Nadeem Iqbal Faculty of Business Administration BZU Sub Campus, Dera Ghazi Khan, Pakistan

EMPIRICAL RELATIONSHIP BETWEEN FOREIGN DIRECT INVESTMENT AND ECONOMIC OUTPUT IN PAKISTAN. Sajid Rahman Khattak Muhammad Ali Jinnah University, Pakistan Nadeem Iqbal Faculty of Business Administration BZU Sub Campus, Dera Ghazi Khan, Pakistan Muhammad Arif Khattak Muhammad Ali Jinnah University, Islamabad,Pakistan Abdul Qadeer Muhammad Ali Jinnah University, Islamabad,Pakistan Abstract This paper examines cointegration and causal relationship for both short and long run between foreign direct investment and economic output in Pakistan from the period 1972 to 2008. For data analysis the study use various econometrics model such as Augmented Dickey Fuller test, Enger-Granger two step cointegration test, Granger Causality test, Vector Error Correction Model (VECM). The results indicates that there is a short as well as long run relationship found between foreign direct investment and gross domestic product growth rate. The results also indicate that there is Uni-directional relationship (not Bi-directional) between foreign direct investment and gross domestic product in Pakistan which means FDI caused economic output in Pakistan. Keywords: Foreign direct investment, economic output, gross domestic product, ADF, Enger-Granger two step cointegration, GC, VECM. 1. Introduction Present day world is considered a global village. Due to technological advancement one can move around the world within a few hours or days also can handle and manage their business operations across their country boundaries. Countries become boundary less due to COPY RIGHT 2012 Institute of Interdisciplinary Business Research 854

fast technological advancement. Such situation motivates investors to increase their investment in different countries and to reach their products throughout the world. Multinational companies (MNEs) want to operate in one are more countries for the purpose to boost their sales as well income. Operating MNEs in the host countries can have several advantages to the host country as well such as, unemployment rate are decrease, new technology are come to the country, knowledge and skills sharing between foreign and host country employees, competition becomes tense because the local firms tries to beat the market and get competitive advantages which also led to reduce their prices to reasonable level (compared to monopoly or oligopoly). Foreign direct investment (FDI) is generally considered to be an instrument of cash and non-cash inflow into the host country from overseas. According to World Trade Organization (WTO) FDI occurs when an investors based in one country acquires an assets in another country with this intention to manage that assets as well is called foreign direct investment. FDI plays an essential role in the economic development of the countries especially in developing countries like Pakistan. The concept economic globalization allows investors to produce or sells their products across different countries; this gives us an imperative ingredient in the form of FDI. Private capital flow in the form of FDI is one dazzling feature of the present day world. Both developed and developing countries tries to attract multinational corporations to come and operate in their country. In the perspective of new theory of economic growth FDI is considered as an engine of economic growth. FDI Inflows to South Asian Countries FDI inflows increased speedily in developing countries especially In South Asia in 1980s. The drift in FDI inflows is different for each South Asian countries depends on their COPY RIGHT 2012 Institute of Interdisciplinary Business Research 855

respective government policies. FDI inflows were $0.83 billion in 1980 to 1984, and the growth was measured 5.34 % annually (Mortaza et al. 2007). According to ABD (2007) FDI inflows to South Asian countries was about $24.3 billion which is 132.9% higher than 2005. According to Mortaza et al. (2007) the most favorable destination for FDI is Pakistan and India followed by Sri Lanka and Bangladesh. FDI in Pakistan After its creation in 1947, the average economic growth rate of Pakistan was higher than the world economic growth rate. Pakistan achieved much admires to its economic progression in 1960s, because Pakistan was considered a model for economic development in the world. Unfortunately, in 1990s economy growth becomes slowdown due to hasty economic policies, economic mismanagement, and a huge amount of public debt. To compete globally Pakistan changed their economic policy by adopting market based economic policy. The government provides fair trade policy, fiscal incentives, and tariff facilities to foreign investors to make attractive investments region in the world. FDI inflow increased significantly in Pakistan in energy, telecommunication and agriculture sectors. Decline FDI in Pakistan Government of Pakistan stated three reasons for the slow performance of the various sectors these are global financial crisis, security situation and flood situation in Pakistan. The table and graph shows that FDI level increases in 2001-2002 and 2007-2008 so the above stated reasons are solely not responsible for decline in FDI. The actual reasons for FDI decline are, government did not give proper attention to economic growth, energy and gas crisis in Pakistan, and the government faulty and arrogant approach to international investors led to COPY RIGHT 2012 Institute of Interdisciplinary Business Research 856

decrease FDI inflow in Pakistan. Table 1 and 2 shows FDI inflows and outflows from 1972-2008 respectively. Table 1 Foreign direct investment, net inflows (% of GDP) Year Value Year Value Year Value 1976 0.06 1988 0.48 2000 0.42 1977 0.10 1989 0.52 2001 0.53 1978 0.18 1990 0.61 2002 1.14 1979 0.30 1991 0.57 2003 0.64 1980 0.27 1992 0.69 2004 1.14 1981 0.38 1993 0.68 2005 2.01 1982 0.21 1994 0.81 2006 3.35 1983 0.10 1995 1.19 2007 3.90 1984 0.18 1996 1.46 2008 3.32 1985 0.42 1997 1.15 1986 0.33 1998 0.81 1987 0.39 1999 0.84 Table 2 Foreign direct investment, net outflows (% of GDP) Year Value Year Value Year Value 1976 0.000 1988 0.033 2000 0.015 1977 0.000 1989 0.107 2001 0.043 1978 0.000 1990 0.005 2002 0.039 1979 0.000 1991-0.008 2003 0.023 1980 0.000 1992-0.024 2004 0.057 1981 0.000 1993-0.004 2005 0.040 1982 0.000 1994 0.002 2006 0.085 1983 0.000 1995 0.001 2007 0.068 1984-0.015 1996 0.011 2008 0.030 1985-0.025 1997-0.039 1986-0.002 1998 0.080 1987 0.058 1999 0.033 COPY RIGHT 2012 Institute of Interdisciplinary Business Research 857

Figure 1 Graphical representation of FDI Flow in Pakistan The above graph show the FDI flow in Pakistan from 2002 to 2011. If we see it FDI inflow in the start from 2002 to 2005 are increasing with slow growth but in 2007 and 2008 FDI increased so much and cross the limit of $16 billion, after that the flow start decreasing from 2009 to 2011 to the amount $6 billion. The main reasons of this decreased are investment environment in the country (which is not so good) and GDP growth rate of the country (although GDP of the country increasing but the problem of electricity and gas shortage can decrease the investors confidence to invests in Pakistan). COPY RIGHT 2012 Institute of Interdisciplinary Business Research 858

The remaining paper are divided into four section; section two describe literature review, section three discuss methodology of the study, section four discuss results of the study, and section five conclude the paper. 2. Literature Review Agarwal (2000) investigated the economic impact of FDI in South Asia by understanding time series, cross section analysis of panel data from five countries including Pakistan, India, Sri Lanka, Nepal and Bangladesh. The study argues that, FDI impact GDP growth rate from negative to positive and to strongly positive. There is a negative impact of FDI inflow on GDP growth rate in 1980, while in early eighties a positive impact were shown, and strongly positive relations were shown between FDI inflows and GDP growth rate. Import substitution policies were followed by most South Asian countries which had also high import tariffs in the 1960s and 1970s. These policies gradually changed with the passage of time, and mostly the countries adopted market oriented policies. Growth impact of FDI tends to be greater under in export promotion trade regime compared to an import substitution regime. Regale and Chakraborty (2002) investigated long run and short run effects of FDI. They selected 23 countries for their studies. They found that, there was a long run co integration relationship exists between FDI and GDP for all 23 countries. Further, they stated that, bidirectional economic causality were exist between FDI and GDP in closed economy countries for short run, and for long run uni-directional causality exists between FDI and GDP in closed economy countries. COPY RIGHT 2012 Institute of Interdisciplinary Business Research 859

Sahoo (2005) explored the impact of FDI on manufacturing sectors in India. The study found that there is direct impact of FDI inflow in electronics, chemical, and electrical, while there is indirect impact of FDI inflow in drugs and pharmaceutical sectors. They also argues that FDI is an important vehicle for transforming technology, skills, knowledge and it have long run effect on growth. Wang (2002) explored the relationship between FDI and economic growth and found a significant relationship between them. Liv and Sincilair (2002) found the long run relationship between FDI, economic growth, and trade in China. They found that bidirectional causal relationship among FDI growth and export. Besides there positive relationship some study also found negative relationship between FDI and GDP as well such as, Levine (2002) studied the impact of FDI and GDP growth rate and found no significant positive impact between FDI and GDP growth rate. Brecher and Alejandro (1977) found negative relationship between FDI and GDP growth. They stated that foreign capital can lower economic growth by earning excessive profits in the country with the severe trade distortion such as high tariff. 3. Methodology of the study The study examines cointegration relationship both long run and short run between foreign direct investment (FDI) and gross domestic product (GDP) in Pakistan. The study use FDI as an independent variable and GDP as a dependent variable, their log form LFDI and LGDP also taken. Data were taken from 1972 to 2008 from World Bank website. The study use Augmented Dickey Fuller (ADF) test, Engle Granger cointegration test, and Granger causality test to establish cointegration and causal relationship between FDI and GDP. COPY RIGHT 2012 Institute of Interdisciplinary Business Research 860

3.1 Augmented Dickey Fuller (ADF) test ADF test is applied to check whether data are stationary at level or at first difference. The test consist the following two regressions: Y t = α + x t β + ϵ t 1 Where x and y are variables and ϵ t is the error term. The test is performed under null of nonstationarity. ΔY t = β o + β 1 t + δy t-1 + α m i=1 ΔY t-1 + ϵ t.. 2 Where Y t indicate variables GDP and FDI, Δ is the changes or difference operator, t = time, L = lags number, ϵt is error term, β o, β 1, δ is constant variance, and ΔY t-1 is the difference between ΔY t-1 - ΔY t-2. The null hypothesis can be rejected i.e. the series is stationarity if t- stat value is negatively less than the critical values at 1%, 5%, and 10% significant level respectively. 3.2 Engle Granger cointegration test This test is used to check long run and short run equilibrium relationship between the FDI and GDP. The following two equations are used for both long run and short run relationship. For long run relationship LGDP = α + δlfdi t + ϵ t 3 From the above equation we collected the residual values (ϵ t ), and then used this data of ϵ t and applying stationarity test to identify integrated order. Variables are cointegrated i.e. long run relationship exist, if the integrated order of ϵ t is less than the integrated order of linear combination of the variables of I (1). COPY RIGHT 2012 Institute of Interdisciplinary Business Research 861

For short run relationship ΔLGDP t = c + p i=1δδlfdi t-1 + μ t ECM t-1 + ϵ t 4 Where ΔLGDP t-1 is the first difference, c is constant coefficient, ΔLFDI t-1 is the first difference, and ECM is error correction mechanism term. 3.3 Granger Causality test This test is used to check causal relationship between these two variables GDP and FDI, and where the relationships between them are uni-directional or bi-directional. According to this approach, assume Y (GDP) indicates economic growth caused by another variable X (FDI), and we assumed that Y can be better from the past values of Y and X than from the past values of Y alone. Through VAR model we test these hypotheses: LGDP = n i=1 α i LFDI t-1 + n i=1 β j LGDP t-j + ϵ 1t.5 LFDI = n i=1 λ i LFDI t-1 + n i=1 β 2j LGDP t-j + ϵ 2t.6 Where LGDP and LFDI denotes log values of gross domestic product and foreign direct investment. We assumed that distribution of ϵ 1t and ϵ 2t are uncorrelated. Equation (5) states that current LGDP is related to the past values of itself as well as that of FDI and Equation (6) states that current LFDI is related to the past values of itself as well as that of GDP. 4. Empirical Results The results show that, ADF statistics values of LGDP in the level with intercept and trend & intercept (-0.3895 and -1.923 respectively) are greater than the critical values at 1%, 5%, and 10% significance level. So the null hypothesis cannot be rejected. This means that in the level LGDP is a unit root problem. Table 3 also demonstrates that, ADF test statistics values (-8.203 and -8.445) are smaller than the critical values of both intercept and intercept and COPY RIGHT 2012 Institute of Interdisciplinary Business Research 862

trend at significant levels when LGDP is tested with first difference. The result shows that LGDP has not any unit root problem so the null hypothesis can be rejected. On the other hand ADF test statistics LFDI values is higher than the critical values at the same significance level in both intercept and intercept and intercept and trend. This results show that null hypothesis cannot be rejected and the series is not stationary. Although at 1 st difference the values of ADF test statistic is less than critical values. Table 5 shows that ADF test statistics value is -4.5584, -3.5402 in first stage estimation which is smaller than critical values at 1%, 5%, and 10% respectively. This results shows that Residual series is stationary which prove that both FDI and GDP are cointegrated that there is a long run equilibrium relationship exists between FDI and GDP. Table 6 shows the results of short run relationship between FDI and GDP. The ECM t-1 values is negative but significant (ECM t-1 used as Res). The results in table 6 show that 25.39% disequilibrium in the short run and deviates with long run each year. The adjusted coefficient values of ΔLFDIt -1 and t-stat is significant at P- values. These results shows that there is short run as well as long run relationship exist between FDI and GDP. Table 7 shows granger causality results and found that F-Stat value is too higher at 5% significant level which indicates that GDP does not Grander Cause FDI in Pakistan. This also shows that there is Uni-directional relationship exist between GDP and FDI. This result is similar with (Lan, 2006; Aqeel and Nishat, 2005; Athukorala, 2003; Sekman, 2007). COPY RIGHT 2012 Institute of Interdisciplinary Business Research 863

5. Conclusion There are lot of research exists to find the relationship between foreign direct investment and economic growth, some study found significant positive relationship while some also found negative relation as well. The purpose of this study is to investigate the relationship between foreign direct investment (FDI) and economic growth or gross domestic product (GDP) in Pakistan from 1972 to 2008. To check this relationship various tests are applied i.e. ADF test to check the stationarity, VECM, Enger Granger Causality test. We found that there is a long run as well as short run causal relationship exists between FDI and GDP. We also found that there is no granger causality from GDP to FDI, which shows that there is Uni-directional relationship found between FDI and GDP in Pakistan. It means that there is a direct relationship of foreign direct investment and economic growth in Pakistan. So it is good for Pakistani economy to attract more and more FDI to strong their economy. The government of Pakistan takes necessary actions and changes those rules which create a problem for foreign investors to invest in Pakistan in such a way that they invest without any hesitations. This can also lead economy from all sides i.e. knowledge and skills sharing, management skills, reduce unemployment, increase in per capita income, competitive environment etc. COPY RIGHT 2012 Institute of Interdisciplinary Business Research 864

References [1] Agarwal, Pradeep (2000), Policy Regime and Industrial Competitiveness: A Comparative Study of South Asia and India, Macmillan, UK. [2] Alguacil, M. T. and V. Orts (2002), A Multivariate Cointegrated Model Testing for Temporal Causality between Exports and Outward Foreign Investment: The Spanish case, Applied Economics, 34,119-32. [3] Alguacil, M. T. A. Cuadros and V. Orts (2002), Foreign Direct Investment, Exports and Domestic Performance in Mexico: A Causality Analysis, Economic Letters, 77, 371-76. [4] Bende-Nabendem, L. Ford, B. Santoso and S. Sen (2003), The Interaction between FDI, Output and the Spillover Variables: Cointegration and VAR Analysis for APEC, 1965-1999, Applied Economics Letters, 10, 165-72. [5] Baharumshah, A.Z. and M. A.M Thanoon (2006), Foreign capital flows and economic growth in East Asian countries, China Economic Review, 17, 70-83. [6] Balasubrament, V. N., M. Salisu and D. Sapsford (1996), Foreign Direct Investment and Growth in EP and IS Countries, Economic Journal, 106: 92-105. [7] Hsiao, and Hsiao, M. C. W. (2006), FDI, exports, and GDP in east and southeast Asia- Panel data versus time series causality analysis, Journal of Asian Economics, 17(2006): 1082-1106. [8] Jaya Gupta (2007), Globalization and Indian Economy: Sector-wise Analysis of FDI inflows. [9] Jayashree Bose (2007), FDI inflows in India and China-A Sectoral Experiences, ICFAI University Press, Hyderabad. COPY RIGHT 2012 Institute of Interdisciplinary Business Research 865

[10] Carkovic and Levine (2002), Does foreign direct investment accelerate economic growth? [11] Chakraborty, C. and P. Basu (2002), Foreign Direct Investment and growth in India: a cointegration approach, Applied Economics, 34, 1061-73. [12] Zhang, K.H (2005), How does FDI affect a host country s export performance? The case of China, China Economic Review, 11, 385-396. [13] Muhammad Shahbaz and Naveed Aamir (2008), Direct Foreign Investment and Income Distribution: A Case Study of Pakistan, International Journal of Finance and Economics. COPY RIGHT 2012 Institute of Interdisciplinary Business Research 866

Annexure Table 3 ADF test for FDI and GDP Variables Level/ 1 st difference Augmented Dickey Fuller Statistics (ADF) test With Intercept With trend and Intercept t-statistics t-statistics 1% 5% 10% 1% 5% 10% LGDP Level -0.389534-3.6268-2.9458-2.6115-1.9193-4.2349-3.5403-3.2024 1 st Difference -8.202848-3.6329-2.9484-2.6128-8.4363-4.2436-3.5442-3.2046 LFDI Level -0.495709-3.6267-2.9458-2.6115-3.5228-4.2349-3.5403-3.2024 1 st Difference -8.116388-3.6329-2.9484-2.6128-7.9342-4.2436-3.5442-3.2046 Table 4 Long run relationship between FDI and GDP Dependent Variable: LGDP, Model: Least Squares, Sample: 1972-2008, Included observation: 37 Coefficient Std. Error t-statistic Prob. Constant (C) 8.4325 0.1034 81.5432 0 LFDI 0.4160 0.01889 22.0121 0 R-squared 0.9335 Mean dependent var 10.577 Adjusted R-squared 0.9307 S. D. dependent var 0.8015 S.E of regression 0.21099 Akaike info criterion -0.2215 Sum squared resid 1.5581 Schwarz criterion -0.1344 Log likelihood 6.0972 Hannan-Quinn criter. -0.1908 F-statistic 484.5354 Durbin-Watson stat 1.2481 Pro(F-statistic) 0 Table 5 ADF test saved for residual Series ADF t statistics Test Critical Values with Trend & Intercept 1% 5% 10% Res (saved as residual) -4.5494-4.2349-3.5403-3.2024 The long run OLS models is LGDP = 8.4325 + 0.4160*LFDI COPY RIGHT 2012 Institute of Interdisciplinary Business Research 867

Table 6 Short run Relationship between FDI and GDP Dependent Variable: DLGDP, Model: Least Squares, Sample: (adjusted) 1972-2008, Included observations: 37 after adjustment Coefficient Std. Error t-statistic Prob. Constant (C) 0.10307 0.0135 7.5936 0 DLFDI(-1) -0.03665 0.0237-1.5425 0.1327 RES(-1) -0.2539 0.0747-3.3956 0.0018** R-squared 0.2650 Mean dependent var 0.0937 Adjusted R-squared 0.2190 S. D. dependent var 0.0858 S.E of regression 0.0758 Akaike info criterion -2.2391 Sum squared resid.1839 Schwarz criterion -2.1057 Table 7 Granger Causality test Null hypothesis Observations F-Stat Probability DLGDP does not Granger Cause with DLFDI 33 0.2798 0.8485 DLFDI does not Granger Cause with DLGDP 33 4.6455 0.0099 COPY RIGHT 2012 Institute of Interdisciplinary Business Research 868