Download FDI And Trade In India – A Gravity Model Analysis - Econ

FDI And Trade In India – A Gravity Model Analysis
Mayank Nagpal
This paper aims to study the impact of Foreign Direct Investment inflows on Trade volumes in
India using the Gravity Model Analysis. We use the gravity model to study the motive of foreign
investment in India. Even though the results tend to suggest that a major portion of FDI is
resource seeking, there seems to ample theory to argue against this hypothesis.
Introduction
Foreign direct investment (FDI) in India has played an important role in the development of the
Indian economy. Until 1991, India followed a fairly restrictive foreign private investment policy
when compared to industrialized countries and relied more on bilateral and multilateral loans
with long maturities. Foreign direct investment was perceived only as a means of acquiring
industrial technology not available in India through capital goods import. India’s Foreign policy
was very similar to other rapidly industrializing Asian economies with foreign investment being
permitted only in designated industries, subject to varying conditions. The Foreign Exchange and
Regulation Act (FERA), 1974 restricted foreign firm’s equity holding only up to 40 per cent
discretion. Many believe that such a restrictive policy not only retarded the growth of India’s
technical capability, but also led to a loss of export opportunity of labour intensive goods. In
contrast, growth in exports of such labour intensive goods led to the successful development of
many successful East Asian economies.
After gradual relaxation of foreign investments in 1980’s, liberalization in 1991 and deregulation
since then helped open India’s markets to FDI. Since then, India has sought to consciously
‘benchmark’ its policies against those of other south-east Asian economies so as to attract a
greater share of the world FDI inflows. Over the decade of the 1990’s foreign investment was
permitted in almost all sectors of the economy (barring agriculture, and, until recently, real
estate). Moreover, laws were changed to provide foreign firms the same standing as the domestic
ones. Net FDI inflow in India reached 70630 crores in the 2006-07 financial year, an increase of
187% from the financial year 2005-06 with the largest share of Investment coming from
Mauritius followed by US and the UK. The table below shows the share of the top 10 investing
countries in India.
Top 10 Investing Countries in India, 1991-20001
Country/Region
Share (in Per Cent)
US
20.4
Mauritius
11.9
UK
6.4
Japan
4.0
South Korea
3.9
Germany
3.4
Australia
2.7
Malaysia
2.3
France
2.1
Netherlands
1.9
Source: Handbook of Industrial Policy and Statistics, 2001.
In 1998 and 1999, the Indian government announced a number of reforms designed to
encourage FDI and present a favorable scenario for investors. FDI is now seen as a source of
scarce capital, technology and managerial skills that were considered necessary in an open,
competitive, world. FDI in India has, in a lot of ways, enabled India to achieve a certain degree
of financial stability, growth and development. In recent years India has been a favoured
destination for foreign investors, mainly due to the large market for their products. FDI
investments are permitted through financial collaborations, through private equity or preferential
This table has been taken from- R. Nagaraj, “Foreign Direct Investment in India in the 1990s: Trends and
Issues”, Economic and Political Weekly, April 26, 2003
Source of the table: Handbook of Industrial Policy and Statistics, 2001 .
1
allotments, by way of capital markets through Euro issues, and in joint ventures. On the other
hand, FDI is not permitted in the arms, nuclear, railway, coal & lignite or mining industries.
Literature Review
Increasing globalisation and FDI leading to fragmentation of the production process over the
world has completely changed the international trade scenario facing the world. This has resulted
in the replacement of the traditional inter-industry trade with intra-industry and intra-product
trade. Even though the theoretical literature examining the determinants of Foreign Direct
Investment assumes that firms either supply a foreign market through exports or establish
production facilities in that country, empirical studies have shown that trade between two
countries and FDI between them are complementary to each other. In fact most studies, predict a
two way linkage between FDI and trade volumes. Studies such as, Blonigen (2001), who finds
evidence of both substitution and complementary effects between affiliate production and
exports of Japanese auto parts for the U.S. market2 and Aizenman, Joshua, Noy, Ilan (2005)3
investigate the two-way feedbacks between various categories of trade have found both a
positive and negative relationship between trade and FDI. They analyse whether the impact of
FDI on Trade is different for countries in different stages of development.
Other studies and literature on the impact of FDI and Trade (such as Hortsmann and Markusen
(1992) and Helpman (1984)) propose two opposing ways of the relationship between trade and
FDI. In case of horizontal FDI (i.e. FDI between two countries having similar endowments)
Trade and investment act as substitutes to each other as in such a case instead of exporting its
products, the Multi- National Enterprise (MNE) would start producing those products in the host
country by setting up a production unit there. This can be advantageous if in the long run trade
costs are higher than the costs of setting up a plant in the host country. In case of vertical FDI
(i.e. FDI between two countries with dissimilar endowments) the production process is split
Blonigen, Bruce A., and KaSaundra Tomlin, “Size and Growth of Japanese Plants in the United States,”
International Journal of Industrial Organization,
2
Aizenman, Joshua, Noy, Ilan, “FDI and Trade – Two Way Linkages? “, UC Santa Cruz: Department of
Economics, UCSC. Retrieved from: http://escholarship.org/uc/item/301285n0
3
between segments which are relatively intensive in different factors of production. For example
if a MNE from a capital abundant country sets up a plant in a labour abundant country those
segments which require labour intensively would be produced in the new plant set up in the
labour abundant country. In such a case the increased FDI would lead to an increased Trade as
the local production might require inputs that continue to be imported, such as components and
machinery. If a firm can produce a product at a lower cost in the host country than in its home
country, it would produce in its new plant and then import the goods produced there. Thus
vertical FDI should increase both exports and imports between the two countries.
Moreover, even though the view that FDI is a way of firms in the advanced nations fleeing from
their high-cost domestic production sites and relocating production in low-wage areas may be
true to a large extent, it is beneficial to the country in general as well as this cost minimizing
behaviour of the firm would result in a higher degree of specialisation. Trade theory suggests that
International Trade (which is always welfare improving) is a result of higher degree of
specialisation which in this case occurs due to the increased FDI in the labour abundant country.
According to Edward M. Graham4, Foreign Direct Investment stimulates rather than displacing
trade. According to him FDI enables a firm to establish a larger distribution base and thus not
only produce a larger number of commodities but also increase the number of products sold in
the foreign market.
Faster rising merger and acquisition across the regions over the globe has given a boost to the
flow of Foreign Direct Investment. According to the UNCTAD estimates, FDI inflows in 2006
reached at US $1.2 trillion. Though developed nations over the world had attracted a huge sum
of FDI in 2006, still the flows to developing nations were significant in the same year. FDI
inflows to the developed countries increased by 48 percent over the previous year. A major
motive of FDI among developed countries (horizontal FDI) is capturing the market of the
country where the foreign capital is invested in. On the other hand in case of firms from
developed countries investing in developing countries, the motive seems to be to minimize cost
by making use of the cheaply available abundant factor in the host country.
4
Senior Fellow at the Institute for International Economics in Washington, DC
FDI in India is generally considered to be market seeking rather than resource seeking. Stricter
labour laws as compared to other developing countries like China discourages foreign firms to
make use of the cheaply available resource here, i.e. labour. Thus the incentive for vertical
investment in India is less than that of investing in China and making use of cheaper labour
there.
Data & Methodology
We have collected data for different variables on a country-wise basis from various resources for
the years 1996 to 2004. Data sources for all the different variables used in the analysis have been
given at the end of the paper.
We use the Gravity Model analysis to study the effect of FDI inflows into India from various
countries on volumes of trade between India and those countries. The Gravity Model of trade is a
simple modification of Newton’s law of gravitation in physics. It states that the volume of trade
between two countries is positively related to the product of the GDP between the two countries
and is inversely proportional to the distance between them. Thus the original gravity model is
𝑻𝒓𝒂𝒅𝒆𝒊𝒋 = 𝑲(𝑮𝑫𝑷𝒊 𝑮𝑫𝑷𝒋 )/𝑫𝒊𝒔𝒕𝒂𝒏𝒄𝒆𝒊𝒋
The modified gravity model takes natural logs on both sides of the equation and thus its new
form is.
𝒍𝒏(𝑻𝒓𝒂𝒅𝒆𝒊𝒋 ) = 𝜶𝟏 𝒍𝒏(𝑮𝑫𝑷𝒊 ) + 𝜶𝟐 𝒍𝒏(𝑮𝑫𝑷𝒋 ) + 𝜶𝟑 𝒍𝒏(𝑫𝒊𝒔𝒕𝒂𝒏𝒄𝒆𝒊𝒋 ) + 𝒖𝒊𝒋
In the new gravity model equation for our analysis we use various other relevant variables and
run a Tobit regression model to estimate the coefficients and then interpret the results
accordingly. We use the panel data approach as it not only increases our degrees of freedom but
also helps in capturing the heterogeneity caused by over time. We run the following Tobit
regression model for our analysis
𝐥𝐧(𝐞𝐱𝐩𝐨𝐫𝐭 𝒊𝒕 + 𝟏) ∗
= 𝛃𝟎 + 𝛃𝟏 𝐥𝐧(𝐆𝐃𝐏𝐢𝐭 ) + 𝛃𝟐 𝐥𝐧(𝐝𝐢𝐬𝐭𝐚𝐧𝐜𝐞𝐢 ) + 𝛃𝟑 (𝐜𝐨𝐦𝐦𝐨𝐧 𝐛𝐨𝐫𝐝𝐞𝐫𝐢 )
+ 𝛃𝟒 (𝐜𝐨𝐦𝐦𝐨𝐧 𝐥𝐚𝐧𝐠𝐮𝐚𝐠𝐞𝐢 ) + 𝛃𝟓 (𝐜𝐨𝐦𝐦𝐨𝐧 𝐥𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐨𝐟𝐟𝐢𝐜𝐢𝐚𝐥𝐢 )
+ 𝛃𝟔 (𝐜𝐨𝐦𝐦𝐨𝐧 𝐜𝐨𝐥𝐨𝐧𝐢𝐬𝐞𝐫𝐢 )
+ 𝛃𝟕 𝐜𝐨𝐥𝐨𝐧𝐢𝐚𝐥 𝐥𝐢𝐧𝐤 𝐢 +𝛃𝟖 (𝐀𝐟𝐫𝐢𝐜𝐚)+𝛃𝟗 (𝐀𝐬𝐢𝐚)+𝛃𝟏𝟎 (𝐄𝐮𝐫𝐨𝐩𝐞) + 𝛃𝟏𝟏 (𝐎𝐜𝐞𝐚𝐧𝐢𝐚)
+ 𝛃𝟏𝟐 𝐥𝐧(𝐩𝐨𝐩𝐮𝐥𝐚𝐭𝐢𝐨𝐧𝐢𝐭 ) + 𝛃𝟏𝟑 (𝐒𝐚𝐦𝐞 𝐜𝐨𝐮𝐧𝐭𝐫𝐲 ) + 𝛃𝟏𝟒 (𝐞𝐱𝐜𝐡𝐚𝐧𝐠𝐞𝒊𝒕 )
+ 𝜸(𝒀𝒆𝒂𝒓 𝑫𝒖𝒎𝒎𝒊𝒆𝒔) + 𝛂 𝐥𝐧(𝐅𝐃𝐈 𝐢𝐧𝐟𝐥𝐨𝐰𝐢𝐭 + 𝟏) + 𝐮𝐢𝐭
With 𝐮𝐢𝐭 = 𝐍(𝟎, 𝝈𝟐 )
𝐥𝐧(𝑰𝒎𝒑𝒐𝒓𝒕𝒊𝒕 + 𝟏) ∗
= 𝛃𝟎 + 𝛃𝟏 𝐥𝐧(𝐆𝐃𝐏𝐢𝐭 ) + 𝛃𝟐 𝐥𝐧(𝐝𝐢𝐬𝐭𝐚𝐧𝐜𝐞𝐢 ) + 𝛃𝟑 (𝐜𝐨𝐦𝐦𝐨𝐧 𝐛𝐨𝐫𝐝𝐞𝐫𝐢 )
+ 𝛃𝟒 (𝐜𝐨𝐦𝐦𝐨𝐧 𝐥𝐚𝐧𝐠𝐮𝐚𝐠𝐞𝐢 ) + 𝛃𝟓 (𝐜𝐨𝐦𝐦𝐨𝐧 𝐥𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐨𝐟𝐟𝐢𝐜𝐢𝐚𝐥𝐢 )
+ 𝛃𝟔 (𝐜𝐨𝐦𝐦𝐨𝐧 𝐜𝐨𝐥𝐨𝐧𝐢𝐬𝐞𝐫𝐢 )
+ 𝛃𝟕 (𝐜𝐨𝐥𝐨𝐧𝐢𝐚𝐥 𝐥𝐢𝐧𝐤 𝐢 )+𝛃𝟖 (𝐀𝐟𝐫𝐢𝐜𝐚)+𝛃𝟗 (𝐀𝐬𝐢𝐚)+𝛃𝟏𝟎 (𝐄𝐮𝐫𝐨𝐩𝐞)
+ 𝛃𝟏𝟏 (𝐎𝐜𝐞𝐚𝐧𝐢𝐚) + 𝛃𝟏𝟐 𝐥𝐧(𝐩𝐨𝐩𝐮𝐥𝐚𝐭𝐢𝐨𝐧𝐢𝐭 ) + 𝛃𝟏𝟑 (𝐒𝐚𝐦𝐞 𝐜𝐨𝐮𝐧𝐭𝐫𝐲 )
+ 𝛃𝟏𝟒 (𝐞𝐱𝐜𝐡𝐚𝐧𝐠𝐞𝒊𝒕 ) + 𝜸(𝒀𝒆𝒂𝒓 𝑫𝒖𝒎𝒎𝒊𝒆𝒔) + 𝛂 𝐥𝐧(𝐅𝐃𝐈 𝐢𝐧𝐟𝐥𝐨𝐰𝐢𝐭 + 𝟏) + 𝐮𝐢𝐭
With 𝐮𝐢𝐭 = 𝐍(𝟎, 𝝈𝟐 )
Where, 𝒍𝒏(𝐞𝐱𝐩𝐨𝐫𝐭 𝒊𝒕 + 𝟏) = 𝐥𝐧(𝐞𝐱𝐩𝐨𝐫𝐭 𝒊𝒕 + 𝟏) 𝒊𝒇 𝐥𝐧(𝐞𝐱𝐩𝐨𝐫𝐭 𝒊𝒕 ∗ +𝟏) > 0 & 𝒍𝒏(𝐞𝐱𝐩𝐨𝐫𝐭 𝒊𝒕 ∗
+𝟏) = 𝟎 𝒊𝒇 𝒍𝒏(𝐞𝐱𝐩𝐨𝐫𝐭 𝒊𝒕 + 𝟏) ≤ 𝟎
𝒍𝒏(𝐈𝐦𝐩𝐨𝐫𝐭 𝒊𝒕 + 𝟏) ∗= 𝒍𝒏(𝐈𝐦𝐩𝐨𝐫𝐭 𝒊𝒕 + 𝟏)𝒊𝒇 𝒍𝒏(𝐈𝐦𝐩𝐨𝐫𝐭 𝒊𝒕 + 𝟏) > 0 & 𝒍𝒏(𝐈𝐦𝐩𝐨𝐫𝐭 𝒊𝒕 +
𝟏) ∗= 𝟎 𝒊𝒇 𝒍𝒏(𝐈𝐦𝐩𝐨𝐫𝐭 𝒊𝒕 + 𝟏) ≤ 𝟎
In case where we take logs in the regression, we add 1 to the value of the variable as for
observations where the variables take zero values logs of these would be undefined. As the
dependent variable in this case has a large number of zero values we use the Tobit model for our
analysis. We run a pooled Tobit Model regression using data for the years 1996 to 2004. The
statistical package used for running the regression is STATA 10.

Exportit- Export from India to country i in year t.

Importit- India’s imports from country i in year t.

Distancei- Distance of country i from India

𝐏𝐨𝐩𝐮𝐥𝐚𝐭𝐢𝐨𝐧𝐢𝐭 - Population of country i in year t

𝐅𝐃𝐈 𝐢𝐧𝐟𝐥𝐨𝐰𝐢𝐭 - FDI inflow from country i in year t

𝐄𝐱𝐜𝐡𝐚𝐧𝐠𝐞𝒊𝒕 - Exchange rate of country i with respect to US dollars in year t. Ideally we
should have used the exchange rates of each currency with respect to Indian Rupees to
capture this effect but as this data was unavailable, we have used the exchange rate with
respect to dollars. As this rate may be unable to capture the exchange rate with respect to
the rupee, we should be extremely careful in interpreting the results.

Year dummies- The use of time effects tr is motivated by findings in Baldwin & Taglioni
(2006)5. The paper shows how an exclusion of such time effects may result in significant
misspecifications.

Dummies for Various Continents to take into account the cultural factors which might
affect trade between two countries. The dummies take the value 1 if the country belongs to
that particular continent and zero otherwise

Other dummies which take in account the relationship between countries such as common
colonial history, common language and if the countries were the same at one time.

Common border dummy which captures the border effects.
The coefficients of GDP and dummies indicating a historical relationship between countries is
expected to positive. On the other hand, coefficient of distance is expected to be negative. The
exchange rate of a country’s currency with respect to the Indian rupee is expected to have a
Richard Baldwin & Daria Taglioni , “Gravity Model for Dummies and Dummies for Gravity Equations”,
Working Paper 12516,September 2006 National Bureau of Economic Research.
5
positive relationship with India’s imports from that country, whereas a negative relationship is
expected between exchange rate (with respect to the rupee) and India’s exports to that country.
We estimate two regressions and analyse the revealed effects of various factors on exports and
imports separately. A positive coefficient on the variables would imply that they have a positive
effect on trade and a negative coefficient would suggest otherwise. For this study the variable of
our interest is FDI inflows and we need to analyse the value and the sign of α. A positive
coefficient would suggest that FDI and trade are complementary to each other and that increasing
FDI in the country would lead to increase in the volume of trade. On the other hand a negative
coefficient would indicate substitutability between Trade and FDI.
Results
We run Tobit Model regressions with Export and Import as the two dependent variables in two
separate regressions and get the results given in the appendix.
As expected we get a positive and significant coefficient for log of GDP for both the regressions
implying that the data supports the hypothesis that GDP has a positive impact on trade between
two countries, i.e. India would trade more with a country having higher GDP than with a country
having lower GDP. The data suggests that an increase in GDP by a single percent would lead to
an increase in imports by 1.47% and exports by 0.62%. The rise in imports is because increase in
GDP of the partner country would mean that a larger amount and variety of goods are produced
there which might lead to increased demand of their products in India. On the other hand, rise in
exports is due to the rise in production. Population of the partner country has a positive and
significant impact on India’s export. This may be due to higher demand for India’s exports in
highly populated countries. This effect does not hold for India’s imports indicating no such
relationship between the value of goods imported by India from a country and the population of
the country. The coefficient indicating the effect of exchange rate of the partner countries
currency with respect to US dollars is insignificant for both exports and imports. This is along
expected lines as the exchange rates with respect to US dollars may not be able to capture the
effect of a fall or rise in that currency’s exchange rate with respect to the Indian rupee.
The positive coefficient on the year dummies indicate that with respect to the trade value in 1996
the trade value seems to be higher for years after 1999-2000. This may be due to the effect of
globalisation and improving trade relationships between India and the rest of the world.
The negative and significant coefficient on the same country dummy depicts the negative impact
that worsening of relations with a country like Pakistan has had on trade between the two
countries. Even though the positive coefficients on common border and common language
contradict the aforesaid observation, this may be due to the good relations India has with
countries like Bangladesh, Nepal, Bhutan and Sri Lanka. Also border effects and ease of trade
with neighbouring countries have positive effects on trade.
Unexpectedly, the coefficient on distance is not significantly different from zero implying that
distance between India and other countries does not have any effect on the volumes of trade
between the two countries. The result seems to suggest that gains from globalisation, improved
relations and trade seem to have overshadowed the negative effects from transport costs and
other trade costs. This might suggest that, with globalisation and technology the trade hindering
effects of distance seem to have reduced. But we need to be doubly sure before making such
conclusions as most studies have predicted that even after taking into account the huge effect of
globalisation and reduced trade costs, the effect of distance on Trade seems to be negative. Thus
we cannot make any conclusions from the coefficient of distance without further analysis of the
theory.
The variable of interest in our study, i.e. FDI inflows into India has a positive and significant
coefficient for both the regressions implying that FDI inflows in India are complementary to
trade. The coefficients suggest that one percentage increase in FDI would increase imports by
0.19% and exports by 0.22%. This would normally indicate vertical FDI, where capital is
invested so as to make use of the factor available cheaply in the host country. The data therefore
suggests that the bulk of the FDI inflows in India are aimed at making use of the cheaply
available factor, i.e. labour to minimise production costs and then import back the goods
produced here cheaply. The data seems to suggest that rise in exports from the partner country to
India is due to the export of inputs, required for the production of these labour intensive
products, to India. FDI may also result in an increase of exports from India to other countries as
well as MNEs may use the production units here to produce goods which are exported to these
countries. This seems to be against our expectations as FDI in India is majorly believed to be
market seeking rather than resource seeking. Moreover the above mentioned export is found to
form a very small part of the total exports Strict labour laws and other controls discourage
resource seeking FDI in India and thus we need to be careful in interpreting the coefficient.
Conclusion
The results indicate a positive relationship between FDI and exports as well as FDI and imports.
It is found that the complementary relationship between FDI and trade dominates. The data thus
suggests that a major portion of FDI is aimed at making use of the cheap labour available in
India. At First, they may invest in order to reduce their overall production costs by exploiting
regional differences in labour costs, tax regimes and transportation costs among other factors.
These differences occur due to the difference in endowments of the two countries. But with time
these production units may be transformed in to export platforms from which they serve both
national and international markets. Given the large consumer base in India, even though, initially
a firm may have a resource seeking motive for investing in India, after some time the firm’s
market seeking motive would be combined with its resource seeking motive. Thus even though,
the results suggest that FDI has a positive effect on trade in India, it does not necessarily imply
that FDI in India is primarily resource seeking or vertical in nature. In fact, as explained above
even market seeking FDI may result in an increase in exports, as in addition to capturing the
home country’s market, the production center also exports the produced goods to other countries
in the international market. Another reason for the unexpected positive coefficient on FDI could
be that the factors which effect Trade and FDI, such as diplomatic relations between two
countries and their GDPs could be common to both. Thus the coefficient on FDI may just be
capturing the effects of these variables on both FDI and Trade rather than the effect of FDI on
Trade.
Appendix
Results for the Regressions
Dependent Variables
ln(Exports+1)
Independent
Variables
Coefficient
ln(Distance)
-.3213366
Standard
Error
.2105078
ln(Imports+1)
P Value Coefficient
Standard
P Value
Error
0.127
.348342
.3314985
0.341
ln(GDP)
.618453
.0650767
0.000
1.466452
.1081434 0.000
ln(Exchange Rate)
.0144687
.0222672
0.516
.0549045
.0368347 0.136
ln(Population)
.4200134
.0651202
0.000
.1726422
.1083442 0.111
America
-.2823368
.2208541
0.201
-2.199196
.3685044 0.000
Asia
-.0148552
.2491023
0.952
-.0111749
.4118655 0.978
Europe
-.444077
.2112493
0.036
-.7314617
.3499955 0.037
Pacific
-.0132153
.2667457
0.960
-.0037779
.4530967 0.993
Common Border
.9629148
.4102638
0.019
3.507992
.6758097 0.000
Common Language Off -.713187
.2271301
0.002
-.7555469
.3770964 0.045
Common Language
.4622181
.1987026
0.020
.0415205
.3313031 0.900
Colonial Link
.5775905
.65784
0.380
.4664463
1.08199
Common Coloniser
.8938856
.1542283
0.000
1.272329
.2572771 0.000
Same Country
-1.611408
.5370004
0.003
-2.827903
.8840612 0.001
Ln (FDI +1)
.224723
.0252403
0.000
.1893899
.0416358 0.000
Year 1997
.0111702
.2049258
0.957
-.059227
.3448766 0.864
Year 1998
.050326
.2050161
0.806
.1957411
.3438788 0.569
Year 1999
.3030821
.2049325
0.139
.6559854
.3434322 0.056
Year 2000
.5684728
.2050302
0.006
.8359857
.3424089 0.015
Year 2001
.6705245
.2050963
0.001
.8556473
.3424819 0.013
Year 2001
.8008362
.2052292
0.000
1.092457
.3426846 0.001
Year 2002
1.113125
.2051925
0.000
1.626894
.341851
Year 2003
1.266516
.2053041
0.000
1.80208
.3422685 0.000
Intercept
-9.756172
1.904436
0.000
-33.83568
3.1574
0.666
0.000
0.000
References
•
Ana Paula Africano and Manuela Magalhães, FDI and Trade in Portugal – A Gravity
Model Analysis
•
Edward M. Graham, Working Together: Foreign Direct Investment and Trade,
Economic Reform Today,1997
•
José Pedro Pontes (ISEG/UTL and UECE), FDI and trade: complements and
substitutes
•
Yong Li, The impact of FDI on trade: evidence from China's bilateral trade, Journal for
the Academy of Business and Economics, Jan 2003
•
Will Martin and Cong Pham (World Bank), Estimating the Gravity Model When Zero
Trade Flows Are Important.
•
Joshua Aizenman and Ilan Noy, FDI and Trade -- Two Way Linkages?, NBER
working paper no. 11403
•
José Pedro Pontes, A non-monotonic relationship between FDI and trade
•
Martin, Will and Pham, Cong S., Estimating the Gravity Equation when Zero Trade
Flows are Frequent.
•
Timo Mitze, Bj¨orn Alecke & Gerhard Untiedt, “Trade, FDI and Cross-Variable
Linkages: A German (Macro-)Regional Perspective”, MPRA Paper No. 12245, posted
17. December 2008
•
Hidemi Kimura & Yasuyuki Todo, “Is Foreign Aid a Vanguard of FDI? A GravityEquation Approach”, RIETI Discussion Paper Series, February 2007
•
Richard Baldwin & Daria Taglioni , “GRAVITY FOR DUMMIES AND DUMMIES
FOR GRAVITY EQUATIONS”, Working Paper 12516,September 2006 National
Bureau of Economic Research.
•
Blonigen, Bruce A., and KaSaundra Tomlin, “Size and Growth of Japanese Plants in
the United States,” International Journal of Industrial Organization.
•
R. Nagaraj, “Foreign Direct Investment in India in the 1990s: Trends and Issues”,
Economic and Political Weekly, April 26, 2003
Data Sources
•
FDI inflow data from Indiastats.comhttp://www.indiastat.com/industries/18/foreigndirectinvestment/105/foreigndirectinvestm
ent/17578/stats.aspx
•
Data on Exports and Imports from World Integrated Trade Solution (WITS) database
published the World Bank.
•
Data on GDP from World Development Indicators (WDI) Database published by the
World Bank.
•
Data on Population, Language, Boundary, Distance, and other Dummies is sourced
from CEPII
•
Data on the Foreign Exchange Rates are obtained and converted from the International
Financial Statistics Database 2003 by the International Monetary Fund (IMF).