What factors matter in attracting FDI?

Foreign direct investment (FDI) plays an important role in the long-run economic growth of a country. FDI develops productive capacity through transfer in technology, enhances domestic labour skills through global managerial practices and contributes to human capital development. FDI assists in integrating the domestic markets with the global market. Furthermore, FDI bridges the gap between domestic savings and investment and spurs economic growth which is a powerful tool for alleviating poverty. Although developing countries understand the need for FDI to boost economic growth in their countries, not all countries have been successful in attracting FDI equally.
As FDI inflow for the countries is important, we have constructed rankings of countries using the averages of Foreign Direct Investment-Gross Domestic Product (FDI-GDP) ratio and FDI per capita for the latest 5-year period (2011-2015) for 179 countries to observe the highest and lowest recipients of FDI. The data of FDI-GDP ratio is obtained from the World Bank's WDI database, and the FDI per capita is calculated using data of FDI net inflow and total population from the WDI.
Top and bottom 10 countries in terms of FDI-GDP ratio and FDI per capita are shown in Tables 1 and 2 respectively. Luxembourg ranked the top in cases of both FDI-GDP ratio and FDI per capita. Also, Malta, Ireland, Netherlands and Singapore consistently appeared among the top 10 for both the Tables 1 and 2. In both Tables 1 and 2, among the bottom 10 countries, Nepal, Afghanistan, Burundi, North Korea and Pakistan are in common. The rankings of the South Asian countries are depicted in Table 3. Among the South Asian countries, Maldives topped the list in both cases with global rankings of 16th and 30th respectively, whereas, Pakistan, Afghanistan and Nepal consistently ranked at the bottom. In the case of FDI-GDP ratio, India, Bangladesh and Sri Lanka ranked at 136th, 149th and 159th respectively. However, In the case of FDI per capita, Sri Lanka, India, and Bangladesh ranked at 135th, 156th and 168th respectively. Except Maldives, all South Asian countries have FDI-GDP ratio much lower than 2 per cent, whereas most of the Southeast Asian countries have FDI-GDP ratios well above 2 per cent. For example, during the same period, the average FDI-GDP ratios of Malaysia, Indonesia, Thailand, Vietnam were 3.65 per cent, 2.38 per cent, 2.07 per cent and 5.42 per cent respectively. Even the LDCs like Cambodia, Lao PDR and Myanmar had much higher FDI-GDP ratios, which were 8.98 per cent, 5.43 per cent and 3.15 per cent respectively.
This article aims to examine the factors that affect the FDI inflow in a cross-country and over time framework. We have constructed an unbalanced panel data covering 217 countries over a period of 56 years (1960 to 2015), and the data is obtained from the WDI. We have conducted a series of fixed effect panel regressions. The dependent variable is considered to be the FDI-GDP ratio (measured in percentage) or FDI per capita (measured in million US$), and the explanatory variables are trade-GDP ratio (trade as a  per cent of GDP), used as a proxy for economy's openness, electric power consumption (measured in kWh per capita), used as a proxy for infrastructure, domestic investment-GDP ratio (gross fixed capital formation as  per cent of GDP), used as a measure of the magnitude of domestic investment, and natural logarithm of population or GDP used as  proxies for the market size.
The results of the basic fixed effect panel regression model, considering FDI-GDP ratio as the dependent variable, show that all these four explanatory variables have statistically significant and positive associations with the FDI-GDP ratio. 1 percentage point increase in the trade-GDP ratio is associated with 0.1 percentage points increase in the FDI-GDP ratio; 100 unit rise in the electric power consumption per capita is associated with 0.04 percentage points increase in the FDI-GDP ratio; 1 percentage point increase in the domestic investment-GDP ratio is associated with 0.14 percentage points rise in the FDI-GDP ratio; and finally, 1 per cent increase in the size of the population is associated with 0.03 percentage points rise in the FDI-GDP ratio. When the variable 'population' is replaced by 'GDP' to reflect market size, the results are also consistent.
This article also explores whether quality of institution affects FDI. Institutional variables such as bureaucracy quality, law and order, control of corruption, government's stability, democratic accountability and investment profile are considered from the International Country Risk Guide (ICRG) for 126 countries over a time period of 27 years (1984 to 2010). Out of all these six institutional variables, government's stability and investment profile appear to be statistically significant with positive sign. According to the ICRG, 'government's stability' is a measure of both of the government's ability to carry out its declared programme(s), and its ability to stay in office. The risk rating assigned is the sum of three subcomponents: government unity, legislative strength, and popular support. Also, the ICRG suggests that 'investment profile' is a measure of the factors affecting the risk to investment that are not covered by other political, economic and financial risk components. The risk rating assigned is the sum of three subcomponents: contract viability/expropriation, profits repatriation, and payment delays. The regression results suggest that on an average, 1 point rise in the index of government's stability is associated with 0.11 percentage points rise in the FDI-GDP ratio. Also, 1 point rise in the index of investment profile is associated with 0.27 percentage points rise in the FDI-GDP ratio. While the dependent variable in the panel regression model is replaced by the FDI per capita, the results obtained are largely consistent with those of the model considering FDI-GDP ratio as the dependent variable.
The aforementioned analysis highlights on the fact that certain factors are the key to attracting FDI, and policies should be designed to take into account these factors. To attract FDI, relevant trade policy reforms leading to higher degree of openness are essential. With the increased importance of globalisation, trade openness has become a key component to growth. Liberalisation of trade leads to greater specialisation and division of labour leading to higher productivity and export capabilities. Furthermore, infrastructural development is needed to attract larger FDI in an economy. A major component of infrastructure is electricity, and analysis earlier has shown that electric power consumption is strongly and positively associated with inflow of FDI. Infrastructure also includes roads and highways, railways and waterways, telecommunication services, etc. These services assist in smooth operation of the businesses and promote greater productivity with the possibility of further investment. The regression results also show that FDI is positively associated with the magnitude of domestic investment. Low or stagnant domestic investment may show lack of business confidence by the domestic investors, which may convey negative messages to the foreign investors. Therefore, government needs to improve the business environment, reduce the cost of doing business and facilitate domestic investment through eliminating policy-induced and supply-side constraints. All these have also been reflected by the regression results that a better investment profile facilitates larger inflow of FDI. It is also important to note that government's stability is a crucial issue. Two aspects of government's stability, i.e. political stability and stability in economic policies are both important. It has to be ensured that the country is not in political conflicts which can affect business operation and planning. Also, ensuring stability in economic policies with no policy reversals and continuation of progressive economic reforms is immensely important.
Dr. Selim Raihan is Professor, Department of Economics, University of Dhaka, Bangladesh, and Executive Director, South Asian
Network on Economic
Modeling (SANEM).
[email protected]
Fayeza Ashraf, Research
Associate, SANEM.
[email protected]