Does corruption matter for FDI flows in the OECD? A gravity analysis

Abstract

In this paper, the effect of corruption on foreign direct investment (FDI) flows is analyzed. The literature is thus far divided regarding the effects of corruption: One hypothesis argues that corruption greases the wheels of government and is therefore beneficial while the other hypothesis argues that it sands the wheels of government leading to suboptimal results in an economy. For the empirical analysis, a dataset consisting of bilateral FDI data from the OECD and the control of corruption measure from the World Governance Indicators of the World Bank is compiled. To further analyze the effects of corruption the Panama Papers revelation is used as a corruption increasing event and the implementation into law of the OECD Anti-Bribery Convention is used as a corruption decreasing event. Finally, the difference between corruption levels in the target and the origin country, will be examined. Then, a gravity model with dyadic and time-fixed effects is employed to analyze the data. Findings are ambiguous in that corruption is positively correlated with FDI inflows in the target country and negatively correlated with FDI inflows in the origin country. The Panama Papers variable shows strong evidence, that the release of the Panama Papers resulted in a drop in FDI flows. Therefore, it seems that corruption has complex country specific effects and that target and source countries have to adopt varying policies with regards to corruption. The general effect of corruption harms FDI flows, as shown by the Panama Papers revelation.

FDI propensity and geo-cultural interaction in former Yugoslavia: pairwise analysis of origin and destination countries

“…3 Observations by Bitzenis ( 2004 ) about the importance of European integration renders it unsurprising that the only major non-European origin is the United Arab Emirates (UAE), while Russia and Turkey straddle Europe and Asia. Table 1 is consistent with the gravity model’s premise that geographic proximity helps explain the locations chosen by MNEs (Kleinert & Toubal, 2010 ; Zander, 2021 ).…”

“…Following Bandelj ( 2002 ), robust approaches should include relational features that either link or separate the origin and destination countries, thereby facilitating or inhibiting FDI. Examples of relational features include geographic distance (Bitzenis, 2004 , 2016 ), cultural similarities (Bitzenis, 2004 ; Jaklić & Svetličić, 2016 ), and relative corruption (Zander, 2021 ).…”

“…Additional relational measures facilitating FDI include similarity in corruption levels (Habib & Zurawicki, 2002 ; Bitzenis, 2006 ; Bojnec and Fertö, 2018 ; Cieślik, 2020 ; Zander, 2021 ). Pairs of countries might be highly transparent (low corruption levels, like in Denmark and Canada) or highly corrupt (Russia and Bulgaria).…”

“…Additional relational measures facilitating FDI include similarity in corruption levels (Habib & Zurawicki, 2002;Bitzenis, 2006;Bojnec and Fertö, 2018;Cieślik, 2020;Zander, 2021). Pairs of countries might be highly transparent (low corruption Bitzenis (2004), Kekic (2005) (−) High risk countries as well as their unstable neighbors discourage FDI Corruption Habib and Zurawicki (2002), Bitzenis (2006), Bojnec and Fertö (2018), Zander (2021) (−) Firms seek familiar levels of transparency, ( +) Bitzenis observes firms from corrupt countries seek opportunities in other corrupt countries levels, like in Denmark and Canada) or highly corrupt (Russia and Bulgaria). In each case, an MNE's familiarity with business practices at a destination can make FDI more likely to occur (Bitzenis, 2006;Bojnec and Fertö, 2018).…”

Non-linear ADRL estimation of corruption and FDI inflow to Ghana

“…The West African regional bloc is widely diversified across various relevant matrices (Nageri and Gunu, 2020). The evidence that FDI inflow reacts differently to distinctive social, demographic and cultural variables (Cuervo-Cazurra, 2006; Sambharya and Rasheed, 2015; Jiménez et al , 2017) led Zander (2021) to provide a compelling case for country-based studies about the relationship between corruption and FDI with his assertion that corruption has “complex country-specific effects” regarding the adoption of varying policies. Zangina and Hassan (2020) also confirm the country-specific nature of corruption.…”