FDI, income inequality and poverty: a time series analysis of Portugal, 1973–2016

Abstract

Using time series data for Portugal between 1973 and 2016, this paper examines to what extent, inward FDI contributes to income inequality and poverty in the long-run. It was found that increased flows of inward FDI are associated with a less unequal income distribution and lower poverty rates. The results further suggest that, in the Portuguese case there is mutual causality between inward FDI and poverty in the long run, i.e., FDI significantly reduces poverty, and lower levels of poverty lead to higher inward FDI flows. In the case of inequality, the evidence shows that FDI does not contribute to higher (or lower) income inequality. Instead, more unequal income distributions significantly and negatively impact on inward FDI in the long run. Finally, human capital emerged as a key determinant to mitigate income inequality and circumvent poverty, contributing, indirectly, to fostering additional FDI inflows. Such results call for integrated public policy interventions that emphasize social and institutional dimensions.

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Notes

  1. 1.

    Mah (2012) analyzed the FDI-inequality nexus, but not the FDI-poverty nexus, for South Korea, a high-income country by today’s standards. However, in 13 out of 20 years analyzed by Mah (2012), South Korea was classified as upper middle-income and not high-income country.

  2. 2.

    In the Annex, Tables 10 and 11 present an organized selection of studies on FDI and Inequality/ Poverty, respectively, with a focus on the Portuguese economy. This selection shows that the literature on Portugal and FDI has not addressed inequality/poverty issues (except for the micro level studies by Martins 2004, 2011), whereas the vast and diverse literature on inequality and poverty has overlooked the topic of FDI.

  3. 3.

    The Gini index is an economic measure of income inequality, based on Lorenz Curve, ranging from a minimum of 0 (perfect equality in income distribution) to 1 (or 100) (total inequality, where only one individual has gained all the income). The poverty rate, or more correctly, at-risk-of-poverty rate represents the share of persons with an equivalized disposable income below the at-risk-of-poverty threshold (which is set at 60% of the national median equivalized disposable income), after social transfers.

  4. 4.

    Single-country studies whose unit of analysis is the company, the industry or the region are not object of review. For relevant comprehensive reviews, see Ma (2013), Wood (2018), and Cavanaugh and Breau (2018).

  5. 5.

    Given the low number of studies obtained, we complemented the search through a snowball procedure based on the references of other empirical studies. We found some additional, but still very few studies through this method. After reading them, we decided to exclude them from this review due to their questionable scientific quality (the journals where these papers were published are likely to be classified as predatory, according to Beall’s List – see https://beallslist.weebly.com/).

  6. 6.

    According to the World Bank list (June 2018), in http://databank.worldbank.org/data/download/site-content/CLASS.xls, last accessed in August 2018.

  7. 7.

    According to the World Bank Analytical Classifications, South Korea last entered the high-income category in 2001.

  8. 8.

    The full dataset used for the estimation in Table 12 in Annex.

  9. 9.

    It is thus important to separate the situations in which inequality increases because some get richer and some poorer, from those where some get richer, but no one gets poorer (as the theory of international trade predicts if the necessary income transfers are made). We acknowledge one of the referees for underlying this issue.

  10. 10.

    For poverty the VAR and testing procedures would be analogous.

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Acknowledgments

The authors would like to thank Margarida Duarte (the associate editor) and two anonymous referees for constructive criticism and helpful suggestions. The authors also acknowledge the valuable remarks of Margarida Mello and Natércia Fortuna. Responsibility for any errors rests exclusively with the authors.

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Annex

Annex

Table 10 A selection of studies on FDI and Portugal
Table 11 A selection of studies on Inequality/ Poverty and Portugal
Table 12 Time series used to compute relevant variables
Table 13 Long-term relations of inequality-FDI and poverty-FDI, Portugal, 1990–2016
Fig. 6
figure6

Logarithm of the variables in levels and 1st differences

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Teixeira, A.A.C., Loureiro, A.S. FDI, income inequality and poverty: a time series analysis of Portugal, 1973–2016. Port Econ J 18, 203–249 (2019). https://doi.org/10.1007/s10258-018-00152-x

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Keywords

  • FDI
  • Inequality
  • Poverty
  • Portugal
  • Johansen cointegration
  • Granger (non-) causality

JEL classifications

  • D63
  • I32
  • F30
  • O52
  • C32