Assessing the relationship between total factor productivity and foreign direct investment in an economy with a skills shortage: the case of South Africa

This paper assesses the relationship between total factor productivity (TFP) and foreign direct investment (FDI) in a country with skills shortage. South Africa is used as a case study. Literature is inconclusive on how FDI should affect TFP. This paper shows that it is important to account for the interactivity between FDI and human capital when assessing the effects of FDI on TFP. Moreover, the empirical results show that, contrary to countries with abundance of skills, in countries with skills shortage, it is in fact the change in stock of human capital or human capital accumulation – that matters in determining the effects of FDI on TFP. Introduction Economic growth is widely considered as a primary objective of economic policy. Several studies have shown that economic growth is a prerequisite for countries to attain economic development, income redistribution, poverty reduction and full employment (Bean and Pissarides, 1993; Eriksson, 1997). The primacy of economic growth has spawned a plethora of economic models attempting to explain its drivers. The Solow (1956) growth model, commonly referred to as the exogenous growth model, outlines a theoretical growth model that suggests that the accumulation of factors of production and technological changes are the main drivers of economic growth. Moreover, in the Solow growth model, the accumulation of factors of production is subject to diminishing marginal returns and therefore reaches a steady state. In the long term, according to Solow, factors of production cannot sustain economic growth. However, technological changes, or total factor productivity (TFP), which does not embed the diminishing marginal returns characteristic, is generally considered as the main and sustained driver of long-term economic growth (Mankiw, Romer and Weil, 1992; Solow, 1957). Another important growth theory is the endogenous growth theory. In this theory, TFP is endogenously determined within the economic system and human capital, amongst other variables, and is an important determinant of TFP. Human capital refers to the stock of knowledge, creativity and experience that subsists in labour and in entrepreneurs (Romer, 1986). Assessing whether TFP is exogenous or endogenously determined is a matter for empirical analysis. While many studies in growth literature focus on determining the drivers of TFP, and make the assumption that it is in fact endogenously determined, very few studies endeavour to investigate whether TFP is in fact endogenously, or exogenously, determined. For example, Paquet and Robidoux (2001) use an ordinary least squares (OLS) regression technique to conclude the exogeneity of TFP in Canada. On the other hand, an endogeneity test in Liu and Wang (2003) concluded that TFP is in fact endogenously determined in the Chinese economic system. On balance, most studies support the endogeneity of TFP (Caves, 1974; Germidis, 1977; Haddad and Harrison, 1993; Kokko, 1994; Miller and Upadhyay, 2000; Xu, 2000; Yannikkaya, 2003). The literature foregrounds the importance of foreign direct investment among other variables, to assess the determinants of TFP (Miller and Upadhyay, 2000; Yannikkaya, 2003). For example, Kokko (1994) shows that FDI may create a channel for technological spillovers and knowledge transfers from foreign producers operating domestically to local producers, thus improving domestic TFP. However, empirical studies regarding the effects of FDI on TFP struggle to find consensus on how FDI affects TFP. Caves (1974), Kokko (1994), and Xu (2000) show that FDI positively affects TFP growth, whereas Germidis (1977), and Haddad and Harrison (1991), inter alia, show no spillovers between FDI and productivity. Other studies, such as Aitken and Harrison (1999), and Haddad and Harrison (1993), show a negative relationship between FDI and TFP growth. A number of studies show that the availability of skilled labour or human capital in the economy plays an important role on determining how FDI affects TFP (Aitken and Harrison, 1999; Germidis, 1977, inter alia). In fact, studies demonstrate the importance of the interaction between FDI and human capital in determining the effect of FDI on TFP. For example, Blomström and Kokko (2003) show that the spillover effects from FDI into host countries is constrained by the stock of human capital. Liu (2008) makes use of the endogenous growth framework to show how FDI generates externalities in the form of technology transfer necessary for economic growth. Liu shows that the spillover effect can work in the opposite direction and depends on the amount of resources devoted to human capital development in a specific economy. In light of the uncertainty over how FDI affects TFP, this paper contributes to the literature on the determinants of TFP, by showing that it is in fact the interaction between human capital accumulation and FDI that determines how FDI transmutes to technological change in an economy with a skills shortage, such as South Africa. Studies have emphasised the interaction between FDI and the stock of human capital in determining the link between FDI and TFP (Alfaro et al., 2009; Kokko, 1996). However, this paper demonstrates that in economies with skill shortage, it is in fact the change in stock of human capital – human capital accumulation – that determines the threshold effect of FDI on TFP. In fact, this paper shows that it is the extent of the growth of human capital that determines how FDI affects TFP, in a country characterised by a skills shortage. This paper also assesses whether TFP is endogenous or exogenous in South Africa. The assessment is conducted in order to investigate whether technological change is acquired or intrinsic to an economy with a skills shortage, such as the one in South Africa. Many studies allude to the fact that technology is transferred from developed to emerging or developing economies, rendering technological change exogenous in these economies (De la Potterie and Lichtenberg, 2001). South Africa experiences a serious shortage of skilled labour. This shortage impacts negatively on the country’s economic growth prospects and severely affects the country’s socioeconomic and development goals. The shortage has been largely attributed to the poor quality of education and the failure of the training system to supply the economy with much-needed skills (Allais, 2012; Rasool and Botha, 2011). While a number of studies make reference to the Chinese experience that shows that attracting FDI is an effective way of advancing technological change to host countries (Liu and Wang, 2003), this paper shows that the effect of FDI on technological change or TFP, is constrained by the capacity for growth in the rate of human capital development in an economy with a shortage of skills. This paper conducts the empirical analysis on the relationship between FDI and TFP by means of the cointegrated VAR model, which makes use of interaction variables to identify the threshold at which the effects of FDI on TFP changes. This paper demonstrates that FDI positively affects TFP in South Africa when human capital accumulates at an annual growth rate above 2.5%. Otherwise, the effects of FDI on TFP are negative. A brief outline of the methodology and presentation of the data used and results obtained is presented next, followed by a considered conclusion and pointers for further study. Methodology, data and discussion of results In order to assess the determinants of TFP and uncover the effects of FDI on TFP, this paper makes use of the cointegrated VAR model (Hansen and Johansen, 1999). Following the literature on the determination of TFP (Liu, 2008; Romer, 1997), the data used in the econometric analysis comprises the total factor productivity (TFP), the net foreign direct investment per GDP (FDI), human capital accumulation (DHC) and trade openness (OPEN). All the variables are in natural logarithm, except FDI, as the variable represents the net foreign direct investment and contains negative values. All the variables are obtained from the Penn World Table version 9 (PWT9). To maintain robustness, in addition to the TFP obtained from the PWT9, the TFP was estimated as a residual of the Cobb Douglas function, using growth accounting. Figure 1 shows that the TFP obtained from the PWT9 database (TFP) co-trend with the one obtained from the growth accounting procedure (TFP-GA). Figure 1. The trend of TFP and TFP-GA for South Africa 2.20 2.25 2.30 2.35 2.40 2.45 2.50