Impact of IMF Funding on Pakistans economy

Impact of IMF Funding on Pakistans economy Introduction The funding by International Monetary Fund (IMF) to developing countries has always raised a debate on its positive and negative impacts on the economy of the creditor country. Pakistan has an extended history of funding from IMF starting from 1958 to 2004 in various time spans and now the current agreement from 2008. This study analyzes the impact of IMF funding on Pakistan. Although there has been criticism regarding both issues of policies and the funding impact but the focus of this research is to study the impacts and not to discuss or criticize the policies of IMF. The IMF works to foster global growth and economic stability. It provides policy advice and financing to members in economic difficulties and also works with developing nations to help them achieve macroeconomic stability and reduce poverty. It is working to foster global monetary cooperation, secure financial stability, facilitate international trade, promote high employment and sustainable economic growth, and reduce poverty around the world. Although monetary fund provides financial assistance to the developing countries but its role in economic prosperity has been highly criticized from the last few years due to its strict policies and restrictions imposed on the borrower country. Under current agreement, IMF imposes 11 main conditions on Pakistan which includes: introduction of the Central Excise Duty on service and agricultural sector, reduction in the expenditures on Public Sector Development Program, devaluation of rupee, freezing of non-development expenditure under the defense budget, non-provision of supplementary grants to government departments, ending subsidy on gas and electricity, reduction in non-development expenditure of civil departments and federal ministries, increase in markup rate of banks and on inter-bank transactions, uniformity in the inter-bank and open market dollar exchange rate and stoppage of government financial intervention in stock markets. The main aim of IMF behind imposition of policies is to increase the revenues of the borrower country. But some studies reveal that it affects the economy both directly and indirectly. Directly it imposes impact in the sense of control of certain variables on which it put restrictions and indirectly with regard to the relationship of these variables with other macroeconomic driving variables that drives the economic growth. The matter here is not the IMF funding but the policy impositions that could impact the economic growth. IMF provides funds for the three major areas, to reduce deficit of fiscal account and current account and to increase the revenues. The question here arises that whether the increase in taxes, elimination of subsidies and development projects will help boost the economy or causes the real GDP to fall from the expected value through increased inflation. An extensive research has been done to address the issue of IMF policies and impact on economy of the borrower country but there are conflicting results derived by different researchers due to particular conditions related to that country, the researches that tried to study all countries under IMF program also reveals contradicting results. This study focuses specifically on Pakistan so that particular effects could be revealed that IMF funding is pouring on Pakistans economy. Problem statement The problem statement of research is Impact of IMF funding on Pakistans economy. Major variables that are used in this study include IMF funds and macro economic variables that are the indicators of an economy i.e. real GDP, employment rate, current account balance, balance of payments and FDI. Objectives The objectives of our study are: To study how IMF funding is putting its effect on economy of Pakistan. To reveal that whether there is any significant relationship between IMF funding and economic growth and if there is a relationship then whether it is positive or negative. To draw conclusion and make recommendations through analysis that whether Pakistan should borrow from IMF or seek other ways of borrowing Significance Although a number of studies have addresses the stated issue but these researches mostly carried out aggregate affect taking into account all the countries under IMF program. The Research that we are going to conduct will try to find out impact of IMF funding on economic growth in particular scenario of Pakistan. Delimitation Our scope of study will be limited to the impacts on Pakistan economy. More over the variable that we will use for analysis of economic growth will be only major macroeconomic variables which are majorly contributing towards the growth factor. In our study we are not considering the political instability and inconsistency in the prevailing policies and other social environmental issues that could impact economic growth side by side. Chapter 2 Review of Related Literature This chapter includes the work done in the same area by other researchers. It put a glance on studies of some of the researchers along with their proposed conclusions Literature review IMF funding has been one of the most debated issues from the last few years in terms of its policies, restrictions and its impact on the economy of countries under IMF programs. A number of studies have been done in this regard. However the results of these studies are contradicting making this issue still debatable. Recent studies have produced mixed and sometimes puzzling results regarding the impact of IMF programs on a nations balance of payments, current account balance, foreign direct investment, real GDP, per capita income and long-run economic growth. Martin Feldstein (1998) argues that the IMF required excessively large reductions in government deficits and restrictions on monetary policy. These restrictions resulted in substantial increases in tax rates, interest rates and increase in current account deficit. Feldstein argues that Asian economies have experienced a recession that worsened their economic problems as a result of these policy changes. Feldstein argues that many of the mandated reforms involve unjustified interference with national autonomy and have little or no relationship to the goal of resolving the payment problem. He notes that it would have been better to allow more time for negotiations between borrowers and lenders before providing IMF loans to a country experiencing payment problems. Ho: There is no significant Impact on the current account deficit by increasing Government Expenditure through IMF Funding. H5: There is significant Impact on the current account deficit by increasing Government Expenditure through IMF Funding. Doug Bandow (1999) argues that the existence of IMF bailouts creates a moral hazard problem that encourages countries to not solve their fundamental problems. He suggests that all nations would benefit if healthy economies quarantined sick economies instead of providing economic assistance. Bandow argues that IMF assistance programs increase risk for healthy economies and do not provide long-term benefits for troubled economies. He notes that most IMF borrowers have received aid for a decade or more. Jensen (2004) suggests that international capital markets perceive IMF intervention as a negative development. Regardless of factors driving their decisions, Jensens research provides strong evidence that developing countries pay a serious price when they take advantage of IMF assistance. His research strongly reveals a negative relationship between IMF funding and foreign direct investment in the country. According to him investors dont perceive this funding in a positive way that why reducing net investment level in the country and as a result hindering economic growth. For impact of IMF on FDI following hypothesis is developed: Ho: There is no significant Impact on the FDI by increasing Government Expenditure through IMF Funding. H1: There is significant Impact on the FDI by increasing Government Expenditure through IMF Funding. On the other hand there are a number of researchers like Dicks Mireaux (2000), who have found strongly positive economic growth effects of IMF funding. These researches found that there is appositive impact of IMF funding on the economy. While there are also studies which concluded that are no significant effects of IMF on the economy of a country under IMF agreement like, Hardoy(2003) and Hutchison (2004), who argue that IMF funding does not pour any significant impact on the economy of the borrower country. Mireaux argue that economy grows due to the increased tax revenues. Following hypothesis has been developed between tax revenue and IMF funding. Ho: There is no significant Impact on the Tax Revenue by increasing Government Expenditure through IMF Funding. H3: There is significant Impact on the Tax Revenue by increasing Government Expenditure through IMF Funding. Nunnenkamp(1999) in his article discussed that IMF is under serious attack as critics blame that IMF lending lead to financial crisis and suggests to stop IMF funding also the researcher discussed the consequences of ending the lending ODriscoll (1997) in his article has conducted the descriptive research about the IMF policies towards developing countries by keeping the focus on USA economy. The Policy making of IMF for the developing countries are without any backing of historical decisions taken by the developing countries in past. Thus the financial crises and current account deficit crises is mainly attributed to such policy making. The researcher has give example of Asia in which case the above discussion is particularly true which roots in 1995. The IMFs handling of the Mexico crisis firmly established moral hazard in international lending and sowed the seeds for the Asian crisis. Thus far, IMF policy in Asia largely repeats the policy mistakes in Mexico.   Gina (2007) indicates in his article that the reforms enacted by Congress in USA are an important first step toward reforming the IMF. Even more important than the reforms, however, was the congressional debate over IMF funding. That debate focused attention on the process and Substance of IMF policymaking and even questioned the need for that organization in the post-Bretton Woods world. Przeworski and Vreeland (2000) Using a bivariate, dynamic version of the Heckman selection model, we estimate the effect of participation in International Monetary Fund IMF programs on economic growth. We find evidence that governments enter into agreements with the IMF under the pressures of a foreign reserves crisis but they also bring in the Fund to shield themselves from the political costs of adjustment policies. Program participation lowers growth rates for as long as countries remain under a program. Once countries leave the program, they grow faster than if they had remained, but not faster than they would have without participation. So for the relation between IMF and GDP following hypothesis are developed: Ho: There is no significant Impact on the GDP by increasing Government Expenditure through IMF Funding. H1: There is significant Impact on the GDP by increasing Government Expenditure through IMF Funding. The estimates of Barroa Lee (2005) shows that a higher IMF loan-participation rate reduces economic growth. IMF lending does not have significant effects on investment, inflation, employment, government consumption, and international openness. However, IMF loan participation has small negative effects on democracy and the rule of law. Ho: There is no significant Impact on the Employment by increasing Government Expenditure through IMF Funding. H2: There is significant Impact on the Employment by increasing Government Expenditure through IMF Funding. Chapter 3 Research Methodology This chapter includes the theoretical model, data collection technique and methodology approach used for the analysis Theoretical model Economic Growth Real GDP IMF Funding Employment FDI RRevenue Current Account Balance Data collection Secondary source for the data collection has been used in this research. For this purpose most of the data will be collected from the Economic Survey of Pakistan, international monetary fund web site and state bank of Pakistan website. The dependant variables that have been used to analyze the economic growth include: balance of payment, current account balance, real GDP, rate of employment and foreign direct investment. These are the major variables that are the determinants of economic growth of a country. The independent variable is the amount of funding by IMF. Data analysis Regression analysis is used for analyzing the impact of IMF funding on Pakistans economy. Data is analyzed using SPSS. Data for the IMF funding in Pakistan is in detail below:   YEARS IMF FUNDING 1973-1974 527 1974-75 1990 1975-76 1987 1976-77 2497 1977-78 232 1978-79 3406 1979-80 644 1980-81 3789 1981-82 6079 1982-83 7266 1983-84 2812 2000-01 35400 2001-02 65460 Chapter 4 Data Presentation and Findings This chapter includes the data which has been used for the analysis, analyzed results and the findings that follow through the analysis Data presentation and findings Following is the detailed data used for the analysis and the findings of the regression analysis. The data is presented separately for each variable used as the measure of economic growth of the country. IMF funding and GDP Data Analysis for First Hypothesis Ho: There is no significant Impact on the GDP by increasing Government Expenditure through IMF Funding. H1: There is significant Impact on the GDP by increasing Government Expenditure through IMF Funding. IMF FUNDING GDP 1974 527 38439 1974-75 1990 39930 1975-76 1987 41229 1976-77 2497 42401 1977-78 232 45679 1978-79 3406 48204 1979-80 644 51736 1980-81 3789 55048 1981-82 6079 59012 1982-83 7266 62975 1983-84 2812 65968 2000-01 35400 180500 2001-02 65460 212200 Findings: To test the hypothesis, linear regression analysis used. The results of regression of One independent Variable (IMF Funding) against GDP (dependent variable) can be seen in the following output. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .971 .943 .937 14025.2195 a Predictors: (Constant), IMF FUNDING ANOVA Model Sum of Squares df Mean Square F Sig. 1 Regression 35481741865.974 1 35481741865.974 180.379 .000 Residual 2163774597.718 11 196706781.611 Total 37645516463.692 12 a Predictors: (Constant), IMF FUNDING b Dependent Variable: GDP Coefficients Unstandardized Coefficients Standardized Coefficients t Sig. Model B Std. Error Beta 1 (Constant) 43492.601 4451.563 9.770 .000 IMF 2.861 .213 .971 13.431 .000 a Dependent Variable: GDP Interpretation of analysis The ANOVA table shows that the F value of 180.379 is significant at the .000 levels. Degree of Freedom column in the table, the first number represent the number of Independent Variable (1) the second number (13) is the data collected for total number of years (N), minus the number of Independent Variable (K) minus 1 or 11=(N-K-1) or (13-1-1)= 12. The F statistics produce (F= 180.379) is significant at the .000 levels. Which shows that Model validity is significant at 0.000 level of significance. What the result mean is that 94.3 percent of variance (R square) in increase in GDP has been significantly explained by increasing Government Expenditure by way of IMF Funding (Independent variable) with standard error of estimate of 14025.2195. Standard error of estimate shows amount falls outside the regression line or shows standard deviation from mean. There is .000 percent or less chance of this is not holding true. There is correlation of 0.971 (denoted as r=0.971) between IMF Funding (Independent variable) and GDP (dependent variable) with level of significance 0.000. so there is positive relationship between the two variables and probability of this is not true is zero percent or less. That is 100 percent of time we would expect that this correlation to exist. There is a beta value of 0.971, which shows that 97.1 percent chance of making TYPE II error if null hypothesis is accepted when it is false. At the same time Un standardized coefficient B= 2.861 indicates that the valu e of GDP increase by 2.861 unit for a one unit increase in Government Expenditure by IMF Funding. What the result mean is that t value 13.431 significant at 0.000. Thus hypothesis 1 is substantiated. IMF funding and employment rate Data Analysis for Second Hypothesis Ho: There is no significant Impact on the Employment by increasing Government Expenditure through IMF Funding. H2: There is significant Impact on the Employment by increasing Government Expenditure through IMF Funding. YEARS IMF FUNDING EMPLOYMENT 1973-1974 527 19.76 1974-75 1990 20.3 1975-76 1987 21.08 1976-77 2497 21.89 1977-78 232 22.73 1978-79 3406 23.62 1979-80 644 24.15 1980-81 3789 24.7 1981-82 6079 25.27 1982-83 7266 25.85 1983-84 2812 26.4 2000-01 35400 37.51 2001-02 65460 38.29 Findings: To test the hypothesis, linear regression analysis used. The results of regression of One independent Variable (IMF Funding) against Employment (dependent variable) can be seen in the following output. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .912 .832 .817 2.5175 a Predictors: (Constant), IMF Funding ANOVA Model Sum of Squares df Mean Square F Sig. 1 Regression 345.318 1 345.318 54.485 .000 Residual 69.717 11 6.338 Total 415.035 12 a Predictors: (Constant), IMF Funding b Dependent Variable: EMPLOYMENT Coefficients Unstandardized Coefficients Standardized Coefficients t Sig. Model B Std. Error Beta 1 (Constant) 22.636 .799 28.328 .000 IMF 2.823E-04 .000 .912 7.381 .000 a Dependent Variable: EMPLOYMENT Interpretation of analysis The ANOVA table shows that the F value of 54.485 is significant at the .000 levels. Degree of Freedom column in the table, the first number represent the number of Independent Variable (1) the second number (13) is the data collected for total number of years (N), minus the number of Independent Variable (K) minus 1 or 11=(N-K-1) or (13-1-1)= 12. The F statistics produce (F= 54.485) is significant at the .000 levels. Which shows that Model validity is significant at 0.000 level of significance. What the result mean is that 83.2 percent of variance (R square) in increase in Employment has been significantly explained by increasing Government Expenditure by way of IMF Funding (Independent variable) with standard error of estimate of 2.5175. Standard error of estimate shows amount falls outside the regression line or shows standard deviation from mean. There is .000 percent or less chance of this is not holding true. There is correlation of 0.912 (denoted as r=0.912) between IMF Funding (Independent variable) and Employment (dependent variable) with level of significance 0.000. So there is positive relationship between the two variables and probability of this is not true is zero percent or less. That is 100 percent of time we would expect that this correlation to exist. There is a beta value of 0.912, which shows that 91.2 percent chance of making TYPE II error if null hypothesis is accepted when it is false. At the same time Un standardized coefficient B= 0.00283 indicates t hat the value of Employment increase by 0.00283 unit for a one unit increase in Government Expenditure by IMF Funding. What the result mean is that t value 7.381 significant at 0.000. Thus hypothesis 2 is substantiated. IMF funding and tax revenue Data Analysis for Third Hypothesis Ho: There is no significant Impact on the Tax Revenue by increasing Government Expenditure through IMF Funding. H3: There is significant Impact on the Tax Revenue by increasing Government Expenditure through IMF Funding. YEARS IMF FUNDING TAX REVENUE 1973-1974 527 9,444.00 1974-75 1990 11,428.70 1975-76 1987 13,914.80 1976-77 2497 16,112.50 1977-78 232 20,041.10 1978-79 3406 23,475.70 1979-80 644 30,720.40 1980-81 3789 36,509.30 1981-82 6079 40,367.60 1982-83 7266 46,475.00 1983-84 2812 55,360.00 2000-01 35400 444,800.00 2001-02 65460 486,000.00 Findings : To test the hypothesis, linear regression analysis used. The results of regression of One independent Variable (IMF Funding) against Tax Revenue (dependent variable) can be seen in the following output. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .958 .917 .910 49565.7061 a Predictors: (Constant), IMF FUNDING ANOVA Model Sum of Squares df Mean Square F Sig. 1 Regression 300517013184.665 1 300517013184.665 122.323 .000 Residual 27024351475.824 11 2456759225.075 Total 327541364660.489 12 a Predictors: (Constant), IMF b Dependent Variable: TAX REVENUE Coefficients Unstandardized Coefficients Standardized Coefficients t Sig. Model B Std. Error Beta 1 (Constant) 10370.086 15732.008 .659 .523 IMF 8.326 .753 .958 11.060 .000 a Dependent Variable: TAX REVENUE Interpretation of analysis The ANOVA table shows that the F value of 122.323 is significant at the .000 levels. Degree of Freedom column in the table, the first number represent the number of Independent Variable (1) the second number (13) is the data collected for total number of years (N), minus the number of Independent Variable (K) minus 1 or 11=(N-K-1) or (13-1-1)= 12. The F statistics produce (F= 122.323) is significant at the .000 levels. Which shows that Model validity is significant at 0.000 level of significance. What the result mean is that 91.7 percent of variance (R square) in increase in Tax Revenue has been significantly explained by increasing Government Expenditure by way of IMF Funding (Independent variable) with standard error of estimate of 49565.7061. Standard error of estimate shows amount falls outside the regression line or shows standard deviation from mean. There is .000 percent or less chance of this is not holding true. There is correlation of 0.958 (denoted as r=0.958) between IMF Funding (Independent variable) and Tax Revenue (dependent variable) with level of significance 0.000. So there is positive relationship between the two variables and probability of this is not true is zero percent or less. That is 100 percent of time we would expect that this correlation to exist. There is a beta value of .958, which shows that 95.8 percent chance of making TYPE II error if null hypothesis is accepted when it is false. At the same time Un standardized coefficient B= 8.362 indicate s that the value of Tax Revenue increase by 8.326 unit for a one unit increase in Government Expenditure by IMF Funding. What the result mean is that t value 11.060 significant at 0.000. Thus hypothesis 3 is substantiated. IMF funding and FDI Ho: There is no significant Impact on the FDI by increasing Government Expenditure through IMF Funding. H1: There is significant Impact on the FDI by increasing Government Expenditure through IMF Funding. YEARS IMF FUNDING FDI 1973-1974 527 -189 1974-75 1990 447 1975-76 1987 675 1976-77 2497 321 1977-78 232 1065 1978-79 3406 1080 1979-80 644 840 1980-81 3789 1225 1981-82 6079 3430 1982-83 7266 1473.5 1983-84 2812 1680 2000-01 35400 19995 2001-02 65460 30051.4 Findings : To test the hypothesis, linear regression analysis used. The results of regression of One independent Variable (IMF Funding) against FDI (dependent variable) can be seen in the following output. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .991 .982 .981 1290.1947 a Predictors: (Constant), IMF ANOVA Model Sum of Squares df Mean Square F Sig. 1 Regression 1010046942.200 1 1010046942.200 606.780 .000 Residual 18310625.532 11 1664602.321 Total 1028357567.732 12 a Predictors: (Constant), IMF b Dependent Variable: FDI Coefficients Unstandardized Coefficients Standardized Coefficients t Sig. Model B Std. Error Beta 1 (Constant) -128.350 409.504 -.313 .760 IMF .483 .020 .991 24.633 .000 a Dependent Variable: FDI Interpretation of analysis The ANOVA table shows that the F value of 606.780 is significant at the .000 levels. Degree of Freedom column in the table, the first number represent the number of Independent Variable (1) the second number (13) is the data collected for total number of years (N), minus the number of Independent Variable (K) minus 1 or 11=(N-K-1) or (13-1-1)= 12. The F statistics produce (F= 606.780) is significant at the .000 levels. Which shows that Model validity is significant at 0.000 level of significance. What the result mean is that 98.2 percent of variance (R square) in increase in FDI has been significantly explained by increasing Government Expenditure by way of IMF Funding (Independent variable) with standard error of estimate of 1290.1947. Standard error of estimate shows amount falls outside the regression line or shows standard deviation from mean. There is .000 percent or less chance of this is not holding true. There is correlation of 0.991 (denoted as r=0.991) between IMF Funding (Independent variable) and FDI (dependent variable) with level of significance 0.000. So there is positive relationship between the two variables and probability of this is not true is zero percent or less. That is 100 percent of time we would expect that this correlation to exist. There is a beta value of 0.991, which shows that 99.1 percent chance of making TYPE II error if null hypothesis is accepted when it is false. At the same time Un standardized coefficient B= .483 indicates that the value of FDI increase by .483 unit for a one unit increase in Government Expenditure by IMF Funding. What the result mean is that t value 24.633 significant at 0.000. Thus hypothesis 4 is substantiated. IMF funding and current account deficit Data Analysis for Fifth Hypothesis Ho: There is no significant Impact on the FDI by increasing Government Expenditure through IMF Funding. H5: There is significant Impact on the FDI by increasing Government Expenditure through IMF Funding. YEARS IMF FUNDING CURRENT ACCOUNT DEFICIT 1973-1974 527 3318 1974-75 1990 10639 1975-76 1987 9212 1976-77 2497 11718 1977-78 232 14835 1978-79