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INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS
JUNE 2011
VOL 3, NO 2
3.2. Variable description
One multiple and one simple regression model is used in the study for analysis. In multiple
regression model one dependent and five independent variables are used for analysis. Dependent
variable is FDI which is calculated as foreign direct investment inflows in Pakistan. Independent
variables are GDP growth rate, physical infrastructure, inflation, average annual exchange rate of
rupee and total trade. The proxy of infrastructure used in the study is length of low type and high
type road network in Pakistan, total trade is calculated as addition of imports plus exports and
other variables are named by their proxies. In simple regression model one dependent and one
independent variable are present. FDI is regressed on stock market capitalization to find out the
relationship present between these two variables.
3.3. Model one:
FDIt= α + β 1
GDPGR+ β 2
PI+ β 3
INF+ β 4
EX+ β 5
TT + Ut
FDI= Foreign Direct investment
GDPGR= GDP growth rate
PI= Physical infrastructure
INF= Inflation
EX= Average annual exchange rate as rupee/$
TT= Total trade
Ut= Error term capturing left over effects
3.4. Model Two:
FDIt= α + β 1
GMCAP + Ut
Where
MCAP= market capitalization
4. Results and Analysis
Table 6.1
Model Summary
Model R R Square
Adjusted R
Square
Std. Error of
the Estimate
1 .977 a .955 .943 366.09673
a. Predictors: (Constant), Physical Infrastructure, Inflation %,
GDP growth rate %, Total Trade, Exchange Rate (Rs)
Table 6.1.1
ANOVA a
Model
1
Sum of
Squares Df Mean Square F Sig.
Regression 5.360E7 5 1.072E7 79.981 .000 a
Residual 2546509.439 19 134026.813
Total 5.614E7 24
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