(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.
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