Foreign Direct Investment and Income Distribution: Evidence from Post-Communist New EU Member States

ABSTRACT

This article gives insight into the influence of FDI on income distribution in post-communist new EU member states. Using the method of seemingly unrelated regressions on panel data from 1990–2014, we find robust evidence of a nonlinear relationship between FDI and income distribution. The observed FDI effect varies by income shares. In the case of the bottom 50% income share, the impact of FDI on income concentration is homogeneous and negative; for the middle 40%, FDI first increases and then reduces its income share, whereas for the top 10% this effect is first negative and then positive.

KEYWORDS:

• foreign direct investment
• income distribution
• post-communist economies
• transition

JEL Classification:

• D31
• F21

Acknowledgments

This research was presented at the conference Economic Turmoil in Contemporary Europe III (29–30th November 2018, Warsaw, Poland). We would like to thank the organizers and audience for stimulating discussions and the anonymous referees for helpful comments and suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. Although labor shares are faced with a secular downward trend, they still account for the largest part of total income. For example, in 2013, the average labor share in the OECD countries was 68% (OECD 2018), while in the new member EU countries, in the period 1998– 2012, this share was 58.8% (Parisi 2017).

2. For more about the link between nomenklatura and income distribution in transition countries, see Milanovic (1998) or Beck and Laeven (2005).

3. Although there are differences between countries, the first period of transition refers to approximately from 1989 until the mid-1990s, the second period from the mid-1990s until the period before accession to the EU, while the post-transition period refers to the period after accession to the EU.

4. As a proxy of brownfield FDI, we use data on cross-border mergers and acquisitions. Data are taken from UNCTAD’s World Investment Report (various years). Given that data on greenfield FDI are not available for the whole analyzed period in UNCTAD’s database, we calculate it by subtracting cross-border mergers and acquisitions from FDI inflows (the same approach was used by Calderón, Loayza, and Servén (2004)).

5. The estimated coefficient of the squared term of FDIstock is not statistically significant and has the same sign as FDIstock in the bottom 50% equation, so that we do not keep FDIstock² in the first regression.

6. The income shares (dependent variables) we used in our model are calculated on the basis of disposable (post-tax and post-transfer) income.