Budget Deficit and Stock Prices: Evidence from Pakistan and India

ijcrb.webs.com INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS SEPTEMBER 2012 VOL 4, NO 5 BUDGET DEFICIT AND STOCK PRICES: EVIDENCE FROM PAKISTAN AND INDIA Faiza Saleem (Corresponding author) Lecturer - Department of Management Sciences, University of Wah The Mall, Quaid Avenue, Wah Cantt (47040) - Pakistan Muhammad Yasir Lecturer - Department of Management Sciences COMSATS Institute of Information Technology Near Officers Colony, Kamra Road, Attock (43600) – Pakistan Farhan Shehzad Independent Researcher – Pakistan Kamran Ahmed Lecturer - Department of Management Sciences, University of Wah The Mall, Quaid Avenue, Wah Cantt (47040) – Pakistan Saba Sehrish Lecturer - Department of Management Sciences, University of Wah The Mall, Quaid Avenue, Wah Cantt (47040) – Pakistan Abstract The objective of this research study is to provide empirical evidence regarding budget deficits and stock prices. We investigate whether changes in deficits cause changes in stock prices and if so, in what direction. Annual data from 1990-2010 for Pakistan and India has been used. Augmented Dickey Fuller (ADF) unit root test, Johansen Cointegration Technique and Granger Causality Test has been used to find out the long run causal relationship between budget deficit and stock prices. This study suggest that high developmental expenditure in Pakistan is the reason for long term positive causal relationship between budget deficit and stock prices in case of Pakistan while in India a long term negative relationship is observed which is due to high current expenditures. Government of both countries must adopt solid tactic to improve budget deficit because stock market performance is influenced by the economic condition of a country along with some other important factors. Key Words: Budget deficit, Stock prices, Cointegration Technique, Granger Causality Test. COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 176 ijcrb.webs.com INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS SEPTEMBER 2012 VOL 4, NO 5 1. Introduction and Literature Review The national budget deficit is defined as the amount by which the government expenditures are more as compared to the revenues it receives from all type of taxes (Anusic 1994). A government can finance its budget deficit by either one of the following five methods and these methods were examined by (Burney and Akhtar 1992): (1) by increasing money supply; (2) by borrowing from the public; (3) by borrowing from the external sources; (4) by drawing on external reserves and (5) by combination of the above four options. Budget deficits impose costs on the economy and have many effects. (Ball and Mankiw 1995) investigated that all the effect of budget deficit followed from a single initial effect: deficits reduce national saving. National saving is the sum of private saving. (the after-tax income that households save rather than consume) and public saving (the tax revenue that the government saves rather than spends). The public .saving will be negative, when the government runs a budget deficit, and this public saving reduces national saving in the economy. The affect of national saving on the economy can be understood by this simple accounting identity. Letting Y denote gross domestic product, T taxes, C consumption, and G government purchases, then private saving is .Y-T-C, and public saving is .T-G. Adding these yields national saving, S: .S = Y - C – G. National saving is current income not used immediately to finance consumption by households, or purchases by the government. The second important accounting identity is the one that divides. GDP into four types of spending: .Y = C + I + G + NX. Output Y is the sum of consumption C,’ investment I, ‘government purchases G, ‘and net exports NX. Substituting this expression for Y into the previous equation for national saving yields .S = I + NX. This simple equation shows the effects of budget deficits. According to this equation national, saving of a country is equal to the sum of investment and net exports. When budget deficits reduce national saving, they must reduce investment; reduce net exports, or both. The total fall in, investment and net exports must exactly match the fall in national saving. To the extent that budget deficit increases the trade deficit (that is, reduce net exports), another effect follows immediately: budget deficits create a flow of assets abroad. It means that when a country imports more than it exports, it does not receive these extra goods and services for free; instead, it gives up assets in return. Initially, these assets may be the local currency,’ but foreigners quickly use this money to buy corporate or government bonds or equity. In any case, when a budget deficit turns a country into a net importer of goods and services, ‘the country also becomes a net exporter of assets. When the national saving declines it will reduces the supply of loans available to private borrowers, which pushes up the interest rate (the price of a loan). Faced with higher interest rates, households and firms choose to reduce investment. ‘Higher interest rates also affect the flow of capital across national boundaries. ‘When domestic assets pay higher returns, they are more attractive to investors both at home and abroad. The increased demand for domestic assets affects the market for foreign currency: if a foreigner wants to buy a domestic bond, he must first acquire the domestic currency. Thus, a rise in interest rates increases the demand for the domestic currency in the market for foreign exchange, ‘causing the currency to appreciate. The appreciation of the currency, in turn, affects trade in goods and services. With a stronger currency, domestic goods are more expensive for foreigners,’ and foreign goods are cheaper for domestic residents. Exports fall,’ imports rise, and the trade balance moves toward deficit. To sum up: (Ball and Mankiw 1995) conclude that government budget deficits reduce national saving, reduce investment, ‘reduce net exports, ‘and create a corresponding flow of assets overseas. These effects occur because deficits also raise interest rates and the value of the currency in the market for foreign exchange. Financial securities that is debt and equity securities are traded on stock exchanges which is called as stock market; it plays an important role in economic prosperity and fostering capital formation and sustaining economic growth (Charles and Adjasi 2008); (Essaied, Hamrita et al. 2009); (Pilinkus 2009); (Quayes 2010). The purpose of the stock market is to facilitate the exchange of securities between lender and borrower, at an agreed price at a real physical locations or a virtual (online). The participants in the stock market range from small individual stock investors to large hedge fund traders who raise capital for expansion. The prices of the securities traded on the stock market are changed on a daily basis and these are determined by demand and supply. However, some of the factors behind COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 177 ijcrb.webs.com INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS SEPTEMBER 2012 VOL 4, NO 5 decreases or increases in the demand and supply of a stock could comprise company fundamental factors, behavioral factors and external factors (Kurihara 2006). The current and the future economic growth of economy may be through that country stock market performance and the stock market performance depends on the country budgets. In a country when the budget is in deficit it will depress the stock prices and undermine the confidence, so the firm ability to get capital on favorable terms will be diminished. Falling current investment reduces future competitiveness of an economy. (Roley, Lawrence et al. 1988) investigated that during recession higher budget deficit leads to boost the stock prices, and the empirical evidence from this study suggested that increases in the structural deficits have historically leads to increase in stock prices and the structural deficit has typically risen during recession and the decreased early in the subsequent expansion. An unsustainable budget deficit indicates either future inflation rate or future tax rate increases. (Sargent and Wallace 1981) say that the unsustainable budget deficit will eventually have to be managed because large budget deficit will increase inflation. (Greenspan and Allen 1995) investigate that decrease in budget deficit will reduce inflationary expectations. Inflationary expectations may have reverse effects on equity prices. For example, increase in inflationary expectations may give benefit to equity instruments by decreasing the real value of corporate debt, thus increasing the firm’s value. On the other hand, a decrease in the future inflation rate may decrease equity values because the real value of debt increases, reducing the firm’s value. Furthermore, a decrease in inflationary expectations decreases nominal interest rates which may cause stock prices to go up because lower rates mean a higher present value of the future stream of corporate earnings. But lower inflationary expectations may also lower the expected future stream of earnings which could lower stock prices. So the inflationary expectation effect on stock prices may be neutral or indeterminate. Budget deficits also affect stock prices through anticipated future taxes, particularly if tax rates are below their revenue-maximizing levels. (Hall and Taylor 1993) and (Ball and Mankiw 1995) claim that increase in budget deficit forecast future tax increases, which may decrease current consumption by households and harm stock prices and vice versa, this explanation is supported by the notion of Ricardian Equivalence. The competitiveness of domestic products on the world market is also affected by budget a deficit which will ultimately affect that’s country stock market. (Ball and Mankiw 1995) examined that decrease in deficit causes interest rates to fall which means that U.S. financial assets become less attractive abroad and the demand for the dollar drops. Hence, the exchange value of the dollar goes down. However, U.S. products will become more competitive abroad and stock prices should raise as demand for U.S. products rises. (Aggarwal and Raj 1981) claimed that stock prices of both domestic and multinational firms are affected by the exchange rate. For example, variations in the exchange rate will affect the foreign and domestic profits via cost and revenues. Once the profit or loss is announced, stock prices respond accordingly. It is a general concept that the economic news may cause variation in aggregate stock returns and this concept was examined by (Cutler, David et al. 1987) in US economy. Monthly data of real dividend, money supply, inflation rate, interest rate and stock return for the period 1926-1985 has been used. Results from vector autoregression showed that a substantial fraction of return variation cannot be fully explained by macroeconomic news there are many other factors that affect the movement of stock return. (Adrangi and Allender 1998) provide empirical evidence regarding budget deficit and stock prices in industrialized countries such as Japan, US, France and Germany by using Monthly data from 1974-1995. Granger causality, VAR test results showed a negative relationship between budget deficit and equity returns in the U.S. However, in Japan, France and Germany change in deficits do not affect the equity market returns. (Quayes 2010) studied the association between budget deficit and stock prices by integrating the effects of inflation and the demographic structure The model incorporates demand and supply functions to capture the impact of real GDP, inflation, demographic transition, and budget deficit, on the stock prices. The results from cointegration analysis show that both budget deficits and inflation have a negative impact on stock prices. The above discussion indicates that there are several factors that affects or affected by budget deficit which will then affect stock prices and there is no specific economic theory that explains the answer as to how budget deficit affect stock prices. So the purpose of this research is to provide some empirical evidence regarding budget deficits and their effects on stock prices. This study investigates whether changes in deficits cause changes in stock prices and if so, in what direction. The study use Co-integration technique and Granger causality tests to assess the long run causal relationship between budget deficits and stock prices in Pakistani and Indian economies. COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 178 ijcrb.webs.com INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS SEPTEMBER 2012 VOL 4, NO 5 The remainder of this paper is organized as follows. Section 2 discusses the data and methodology. Emperical results and their discussion are presented in section 3. A brief summary, conclusion and recommendation are the subject of the final section. 2. Data and Methodology Annual data from 1990-2010 for budget deficit and stock prices has been used for this research study. Stock price indices under consideration are KSE 100 index for Pakistan and BSE 200 index for India. Data for government budget deficit as a percentage of GDP for Pakistan and India has been taken from the Asian Development Bank web site and data for index has been taken from Karachi stock exchange, Bombay stock exchange, and Yahoo Finance. The study applied descriptive statistics, Augmented Dickey Fuller (ADF) Unit Root test proposed by (Dickey and Fuller 1979, 1981), Johansen’s co-integration test proposed by (Johansen 1990) and Granger-causality test proposed by (Granger 1988), (Engle and Granger 1987). E-Views 7 statistical package was used for these analyses. Similar types of test analysis techniques have been used by (Geetha, Mohidin et al. 2011) for measuring long run causal relationship between macroeconomic variables and stock market for the case of Malaysia, United State and China respectively. 2.1 Procedure The annual data collected for KSE 100 index for Pakistan, BSE 200 index for India and government budget deficit as a percentage of GDP for Pakistan and India was entered into MS Excel sheet which was then transferred to EViews software for analysis purposes. Firstly, the descriptive analyses were conducted through E-Views to know the mean, median, standard deviation, skewness, kurtosis and the like statistics. Then unit root (ADF) test was applied to check the stationary status of the data, in order to have good analysis. After which Johansen’s co-integration test was applied to check the cointegration between variables. At the end the Granger causality test was applied to measure the causal relationship between budget deficit and stock prices for Pakistan and India. 3. Results and Discussion The results obtained from descriptive statistics, Augmented Dickey Fuller test, Johansen’s Co-integration test and Granger causality test are presented and discussed in detail in this section. 3.1 Descriptive statistics Table 3.1 provides self-explanatory descriptive statistics analysis done through E-Views statistical software. Pakistan Budget deficit (BD) has the mean of -5.6358 with standard deviation of -5.1400. India Budget deficit (BD) has the mean of -5.1400 with standard deviation of 1.2557 respectively. KSE-100 index Return has the mean of 14.8221 and standard deviation of 33.6988. BSE-200 index Return has the mean of 19.7862and standard deviation of 31.2331. The values of median, maximum, minimum, skewness, kurtosis, jarque-bera, probability and observations are also given for these two variables in the Table 3.1. Insert Table 3.1 Here 3.2 Augmented Dickey Fuller test (ADF) Augmented Dickey Fuller test has been used to find out the stationary status of the data at level or at first difference. Figure 3.1 shows the graphical representation of budget deficit as a percentage of GDP for Pakistan, Figure 3.2 shows the graphical representation of KSE-100 index return, Figure 3.3 shows the graphical representation of budget deficit as a percentage of GDP for India and Figure 3.4 shows the graphical representation of BSE-200 index return respectively. The graphs show that in both countries budget deficit as a percentage of GDP and index return (KSE100, BSE-200) has no trend in the data set, so the study use the condition of intercept without trend in ADF test. Lag length for all the variable is based on the Schwarz Info criteria (SIC). Insert Figure 3.1 Here Insert Figure 3.2 Here Insert Figure 3.3 Here Insert Figure 3.4 Here Table 3.2 shows the result of unit roots test for variable that are Budget deficit (BD) and KSE-100 index return for Pakistan. ADF test result shows that data is stationary at lag order 1 and the order of integration is I (1). The test results reject the null hypothesis that there is a unit root in the first difference for budget deficit and stock prices. The value of the Durbin-Watson statistics is also acceptable for Pakistan. Insert Table 3.2 Here COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 179 ijcrb.webs.com INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS SEPTEMBER 2012 VOL 4, NO 5 Table 3.3 shows the result of unit roots test for variable that are Budget deficit (BD) and BSE-200 index return for India. ADF test result shows that data is stationary at lag order 1 and the order of integration is I (1). The test results reject the null hypothesis that there is a unit root in the first difference for budget deficit and stock prices. The value of the Durbin-Watson statistics is also acceptable for India. Insert Table 3.3 Here 3.3 Johansen co-integration test The ADF unit root test confirms the data stationarity, now the cointegration tests have been applied for both countries to identify any possible long-run equilibrium relationship between budget deficit and stock return. In case of Pakistan the null of no cointegrating vector can be rejected for budget deficit and KSE-100 index return used in the study (see Table 3.4) because the value of both Trace statistics and Max-Eigen statistic is greater than the critical value at 5% level of significance. This indicates that the annual data for this study from 1990 to 2010 support the intention that in Pakistan there exist a long term relationship between budget deficit and stock prices. Insert Table 3.4 So the normalized cointegration equation for this model is: Stock Prices = α + β1 Budget Deficit SP = 77.62785+ 11.24462 BD ------------------------------------------------------------------------------------ (3.1) The equation (3.1) indicates that a 1 percent increase in the budget deficit, the stock prices is predicted to increase by 11.24462 percent. α is 77.62785, which is the average value of the dependent variable (stock prices) when the independent variable (budget deficit) is zero. This shows that there is positive long term relationship between budget deficit and stock prices index in Pakistan. The result is supported from the work of (Roley, Lawrence et al. 1988) who investigates that higher budget deficit leads to boost the stock prices. In case of India the null of no cointegrating vector can be rejected for the budget deficit and BSE-200 index return used in the study (see Table 3.5) because the value of both Trace statistics and Max-Eigen statistic is greater than the critical value at five percent level of significance. This indicates that the annual data for this study from 1990 to 2010 support the intention that in India there exist a long term relationship between budget deficit and stock prices. Insert Table 3.5 So the normalized cointegration equation for this model is: Stock Prices = α - β1 Budget Deficit SP = - 262.4666 -54.44765BD ------------------------------------------------------------------------------------ (3.2) The equation (3.2) indicates that a 1 percent increase in the budget deficit, the stock prices is predicted to decrease by 54.4476 percent. α is - 262.4666, which is the average value of the dependent variable ( stock prices) when the independent variable(budget deficit) is zero. This shows that there is a long term negative relationship between budget deficit and stock prices index in India. The result is supported from the work of (Adrangi and Allender 1998) who investigates a negative association between budget deficit and stock prices in U.S. 3.4 Granger causality test This test tells us about the direction of causality, and table 3.6 shows the result of Pairwise causality for Pakistan and India. The two null hypothesis are: (a) does budget deficit cause Stock Prices Return (KSE-100 Index, BSE-200 Index)? (b) does Stock Prices Return (KSE-100 Index, BSE-200 Index) cause budget deficit? Insert Table 3.6 The results of Granger causality test for Pakistan reveal a unidirectional causality running from budget deficit to stock prices. This result confirms our previous finding that a positive cointegrating relationship exists between budget deficit and stock prices in Pakistan. For India the results reveal no causality running from budget deficit to stock prices and from stock prices to budget deficit. This result confirms our previous finding that a negative cointegrating relationship exists between budget deficit and stock prices in India. 4. Summary, Conclusion and Recommendations The intention of this research study is to investigate the long run relationship between budget deficit and stock prices for two South Asian economies, Pakistan and India. This research study use annual data on budget deficit as a percentage of GDP, stock price index return (KSE 100 Index, BSE 200 index) from 1990 to 2010. Augmented COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 180 ijcrb.webs.com INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS SEPTEMBER 2012 VOL 4, NO 5 Dickey Fuller (ADF) test, Johansen Cointegration technique and Granger causality tests has been used to assess the relationships; between budget deficit and stock prices. Evidence from Pakistan reveals that a long run positive causal relationship exists between budget deficit and stock prices and these findings are compatible with the work of (Roley, Lawrence et al. 1988). Reasons for this positive relationship are the economic condition, economy is not fully employed and developmental expenditures are also too high as compared to the current expenditures. The evidence also suggests that increases in the structural deficit have historically led to slight increases in stock prices. The structural deficit has typically risen during recessions, and then decreased early in the subsequent expansions. On the contrary, in India a long run negative relationship is observed and these findings are analogous with the work of (Adrangi and Allender 1998) the reason is high current expenditures. The findings for India implies that as deficits increase, future tax burden, interest rates, and the dollar's value increase, leading to decrease in corporate profits because of weak domestic as well as export revenues. So, sales decreases which ultimately lower net earnings, thus, decreasing equity prices. In case of Pakistan, a positive association among budget deficit and stock prices is evident. However, reverse situation is true for India. India has used its enormous work force to establish industrial stability whereas Pakistan is still trying to achieve industrial stability. India is a safe investment option for foreign companies whereas Pakistan is considered a liability; its dependence on foreign aid is increasing instead of being reduced. Pakistan is currently under debt to the World Bank, the IMF and various countries; however India managed to become a power source. In case of Pakistan, less industrialization, in-efficient capital market, unemployment, and economic condition are few other reasons due to which result shows a positive correlation. Government must adopt solid tactic to improve budget deficit. High population growth rate, lack of public awareness of environmental related education, mismanagement of natural resources, widely unplanned urban and industrial expansions are the core hard issues. Monitoring authorities should concentrate on resource utilization; a concrete strategy must be implemented and monitored so the optimal results can be achieved. Industrialization can also play a very vital role. If a country’s exports are larger than its imports, the country excels, whereas the reverse case spells certain doom. It does not take a genius to guess that Pakistan falls into the latter category. Government should induce initial capital to progress industrialization, beside that nuclear power and coal resources should be utilized fully to cope with energy disaster, which is one of the major obstacles in industry progress. Capital market of Pakistan is also not much developed as compare to India capital market. This is also one of the major sources of positive correlation in case of Pakistan. The Securities and Exchange Commission of Pakistan (SECP) should formulate a comprehensive policy for dealing with companies in default of securities market laws to protect the investor, enhance transparency and improve member listing. Attractive strategies should be adopted to attract foreign investors. COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 181 ijcrb.webs.com INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS SEPTEMBER 2012 VOL 4, NO 5 References Adrangi, B. and M. Allender (1998). "Budget Deficits and Stock Prices: International Evidence." Journal of Econoraics and Finance 9(22): 57-66. Aggarwal and Raj (1981). "Exchanges Rates and Stock Prices: a Study of The U.S. Capital Markets Under Floating Exchange Rates." Akron Business and Economic Review 12: 7-12. Anusic, Z. (1994). "Budget Deficit and Inflation." Croatian Economic Survey 1. Ball and Mankiw (1995). "What Do Budget Deficit Do?" National Bureau of Economic Research 5263: 1-36. Burney and Akhtar (1992). "Government Budget Deficits and Exchange Rate Determination: Evidence from Pakistan." The Pakistan Development Review 31(4): 871-882. Charles and Adjasi (2008). "Effect of Exchange Rate Volatility on the Ghana Stock Exchange." African Journal of Accounting, Economics, Finance and Banking 3(3). Cutler, David, et al. (1987). "What Moves Stock Prices?" Journal of Portfolio Management 15(3). Dickey, D. A. and W. A. Fuller (1979, 1981). "Likelihood Ratio Tests for Autoregressive Time Series with a Unit Root." Econometrica 49: 1057-1072. Engle, R. and C. W. J. Granger (1987). "Cointegration and the error correction representation, estimation and testing." Econometrica 55: 251-276. Essaied, M., Hamrita, et al. (2009). "The Multi-Scale Interaction between Interest Rate, Exchange Rate and Stock Price." MPRA 18424(6). Geetha, C., R. Mohidin, et al. (2011). "The Relationship between Inflation and Stock Market: Evidence from Malaysia, United States and China." International Journal of Economics and Management Sciences 1(2): 1-16. Granger, C. W. J. (1988). "Some recent developments in a concept of causality." Journal of Econometrics 39(1/2): 199-211. Greenspan and Allen (1995). "What Do Budget Deficits Do? General Discussion, Budget Deficits and debt: Issues and Options, edition." Federal Reserve Bank: 139-149. Hall and Taylor (1993). " Macroeconomics." Johansen (1990). "Maximum likelihood and inference on cointegration with applications to the demand for money pp. 169-210." Oxford Bulletin of Economics and Statistics 52: 169-210. Kurihara (2006). "The relationship between exchange rate and stock prices during the quantitative easing policy in Japan." International Journal of Business 11(4): 375-386. Pilinkus, D. (2009). "Stock Market and Macroeconomic Variables: Evidence from Lithuania " Economics & Management 14: 1822-6515. Quayes, S. (2010). "Does budget deficit lower equity prices in USA." Elsevier 107: 155-157. Roley, V., Lawrence, et al. (1988). "Federal Deficit and Stock Market." Economic Review. Sargent and Wallace (1981). "Some Unpleasant Monetarist Arithmatic." Federal Reserve Bank of Minneapolis Quarterly Review: 1-17. COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 182 ijcrb.webs.com INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS SEPTEMBER 2012 VOL 4, NO 5 Annexure Figure. 3.1. Budget Deficit as a Percentage of GDP for Pakistan BD AS A % OF GDP -2 -3 -4 -5 -6 -7 -8 -9 90 92 94 96 98 00 02 04 06 08 10 Figure. 3.2. KSE-100 Index Return for Pakistan INDEX RETURN 100 80 60 40 20 0 -20 -40 90 92 94 96 98 00 02 04 06 08 10 Figure. 3.3. Budget Deficit as a Percentage of GDP for India BD AS A % OF GDP -2 -3 -4 -5 -6 -7 -8 90 92 94 96 98 00 02 04 06 08 10 Figure. 3.4. BSE-200 Index Return for India INDEX RETURN 100 80 60 40 20 0 -20 -40 90 92 94 96 98 00 02 04 COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 06 08 10 183 ijcrb.webs.com SEPTEMBER 2012 VOL 4, NO 5 INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS Table: 3.1. Descriptive Statistics PAKISTAN INDIA Budget Deficit KSE 100 Index Budget Deficit BSE 200 Index Mean -5.6358 14.8221 -5.1400 19.7862 Median -5.6461 9.6600 -5.3380 27.4200 Maximum -2.3047 83.4300 -2.5649 90.5100 Minimum -8.7393 -35.5500 -7.8353 -30.0800 Std. Dev. -5.1400 33.6988 1.2557 31.2331 Skewness 0.0159 0.3306 -0.0508 0.2797 Kurtosis 2.2727 2.1409 2.7893 2.5541 Jarque-Bera 0.4638 1.0284 0.0479 0.4478 Probability 0.7930 0.5980 0.9763 0.7994 Observations 21 21 21 21 Table: 3.2. Results of Augmented Dickey Fuller test for Pakistan Variables ADF Test Statistics ADF test statistic-BD -6.1286 ADF test statistic-kSE100 Index Return -5.6632 Critical Values 1% critical value -3.8315 5% critical value -3.0300 10% critical value -2.6552 1% critical value -3.8574 5% critical value -3.0404 10% critical value -2.6606 Order of Integration I(1) I(1) Variable Coefficient Std.error t- Statistics Prob. D(BD(-1)) -1.2955 0.2114 -6.1287 0.0000 D(KSE_100_INDEX(-1)) -2.1755 0.3841 -5.6632 0.0000 Table: 3.3. Results of augmented Dickey Fuller test for India Variables ADF test statistic-BD ADF test statistic-BSE200 Index Return ADF Test Statistics -5.3418 -9.0565 Critical Values 1% critical value -3.8574 5% critical value -3.0404 10% critical value -2.6606 1% critical value -3.8315 5% critical value -3.0300 10% critical value -2.6552 Order of Integration I(1) I(1) Variable Coefficient Std.error t- Statistics Prob. D(BD(-1)) -1.5427 0.2888 -5.3418 0.0000 D(BSE_200_INDEX(-1)) -1.6798 0.1855 -9.0565 0.0000 COPY RIGHT © 2012 Institute of Interdisciplinary Business Research 184 ijcrb.webs.com SEPTEMBER 2012 VOL 4, NO 5 INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS Table: 3.4. Results of Johansen co-integration test for Pakistan Hypothesized Number of CE(s) Eigenvalue Trace Statistics Max-Eigen Statistics 5 Percent Critical Value r =0* 0.519504 16.64078 14.65873 14.07 r< 1 0.094350 1.982053 1.982053 3.76 Normalized Co integrating Coefficients KSE-100 Index Return Budget Deficit (BD) C 1 -11.24462 -77.62785 (2.59967) [-4.32541] Trace test and Maximum Eigen value indicates 1 cointegrating equations at the 5% level and * denotes the rejection of null hypothesis at the 0.05 level of significance. Table: 3.5. Results of Johansen co-integration test for India Hypothesized Number of CE(s) Eigenvalue Trace Statistics Max-Eigen Statistics 5 Percent Critical Value r =0* 0.473760 20.28177 20.28177 15.49471 r< 1* 0.310708 7.441813 7.441813 3.841466 Normalized Co integrating Coefficients BSE-200 Index Return Budget Deficit (BD) C 1 54.44765 262.4666 (15.5449) [ 3.50261] Trace test and Maximum Eigen value indicates 2 cointegrating equations at the 5% level and * denotes the rejection of null hypothesis at the 0.05 level of significance. Table: 3.6. Results of Granger causality test for Pakistan and India Pairwise Granger Causality Tests for Pakistan Null Hypothesis: Budget Deficit doesnot Granger Cause KSE-100 Index Return Obs F-Statistic Prob. 20 3.09577 0.0049* 0.60649 0.5581 Obs F-Statistic Prob. 20 1.23897 0.3177 0.29803 0.7466 KSE-100 Index Return doesnot Granger Cause Budget Deficit Pairwise Granger Causality Tests for India Null Hypothesis: Budget Deficit doesnot Granger Cause BSE-200 Index Return BSE-200 Index Return doesnot Granger Cause Budget Deficit COPY RIGHT © 2012 Institute of Interdisciplinary Business Research View publication stats 185