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Erschienen in: Public Choice 3-4/2020

18.12.2019

The determinants of cross-border corruption

verfasst von: Laarni Escresa, Lucio Picci

Erschienen in: Public Choice | Ausgabe 3-4/2020

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Abstract

We reconsider the question of what determines corruption at the cross-national level, using new methods and data: observations of occurrences of cross-national corruption. We find that economic development and a small population is associated with lower levels of corruption, as are freedom of the press, political rights, the presence of established democratic institutions, the salience of women’s role in society, and low exports of natural resources such as oil. The particular structure of the data also allows for the first time to consider the “relational aspects” of corrupt relationships, which come to the fore when parties to the corrupt transaction, the briber and the bribee, reside in different countries. Overall, we find limited evidence that the relational factors that we consider affect corruption, beyond the effects that they often have on bilateral trade.

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Fußnoten
1
See, for reviews, Lambsdorff (2006), Treisman (2007, 2015) and Klitgaard (2017).
 
2
Victimization statistics, obtained from surveys aimed at eliciting information on bribes being paid, have been used more rarely in the relevant studies. On their shortcomings, see Treisman (2007) and Kraay and Murrell (2016).
 
3
Brewster (2017) provides a convincing explanation of the main drivers of FCPA enforcement. For the determinants of the overall enforcement of the OECD’s Anti-Bribery Convention by signatories other than the United States, see Kaczmarek and Newman (2011) and Choi and Davis (2014). To date, 44 countries have signed the Convention, eight of which are non-OECD countries.
 
4
We refer to the probability that a corrupt transaction is observed once it has occurred. On the other hand, the total number of corrupt transactions associated with a given foreign country obviously depend on that country’s characteristics. The “equal treatment assumption” corresponds to Assumption 1 in Escresa and Picci (2017, Appendix A), where its role is considered in guaranteeing the validity of their measure of corruption.
 
5
The Poisson estimator is applied frequently in the international trade literature to datasets with structures similar to ours (following Silva and Tenreyro 2006). The known presence of convergence problems led us to use the Windmeijer and Silva (1997) version of the estimator—as implemented in the PPML routine in Stata. The occurrence of zeros in the dependent variable might have suggested the use of a zero-inflated formulation of the Poisson model. However, the determination of the presence of corrupt exchanges between two countries, vis a vis their intensity, do not seem to be two logically distinct problems, as is somehow implied when estimating such an empirical model. The results might suffer from various forms of endogeneity, which is notoriously difficult to treat because of the dubious validity—or strength-of a rather long list of candidate instruments that have been proposed. See Treisman (2007) for IV results using perception-based (and also experience-based) measures, and for some comments on the broader issue of finding suitable instruments.
 
6
The determinants of the enforcement of the Convention (or of the FCPA) are not directly relevant and beyond the scope of our study. See for instance, Kaczmarek and Newman (2011) on how FCPA prosecution of non-US corporations might have pushed foreign countries to comply better with the Convention, and Brewster (2017) on how US compliance with the FCPA improved following the adoption of the Convention. Choi and Davis (2014), on the other hand, present an analysis that is conditional on FCPA enforcement, focusing on the level of sanctions.
 
7
Several factors influencing the way in which corruption cases are judged, together with the criterion of presumption of innocence, likely lead to many false negatives, thus providing a further justification for considering cases regardless of their outcomes (that is, including acquittals).
 
8
We cannot rule out the possibility that countries co-ordinate to carry out such industry-, or country-, “sweeps”, but we are not aware of any evidence pointing to the presence such complex form of international coordinated action. We are grateful to Matthew Stephenson for pointing out this and other possible departures from the equal treatment assumption.
 
9
For several of the variables, we observe large partial correlation, which might lead to multicollinearity. In interpreting the signs of the correlations between variables, attention should be paid to how they are defined (see the Data Appendix). For example, for Democracy, higher values correspond to “more”, whereas for Freedom of the press the opposite holds.
 
10
Treisman (2007) also considers a series of control variables representing historical characteristics of countries, such as their legal origin or colonial past. He finds that entering them does not influence the qualitative results for the other variable of interests. Also, the abundance of fixed effects in our model creates problems in identifying too many time-invariant variables – an issue that is familiar in the international trade literature.
 
11
Our results do not suffer from the sample bias suggested in Knack and Azfar (2003), since the availability of the dependent variable is not conditional on levels of corruption.
 
12
Giana Mildred, Santos Lim and Lorenzo Crippa contributed to different updates of the dataset.
 
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Metadaten
Titel
The determinants of cross-border corruption
verfasst von
Laarni Escresa
Lucio Picci
Publikationsdatum
18.12.2019
Verlag
Springer US
Erschienen in
Public Choice / Ausgabe 3-4/2020
Print ISSN: 0048-5829
Elektronische ISSN: 1573-7101
DOI
https://doi.org/10.1007/s11127-019-00764-7

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