors related to households, individual and environmental. Similar findings were made by Hoeck et al. (2003) who observed that monsoon rains in neighborhood areas increased the population of mosquitoes. According to Sukri et al. (2003) as well as Wilder - Smith and Gubler (2008) ideal conditions for dengue fever transmission were stated to be enhanced by high population density of both humans and mosquitoes. While Siqueira-Junior et al. (2008) reported that spatial distribution of dengue cases depended on the community status of individuals, additional factors such as demographic density, population motility and sanitation contributed to the spread of mosquitoes and dengue incidence.
The above review of the previous studies shows that these studies have only provided limited information on the disease pattern. Accordingly, it is obvious that more conceptual and theoretical work is needed to develop a better understanding of this field.
Objectives
The objective of this study is to analyze the seasonal pattern of Dengue in Sri Lanka. There are numbers of diseases which show seasonal pattern ranging from childhood diseases such as measles, chicken pox and faeco-oral infections to vector-borne diseases such as Leptospirosis and Dengue (Grassly et al. 2006). Only a few numbers of research papers could be found on this subject. Therefore, it is important to study the epidemiological dynamics of a disease in terms of planning control strategies.
Methodology
Nationally accepted data on reported dengue cases and population were used as secondary data in this study. As far as the data on Dengue reported cases are concerned, monthly as well as biweekly reported numbers were used and they were categorized based on districts and MOH (Medical Officer of Health) areas. The data were analyzed using Excel to evaluate the spatial distribution and the relationship with population variables. Various charts and graphs are used to describe the relationships between variables as well as the disease prevalence across the year and districts.
This study used two type of data. They are reported dengue cases and population data. The data on reported dengue cases used in this article were retrieved from the information published by the Epidemiology unit of Sri Lanka ministry of health. Those are freely available in their official website(www.epid.gov.lk). Population data which are used while preparing this article were taken from the official website of the Department of census and statistics of Sri Lanka (www.statistics.gov.lk). The data on reported dengue cases from January 2002 to June 2017 were used to analyse of this study.
Results and Discussion
Dengue fever is an infectious tropical disease caused by the denguevirus and it is transmitted by several species of mosquito that breed under different climate situations(Athukorala, 2016). Infection with a different type increases the risk and there is no available vaccine, to prevention reducing the habitat and the number of mosquitoes and limiting exposure to bites. According to the WHO report (2012) approximately 2.5 billion people, two fifths of the world's population is now at risk from dengue and estimates that there may be 50 million cases of dengue infection worldwide every year. The disease is now endemic in more than 100 countries.
As far as the reported dengue cases since 2002 in Sri Lanka are concerned, it is noteworthy that there is an increasing trend over the time. There were 8,931 cases in 2002 and it was increased up to 55,150 by 2016. The difference is 46,219 and it was 517.5 % increment. More steep increment is observed in 2009 and it was 35,095 cases island’s cumulative. The dengue cases were increased by 20,055 and the increment is 57.14 % from 2009 to 2016. More intensive increment can be observed from 2009 to 2016 and more in 2017 making cumulative cases 83,997 only till June.
There is distinctive pattern of dengue disease throughout the year. This is generally equal in almost every year. There are two dengue case peaks in a year while no zero case months. One peak is in June/ July while other peak is in December/ January. This characteristic “W" pattern is evidenced in every year from 2012 and this is clearly seen in monthly average of dengue cases in Sri Lanka. The height of the peaks is becoming increased over the years. Usually the middle year peak is higher than the early/end year peak but this pattern was differed in 2013 and 2015 making the early/end year peak higher. There is a slight difference of peak month between months in district level case analysis. But the general pattern can be observed in almost all districts.
The cause for this phenomenon might include several factors includingclimate change and the virulence of the causative agent. More researches are needed to solve this problem. There is a strong relationship between cumulative dengue cases and population density in district level analysis. Every year, Colombo district records the highest numbers of cases and it has a population density of 3330 people’s per km² in 2001 census which is the highest of the island. Interestingly this trend can be observed in every district.
Conclusion and Policy Implications
Dengue represented a significant economic burden on the communities. It can result in loss of lives, considerable expenses to the family for the hospitalization and care of the patient, in addition to travel costs, loss of work among patients and their career, considerable expenses to ministry of health and local government authorities for mosquito control activities and disruption of health care services and economics, including loss of tourism revenue. Government in Sri Lanka allocate over Rs. 300 million as the direct cost of control measures for dengue in each year.
Dengue has a distinctive disease pattern over the time. This is similar in almost every year. Characteristic “ W “ pattern is observed with two peaks. There is a strong relationship between dengue numbers of cases and population density in district level. Reason for these characteristics should be analyzed furthermore and more research are needed.According to the result of this study it is clear that the selection of high risk areas for dengue transmission should be based on population density rather than the reported numbers of cases. A threshold value should be assigned in terms of risk area selection and it will be helpful in dengue prevention programs. The threshold values can be decided up to Divisional secretariat level and it needs more expertise researches.
A study of this nature helps develop a program for changing peoples’ behavior with the changes of climate in any country while minimizing the social cost of climate change. The overall findings of this research will help implement policies to reduce spread of dengue related diseases that is increasingly posing a major challenge in the health sector in the country. The results of the study will provide an opportunity to make necessary policies that provide incentives to reduce of spreading dengue related diseases at the household and district level which generate regional as well as global benefits in the future.
References
Athukorala, W. 2016. Estimating the health cost of climatic change related diseases: A case of Dengue in Sri Lanka. Unpublished Report. Department of Economics and Statistics, University of Peradeniya.
Alberini, A. and A. Krupnick . 1998. Air Quality and Episodes of Acute Respiratory Illness in Taiwan Cities: Evidence from Survey Data. Journal of Urban Economics, 44(1): 68-92.
Hopp, M.J. and Foley, J.A. 2001.Global – scale relationships between climate and the dengue fever vector, Aedes aegypti. Climate Change, 48,441-463.
Lowe. R., Bailey, T.C., Stephenson, D.B., Graham. R., Coelho, C.A.S., Carvalho, M. and Barcellos. C. 2011. Spatio-temporal modeling of climate-sensitive disease risk: towards an early warning system for dengue in Brazil. Computers and Geosciences 37, 371–381.
(University of Peradeniya, 2017-10-12) Nagarajah, N.; Ranasinghe, K.; Kavitharan, S.
Introduction
Climate change is happening and is felt deeply globally. Sri Lanka is already facing the adverse impacts of climate change in the form of droughts, unprecedented and rising temperature, floods, unseasonal rain, and coastal erosion. As a small island nation, Sri Lanka falls into the UNFCCC and IPCC's category of 'vulnerable' Small Island nations which are under serious threat from various climate change impacts, such as sea level rise and severe floods and droughts (Climate Change Secretariat, 2014). These threats are considered to have significant negative consequences on various sectors within Sri Lanka (Athukorala, 2015).
Sri Lanka is a negligible contributor to global warming. However, as a nation, we are highly vulnerable to the impacts of climate change. Sri Lanka has ratified the United Nations Framework Convention on Climate Change (UNFCC) in November 1993 and became a party to the Kyoto Protocol in 2002. The national Climate Change Policy of Sri Lanka aims to sensitize and make aware the communities periodically on the country’s vulnerability to climate change and to enhance knowledge on the multifaceted issues related to climate change in the society and build their capacity to make prudent choices in decision- making.
A number of research were done in Sri Lanka on the different causes of climate change. However, there is little literature to understand Sri Lankans’ awareness about climate change to determine if they act as responsive citizens to their share of emissions. According to Margaret Gardner, “in the next 55 years the greatest threat to Sri Lanka will be from climate change. Sri Lanka is particularly vulnerable to rising sea levels and weather-related disasters have the potential to set back any gains made in agriculture, fisheries and even services such as tourism” (Fernando, 2017). This paper helps to determine the success of using the environment valuation methods as a pragmatic approach to monitor the ‘nationally determined contributions’.
Objective
The objective of this paper is to understand people’s awareness on climate change and its impact, to investigate the relationship between household income and the level of awareness on climate change and to investigate the demand for climate change mitigation action by their willingness to pay to compensate their emissions and damages to the environment.
Methodology
The survey was done from May to June 2017 by gathering primary data using a semi-structured questionnaire in both local languages as well as an online survey. The respondents represented different age groups, gender, education status and income levels. 120 respondents from 15 districts consisted of farmers, government and non-government employees, school children, self-employed and unemployed. They are between the ages of 15 to 67. 87 % represent rural sector and 13 % represent urban sector. Also 55 % of the respondents are females. The secondary data on climate change was gathered from on-line sources.
Average imputation and common-point imputation are being used to fill the missing vital data. These methodologies analyses the association between categorical variables. Microsoft Excel and Minitab were used to obtain an accurate assessment of relationships, and possible contradictions found in the data by generating graphs, charts, cross tabulation and descriptive statistics. The contingent valuation method was applied in this study by asking the respondents for their Willingness to Pay (WTP) to offset their contribution to climate change and damages to the environment.
Results and Discussion
People’s awareness on climate change and its impact
In our sample 99 % of the respondents have stated that they are aware of the concept of climate change irrespective of gender, age, educational background, income level or their locality. Among those who are aware of climate change 41 % had come to know through media, 35 % have felt it and 14 % have heard it from other people. The survey indicate that 14.5 % respondents thought climate change was caused only by humans, while 9.6 % thought it happens naturally. 75 % of the respondents indicated that the cause for climate change is both by human and natural reasons.
When the respondents were asked to rate top three environmental issues; first rated issue was deforestation with 93 %, second highest was extreme weather conditions i.e. rains and droughts (82.5 %). Third rated with 75 % was water pollution. Findings also reveal how respondents conceptualize climate change; while majority of them interpret it as the rise in temperature and global warming, droughts, heavy rains, irregular rain patterns and floods, others interpret it as storms and strong winds, strange weather patterns, irregular climate, rise in sea water level, spread of diseases, Tsunami, disturbance to natural cycle, presence of Elnino and Lanino, failed agriculture and change in harvest patterns. While few relate it with melting of glaciers, depletion of Ozone layer and GHG emissions. Likewise, people’s beliefs about air pollution, factory / vehicle emissions, deforestation, and unplanned development are also again a way of anchoring climate change. The survey finding also indicated that the respondents are aware that the prevailing climatic conditions are impacts of climate change. Majority of the respondents felt that drought, floods and global warming are impacts of climate change; 36 %, 26 % and 25 % respectively.
The relationship between household income and the level of awareness on climate change
Results indicate there is no relationship between household income and the level of awareness on climate change (figure 1). Of those who are aware of climate change 28.3 % are very low, 28.3 % are middle, 24 % are average and 7.5 % are upper class income earners. 93 % of people agree that climate change is a common problem for everyone. Again, their income level and answers do not show any relationship. However, 39 % involved in farming strongly agree that climate change to be a common issue.
When judgments of other issues are solicited, climate change is invariably not the highest or most important priority for many people. Only 17 % of the respondents believed that environment was a pressing issue in Sri Lanka. Environmental problems were rated seventh place of ten other current problems given. Understanding people’s perceptions as contributors for the climate change is an important indicator of awareness. It is evidence that 90 % of people believe they contribute to climate change in some way. Of the respondents, 48 % are females and 48 % are involved in farming. Comparing it with the level of income, 28 % of very low-income holders, 20.8 % of average and 23 % of middle income earners believed that they are contributing to the climate change (figure 2). Neither gender, age, education nor income level or if farmer or not suggest a correlation.
The demand for climate change mitigation action by their willingness to pay to compensate the damage caused by them to the environment.
The respondents were introduced to a hypothetical fund called ‘Green Future’ which will be exclusively used for tree planting to compensate for the anthropogenic effects. The respondents were asked for their WTP for the fund and if they were willing, the maximum amount they can contribute annually. Further, 78 % of the respondents were willing to pay for the green future fund and out of them 42.5 % were females and 40.8 % were advanced level students and 15 % of them were graduates. The youth are sensitive to the climate change and proactive to make an action. A correlation cannot be observed between income level and peoples’ WTP. Approximately 22 % of those who were not willing to pay, stated their reason as their income being low or them willing to spend the money on other things. Further, 83 respondents stated a maximum amount they are willing to contribute annually to offset their emissions and harm to the environment. The amount ranged between Rs. 50 to Rs. 12,000. Out of those who are willing to pay and who earn more than Rs. 1,000.00 monthly income; people are willing to contribute 0.69 % (on an average) of their monthly income for the ‘Green Future’ program. Their average annual contribution in rupees amounts to Rs. 2,154.
Conclusion and Policy Implications
Sri Lankan’s awareness on climate change is in satisfactorily high level. Media is the main source people had come to know about climate change. The way people have described climate change varied from bringing out real-time examples, to attempts for text-book definitions. Placed among other problems country currently faces, their ranking for the environment as a topic was towards the lower side.
There is no relationship between Sri Lankan’s awareness level on climate change and their income. The conclusion holds still with the farmers and non-farmers responses. 78 % of the respondents were willing to pay for a hypothetical fund that will be used for replanting trees. Of the people who are able to pay, and have suggested an amount, it is about 0.69 % of their monthly income and annually it will amount to Rs. 2,154.41. Despite high awareness level, when it comes to action, the youth are keen to express climate change and even ready to take action. As a recommendation, the respondents suggest that Sri Lankans have to change the lifestyles to reduce energy consumption in order to address climate change.
References
Athukorala, W. (2015). Education, Attitudes and Agricultural Biodiversity: An Application of Randomised Control Method. Sri Lanka Journal of Economic Research, 3(1): 115-132.
Climate Change Secretariat - Ministry of Environment and Renewable Energy, Sri Lanka. 2014. Technology Needs Assessment and Technology Action Plans for Climate Change Adaptation.
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(University of Peradeniya, 2017-10-12) Ashfaque, Ismail
Introduction-
It is woeful that in Pakistan the most crucial aspect of well-being is also the most neglected. Discussions around health policy in Pakistan’s 70-year history have received little or no space in the agenda of any government – civil or military - that has taken over. While specific health related crises such as the spread of polio and child deaths in the tend to take the media by storm, a meaningful debate around the causes actually spurring such abysmal health services is appallingly absent. The indifference of Pakistan’s government to health is reflected in the fact that a measly 0.9 % of the GDP is spent on health with only a third of that being allocated to public sector health services, leaving the public availing these services from the private sector primarily through out-of-pocket payments.
This apathy is evident in health indicators such as to name a few, the infant mortality is sky-rocketing to 66 per 1,000 births as opposed to 38 in India or a mere 8 in Sri Lanka and life expectancy in the nation for women is 67 years as compared to 73 in Bangladesh and 78 in Thailand. However, while these numbers speak volumes about the dismal quality of healthcare provided in Pakistan, they also remind us that behind these facts and figures lie heart-wrenching stories of countless lives that were ruined and cut short due to health facilities lacking the necessary care. Information failure, lack of accountability, miserly and mismanaged government funding and readiness on part of healthcare providers coupled with poor training amongst other deep-rooted problems are responsible for the dreadful condition of the country’s healthcare sector. After extensive research though we have deduced information failure as being the primal cause behind a great proportion of the problems that the healthcare sector faces and therefore our research aims to focus on solutions addressed specifically to overcome it (Malkani, 2016).
A systematic literature review being drawn from various sources has helped us analyze the major themes plaguing the health sector as a result of information failure. Assuming their prominence from the frequency of times they were mentioned in our sources along with the significance of their impact, we have narrowed down these themes and selected two to focus on for the purpose of this paper:
• Mismanaged Data Collection and Record-Keeping
• Staff Absenteeism
Keeping in special consideration the deep-rooted problems common to both the general concerns plaguing the healthcare sector and our specific areas of focus, our paper aims to expand beyond the traditional methods of physical contact with patients to the virtual platforms of e-Health as proposed solutions to correct information failure. E-health systems entail many sub-facilities including telemedicine, tele-education, telematics for improved management of healthcare and research, giving access to improved access and quality of healthcare. Both biblical and new models of healthcare are globally serving the masses side by side, with the latter pulling forward in most developed and developing societies alike, but in Pakistan the concept of e-Health is still relatively alien. Computer based health information systems are becoming the order of the day but their spread in Pakistan is still limited.
Objectives-
The main objective of this study is to identify the relationship between information failure and poor health services in Pakistan. It also will investigate whether information communication technology (ICT) can fill the gap in the future.
Methodology-
After a stringent evaluation of the sources used based on the credibility of their database (journal/website/newspaper), we compiled and analyzed data from several studies. We evaluated the methods of how ICT could be used to improve the health systems in Pakistan, and how the health system lacks behind in the country and developed policy recommendations based on the literature used in the report.
Results and Discussion-
The World Health Organization (WHO) has listed Pakistan as one of the fifty-seven countries with a critical deficiency in its Human resources for health (HRH) (MLHW 102). The problem of health workforce deficiency is two-pronged. Firstly, there is no specific department dedicated to HRH within the ministry of health, and along with the inadequate training programs and unrevised health curriculums, health force that is being produced is simply not competent enough.With an absence of a department whose specific function is to monitor the workforce, ‘slackers’ take advantage of the information failure resulting from the fact that they have to meet low standards of accountability and do not take their public-sector duties seriously. Secondly, in Sindh alone, 35.7 percent of public-sector doctors are absent from their workplace during normal working hours (Agboatwalla and Niazi, 2010). This proportion is higher amongst rural regions as compared to urban regions.
A cause of inefficiency in itself, absenteeism further abates the efficient delivery of public health services within the country by presenting a dual obstacle- not only does absenteeism translate into leakage in budgetary allocations as absence of health workers entails that budgetary allocations do not reach the beneficiaries; but absenteeism also leads to poor health service delivery due to unavailability of health personnel (Agboatwalla and Niazi, 2010).
Therefore, without the correction of information failure and a way forward being devised to improve standards of accountability and monitoring, increasing spending on the health sector is futile. Chaudhury et al. (2011) study staff attendance in health facilities in Bangladesh, Ecuador, India, Indonesia, Peru and Uganda to find that some common themes persist across countries such as generally higher absence rates in poorer regions, higher absence rates amongst higher-ranking and more powerful providers (such as the doctors), and higher absenteeism amongst men as compared to women. They also observe low evidence of financial incentives decreasing absenteeism, and instead find greater evidence that infrastructure plays a crucial role in increasing staff attendance.
We have identified the efficient keeping of medical records as a high-threat problem to Pakistan’s healthcare institution due to the fact that record-keeping is a government’s administration’s basic tool. With records that are accurate and up-to-date, viable information is provided and this lays the foundation for future decision making and planning. A structured and effective medium to maintain records is needed such that it coordinates the care the patient receives in every department that they have received treatment in; with this not only serving the purpose of the patient receiving higher quality healthcare due to the staff having access to a complete medical history but also with the records providing evidence for the hospital’s accountability for its actions and perhaps also direction for future medical research.
In line with new policies emphasizing better health care services including Millennium Development Goals, the Pakistan Government has introduced a series of federally funded vertical and horizontal programs such as Lady Health Worker Programme, Expanded Programme on Immunization, National Maternal and Child Health Programme and Tuberculosis and HIV/AIDS Control Programme. Mismanaged record keeping is not only a consequence of information failure but also a cause of it. The purpose of this section is to highlight how important it is to carry out efficient and structured record keeping by ensuring that the information failure it both entails and creates is overcome, so as to not only record medical information of patients during consultation accurately leading to proper diagnosis and treatment but also for the successful execution of any health-related initiative.
Conclusion and Policy Implications-
This report has discussed two major problems in the health sector that are caused by poor information which have often been given secondary importance in the literature on health policies. Firstly, ICT could significantly improve the condition of record keeping in Pakistan, which is a high-threat problem to the healthcare institution of Pakistan. An efficient record keeping system could improve the treatment the patient receives and also provide more informed directions for future research. The use of Electronic Health Records (EHRs) would significantly improve the record keeping system and provide quick and accurate medical information. Secondly, poor management and information flow results in stock unavailability in the pharmacies. An investment into an IT based management system could improve the budgeting and forecasts for the future, which would balance the levels of supply of different medicines. A more informed higher-level management would improve the accountability of the corruption and inefficiencies of the lower level workers.
References-
Afzal, U. and A. Yousuf. 2013. The State Of Health In Pakistan: An Overview. The Lahore Journal of Economics, 18. 233-247.
Agboatwalla, M. and T. A. Niazi. 2010. To Assess the Extent Of Absenteeism I N The Health Sector In Pakistan. Transparency and Accountability Project the Brooking Institution-WA
Ahmed, J. and B. Shaikh. 2008.. An All Time Low Budget for Healthcare in Pakistan. Journal of the College of Physicians and Surgeons Pakistan, 18(6):388-91.
Banerjee, Abhijit V., Duflo, E. and R.l Glennerster.2008. Putting A Band-Aid on a Corpse: Incentives For Nurses in the Indian Public Health Care System. Journal of the European Economic Association 6(2-3): 487-500.
