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Determinants of foreign direct
investment in Real estate
in European countries –
panel data analysis
Sviatlana Anop
Royal Instritute of Technology (KTH),
Stockholm, Sweden
Introduction
The goal of this study is to highlight
theoretical and empirical findings about
determinants of foreign direct investment
in real estate in developed European
countries-members of OECD.
Introduction
Figure 1. FDI Inflows and outflows, 1999-2007, and 2008 forecast
Source: OECD
Introduction
Literature review
• Market-size hypothesis: international
investments are “attracted by both the size of the
host country and by the purchasing power of its
inhabitants.” Sader (1993)
• Nonnemberg and Cardoso de Medonco (2004)
and Mottaleb (2007) have shown that such
factors as the size and rate of growth of the
GDP, the availability of skilled labor, modern
communication facilities significantly affect the
inflow of FDI in developed countries
Contribution
• However almost no research was done regarding
investments in particular industries and assets, and
more specifically regarding FDI in real estate.
• Moshirian F., Pham T. (2000) in their study of US
FDI show that US financial wealth, US FDI in
manufacturing and banking, US bilateral trade,
foreign current account balance and US foreign
financial liabilities contribute positively to the
expansion of US FDI in real estate.
• This study investigates determinants of FDI in real
estate in 15 OECD Countries of European area for
1996-2007
Data
Open data source:
http://stats.oecd.org/index.aspx
The annual panel data consists of 15 OECD
countries of European area and runs from
1996-2007 both are inclusive.
List of countries
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Austria
Czech republic
Denmark
Finland
France
Germany
Greece
Hungary
Netherlands
Norway
Poland
Slovak republic
Spain
Sweden
United Kingdom
General dynamic model
FDIREi,t= ai +β1GYi,t-1+β2yi,t-1+β5h i,t-1+β6road i,t-1+εit
where FDIRE - FDI in real estate,
GY - real GDP growth,
y - GDP,
h - human capital,
road – road infrastructure.
Descriptive statistics
Main variables in the model:
• FDI in RE is measured in millions US Dollars.
• The Gross Domestic Product (GDP) measured in billion
US Dollars is the way of measuring the size of country’s
economy.
• Real GDP growth is measured in percentage
• Human capital is measured as a tertiary rate of the
country. This is a percentage of population age 24-65
that enrolled in the tertiary schools.
• Road reflects road infrastructure in the country and is
measured as road fatalities per million inhabitants.
Descriptive statistics
First-difference model
ΔFDIREi,t=β1ΔGYi,t-1+β2Δyi,t-1+β5Δhi,t-1+
+β6Δroadi,t-1+Δεit
where FDIRE - FDI in real estate,
GY - real GDP growth,
y - GDP,
h - human capital,
road – road infrastructure.
Fixed effect model
FDIREi,t = ai+β1GYi,t-1+β2yi,t-1+β5hi,t-1+β6roadi,t-1+ εit
where FDIRE - FDI in real estate,
GY - real GDP growth,
y - GDP,
h - human capital,
road – road infrastructure.
Results
Dinamic model
• Wooldridge test: no serial autocorrelation
• Fist-difference model: no significant estimators
• Fixed effect model:
GDP growth is not signiciant,
GDP size is significant, positive effect,
human capital and road infrastructure are
significant, negative effect
• Random effects model: only GDP size is
significant, positive effect
Sensitivity analysis
Thank you!