Download Table 1. Fixed Sector and Trade Bloc Effects Regressors

Investment in a Small Remote Economy
Helga Kristjánsdóttir
Balance of Payments
Assets
Liabilities
Debt
Equity
Eq 10%
Eq <10%
Portfolio Equity
FDI
Mergers & Acquisitions
Greenfield Investment
FDI that involves
merging with,
or acquiring,
existing assets.
Think of the North Atlantic country Iceland with FDI in recent
years resembling the pattern before the economic crash, so the
dataset pre-crash can be used to explore potential long-term
trends. Investment is explained by geographic location and
country size, using a gravity model to account for the country‘s
exceptional remoteness and sparseness. A unique extension of
the gravity model implies usage of the hyperbolic sine function
together with simultaneous estimation of investment sector and
trade bloc effects.
FDI that involves
construction of a new
plant in a “greenfield”.
Contrasts with brown
field investment.
The data dimensions allow for model enlargements, to account for difference between investment
sector and investment blocs simultaneously, an analysis that is rarely possible. This last procedure
involves application of the inverse hyperbolic sine function, and I am able to control for both fixed
sector and bloc effects at the same time, which is truly unique for this model type.
The question to answer in this paper, is how the model works when the size difference between the
source and the recipient country of investment is particularly substantial. Previous research on FDI is
extensive but has not covered this situation. Furthermore, when it comes to FDI in Iceland, current
circumstances are similar to those before the economic boom and crash.
Pre-crash, the bulk of FDI was related to the power intensive sector, a trend that is repeating itself
today. The historical data can therefore potentially help to explain current economic forces and predict
the future trends as the power intensive sector continues to be of great importance in the modern
international economy. This case country is even more interesting in today‘s market because it has an
abundance of energy that can‘t be exported directly, and it is of the most valuable type, renewable
and completely environmentally friendly. The research can potentially be meaningful for source
countries looking for investment opportunities in the North Atlantic or in relatively small economies in
general.
A significant fixed difference is found in the amount of FDI made by individual countries. Findings
indicate that EU member countries have more incentives for making investment than countries with
no trade-bloc membership. Moreover, when compared to member countries of the EU trade bloc,
EFTA and NAFTA member countries are estimated to have more incentive for undertaking foreign
direct investment.
Foreign direct investment is found to be negatively affected by distance, and in most cases to be
negatively affected by population of the host and source country, however positively affected by their
gross domestic products. Such opposite signs estimates for gross domestic products and population
indicate foreign direct investment to be affected by distance and wealth, rather than market size. In
other words, geographical location and income per capita welth of nations appear to be more
important in this situation than size of nations.
The fact that the end result of this gravity model analysis indicates that foreign direct investment tends
to be driven by wealth rather than market size effects, may have some implications for other relatively
small economies wanting to receive FDI from larger ones, as well as for the larger countries
considering their FDI options.
Table 1. Fixed Sector and Trade Bloc Effects
Regressors
IHS Robust
Host Country GDP
2.189**
(2.44)
Source Country GDP
1.053***
(5.54)
Host Country Population
-2.127
(-0.84)
Source Country Population
-0.892
(-5.13)
Distance
-0.068
(-0.24)
Power Intensive Ind.
0.575***
(5.29)
Comm. and Fin. Ind.
0.649***
(6.58)
Other Industries
0.435***
(5.32)
EFTA
0.484***
(3.57)
NAFTA
0.357**
(1.99)
NON Bloc Members
-0.236
(-0.45)
Constant
10.949***
(3.34)
Observations
740
Log-Likelihood
-1091.20
Degrees of Freedom
11
R-Squared
0.1814
Note: Robust t-statistics are in parentheses below the coefficients. ***, ** and *
denote significance levels of 1%, 5% and 10%, respectively.