Abstract
The aim of this paper is to analyse the determinants of direct cross-border public procurement in the EU Member States. For this purpose, we use a unique dataset based on data published on Tenders Electronic Daily which covers public procurement contract award notices for the 2008–2012 period and consists of more than 30 variables. Among others, results of the econometric estimation suggest that the probability of awarding a contract cross-border depends positively on the value of the contract and negatively on the number of bids. Among awarding country characteristics, GDP per capita and trade-to-GDP ratio are found to positively impact the probability of a cross-border award. Our results also provide econometric evidence for predictions from the economic theory. We make the case for the importance of product market regulation indicators used as proxies for anticompetitive practices, such as regulatory protection of incumbent firms and barriers to foreign direct investment, as well as the scope of public enterprises, and show that they have a significant negative impact on the probability of a cross-border win.
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Notes
Cernat and Kutlina-Dimitrova (2015).
See also the EU’s official submission to the WTO reported under Article XIX:5 of the Government Procurement Agreement (GPA), available online at: http://www.wto.org/english/tratop_e/gproc_e/notnat_e.htm#statPro.
See Trionfetti (2000).
Tenders Electronic Daily, Supplement to the Official Journal of the European Union, accessible at http://ted.europa.eu/TED/main/HomePage.do.
See also Evenett and Hoekman (2004).
The paper does not assess the level of openness of EU public procurement markets as, due to data limitations, only data on direct cross-border procurement is available.
The raw dataset was processed so as to remove extreme values and exclude a large number of reporting errors due to non-compliance. See also Sect. 3.4.
A study on public procurement in the EU estimates the share of indirect cross-border procurement at 11.4 % in terms of the number of awards and 13.4 % in terms of value. For a detailed assessment of the magnitude and determinants of indirect cross-border procurement in the EU see Ramboll/HTW Huhr (2011).
For the classical directive see Directive 2004/18/EC of the European Parliament and of the Council of 31 March 2004 on the coordination of procedures for the award of public works contracts, public supply contracts and public service contracts. For the utilities directive see Directive 2004/17/EC of the European Parliament and of the Council of 31 March 2004 coordinating the procurement procedures of entities operating in the water, energy, transport and postal services sectors.
Crown Commercial Service (2015).
See also PwC, London Economics and Ecorys (2011).
McAffee and McMillan (1989).
See also Evenett and Hoekman (2004).
The GPA currently includes 45 WTO member countries, while another 29 countries and four international organisations participate as observers.
See also Evenett and Hoekman (2004).
It is worth pointing out that trade policy variables are not suited for this country sample as tariffs are zero among EU Member States and the variation in the remaining non-tariff barriers is too low to be statistically significant.
The negotiated free trade agreement between the EU and Canada is an exception as Canada has committed for the first time its local level procurement in a bilateral free trade agreement. See European Commission (2013).
A discussion on NAFTA and the EU-Chile agreement is available in Dawar and Evenett (2011).
Own calculations, based on the EU official submission to the WTO reported under Article XIX:5 of the GPA, Available online at: http://www.wto.org/english/tratop_e/gproc_e/notnat_e.htm#statPro.
See also Evenett and Hoekman (2005).
In this paper we estimated both: a binary logit and probit model. Note however that results of a probit model are by nature similar to the results of a logit model. The logit model, however, performed better in terms of likelihood and goodness of fit statistics. For this reason the results section reports the logit model specifications.
Thus \( \text{e}^{\upbeta } \) and \( \text{e}^{\upgamma } \) represent the multiplicative effect on the odds of increasing \( \text{X}_{\rm irt}, \text{Y}_{\text{rt}} \) by 1, holding the other independent variables constant. The multiplicative effect of \( \text{e}^{\upmu } \) of the dummy variable set and FE has to be considered with respect to the corresponding omitted dummy variable.
The removal of outliers was in line with standard statistical procedures. Although outliers could also contain meaningful economic information, here we have chosen to consider the average trends in the data. More importantly, however, we also have strong reasons to believe that many of the outliers are in fact due to errors in the automated conversion of the award notices data from PDF to database formats.
Odds ratios measure the probability of the event divided by the probability of the non-event for the average (contract) of the sample, while marginal effects depict the change in probability of the event at the margin of the dependent variable average.
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Acknowledgments
The authors would like to thank Bernard Hoekman, Susan Stone, Xosé-Luís Varela-Irimia and Lucian Cernat, as well as their colleagues in DG Trade and DG Internal Market, Industry, Entrepreneurship and SMEs of the European Commission for valuable comments and fruitful discussions.
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The opinions expressed in this paper are the authors’ own and do not necessarily reflect the views and opinions of the European Commission.
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Kutlina-Dimitrova, Z., Lakatos, C. Determinants of direct cross-border public procurement in EU Member States. Rev World Econ 152, 501–528 (2016). https://doi.org/10.1007/s10290-016-0251-3
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DOI: https://doi.org/10.1007/s10290-016-0251-3