Review of Economics and Development Studies Vol.2, No 2, December 2016 103 Volume and Issues Obtainable at Center for Sustainability Research and Consultancy Review of Economics and Development Studies ISSN:2519-9692 ISSN (E): 2519-9706 Volume 2: Issue 2 December 2016 Journal homepage: www.publishing.globalcsrc.org/reads Public Spending and Macroeconomic Performance in Pakistan: An Empirical Analysis 1 Imran Sharif Chaudhry, 2 Gulshan Ameer, 3 Syed Ali Akbar Rizvi 1 Director, School of Economics, Bahauddin Zakariya University Multan, Pakistan, imran@bzu.edu.pk 2 M.Phil Scholar Bahauddin Zakariya University Multan, Pakistan, gulshan-ameer1@hotmail.com 3 Former M. Sc. Scholar, School of Economics, Bahauddin Zakariya University Multan, Pakistan Syedali_akbar@hotmail.com ARTICLE DETAILS ABSTRACT History Revised format: May 2016 Available online: Jun 2016 Public spending management is the base of stable macroeconomic environment .This empirical study has explored the relation between public spending and economic performance, in the context of Pakistan. An attempt is made to examine the growth effects of public spending for the economy of Pakistan. To observe the public spending and Pakistan’s macroeconomic performance, time series data has been used for the period of 1972-2012. GDP growth has taken as the dependent variable. By applying the Auto regressive Distributive Lag (ARDL) technology macroeconomics performance of Pakistan has been analyzed. Our results indicate that government expenditure has positive and significant effects but excessive government expenditure have negative effects on the economy’s performance. This study may suggest that provision of more incentives to the main sectors of the economy will lead to the sound economic conditions. © 2016 The authors, under a Creative Commons Attribution- NonCommercial 4.0 Keywords Public Spending, Economic Growth, ARDL, ECM, Pakistan JEL Classification H50, H52, F43, C30, C32 Corresponding author’s email address: imran@bzu.edu.pk Recommended citation: Chaudhry, I. S., Ameer, G. and Rizvi, S.A.A. (2016). Public Spending and Macroeconomic Performance in Pakistan: An Empirical Analysis. Review of Economics and Development Studies, 2 (2) 103-116 DOI: https://doi.org/10.26710/reads.v2i2.128 1. Introduction Prudent public spending management is the base of stable macroeconomic environment. Public spending also effects the private sector’s investment and its contribution to economic growth. Fiscal variables have direct as well as indirect effect on the economic performance of an economy through taxation and government spending. Public spending theory explains that increasing state activity promotes efficient allocating resources, rapid economic development, technological development and social welfare. Government expenditures involve economic benefits and costs (Grossman, 1988). As a result of efficient resource allocation, economic and social conditions of the country are positively affected. Public sector of an economy is considered as an administrative for the productive functions and this sector owns the large fraction of economy’s resources. By utilizing the economy’s resources, government activities provide the beneficial services for the well being of the society and thus effect the economic growth. So Wagner’s law has established the link between government activities and economic development. http://www.publishing.globalcsrc.org/reads mailto:gulshan-ameer1@hotmail.com mailto:Syedali_akbar@hotmail.com Review of Economics and Development Studies Vol.2, No 2, December 2016 104 Public investment which comprises the more than half of total investment also promotes the developmental process. Economists argue that capital investment promotes the technological innovations and specialization and thus leads to economic development. Public investment is a major tool which not only efficiently utilizes the productive resources but also increases the GDP to enhance the economic performance. Government expenditures are used for number of purposes. The basic and important task accomplished by public expenditure is to maintain the law and order, provision of defense to the country and infrastructural development and betterment. A large share of revenue collected by the government is utilized to build roads, hospitals, dams, schools and in the provision of some other basic necessities to people. Public expenditure also improves the distribution of income. It leads to the better access to the total resources of the people and hence improving the living standards. Public spending plays vital role to achieve the sustainable growth of the economy but allocation of public expenditure is another crucial phenomenon. An economy can gain more significant and positive impact by allocating the public expenditure on productive activities. However excessive public spending on unproductive tasks might lead towards creating worse economic conditions. As Pakistan is facing low GDP growth rate so it is very necessary to analyze that relation between public spending and macroeconomic performance of Pakistan. The rest of the article is prearranged as follows. Section 2 presents Literature review. Data and methodology is given in section 3 while section 4 is reserved for Empirical results and their discussion. At the end, conclusion and recommendations are given regarding public spending. 2. Literature Review The previous economic literature in particular confirms the importance of public spending in economy’s performance. (Landau,1986, Barro, 1990, Aschauer, 1996). Some significant studies are reviewed. Lucas (1988) in his study focused on the focal features of economic growth by considering Neo- classical growth theory. In his study three models presents the diversity of conclusion. The study concludes that same pattern of growth cannot be useful for developed and developing countries. Barro (1990) observed the negative relation between economic growth and tax financed public services by extending a simple endogenous growth model. The difference in preferring public and private services causes the variation in consumption and expenditure share. The study shows the negative link of this variation to economic growth rate. Munnell and cook (1990) explored the positive link between public spending productivity and economic growth by using the data for the period of 1970-1988 for US states. The exercises of their work prove that public Investment has statistically significant and positive effect on productivity. Barro (1996) presented the empirical framework based on new version of Neo- classical growth model for the panel of 100 countries over a period of 30 years. The positive link is described between public capital and economic growth while public capital is explaining the broader aspect of government policies. Devarajan et al. (1996) have studied the relation between public expenditure and economic growth. They took the annual data of 43 developing countries. They derived that by changing the composition of public spending economy could get the steady state growth. By interpreting the results of the model, they obtained the surprising results. Productive expenditure has negative relation with economic growth. While current expenditure contributes the higher economic growth. They showed that an excessive amount of productive expenditure become mostly unproductive. They declared that government of developing countries is misallocating the public expenditure. Developing countries utilize the more resources for capital expenditure than current expenditure. While developed countries have proper allocation of resources. They concluded that proper allocation of government resources and proper composition of public capital can lead the economy to steady state growth rate. Review of Economics and Development Studies Vol.2, No 2, December 2016 105 Iqbal and Zahid (1998) adopted the multiple regression frame work to study the impact of basic macroeconomic variables on the economic growth of Pakistan over the period of 1960-1997. This study explores the positive impact of properly allocated infrastructure on the economic growth. Bose et al. (2003) analyzed the strong difference in the composition of government expenditure between developed countries by examining 30 countries data for the period of 1970s and 1980s. The conclusion of their results is the strong positive relationship between capital expenditure and economic growth while current expenditure have insignificant impact. Bukhari, Ali and et al. (2007) investigated the relation among macroeconomic variables for three East Asian countries for the period of 1970-2000 the result of various econometric techniques show the positive impact of public investment on economic growth. Agenor (2011) exposed the complementary and significant relationship between education, health and infrastructure by designing the macroeconomic models for developing countries. The impact of investment on infrastructure is dependent on the productiveness of the technology. Ellahi and Kiani (2011) analyzed the link between public investment and economic growth for Pakistan economy. The study shows short run as well as long run relationship between public investment and economic growth. However public sector has small impact due to its inefficiency. Nworji et al. (2012) analyzed the impact of public expenditure on economic growth of Nigeria by using the OLS multiple regression technique. Time series data has been taken of the relevant variables for the period of 1970-2009 in Nigeria. Their study focused on the empirical measure of the relation between economic growth and public expenditures. The study showed that recurrent expenditures on economic services and capital area disaggregated components of economic growth. These disaggregated components have negative effect on growth. While statistically these have significant impact. However, economic growth is positively affected by using the recurrent expenditure on social and community services. They concluded that to obtain the economic growth in Nigeria, the use of fiscal policy instruments must be continued. They recommended that more attention must be paid on allocating the government expenditures. The government expenditures should mainly be utilized on productive economic activities to obtain sustained economic growth. For Pakistan economy, Ahmad, Abass et al. (2013) explored the role of public infrastructure on economic growth. By using CGE model and micro simulation model, results show the negative impact of tax financed public investment on economic growth. Onakoya et al. (2013) have examined the effects of public expenditure on economic growth in Nigeria. They adopted the methodology of 3SLS by using the data of Nigeria from 1970 to 2010. Results obtained by applying Durbin Watson statistics. The results declared the positive link between government capital expenditure and output of infrastructural sector. By utilizing the idea of Keynesian school of thought, they attempted to capture the enhanced growth even in the time of depression by increasing government expenditures. The study shows the positive impact of public spending on economic growth as well as enhancing the private sector investments. Government can achieve the more significant and positive results by restructuring its public administration sector in Nigeria. A number of investigations of former work give us the better understanding on the related issue but a little attention has been given to public spending and economy’s performance in long run relationship. The current study provides an analysis of public spending and macroeconomic performance regarding Pakistan economy. This study has used appropriate methodological techniques and model specification to fulfill the deficiencies and flaws of the prior studies. 3. Objectives of the study i) Analysis of the macroeconomic performance of Pakistan with reference to public spending ii) Analysis of link between government spending and economic growth. iii) Analysis of impact of public investment, in industrial and agricultural sector, on growth rate. Review of Economics and Development Studies Vol.2, No 2, December 2016 106 iv) Exploration of some policy implications regarding public spending and economic performance of Pakistan for further investigation. Data and Methodology The proper selection and building of variables and authenticated sources of data are mandatory to achieve the valid and reliable results from the research work. The purpose of this study is to empirically analyze the public spending and macro economic performance in Pakistan. This research work is based on the secondary data for the year 1972-2012. To analyze the relationships, Auto Regressive Distributed Lag (ARDL) approach has been used. Data Sources The compilation and generation of data must be done very cautiously to obtain the accurate and efficient results. The main sources used for the data collection in this study are various issues of Pakistan Economic Survey, Hand Book of Statistics 2011-12 issued by State Bank of Pakistan and World Bank Indicators. The variables, about which data are collected are GDP Growth (GDPG) taken as the dependent variables while Agriculture value added as percent of GDP (AGRI), Industry value as percent of GDP (INDS), Inflation (CPI), Government Fixed Investment (GFCF), Government Expense (GE) and Public Investment (IG) as independent variables. The Empirical Methodology After the selection of data on specific variables the next step is to check the stationarity of data and then choose the appropriate econometric technique through which we can obtain some results. Stationary of Data To analyze the nature of time series data, to check the stationary properties, a number of techniques can be applied. Generally, ADF test is used to check the stationary of variables. If the variables are integrated at same degree then OLS technique can be used. However the combination of variables stationary at I (0) and I (1) in the time series equation shows that variables are not in the same order of integration. To resolve this issue in a better way, econometric theory suggests employing the ARDL approach. Auto regressive Distributed Lag Approach The ARDL approach estimates the long run and short run parameters in a single equation model. By comparing with the other techniques, ARDL approach is the most appropriate technique to apply after checking data stationarity. After estimation of model through ARDL approach the model results will be unbiased and efficient. Auto regressive Distributed Lag Approach has a drawback in its application, when the variables are on high order I (1) stationary then ARDL technique cannot be applied. Model Building The model (1 & 2) describe the impact of public spending on growth rate in Pakistan Review of Economics and Development Studies Vol.2, No 2, December 2016 107 1 2 3 54 6 k k t 0 1 t-i 2 t-i i=1 i=0 k kk 3 t-i 4 t-i 5 t-i i=0 i=0 i=0 k 6 t-i 1 t-1 2 t- i=0 = + (GDPG) + (GE) + (GFCF) + (IG) + (INDS) + (CPI) + (GDPG) + (GE) i i i i i i GDPG                       1 6 3 t-1 4 t-1 5 t-1 t-1 t + ( GFCF) + (IG) + (INDS) + (CPI) + (1)     Here the first difference operator is denoted by Δ. For the short run we used lagged value of first difference independent and dependent variable. In the long run for the dependent and independent variables first lagged values are used. In first model short run and long run coefficients of all the variables are included as well. In first model α1, α2, α3, α4 and α5 are the short run coefficients while β1, β2, β3, β4 and β5 are the long run coefficients. Here the intercept term is α0. However t showed the residual of the model. 1 2 3 54 6 k k t 0 1 t-i 2 t-i i=1 i=0 k kk 3 t-i 4 t-i 5 t-i i=0 i=0 i=0 k 6 t-i 1 t-1 2 t- i=0 = + (GDPG) + (GE) + (GFCF) + (IG) + (AGRI) + (CPI) + (GDPG) + (GE) i i i i i i GDPG                       1 3 t-1 6 4 t-1 5 t-1 t-1 t + ( GFCF) + (IG) + (AGRI) + (CPI) + (2)     Similarly, in model (2) the first difference operator is denoted by Δ. For the short run we used lagged value of first difference independent and dependent variable. In the long run for the dependent and independent variables first lagged values are used. In first two models short run and long run coefficients of all the variables are included as well. In second model γ1, γ 2, γ 3, γ 4, γ 5 and γ 6 are the short run coefficients while φ1, φ 2, φ 3, φ 4, φ 5 and φ 6 are the long run coefficients. Here the intercept term is γ0. However, the μt showed the residual of the model. Wald Test By taking the lagged level variables we will apply joint F-test or Wald coefficient approach. By conducting Wald test the F- statistics will be computed. Then the estimated F- statistics will be compared with the tabulated F- statistics developed by Pesaran et al. (2001). The tabulated F- statistics has two critical bounds. These two bounds are called lower bound and upper bound. The lower bound is denoted by I (0), while the upper bound is denoted by I (1). The long run relationship between the variables exists if estimated F- statistics is greater than upper bound otherwise long run relation does not exist. Then the Wald test will be applied on the lagged variables of the equations 1 and 2. For Model-I Null Hypothesis: β1= β2= β3= β4= β5=0 (No Co-integration exists) Alternative Hypothesis: β1≠ β2≠ β3≠ β4≠β5≠0 (Co-integration exists) Review of Economics and Development Studies Vol.2, No 2, December 2016 108 For Model-II Null Hypothesis: φ1= φ2= φ3= φ4= φ5=0 (No Co-integration exists) Alternative Hypothesis: φ1≠ φ2≠ φ3≠ φ4≠ φ5≠0 (Co-integration exists) 5. Results and Discussion a)Descriptive analysis For better analysis and to produce the quality results, it is very essential to conduct the descriptive analysis. Descriptive analysis is illustrated in table 1. The Descriptive analysis includes mean, median, minimum, maximum, standard deviation, kurtosis, skewness and Jarque Berra test. Table 1: Result of Descriptive Statistics for Model – I&II. Variables/ Statistical Measurement GDP G GOVT. EXPEN SE GOVT. FIXED INVES TMEN T INDU STRY AGRIC ULTUR E PUBLIC INVEST MENT INFLA TION Mean 16.03 11.02 17.83 24.23 26.72 172794 9.78 Median 15.23 10.86 18.2 24 26.2 106482 8.83 Maximum 30.5 16.78 22.5 27.7 36.4 674240 26.6 Minimum 5.76 7.78 12.4 21.7 20.1 3714 2.91 Std. Dev. 2.21 2.28. 1.58 4.43 197269 5.54 Skewness 0.44 -0.326 0.468 0.32 1.42 1.24 Kurtosis 2.84 3.41 2.48 2.43 3.79 4.24 Jarque- Bera 1.42 1.025 1.95 1.27 4.87 13.2 Probability 0.49 0.59 0.37 0.527 0.00059 0.0013 2 Source: Author’s estimation using E-views software b) ADF test of Stationarity The results of ADF test are presented in table 2. The results indicate that some variables are stationary at level while some are stationary at first difference. Table 2: Estimations of Augmented Dickey Fuller (ADF) Test Variables Level 1 st Difference Conclusion AGRICULTURE -3.442 I(0) INDUSTRY -4.943 I(1) GDPG -3.30 I(0) INFLATION -3.82 I(0) GOVT.FIXED INVESTMENT -5.382 I(0) GOVT.EXPENSE -4.048 I(1) PUBLIC INVESTMENT -2.833 I(1) Source: Author’s estimation by applying E-views software Bound test approach to Co-integration: To obtain pragmatic analysis of long run interaction among the variables, we apply the Bound Test. Table presents the results of F-Statistics for the long run relationship. Table 3: Bound test approach to Co-integration Review of Economics and Development Studies Vol.2, No 2, December 2016 109 Bound Test Models F-Stats Lag Prob. Bound Critical Conclusion I (0) I (1) CPIINDSIGGFCFGEGDPG ,,,, 4.21** 2 0.05 2.45 3.61 Co integration exists CPIAGRIIGGFCFGEGDPG ,,,, 3.89** 2 0.05 2.45 3.61 Co integration Exists Note: Bound critical values are taken from the article of Pesaran et al. (2001), Table C1. iii: Case III: Unrestricted intercept and no trend. *, ** and *** certify that co-integration exists at 1, 5 and 10 percent level of significance respectively having k (no of regressors) equal to 5. F-Stats are calculated using E-Views. The calculated F- Statistics is presented in Table 2. F- Statistics value is measured for the two models. The estimated value of F- Statistics for the model-I is 4.21.It shows that the estimated values of F- Statistics are greater than the upper bound value. So it indicates the presence of long run interaction between the variables in both models. Long run and short run estimation for Model-I The long run coefficients of model-I of this study are given below. Here dependent variable is GDPG which shows the GDP growth, while Govt. Expense, Govt. Fixed investment, Public Investment, Industry, Inflation are the independent variables. Table 4: Estimated Long Run Coefficients of Model-I using ARDL Approach ARDL (2, 0, 1, 2, 0, 1) selected based on Schwarz Bayesian Criterion (SBC) Dependent Variable: GDPG Variables Co-efficient Standard Error T-Ratio Probability GE -1.831 0.177 -1.033 0.311 GFCF -0.441 0.239 -1.845 0.076 IG -0.709 0.287 -2.46 0.20 INDS -0.117 0.256 -.457 0.651 CPI 0.545 0.070 7.78 0.000 C 23.63 7.062 3.346 0.002 Source: Author’s estimation by applying Micro-Fit4.1software The results show that gross fixed capital formation and government expenditures have negative impact on GDP growth. Government expenditure on unproductive items has no significant impact on Economic growth (GDPG). These results are alike to results of Devarjan(1996) and Noworji (2010). The proper allocation of public expenditure is required for the betterment of the macroeconomic condition of the economy. Public investment is found to be negative in long run. The negative sign relates to the economic theory as excessive public investment crowd out the private investment. Economic growth rate has negative and insignificant effects of public investment on unproductive items. Our results are harmonized with Ghani and Din (2006). They concluded that economic growth is motivated by the private investment. The effects of public sector are very small due to inefficiency of the sector. Table 5: Short run coefficients estimation for Model -I ARDL (2,0,1,2,0,1)selected based on Schwarz Bayesian Criterion (SBC) Review of Economics and Development Studies Vol.2, No 2, December 2016 110 Explained Variable: GDPG Variables Co-efficient Standard Error T-Ratio Probability dGDPG1 0.34984 0.131 2.665 .012 dGE -0.34863 0.337 -1.032 .310 dGFCF 0.21432 0.5952 0.3600 .72 dIG -0.1067 0.320 -0.333 .74 dIG1 0.12237 0.332 3.718 .001 dINDS -0.22338 0.491 -0.454 .653 dCPI 0.17081 0.192 0.888 .382 dC 44.9894 14.23 3.1616 .004 ecm(-1) -1.9034 0.216 -8.779 .000 R-Squared 0.836 R- Bar-Squared 0.770 AIC -107.79 SBC -117.77 Durbin-Watson Statistics 2.262 F-Statistics 17.311(0.000) The results show that R-Square and Adjusted R-Square for model-I are 83 percent and 77 percent respectively. The R-Square and Adjusted R-Square values express the variations explained by explanatory variables. The results showed that inflation has positive and significant effect on economic growth. These results are theoretically sound. The more profits are gained by the investors with the rise in prices. However, D-W value is 2.26 shows no sign of auto correlation. F- Statistics is significant so the model is good. Interpretation of Error Correction Term (Ecmt-1) The result of error correction term for Model-1 is 1.90 which shows that 190% of disequilibrium will be adjusted. The parameter of adjustment is highly significant and shows the fast speed of adjustment. So 190% disequilibrium is corrected over each year at 1% level of significance. Long run and short run estimation for Model-II Table 6: Estimated Long Run Coefficients of Model-II using ARDL Approach ARDL (2, 0, 1, 2, 0, 1) selected based on Schwarz Bayesian Criterion (SBC) Dependent Variable: GDPG Variables Co-efficient Standard Error T-Ratio Probability GE -0.121 0.1645 -0.7389 0.466 GFCF -0.316 0.227 -1.39 0.176 IG -0.352 0.485 -0.725 0.943 AGRI 0.311 0.1870 1.665 0.107 CPI 0.462 0.801 5.767 0.000 C 9.450 7.722 1.223 0.232 Source: Author’s estimation by applying Micro-Fit4.1software The results indicate that agriculture sector has positive and significant impact on GDP growth. The increase in public spending on agriculture sector increases the total productivity might increase the 3.0 percent of total productivity. These results are alike to results of Aschauer (1989). Armey maintains that low government expenditures can increase economic growth until it reaches a critical Review of Economics and Development Studies Vol.2, No 2, December 2016 111 level. The proper allocation of public expenditure is required for the betterment of the macroeconomic condition of the economy. The negative sign of Government expenditure relates to the economic theory. Government expenditure has different preferences of public and private investment. So, Government expenditure has negative impact on economic growth. Our study results are harmonized the results of Barro (1990) Table 7 Error Correction Representation for the Selected ARDL Model ARDL (2, 0, 1, 2, 0, 1) selected based on Schwarz Bayesian Criterion (SBC) Explained Variable: GDPG Variables Co-efficient Standard Error T-Ratio Probability dGDPG1 0.417 0.132 3.14 0.004 dGE -0.245 0.331 -0.7422 0.464 dGFCF 0.593 0.6247 0.949 0.35 dIG -0.166 0.298 -0.557 0.58 dIG1 0.125 0.317 3,945 0.000 dAGRI 0.630 0.399 1.576 0.125 dCPI 0.099 0.190 0.519 0.607 dC 19.1 15.13 1.263 0.216 ecm(-1) -2.02 0.222 -9.080 0.000 R-Squared 0.849 R- Bar-Squared 0.788 AIC -106.22 SBC -116.20 Durbin-Watson Statistics 2.262 F-Statistics 19.0446(0.000) Source: Author’s estimation by applying Micro-Fit4.1software The results of table 7 indicate that R-Square and Adjusted R-Square for model-II are 84 percent and 78 percent respectively. The R-Square and Adjusted R-Square values show the variations explained by explanatory variables. The results showed that value of the coefficient of Govt. Fixed investment is 0.593 which shows that one unit increase in Govt. Fixed investment (GFCF) increases the Economic growth (GDPG) by 0.593 percent. This is significant and strong effect as the productive activities are directly affected by the expansion of productive infrastructure. However, D-W value is 2.26 shows no sign of auto correlation. F- Statistics is significant so the model is good. Interpretation of Error Correction Term (Ecmt-1) The result of error correction term for Model-II is (-2.02) which shows short run variables approach to long run variables by 202% each year. The value of error correction term is significant and negative. It confirms the presence of unidirectional and long term relationship. Stability Test: To check stability, CUSUM and CUSUMS tests are measured. The cumulative sum of recursive residuals (CUSUM) and the CUSUM of square (CUSUMSQ) tests are applied to assess the parameter stability (Pesaran and Pesaran (1997). Stability means the CUSUM and CUSUMS statistics lie within the critical boundaries of 5 % confidence interval. Graphs 1 and 2 for model-I are plotted which show the results for CUSUM and CUSUMSQ tests. These graphs show the stability of the coefficients of both estimated models. The CUSUM and CUSUMS statistics falls in the critical bounds of 5% confidence interval. It shows that long run and short run estimations are stable. The verification of stable short run and long run estimations are confirmed by the lack of divergence in CUSUM and CUSUMS graphs. Stability Test CUSUM and CUSUMS for model-I Review of Economics and Development Studies Vol.2, No 2, December 2016 112 Stability Test CUSUM and CUSUMS for model-II Plot of Cumulative Sum of Recursive Residuals The straight lines represent critical bounds at 5% significance level -5 -10 -15 0 5 10 15 1974 1979 1984 1989 1994 1999 2004 2009 2012 Plot of Cumulative Sum of Squares of Recursive Residuals The straight lines stand for critical bounds at 5% significance level -0.5 0.0 1984 0.5 1.0 1.5 1974 1979 1984 1989 1994 1999 2004 2009 2012 Plot of Cumulative Sum of Recursive Residuals The straight lines stand for critical bounds at 5% significance level -5 -10 -15 0 5 10 15 1974 1979 1984 1989 1994 1999 2004 2009 2012 Review of Economics and Development Studies Vol.2, No 2, December 2016 113 3. Conclusion This study has been attempted to empirically analyze the impact of public spending and macroeconomic performance in Pakistan. Public spending is considered as the counter piece of government actions or policies which are regarded mandatory for the economic growth. In this study the various components of government spending, their directions and effects are analyzed to facilitate the government policies to attain the economic growth. In this study, the time series annual data for the last 40 years has been analyzed for Pakistan economy. In this study the Pakistan’s economic performance has been analyzed by investigating the public spending of the economy. The economic performance of Pakistan has shown sharp trends from the day of independence to date. These ups and downs are due the increase in population, adverse economic policies and instability of economic and political conditions. All these economic factors caused to the decline in growth rate. In short run Economic growth rate (GDP) is found positive. GDP shows the gross domestic product of a country in a year. In short run the gross fixed capital formation showed the positive and significant impact on GDP. As the gross fixed Investment (GFCF) increases in an economy, the economy grows. While in long run the gross fixed Investment (GFCF) has negative value. This shows the excessive capital formation leads to the decline in Economic growth (GDP). These results are harmonized by the results of Devarajan1996. This study explained the impact of public spending and macroeconomic performance of Pakistan. Policies should be made by the government for the proper allocation of resources between the current and capital expenditure. More incentives must be provided to main sectors of the economy so that their share in GDP will increase and this will lead to the sound economic conditions. Public policies must be directed towards proper control check of government spending especially on productive tasks as compared to unproductive. References Agénor, P. R. (2011). 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