FDI stands for Foreign Direct Investment, a component of a countrys national financial accounts. Foreign direct investment is investment of foreign assets into domestic structures, equipment, and organizations. It does not include foreign investment into the stock markets.[1] Foreign direct investment (FDI) or foreign investment refers to long term participation by country A into country B in management, joint-venture, transfer of technology and expertise. There are two types of FDI: inward foreign direct investment and outward foreign direct investment, resulting in a net FDI inflow. FDI is a measure of foreign ownership of productive assets, such as factories, mines and land. Increasing foreign investment can be used as one measure of growing economic globalization. Foreign direct investment (FDI) plays a multidimensional role in the overall development of the host economies. It may generate benefits through bringing in non-debt-creating foreign capital resources, technological upgrading, skill enhancement, new employment. While FDI is expected to create positive outcomes, it may also generate negative effects on the host economy. The costs to the host economy can arise from the market power of large firms and their associated ability to generate high profits. A recent survey projected India as the second most important FDI destination (after China) for transnational corporations during 2010-2012(ref. UNCTAD). FDI inflows of India amounted to USD 25.88 billion in the fiscal year of 2010(ref. UNCTAD). As per the data, the sectors which attracted higher inflows were services, telecommunication, construction activities and computer software and hardware. Thus FDI helps in boosting the growth of Indian Economy. India is among the emerging economies and since liberalization change of government policies and various factors affected FDI inflow in India. FDI inflows during 1991 was USD 129 million which increased to USD 33613 suggesting an increase of 260 times. [2]
FDI in Telecom sector:
The foreign direct investment in telecom stands at USD 1327 million on 2010-2011. Countries like Europe, Korea, and Japan telecom are likely to enter India, as India is seen as fastest growing telecom market in world[2]. The current tele-density in India is 67.67% and total telephone subscribers as 806.12 million as of Jan 2011.[3].
There are restrictions related to remote access, transfer of network information outside India and international transit routing of Indian traffic. It has been decided to encourage the FDI in telecom services in areas like basic telecom, cellular unified access services, Nat /intranet, long distance Vast, public mobile, radio service .
Effect of FDI in telecom
Telecom service at Subsidized prices
FDI inflows will allow multiple benefits such as technology transfer, market access and organizational skills.
In India where 70% of population still resides in rural areas, there is a dire need of infrastructure in telecom, which FDI can provide.
Harmonious relationship with country from which foreign investment is being made
There will be increase in competition with local players, which will benefit consumers
Telecommunication facility at reasonable price, affordable to many
More technological inflow, will improve voice & data quality
FDI in automobile sector:
FDI inflow for automobile sector in 2010-2011 is USD 1066 million[2]. The automotive sector is one of the core industries of the Indian economy, whose prospect is reflective of the economic resilience of the country. Continuous economic liberalization over the years by the government of India has resulted in making India as one of the prime business destination for many global automotive players. The automotive sector in India is growing at around 18 per cent per annum. The Indian automotive industry started its new journey from 1991 with de-licensing of the sector and subsequent opening up for 100 per cent FDI through automatic route. Since then almost all the global majors have set up their facilities in India taking the production of vehicle from 2 million in 1991 to 9.7 million in 2006 (nearly 7 per cent of global automobiles production and 2.4 per cent of four wheeler production)[4]. After the sector was thrown open to foreign direct investment in 1996, some of the global majors moved in and, by 2002, Hyundai, Honda, Toyota, General Motors, Ford and Mitsubishi set up their manufacturing bases.
Over the past four to five years, the country has seen the launch of several domestic and foreign models of passenger cars, multi-utility vehicles (MUVs), commercial vehicles and two-wheelers and a robust growth in the production of all kinds of vehicles. Moreover, owing to its low-cost, high-quality manufacturing, India has also emerged as a significant outsourcing hub for auto components and auto engineering design. German auto-maker Volkswagen AG, too, is looking to enter India.
India is expected to be the small car hub for Japanese major Toyota. The car like the Swift or Getz is likely to be exported to markets like Brazil and other Asian countries. This global car is crucial for Toyota, which is looking to improve its sales in the BRIC (Brazil, Russia, India and China) markets.
FDI in this sector made India as one of the global manufacturing base for automobile sector. It resulted in manufacturing world class fuel efficient cars at a low cost. This also created employment opportunities for many people in India.
The goal of our study is to investigate the effect of various country specific factors on inflow of FDI in India. Country specific factors such as exchange rate, cost of borrowing, risk conditions of the host country and GDP of the source country affect the FDI inflows.
Problem Statement: How country specific factors affect the flow of FDI in India?
Research Question: What are the country specific factors that affect India's FDI inflow and how significant are each of the factors that affect India's FDI inflow?
Research objective:
To determine the effect of Exchange Rate on flow of FDI.
To determine the effect of Cost of Borrowing on flow of FDI.
To determine the effect of Risk Conditions of source country on flow of FDI.
To determine the effect of GDP of source country on flow of FDI.
Research Design: Causal
Software to be used: SPSS
Statistical Tool Used: multiple Regression analysis.
Dependent Variable: FDI inflows from each country in India. (Share of top investing countries FDI inflows are considered)
Independent Variable:
exchange rate.
cost of borrowing.
risk conditions of the source country
GDP of the source country.
Literature review:
Content Validity:
A past study had been conducted on the impact of country specific factors on FDI inflows of China(Yigang Pan,2003)
Criterion Validity:
Here FDI inflows are a function of exchange rates, cost of borrowing, GDP of the source country and risk factors of the host country
There has been past studies regarding the connection between exchange rates and cost of borrowing with the foreign direct investment of USA and it was found that there has been a systemic effect of exchange rate on FDI flows of USA(Froot and Stein, 1991)
There are existing literatures which found that there is a positive impact of a country's GDP and its FDI outflows of USA(Grosse and Trevino, 1996)
There are past studies which indicate that risk factors of a country affect FDI inflows(Kim and Hwang,1992)
Hypothesis:
1: Exchange rates
H0 : β1 = 0 (FDI inflows are independent of exchange rates)
H1 : β1 ≠0 (FDI inflows are dependent on exchange rates)
First, the appreciation of a source country's currency against that of a host country means that the source country's investment increases in value when denominated into the host country's currency. This makes the investment cheaper from the source country's perspective
Second, currency appreciation makes goods from the source country more expensive when denominated in the host country's currency, making exporting from the source country to the host country less cost-competitive. This motivates firms from the source country to relocate the production of goods to the host country
2: Cost of Borrowing
H0 : β2 = 0 (FDI inflows are independent of cost of borrowing)
H1 : β2 ≠0 (FDI inflows are dependent on cost of borrowing)
Cost of borrowing depends upon the lending rates. Higher lending rates increase costs, causing firms to earn higher profits to meet their expectations net of debt repayments. Firms from countries with low interest rates enjoy a cost advantage that enables them to raise more capital with a lower burden of interest payment. Holding other factors constant, such firms should be able to raise more capital for overseas investment.
3: GDP of source country
H0 : β3 = 0 (FDI inflows are independent on GDP of source country)
H1 : β3 ≠0 (FDI inflows are dependent on GDP of source country)
It is easier for firms from a large home country to raise the capital needed to invest overseas. Larger countries tend to have more firms that can expand into international markets aggressively and on a larger scale. Thus source countries with higher GDP should have higher level of FDI in India.
4: Risk Factor
H0 : β4 = 0 (FDI inflows are independent of risk factors of the source country)
H1 : β4 ≠0 (FDI inflows are dependent of risk factors of the source country)
As the source country becomes more risky firms in those countries will try to invest in less riskier countries to minimize their operational risks. Countries with lower risk score should means that the country is risky and hence they should have higher level of FDI in India.
The empirical model:
As suggested by (Wen Hsien Liu, 2010) and our hypothesis above the model for regression is as follows:
ln FDI = ln α + β3 ln GDP + β1 EX + β2 LR + β4 ln RR
here FDI is annual FDI inflow from each countries to India in the year 2010, GDP is the gross domestic product of that country in 2010, EX is the relative exchange rate, LR is the lending rates of source country and RR is the risk score of the source country. We decided to use regression analysis to find values of β and analyse them.
Data:
FDI inflows to India from top ten investing countries in the year 2010 are considered. Following are the sources of data which are considered for the project.
Sources of data:
FDI inflows from each country: FDI India fact sheet December 2010. (http://www.dipp.nic.in/fdi_statistics/india_fdi_index.htm)
Exchange rate: measured as ratio of INR to currency of each source country in USD. (http://www.oanda.com/currency/average)
GDP: https://www.cia.gov/library/publications/the-world-factbook/fields/2195.html
Cost of borrowing is measured as the lending rates of the central Bank of each of the following countries. Cost of borrowing: https://www.cia.gov/library/publications/the-world-factbook/fields/2208.html
Risk conditions of host country: current risk score of the countries (high score suggests that the country is more riskless) (http://www.euromoney.com/Article/2773235/Country-risk-March-2011-Country-rankings-and-acknowledgements.html)
The data is shown in table 1.
Table 1
countries
fdi (millions USD)
Exchange rate
gdp(in billions USD)
lending rate
risk score
mauritius
10376
0.6788
9.427
19.25
44.78
singapore
2379
0.03009
233.9
5.38
87.48
usa
1943
0.02108
14620
3.25
81.6
uk
657
0.013222
2259
0.63
80.04
netherlands
899
0.01493
770.3
10.01
86.67
japan
1183
1.959
5391
1.6
74.66
cyprus
1627
0.01493
22.75
7.49
77.02
germany
626
0.01493
3306
4.96
84.43
france
303
0.01493
2555
7.46
79.89
uae
629
0.07745
239.7
1.5
69.7
Assumptions of regression:
Homoscedasticity: The variation around the regression equation is same for all the values of the independent variables. To check homoscedasticity the scattered plot of table 3 is observed and based on it it is reasonable to conclude that this assumption is not violated.
Table 3
The residuals should be normally distributed. This is verified using the normal probability plot of the residuals where it is observed that plotted points are fairly close to the straight line as seen in table 4.
Table 4
Multicolliinearity: This problem exists if two independent variables are highly correlated. We use the variation inflation factor test for this problem. Table 5 shows the results of the VIF test. As the VIF is less than 10 this is considered satisfactory.
Table 5
Variable
VIF
Ln GDP
2.248
Ln RR
2.887
EX
1.422
LR
2.369
Mean
2.2315
Autocorrelation: It arises if the successive residuals are correlated. Durbin-Watson test id used to check this. Our DW statistic is 0.839.
The null and alternate hypothesis are:
H0 : No residual correlation (Ï = 0)
H1: positive residual correlation (Ï â‰ 0)
For n=10 abd k=4 dl = 0.38 and du = 2.59 so this leads to inconclusive results.
Thus our regression is considered after checking with the assumptions.
Results:
Table 6 shows the results if the regression
Table 6
Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
Collinearity Statistics
B
Std. Error
Beta
Tolerance
VIF
1
(Constant)
12.276
10.867
1.130
.310
ln gdp
-.105
.183
-.256
-.574
.591
.447
2.238
ln (risk score)
-1.141
2.532
-.228
-.451
.671
.346
2.887
lending rates
.056
.082
.315
.686
.523
.422
2.369
exchange rate
.314
.558
.200
.562
.599
.703
1.422
a. Dependent Variable: ln fdi
Here we find out that for all the cases P>α(0.05) hence we accept our null hypothesis for all the independent variables. Thus we accept our null hypothesis for all variables. Thus β1= β3 = β2= β4 = 0. According to this FDI inflow in India is independent of the factors like exchange rates, GDP of the source country, Lending rates of the source country and risk factors.
Table 7
Model Summaryb
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
Durbin-Watson
1
.745a
.555
.199
.8760881
.839
a. Predictors: (Constant), exchange rate, lending rates, ln gdp, ln (risk score)
b. Dependent Variable: ln fdi
Results from table 7 shows that R2 value is only 0.199 which means that only 19.9 % of the variation in dependent variable is explained by the independent variable which is quite low. This indicates that there may be some other major factor which affect more to FDI inflows which is contrary to previous research findings.
We find out that smaller economies like that of Mauritius and Singapore have much larger FDI inflows than that of USA and Japan. Factors such as risk is not responsible for FDI inflows which may happen due to the fact that India is among the developing countries which is growing at a much faster rate and many MNC are investing in India due to its huge availability of skilled labour at low cost.
Conclusion:
This research is done using only four factors from which we find out that factors like GDP of source countries, Lending rates, risk factors are not responsible for FDI inflows in India which is opposite to the facts which is obtained from the literature review. Hence a more detailed and in depth study is needed and factors of the source country which affect FDI flows in India needs to be revised. India being a developing country is attracting huge foreign investments. In depth work should be carried out and motives of foreign companies having investments in India should be studied. Cross border acquisitions, green field acquisitions should be studied which can help our nation grow at a faster pace.
