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Determinants Of Foreign Direct Investment In Pakistan

CHAPTER 1:

INTRODUCTION

Overview

Globalization which gave birth to the concept of interdependence of countries and their economies is defined as the process through which regional economies, societies, and cultures have become integrated with the assistance of global network of trade, communication and transportation. This allowed the investors to invest or transfer their capital where ever they wanted which introduced the concept of Foreign Direct Investment.

Issues:

Since the recent financial crisis in Asia and Latin America, developing as well as newly industrialized countries have been advised to rely mainly on FDI for economic development and to supplement national savings by capital inflows. Developing countries in particular are in need of investment for their development and the investment amount in majority of cases is greater than the capital internally available. Therefore, FDI has emerged as most important source of generating capital required for development of emerging countries. Currently Foreign Direct Investment has become one of the major sources of economic development, modernization, employment, income growth, capital generation and a channel for the transfer and access to advance technologies as well as organizational and managerial skills. Recognizing this fact, developing countries try their level best to attract as much as of FDI as they can. But attracting FDI is not that much simple, it requires huge efforts on the part of policy makers and government. Variety of factors is considered by an investor before making investment in a particular country. Those are labeled as determinants of FDI, and may vary from country to country. Pakistan is currently facing a huge shortfall of capital to finance its major development projects and to run the government operations smoothly. The country requires capital to fulfill the growing needs in defense, infrastructure, education and many other areas of critical importance to development.

1.2 Problem statement

The objective of this research is to identify the major determinants of the aggregate Inward FDI flow to Pakistan.

1.3 Hypothesis

The research primarily focused on testing the following mentioned hypothesis:

H1: Wage has negative impact on FDI.

H2: GDP has positive impact on FDI.

H3: Infrastructure expenditure has positive impact on FDI.

H4: Taxes has negative impact on FDI.

H5: Inflation has negative impact on FDI.

H6: GDP per capita growth has positive impact on FDI.

H7: Exchange rate has positive impact on FDI.

H8: Interest rate has negative impact on FDI.

1.4 Outline of the Study

1.5 Definitions

Users:

This research will be useful for the national policymakers and government of Pakistan; it will allow them to improve the weak points present in the economy which discourage the FDI inflows to the country.

CHAPTER 2:

LITERATURE REVIEW

A lot of research has already been conducted in the field of identifying the best determinants of Foreign Direct Investment by various researchers. Most of the research work conducted implies that the determinants of Foreign Direct Investment vary from country to country and from location to location. The purpose of this research is to find out the impact of Labor cost (Wage), Inflation (I),Interest rate (IR), Exchange rate (ER), Infrastructure expenditure (IE), Taxes (T), GDP and GDP per capita growth (GDPG) on Foreign Direct Investment (FDI) inflow in Pakistan. The study hypothesizes positive relationship between GDP, GDP per capita growth, Infrastructure expenditure and Exchange rate with FDI whereas Wage, inflation, Taxes and Interest rate relate negatively with FDI.

Pursuing the same objectives Kok and Ersoy (2009) conducted study that made attempt to investigate the best determinants of FDI in developing countries. Study hypothesized and concluded that GDP, inflation, Trade, Gross capital formation, GDP per capita growth and communication (telephone) are positively related with FDI whereas inflation and total debt/ GDP had negative relationship. Barrel and Pain (1996) in their empirical studies found that FDI and both the acceleration and level of GNP were positively related. In addition unit labor cost and relative capital cost also had positive relationship with outward direct investment. Barrel and Pain et al suggest that in short run funds availability affects investment timing. This research is very much related to mine because it tried to identify the role played by demand and relative factor prices, both at home and abroad, and exchange rate expectations in determining the total level of foreign direct investment (FDI) by United States companies. According to Janeba (2002) investment costs and government credibility has significant impact on the level of inward foreign direct investment, suggesting that MNCs would prefer to invest in politically stable countries. The research also concluded that when any politically unstable country has cost advantage over other countries MNC will invest efficient amount in that particular country and will hold excess capacity elsewhere. According to the Conventional wisdom lack of government commitment deters foreign investment in developing countries. Since countries differ in production costs and government credibility, this article explains the pattern of investment in a politically risky world. The research work done by Harvey (1990) focused on the macroeconomic determinants of FDI in addition to variables relating to different industry groups and tries to identify the impact of these variables on the inward FDI flow of the recipient country and suggested that Exchange rate and Sales to have significant impact on the foreign direct investment, whereas taxes did not have any significant role in explaining foreign direct investment.

Following bit different framework research conducted by Rolfe, Ricks, Pointer and McCarthy (1993) made an attempt to check investors’ investment decision on the basis of various investment incentives provided by countries in the Caribbean region. The study demonstrates that all inducements do not evenly plea to all investors. The investment characteristics would determine which incentives firm manager will prefer. According to the study incentives preferred by export firms differ from local market-oriented firms, firms starting operations in a new country have different incentive preferences than do firms interested in expanding or acquiring existing operations, incentive preferences sometimes differ by country of investment, incentives differ depending upon the products produced, large investors prefer different incentives than those preferred by smaller firms and incentive preferences can differ from year to year. In short the research concluded that incentive preferences are a function of the type of investment, the countries involved, the market orientation of the investor, the type of product, the size of the investment, and the investment year.

Terpstra and Yu (1988) tried to examine the impact of firm-specific advantages and locational factors on the foreign investment made by advertising agencies of U.S study focused on impact of host country market size, host country geographic proximity, firm size, firm's international operations experience, oligopolistic reaction, and presence of home country customers abroad on FDI. The research depicted that U.S. advertising agencies prefer to invest in those foreign countries having large market size, did not discriminated countries on the basis of their geographic location, inclined to enter foreign market with bigger firm size, tended international expansion with increasing understanding of international operations, reacted oligopolistically while making foreign investment and followed client firms belonging to home country while going abroad. Additionally research found that oligopolistic reaction had stronger impact in 1984 compared to 1972, intensity of competition had significant impact on oligopolistic reaction and top agencies witnessed stronger impact of oligopolistic reaction.

Study uses macroeconomic variables but more emphasis was given to various ratios relating to capital and labor, it also used “The Heckscher-Ohlin Theory? which states that a country exports those commodities that intensively use the country's relatively abundant factors and imports those goods using its scarce factors intensively. Results indicated that countries like U.S. imported goods whose production required higher capital to labor ratio than the goods exported and when the endowment ratio of capital/labor increased the ratio of capital for each worker in import-competing production to capital for each worker in export production declined (Baldwin 1979). Gopinath and Echeverria (2004) examined the relationship between foreign direct investment (FDI) and trade in a bilateral context, that is, home (source) country's exports and FDI to a host (recipient) country are analyzed using a gravity-model approach. Results suggested that physical distance had negative impact on trade-FDI ratio, this caused nations to switch from export to FDI based manufacturing. Research also found GDP per capita to affect trade-FDI ratio positively and institutional quality strongly encouraged FDI, additionally FDI was also encouraged by regional trading agreements.

The empirical study conducted by Goldberg and Kolstad (1995) stated that exchange rate instability contributed to production internationalization without depressing economic activity in the home country. Furthermore, exchange rate instability stimulated the share of investment activity located on foreign country. Exchange rate volatility did not have statistically different effects on investment shares when one distinguishes between periods where real or monetary shocks dominate exchange rate activity.

Yin (1999) studied the effects of tax incentives on the structure of a domestic industry in terms of price, output, profit, and entry/exit, taking account of technology transfer through FDI. The study found that if the government of the host country provides more tax relief for foreign firms, it will raise total output and reduce price index which will encourage more foreign firms to enter the industry while certain existing host firms will have to exit. Research also suggested that government should be cautious in decreasing rate of taxes to attract FDI.

Vita and Kyaw (2008) used empirically tractable structural VAR model of the determinants of capital flows and variance decomposition and impulse response analyses to investigate the temporal dynamic effects of shocks to push and pull factors on foreign direct investment and portfolio flows. Study suggested that variation in real variables representing economic activity for example domestic productivity and foreign output possess more power in explaining variability in investment flows to developing nations. This research developed structural VAR model to test relative importance of the determinants of disaggregated investment flows to developing countries. The study investigated the degree to which deviations in foreign direct investment and portfolio flows are caused by variety of push and pull factors across different time horizons.

Chen, Chen and Ku (2004) analyzed the pattern of local linkages in foreign direct investment (FDI), treating such local linkages as an investment in local relationships research found that Taiwanese investors in the US are more active in the search of local linkages compared to counterparts in China and Southeast Asia. Research found investors in a producer-driven network are more active in building local linkages than their counterparts in a buyer-driven network. In addition large firms are more active than small firms in pursuing local linkages because of their larger capacity to absorb the risks involved in network integration and their ability to apply relational capital on a larger volume of exchanges. Entry mode also makes a difference to local linkage: FDI taking the form of a joint venture leads to more local linkages than FDI in the form of a wholly owned subsidiary. Amongst the various local linkages, employment of local workers is always the priority undertaking, followed by linkages to local suppliers, local subcontractors and local R&D capabilities.

Studying the impact of FDI on aspects of domestic economies, including international trade, gross fixed capital formation (GFCF), employment, productivity, the balance of payments and overall welfare Hejazi and Pauly (2003) found that FDI was motivated by market access and factor price differences, and on the role of intra-firm trade. According to the research prediction of whether growth in outward FDI will increase or decrease domestic GFCF is not possible. Therefore, comparisons of such growth relative to growth in inward FDI can be a misleading indicator for policy makers. Since the impact of FDI on domestic GFCF depends on the underlying motivation for investment, and not simply on the growth in outward relative to inward FDI, the results are of interest to all countries. The implication of results stated that rapid growth in outward FDI, relative to inward growth, should not be considered as a negative development, and may reflect success.

Chen (1996) suggested that potential for market share extension (MARKET) affects FDI, labor cost (WAGE) does not affect FDI, foreign investors seem to have taken advantage of the western region’s mineral and energy resource abundance regardless of its lower allocative efficiency, interregional railroad connections are important in the foreign investors’ locational choice and foreign investors may not locate near innovative domestic Chinese industries in the eastern and middle regions. The significance of the results obtained is that, the location of FDI seems to have been influenced by the existence of good transportation linkages, technological filtering and, to some extent, by the potential for market-share extension. Locational choice does not seem to have been influenced by consideration of labour cost differences or differences in allocative efficiency.

According to the neoclassical growth model, labor growth and technological progress are considered as exogenous, inward Foreign Direct Investment(FDI) will lead to increase in the investment rate and which will ultimately lead to increase in the growth of per capita income but the growth effect will not last in the long run (Hsiao and Hsiao, 2006).

Papanek (1973) showed significant negative impacts of different types of capital on national savings. Grounded on a sample of 85emerging countries, Papanek found that foreign capital displaced domestic savings. Precisely, the research exhibited that foreign aid, private investment and other capital crowded out national savings, and a reduction in domestic savings could lead to further increase on the dependency on foreign capital.

The empirical studies of Cushman (1985) based U.S. bilateral FDI outflow and inflow data concluded that exchange rate variability had positive relation with set of flows.

Connor (1983) conducted research which focused on inward as well as outward flow of FDI. The study divided country specific advantages into three categories FDI Probability, FDI Propensity and FDI Penetration and their impact on FDI. Larudee and Koechlin (1999) research focuses on the wages or labor costs and productivity in terms of production costs as the determinants of FDI. This research uses "sweatshop labor argument" which relies implicitly on the simplistic trade theory assumption that all firms in a country have access to the same technology. But both MNE theory and abundant evidence assert the contrary: an MNE affiliate derives its labor productivity in significant measure from the firm-specific advantages it brings with it. The differential between source and host country in average manufacturing wage should therefore be an independent determinant of FDI flows.

CHAPTER 3:

PROPOSED METHODOLOGY

3.1 Method of Data Collection

The secondary data necessarily required to perform the research was gathered from the official sites of The World Bank and The State Bank of Pakistan. Additionally, some of the required data was abstracted from the book Statistical Supplement and Yearly Book both being published under the supervision of State Bank of Pakistan.

3.2 Sample Size

The data used for the purpose of research was 30 years annual data of the variables used in research. Data of all the variables belonged to period starting from fiscal year 1980 to fiscal year 2010.

3.4 Research Model developed

FDI= α + β0GDP + β1GDPG – β2Wage- β3I + β4ER + β5IE – β6T – β7IR + µ

Where

FDI = Net amount of Foreign Direct Investment received by Pakistan

Wage = Annual wages paid to a worker, I = Inflation, IR = Interest rate, ER = Exchange rate (ER), IE = Infrastructure expenditure, T = Taxes, GDP, GDPG = GDP per capita growth rate.

3.3 Statistical Technique

Multiple Regression was the statistical technique which was applied to test the hypothesis developed in research. This technique was applied because both the dependent variable and independent variables were scale and under this situation the prediction power of regression analysis is stronger as compared with the other statistical techniques available.

CHAPTER 4: RESULTS

4.1 Findings and Interpretation of the results

The results drawn by applying Multiple Regression analysis were as follows:

Table: 4.1 ANOVA

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

2.524E39

4

6.310E38

1426.142

.000a

Residual

1.106E37

25

4.424E35

Total

2.535E39

29

The Anova table explains the model fit, the F-test is statistically significant, which means that the model is statistically significant, as the sig. value in the Anova table is less than .05 therefore the model fit is good and regression can be applied on the data.

Table: 4.2 Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

Durbin-Watson

1

.998a

.996

.995

6.65146E17

2.744

The model summary table explains what amount of variance in the dependent variable is explained by the independent variables. The value of R-square is .996 which means that approximately 99.6 % of the variance of SQDFDI is accounted for by the model and only .04 % of the variance remains unexplained. Independent variables were square of Infrastructure Expenditure (PSDP Fund), Interest Rate (IR), Inflation (I) and Exchange Rate (ER) and the dependent variable was Square of Net Foreign Direct Investment (SQDFDI).

Table: 4.3 Coefficients

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

Collinearity Statistics

B

Std. Error

Beta

Tolerance

VIF

1

(Constant)

-9.595E17

7.703E17

-1.246

.224

Inflation

-8.806E16

3.960E16

-.037

-2.224

.035

.640

1.562

Interest Rate

2.047E17

6.261E16

.045

3.270

.003

.920

1.086

Exchange rate

-5.646E16

9.021E15

-.125

-6.259

.000

.440

2.273

IE

1.654E8

3349513.619

1.094

49.392

.000

.356

2.809

The co-efficients table shows the significance of individual independent variable in explaining the dependent variable. In the final model square of Infrastructure Expenditure (PSDP Fund), Interest Rate (IR), Inflation (I) and Exchange Rate (ER) were the statistically significant variables. The effect of Inflation (b= -8.806, p=.035) is significant and its coefficient is negative indicating that the greater the inflation rate, the lower the Foreign Direct Investment. The value of beta indicates that 1 unit increase in inflation will decrease FDI by 8.806 units. Similarly, the effect of Interest Rate (b= 2.047, p=.003) is significant and its coefficient is positive indicating that the greater the value of interest rate, the higher the amount of FDI received. The value of beta indicates that 1 unit increase in interest rate will increase FDI by 2.047 units. Next, the effect of Exchange Rate (b= -5.646, p=.000) is significant and its coefficient is negative indicating that the greater the exchange rate, the lower the amount of FDI. The value of beta indicates that 1 unit increase in exchange rate will decrease FDI by 5.646 units. Finally, the effect of Infrastructure Expenditure (b= 1.654, p=.000) is significant and its coefficient is positive indicating that the greater the amount spent by government on infrastructure, the higher the amount of FDI the country will receive. The value of beta indicates that 1 unit increase in amount of infrastructure expenditure will lead to an increase of 1.654 units in FDI.

Empirical Model Developed

FDI = 1.654 Infrastructure Expenditure + 2.047 Interest Rate - 5.646 Exchange Rate - 8.806 Inflation

4.2 Hypothesis Assessment Summary

H. #

Hypothesis

β

Sig.

Result

H1

Wage has negative impact on FDI

---

---

Nil

H2

GDP has positive impact on FDI

H3

Infrastructure expenditure has positive impact on FDI

1.654

.000

Accept

H4

Taxes has negative impact on FDI

H5

Inflation has negative impact on FDI

-8.806

.035

Accept

H6

GDP per capita growth has positive impact on FDI

H7

Exchange rate has positive impact on FDI

-5.646

.000

Reject

H8

Interest rate has negative impact on FDI

2.04

.003

Reject

CHAPTER 5: DISCUSSION, CONCLUSION, IMPLICATIONS AND FUTURE RESEARCH

5.1 Conclusion

Foreign direct invest being the most important factor in the development of developing countries likewise Pakistan. From recent years there has been great fight going on among LDC’s from all over the world to attract higher amount of FDI to fuel their economic growth. This research was intended to find out the impact of macroeconomic variables including GDP, GDP per capita growth rate, Interest rate, Inflation rate, Wage rate, Exchange rate, Tax rate and Infrastructure expenditure (PSDP fund) on the inflow of Foreign Direct Investment in Pakistan. The relationship between wage rate (W) and FDI could not be established because insufficient data was available on the annual wage rate in the country. GDP, GDP per capita growth rate and Tax rate were statistically insignificant in contributing in the final model. The most significant variables in the model were Inflation rate and Exchange rate; both had negative relation with FDI inflow having beta of -8.806 and -5.646 respectively. Interest rate and Infrastructure expenditure (PSDP fund) were positively related with FDI inflow having beta of 2.047 and 1.654 respectively.

5.2 Discussion

5.3 Implications and Recommendations

5.4 Future Research

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