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Review of Middle East Economics and Finance

Ed. by Dibeh, Ghassan / Assaf, Ata / Cobham, David / Hakimian, Hassan / Henry, Clement M.

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1475-3693
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Do Developing Countries Benefit from Foreign Direct Investments? An Analysis of Some Arab and Asian Countries

Weshah A. Razzak / El M. Bentour
Published Online: 2013-12-12 | DOI: https://doi.org/10.1515/rmeef-2012-0031

Abstract

In addition to the widely-believed positive effects on growth, employment, and wages, foreign direct investments (FDI) are often perceived as sources of funds for development. Developing countries, especially low income and emerging economies, welcome FDIs because of their favorable budgetary implications. All of this resulted in increasing global FDIs. We discuss some specification and estimation problems that might affect the estimation of the rate of returns on FDI, and provide new figures for a number of FDI-receiving Arab countries. We compare the results to those of some Asian countries, and discuss the policy implications. There is evidence that Arab countries have, relatively, benefited from their efforts to open their economies, to reform their institutions and to attract FDIs.

Keywords: rate of return on FDI; estimation and specification problems; panel data

JEL Classifications: C13; C14; C21; C23; C26; O24

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About the article

Published Online: 2013-12-12


Rugman (1980) provides a number of examples.

For example see Balasubramanyam, Salisu, and Sapsford (1996) and Kawai (1994) on trade-FDI-growth. Carkovic and Levine (2002) found the effect of FDI on growth is not robust in the presence of openness of trade. Carkovic and Levine (2002) had an interaction term of per capita income and FDI and reports no growth effect. Alfaro et al. (2007) argue that FDI has significant growth effect in countries with relatively more developed financial markets. See also Aitken and Harrison (1999), Haddad and Harrison (1993), and Mansfield and Romeo (1980). The main problem in this literature apparently is an estimation problem pointed out by Carkovic and Levine (2002) and that is not taking into account simultaneity bias, country-specific effects, and the use of lagged dependent variables in growth regression.

There is a literature on estimating the rate of return on investments in human capital and research and development, see Wieser (2007) for a survey of the literature.

The concept of thick-modeling was first introduced by Granger and Yongil (2004).

The Cobb-Douglas Production function is , subscripts aside at this stage, is real output, is a constant exogenous technical progress, is the stock of physical capital, is labor input, and is the error term, which has classical properties. To account for FDI in the production function we assume that the effective stock of capital consists of , which denotes the domestic stock of capital, and , which is the foreign stock of capital, i.e. FDI stock. The production function would have an extra term , where is the rate of disembodied technical change. If the data have unit roots this linear time trend would be a misspecification issue. If, however, we find the data to be trended, but the trend is not stochastic we would have to have this linear trend term back in the specification. It is, however, extremely difficult to discern one from the other.

It would be important to include a measure of the quality of human capital too. Measurement of quality is tricky. There are some data, but the time series are short. Future research must take this variable into account.

The Jorgenson and Fraumeni (1992) method constructs a stock of human capital, which is based on lifetime earnings.

Jallab, Gbakou, and Sandretto (2008) is the only paper we are aware of on the issue of FDI and growth in the Arab countries using a proper estimation technique.

We use panel cointegration tests, the Johansen-Fisher test found in Maddala and Wu (1999), Kao’s (1999) residual test, and Pedroni’s (1999, 2004) residual test. The latter includes a number of tests, which allow for heterogeneous slope coefficients to vary across the panel (the panel v-test, panel test, panel Phillips-Perron test, panel ADF test, group test, group Phillips-Perron test and group ADF test). The null hypothesis is that the residuals are I(1) – no cointegration – and the alternative hypothesis is that the residuals are I(0). For the first 4 tests, the assumption is that under the alternative hypothesis, the residuals have a common AR coefficient. In the remaining 3 tests, the assumption is that the residuals under the alternative hypothesis have an individual AR coefficient. Kao (1999) test is similar to Pedroni’s test in principle, i.e. a residual-based test, but there are cross-section specific intercepts and homogenous coefficients in the first-stage regressors. The null hypothesis is that the residuals are I(1). The Maddala and Wu (1999) Johansen test is similar to Johansen’s time series tests, i.e. a maximum eigenvalue test.

Only the Pedroni (2004) test(s) for the Asian panel has high the p values.

We use a variety of common test statistics such as the Dickey-Fuller (1979), the ADF test, Said and Dickey (1984; Phillips and Perron (1988), and Elliot (1999). We also use different specifications (with and without trend), and test the lag structure using various testing criteria. We also tested the panel of the five countries for a unit root using a variety of common tests such as Levin, Lin, and Chu (2002), Breitung (2000), Im, Pesaran, and Shin (2003), Hadri (2000), Sarno and Taylor (1998) and Taylor and Sarno (1998).

We regress each of the three explanatory variables on a constant and the set of instruments, retrieve the residuals and then estimate the equations with the residuals as additional regressors. We test the hypothesis that the set of the coefficients of the residuals are zero using both F and Chi-squared.

The GMM estimator minimizes with respect to the coefficients matrix for a chosen weighting matrix where ; and is a matrix of instruments.

We found that the p values of the F statistics of the first-stage 2SLS estimator to be very significant, 0.0000 for all six regression specifications for the Arab and the Asian panels. Thus, there is a strong correlation between the instruments and the endogenous variables. See Baum and Schaffer (2003).

We do not use dynamic GMM (Arellano and Bond 1991; Arellano and Bover 1995 and Blundell and Bond 1999) because we are (1) interested in the long-run point elasticity to compute the rate of returns, and (2) because we have a short panel, i.e. N is small.

We also allowed the share of human capital to vary across countries, but we do not report the results to save space. The results are available upon request. We found the coefficient estimate to be insignificant for Algeria. We also found the coefficient estimate to be negative for Jordan and Morocco. A number of papers on growth-FDI seem to report negative coefficients for FDI or human capital in similar specifications (see for example, Kottaridi and Stengos (2010); Varum et al. (2011) and Borensztein, De Gregorio, and Lee (1998)). Finally we found the coefficient to be positive, sizable, and significant for Egypt and Tunisia.

Independent calculations of the ratios of gross operating surplus to GDP from National Income Accounts also reveal similarly high values. These estimates are between 0.35 and 0.78 depending on the specification.

We re-estimated the regressions (GMM) and fixed the coefficient for all Arab countries. The estimated elasticity (is an average elasticity across all Arab countries) is 0.22%.

This coefficient measures the distance from a constant returns to scale. There are different interpretations to this negative value. One is that the production function exhibits a decreasing return-to-scale. This suggests that the Arab markets are small, thus doubling output is costly and requires more than doubling inputs. It could also mean that output in the Arab markets is consistently priced below marginal cost. Basu and Fernald (1997) suggest that this interpretation and decreasing returns to scale sounds illogical for a profit-maximizing firm. However, there is evidence that the majority of firms in the Arab countries are small in size with negative value added, hence non-profitable firms, Alkawaz (2006). Of course a positive value means that the function exhibits an increasing return to scale.

Quantile regressions failed to produce any sensible results for Asia, which may indicate that distributional nonlinearity is insignificant.

A measure of cognitive skills as a proxy for the quality of human capital is found in Trends in International Math and Science (TIMSS), which is an international student’s assessment survey and reports country scores for students in 4th and 8th grades in more than 80 countries, every four years. In the first survey in 1995, the scores for Algeria, Egypt, Jordan, Morocco, and Tunisia were 394.15, 420.40, 439, 372.36, and 439 respectively. In the last published survey in 2007, these scores declined in all countries except Jordan, 381.75, 399.5, 454.5, 319, and 377 respectively. While Korea’s score increased from 568 in 1995 to 575 in 2007, both Thailand’s and Malaysia’s scores declined from 505.5 and 462 in 1995 to 472.5 and 456 in 2007 respectively.

Razzak (2010) estimated a CES production function using cross sectional data of thousands of observations for firms in Egypt, Lebanon, Morocco and Turkey.


Citation Information: Review of Middle East Economics and Finance, Volume 9, Issue 3, Pages 357–388, ISSN (Online) 1475-3693, ISSN (Print) 1475-3685, DOI: https://doi.org/10.1515/rmeef-2012-0031.

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