Abstract
We analyze how service offshoring by Swedish firms is affected by corruption in source countries. The results suggest that firms avoid corrupt countries and that corruption reduces the volume of service offshoring. Analyzing firm heterogeneity, we find that large and internationalized firms are the ones that are the most sensitive to corruption. In addition, sensitivity to corruption tends to increase with falling income in source countries. These results suggest that the gains from reduced corruption may be the greatest for poor countries.
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Notes
In the year 2000, the service sector’s contribution to total value added in OECD countries was 70 %, which was approximately the service sector share for Sweden (69.4 %) in the same year. The share of services of world exports has stayed at approximately 20 % during the last two decades (Lejour and Smith 2008; UNCTAD 2009).
Acknowledging that corruption can be seen as a general index of institutional quality, Márquez-Ramos et al. (2012) showed that institutional barriers have a greater impact on trade flows than tariff barriers.
Analyzing corruption and trade, Méon and Sekkat (2006) used the World Bank governance data of Kaufman et al. (1999) and found that a low level of corruption, well-functioning rule of law, government effectiveness and lack of political violence were all positively correlated with exports in manufactured goods. Similar results were found by Bandyopadhyay and Roy (2007). Acknowledging that corruption can be viewed as a general index of institutional quality, the evidence suggests that weak institutions (a corrupt environment) hamper both inward FDI and trade.
A related literature examines taxes as a component of firm FDI decisions (Blonigen 1995; Devereux et al. 2008). However, offshoring is more concerned with sourcing inputs from an agent in a foreign jurisdiction and less concerned about investment, suggesting that taxes are less relevant for offshoring. In addition, tax data for the countries and period of interest in this analysis is not available. Therefore, the question of taxes as determinants of offshoring is left for future research.
We use firm-level data, and for an individual firm, the level of corruption and other country characteristics are likely to be taken as given. As a robustness test, we have applied the commonly used approach of lagged covariates to address endogeneity (Hendry 1995; Greenaway et al. 2008). The results are robust with respect to the use of lagged covariates. Results available on request.
Tests for the exclusion restriction indicate that these variables are valid. Bernard and Jensen (2004) used firm skill intensity to explain selection with respect to internationalization. The idea is that highly productive and skill-intensive firms are more internationalized than other firms. Similarly, exporters have overcome internationalization barriers and are therefore more likely to engage in service or production offshoring.
See the Appendix for details on the applied regions.
See the Appendix for variable definitions and sources.
Due to incomplete information on some variables for small firms, we limit the analysis to firms with at least 50 employees.
Swedish trade in services equals approximately 20 % of total trade.
Knack and Omar (2003) discuss a set of corruption indices and show that despite methodological differences, the difference between the indices is minor.
A simple correlation analysis between corruption freeness and service offshoring to different countries indicates that the correlation is just over 70 %.
More information on CEPII’s distance measure is found in Mayer and Zignago (2006).
In the Heckman specifications, variables used as exclusion restrictions, the share of skilled labor and export intensity, are highly significant, and significant results for the Mills ratio and test of independent equation (rho = 0) suggest that selection into service offshoring is not random and that the selection models are justified.
As a stability test, we estimated models with both the WB and the International Transparency corruption (IT) index giving close to identical results. Due to the greater coverage of the WB index, this is chosen as our prior choice. Estimations with the IT index are available upon request.
Since count regression techniques model the log of incident counts, the coefficients can be interpreted as follows: for a one unit change in the independent variable, the log of dependent variable is expected to change by the value of the regression coefficient.
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Karpaty, P., Tingvall, P.G. Service Offshoring and Corruption: Do Firms Escape Corrupt Countries?. J Ind Compet Trade 15, 363–381 (2015). https://doi.org/10.1007/s10842-015-0197-5
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DOI: https://doi.org/10.1007/s10842-015-0197-5