2.  The UNCTAD summit shed light on the fact that discussing the
commitment of the G20 countries towards open trade and
investment regimes, expanding markets and resisting
protectionism in all its forms.
 Following the UNCTAD summit in June 2012, a big set of reforms
in FDI was announced by the Indian govt. in September 2012. As
per the reforms, 51% FDI in multi brand retail and 100% retail in
single brand retail was announced. Also 49% foreign investment in
aviation sector was announced. The cap for FDI was raised from
49% to 74% in broadcasting too.
 These developments led us to research as to why a country wants
to induce FDI and what are the factors that induce FDI in any
economy.

3.  Foreign direct investment are the net inflows of investment to
acquire a lasting management interest (10 percent or more of
voting stock) in an enterprise operating in an economy other
than that of the investor.
 It is the sum of equity capital, reinvestment of earnings, other
long-term capital, and short-term capital as shown in the
balance of payments.
 There is ample evidence that FDI is a key ingredient to
sustainable economic growth. Going far beyond simple
financing, FDI is instrumental in the rapid and efficient cross-
border transfer and adoption of best practice

4.  FDI has an important impact on country’s trade balance, increasing
labour standards and skills, transfer of technology, skills and the
general business climate.
 FDI also provides an opportunity for technological transfer and up
gradation, access to global managerial skills and practices ,optimal
utilization of human capabilities and natural resources, making
industry internationally competitive,opening up export
markets,access to international quality goods and services and
augmenting employment opportunities.

5. Literature Review
 A lot of research and analysis of the factors affecting the FDI
have been done already. Not only has the research been done on the
developed nations but also on the developing countries.
 The main literature studied by us includes Analysis of Factors
Affecting Foreign Direct Investment in Developing Countries by
Bushra Yasmin, Aamrah Hussain and Muhammad Ali Chaudhary
and Cheng and Kwan (1999)
 As per the FDI confidence index of A.T. Kearney India has been
ranked 2nd showing the strong confidence of overseas investors in
India.

6.  A recent UNCTAD survey projected India as the second most
important FDI destination (after China) for transnational
corporations during 2010–2012.
 The sectors which attracted higher inflows were services,
telecommunication, construction activities and computer software
and hardware.
 Mauritius, Singapore, the US and the UK were among the leading
sources of FDI.

7.  In 2008-09, FDI stood at $27.3 billion.
 FDI in 2009-10 was $24.2 billion
 In 2010-11, FDI into India declined to $19.43 billion, a
significant decrease from both 2008 and 2009
 Foreign direct investment (FDI) in India may cross $35
billion in 2011-2012 as against $19.4 billion in the last
financial year

8. The objective of this study being conducted is:
 To study the trends and patterns of flow of FDI.
 To assess the determinants of FDI inflows.
 To evaluate the impact of FDI on the Indian
Economy.

9.  The study is based on secondary data.
 The required data has been collected from various sources
i.e. Asian Development Bank’s Reports, various Bulletins
of Reserve Bank of India, publications from Ministry of
Commerce, Govt. of India, Economic and Social Survey of
Asia and from websites of World Bank, IMF, WTO, RBI,
UNCTAD etc.

10. The study has been taken up with the following hypothesis:
 Flow of FDI shows a positive trend over the period 1990-2011.
 FDI has had a positive impact on economic growth of the country.
 The f actors that are effective for the study of trends in FDI are:
• Real GDP per capita
• Trade openness
• Extent of urbanization
• Investment on infrastructure
• Inflation

11. FACTORS AFFECTING FDI
1.Real GDP per capita: FDI is attracted in a country where there
is a huge market potential which is the product of no. of buyers
and their purchasing power which in turn is measured by the
real gdp per capita.
2.Trade openness: Countries with more open economic setup are
believed to be hot property among foreign investors. It is
measured by Taking the sum of imports and exports of a
country.
3.Extent of urbanization: Higher the urbanization higher the
attractiveness of a market.

12. FACTORS AFFECTING FDI (CONT)
4. Investment on infrastructure: FDI is mostly attracted in
a country with decent basic infrastructure as it saves a lot
of time. Expense and energies than those who will have to
develop infrastructure from scratch.
5.Inflation: FDI is affected by the price level changes in the
economy though there is no direct relationship between
the two but the purchasing power of buyers is affected by
inflation thus there purchase preferences

13. To analyse factors that affect the FDI inflows in a country, we have used
“Linear multiple regression model” for testing the hypothesis based on
time series analysis
H0: β =0
H1: β ≠0
Based on the factors stated in the previous section, we formulate the
following equation:
FDI= α + ß₁CGDP + ß₂OPEN + ß₃URB + ß₄INV + ß₅GDPD
With Time series 1980-2010

14. Where,
FDI: Foreign Direct Investment including equity capital, reinvestment of
earnings, other long-term capital, and short-term capital as shown in the balance of
payments (measured in current US$)
CGDP: Real Gross Domestic Product per Capita (constant 2000 US$)
OPEN: Trade openness constructed imports plus exports as percentage of GDP
URB: Extent of urbanization measured by urban population as percentage of total
population
INV: Investment done for infrastructural development (expressed as % of GDP)
GDPD: Inflation represented by GDP deflator (annual %)

15. For precise results hypothesis is been tested under 4 stages for
the following parameters:
 1. Testing the hypothesis about an individual partial
regression coefficient.
 2. Testing the overall significance of the estimated multiple
regression model, i.e. finding out if all the slope
coefficients are simultaneously equal to 0.
 3. Testing the model for the best fit.

16. We tested the hypothesis for the above said parameters and
the results were obtained as follows:
1. Real per capita GDP, trade openness and inflation are
positively related with the FDI inflows for the period
1990-2010.
2. Rate of urbanization and investment showed negative
association with FDI inflows for the same period.

17.  1. Results for urbanization and investment seem to be
incorrect logically and theoretically since they are
positively associated with stock of FDI.
 2. Inflation is believed to have an inverse impact on FDI
but the results demonstrate the reverse.
 3. Except urbanization, none of the factors are statistically
significant. This makes our model very weak.

18. The hypothesis tested in this case is:
H₀: All slope coefficients are simultaneously 0.
H₁: Not all slope coefficients are simultaneously 0.
 We test the overall significance of the model using the F-test
significance. The F-test significance value for this model is 3.724E-
06, which is way less than the value of (1-α) i.e. 0.05. Thus we reject
the null hypothesis and can say that our model is overall significant.
 Goodness of fit is measured by the adjusted R². The value of adjusted
R² is 0.826 or 82% which makes this a model of good fit.

19. As we can see that though the model is overall significant, there is no significant
relationship of individual factors with the dependent variable. We tried to analyse the
reason for such behaviour by finding the extent of multi-collinearity amongst the
variables. Following results were obtained:
 high level of correlation amongst the factors
 All of them move on almost one-on-one basis making the model dubious and
irrelevant
 But this problem is bound to happen on account of less number of degrees of
freedom and also because we were not using panel data.

20.  We tested the hypothesis for the above said parameters and the
results were obtained as follows:
1. Real per capita GDP, trade openness and inflation are
positively related with the FDI inflows for the period 1980-
2010.
2. Rate of urbanization and investment showed negative
association with FDI inflows for the same period

21.  1. Results for urbanization and investment continue to
be incorrect logically and theoretically.
 2. Inflation again demonstrates positive relationship
with FDI stocks.
 3. Except real per capita GDP and urbanization,
none of the factors are statistically significant. Thus our
model remains weak.

22. The hypothesis tested in this case is:
H₀: All slope coefficients are simultaneously 0
H₁: Not all slope coefficients are simultaneously 0
 We test the overall significance of the model using the F-test
significance. The F-test significance value for this model is
1.41256E-09, which is way less than the value of (1-α) i.e. 0.05. Thus
we reject the null hypothesis and can say that our model continues
to be overall significant.
 Goodness of fit is measured by the adjusted R². The value of adjusted
R² is 0.821 or 82% which makes this a model of good fit. In other
words, 82% variation in FDI stocks level is explained by variation in
the independent variables.

23. As we can see that though the model is overall significant, there is no
significant relationship of individual factors with the dependent variable. We
tried to analyze the reason for such behaviour by finding the extent of multi-
collinearity amongst the variables. Following results were obtained:
Even after increasing the degrees of freedom, the problem of multi collinearity
persists. In order to get more accurate we now shifted from absolute
figures to percentage figures. Though most of our variables are already in
percentage terms, we would alter our model a little bit to get more accurate
results.

24.  As increasing degrees of freedom hasn’t worked, we
altered our model a bit.
 We have now expressed the stock of FDI flows as a
percentage of annual GDP.
 The factors selected for the model remain same.
 The time span for the research has been kept as 1980-2010.

25. We tested the hypothesis for the above said parameters and
the results were obtained as follows:
1. trade openness and inflation are positively related with the
FDI inflows for the period 1980-2010.
2. Rate of urbanization ,investment and Real per capita GDP,
showed negative association with FDI inflows for the same
period

26.  1. When we revise the model in the above manner, only
trade openness emerges as significant factor in explaining
changes in FDI stocks.
 2. The reverse behaviour of urbanization, investment and
inflation continues and is unexplainable.
 3. No factor is individually is capable of explaining the
variations on its own.

27. The hypothesis tested in this case is:
H₀: All slope coefficients are simultaneously 0.
H₁: Not all slope coefficients are simultaneously 0.
 We test the overall significance of the model using the F-test
significance. The F-test significance value for this model is 5.86E-
09, which is again quite small as compared to the value of (1-α) i.e.
0.10. Thus we reject the null hypothesis and can say that our model
continues to be overall significant.
 Goodness of fit is measured by the adjusted R². The value of
adjusted R² is 0.79 or 79% which makes this a model of good fit. In
other words, 79% variation in FDI stocks level is collectively
explained by variation in the independent variables

28. Even on repetitive experiments we have been unable to
track the significant factors that affect the inflows of
FDI in a country. We made one last attempt by
converting the model to log-linear model. The
modified model is given in the next section.

29.  We tried various ways of finding significant factors
affecting FDI inflows in a country but couldn’t succeed so
far.
 Final attempt by converting observations to a log-linear
model
 Variables and methodology remains the same.

30. We tested the hypothesis for the above said
parameters and the results were obtained as follows:
 Trade openness and inflation are positively
related with the FDI inflows for the period 1980-
2010.
 Rate of urbanization ,investment and Real per
capita GDP, showed negative association with
FDI inflows for the same period

31. The hypothesis tested in this case is:
H₀: All slope coefficients are simultaneously 0
H₁: Not all slope coefficients are simultaneously 0
 We test the overall significance of the model using the F-test significance. The
F-test significance value for this model is 4.11687E-12, which is again quite
small as compared to the value of (1-α) i.e. 0.10. Thus we reject the null
hypothesis and can say that our model continues to be overall significant.
 Goodness of fit is measured by the adjusted R². The value of adjusted R² is
0.88 or 88% which makes this a model of good fit. In other words, 79%
variation in FDI stocks level is collectively explained by variation in the
independent variables.
 We are now in a position to draw final conclusions about our research.

32. 1. Repetitive experiments revealed that though the overall model for estimating
the factors responsible for inducing FDI stocks was significant; no factor could
individually explain the changes in dependent variables. In other words, there
are some additional factors at play which we may have omitted.
2. Subsequent hypothesis testing also revealed that real per capita GDP, trade
openness and urbanization had strong influence on the model.
3. Urbanization and investment level are believed to induce FDI i.e. they
have positive relationship with FDI. But in our hypothesis, they repeatedly
showed inverse relation with FDI.
4. It maybe because we used a substitute variable in case of investment, but the
behaviour of urbanization was unexplainable.
5. Inflation is purely insignificant variable in explaining variations in FDI
stocks.

33.  The data suffered from the problem of multi-
collinearity. This confirms the fact that such research
should be done extensively with panel data. That
would increase degrees of freedom and would help
reduce multi-collinearity.
 Also a lot of material variables were excluded from
the research in the wake of unavailability of data.
More complete and accurate sources of data need to
be found out to perform this research.

34.  Overall significance of model convinces one that the
selected variables do have an impact on the FDI flows in
the country. With more accurate and detailed data, this
research could be used to predict the value of foreign
capital flows into the country, and that too with a good
level of precision.
 The question as to whether a country can increase FDI
flows by improving on the dependent variable is also
answered by the research. The goodness of fit of the model
shows that most of changes in the independent are duly
explained by dependent variables.