Causal Relationship between Foreign Direct Investment and Economic Growth: Evidence from Turkey

Causal Relationship between Foreign Direct Investment and Economic Growth: Evidence from Turkey

Hasan Bakır (Uludağ University, Turkey) and Filiz Eryılmaz (Uludağ University, Turkey)
DOI: 10.4018/978-1-4666-7288-8.ch020


In this chapter, the authors investigate the causality relationship between the inflows of foreign direct investment (FDI) and economic growth as measured by Real Gross Domestic Product (GDP) per capita in Turkey during the period 1974-2012 by using the Granger causality tests. The causality test indicates that economic growth Granger-causes FDI. This means that there is bidirectional causality from Reel GDP to FDI in Turkey. So the author results support “the growth – driven FDI hypothesis”. This demonstrates that in the related time in Turkey, more direct foreign investment entered the economy together with an increase in economic growth.
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Most economists, politicians and international financial institutions assert that foreign direct investment (FDI) is a keystone in solving economic problems of emerging market economies (Mencinger, 2003: 491). Foreign direct investment can be thought as a factor which can be improve countries’ economies and which it can find a solution to economic problems in developing countries. Economic growth is accreted by capital formation and technological development in domestic countries. In this way, governments of domestic countries use their public funds to attract FDI (Moura & Forte, 2009: 2; Agrawal & Khan, 2011: 71). After 1980s, most developing economies reduced restriction on crucial areas such as trade and finance. By doing that, foreign direct investment easily comes into domestic economy, which can be defined as an inflow. Money inflows to developing economies increased in 1990s and FDI becomes 60 percent of private capital flows in 2000s (Carkovic & Levine 2002: 1).

Although the effect of FDI on economic growth is studied, it has not been created a consensus yet. Some theorists predict that FDI may boost economic growth via technological transfer and business know-how to poorer countries and this process ensure spillover effects for the economy. On the other hand, some theorists do not agree with this view (Aitken & Harrison (1999), Haddad & Aitken (1993), and Mencinger (2003)) and some theorists think that FDI flow affects growth under certain policy conditions (Borensztein et al., (1998), Blomstrom et al., (1994), Alfaro et al., (2004), Moura and Forte (2009)) (Cakovic & Levinie, 2002:1-2; Antwi et al., 2013). For instance, countries with beter developed financial markets will attract for FDI (Soumare & Tchana, 2011: 6). Therefore, the theory related to economic development and FDI is ambiguous.

The positive effect of FDI on economic growth is expected through accumulation of capital and knowledge in domestic country and these factors increase total factor productivity. Transfer of new technologies and know-how, qualified human resources, integration in global markets are required for economic growth in domestic country (Moura & Forte, 2009: 3-4). In literature this views seen as a “FDI led growth hypothesis”. According to this view FDI may enhance the factors such as human capital, technology and investments which are playing an important role in promoting economic development.

As endogenous model suggest that FDI enhance economic growth by diffusing technology from developed countries to developing countries, on the other hand FDI is an important source for domestic investments by providing capital. Therefore, it can be said that FDI fill in the gap of technology and capital stock (Ilgun et al., 2010). FDI helps developing countries to import the necessary technology from abroad. The transfer of technology to firm, including transfer of general knowledge, specific technologies in production and work experience for the labor force, would be difficult, risky and expensive without it. Many externalities coming from FDI make a great contribution to domestic country’s economy and affect its competitiveness by raising productivity (Antwi et al., 2013: 18-19).

Key Terms in this Chapter

Economic Growth: An increase in the capacity of an economy to produce goods and services, compared from one period of time to another. Economic growth can be measured in nominal terms, which include inflation, or in real terms, which are adjusted for inflation. For comparing one country's economic growth to another, GDP or GNP per capita should be used as these take into account population differences between countries.

Time Series Analysis: Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series forecasting is the use of a model to predict future values based on previously observed values. While regression analysis is often employed in such a way as to test theories that the current values of one or more independent time series affect the current value of another time series, this type of analysis of time series is not called “time series analysis”, which focuses on comparing values of a single time series at different points in time.

Granger Causality Test: Granger causality is a statistical concept of causality that is based on prediction. According to Granger causality, if a signal X1 “Granger-causes” a signal X2, then past values of X1 should contain information that helps predict X2 above and beyond the information contained in past values of X2 alone. Its mathematical formulation is based on linear regression modeling of stochastic processes. More complex extensions to nonlinear cases exist, however these extensions are often more difficult to apply in practice.

Unit Root Test: In statistics, a unit root test tests whether a time series variable is non-stationary using an autoregressive model. A well-known test that is valid in large samples is the augmented Dickey–Fuller test.

Augmented Dickey–Fuller Test (ADF): In statistics and econometrics, an augmented Dickey–Fuller test (ADF) is a test for a unit root in a time series sample. It is an augmented version of the Dickey–Fuller test for a larger and more complicated set of time series models. The augmented Dickey–Fuller (ADF) statistic, used in the test, is a negative number. The more negative it is, the stronger the rejection of the hypothesis that there is a unit root at some level of confidence.

Financial Market: A financial market is a market in which people and entities can trade financial securities, commodities, and other fungible items of value at low transaction costs and at prices that reflect supply and demand. Securities include stocks and bonds, and commodities include precious metals or agricultural goods.

Foreign Direct Investment: Foreign direct investment (FDI) is a direct investment into production or business in a country by an individual or company of another country, either by buying a company in the target country or by expanding operations of an existing business in that country. Foreign direct investment is in contrast to portfolio investment which is a passive investment in the securities of another country such as stocks and bonds.

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