Rủi ro tham nhũng trong các thị trường đấu thầu: cái nhìn từ khoa học mạng
Tóm tắt
Chúng tôi sử dụng các phương pháp từ khoa học mạng để phân tích rủi ro tham nhũng trong một tập dữ liệu hành chính lớn với hơn 4 triệu hợp đồng mua sắm công từ các quốc gia thành viên Liên minh Châu Âu, bao gồm các năm 2008–2016. Bằng cách lập bản đồ các thị trường mua sắm dưới dạng các mạng lưới hai phía bao gồm các tổ chức phát hành và người thắng thầu hợp đồng, chúng tôi có thể hình dung và mô tả sự phân bố của rủi ro tham nhũng. Chúng tôi nghiên cứu cấu trúc của những mạng lưới này ở từng quốc gia thành viên, xác định các lõi của chúng và nhận thấy rằng những thị trường tập trung cao thường có rủi ro tham nhũng cao hơn. Ở tất cả các quốc gia EU mà chúng tôi phân tích, rủi ro tham nhũng được phân bố một cách đáng kể. Tuy nhiên, những rủi ro này đôi khi phát sinh nhiều hơn ở lõi và đôi khi ở ngoại vi của thị trường, tùy thuộc vào quốc gia. Điều này gợi ý rằng cùng một mức độ rủi ro tham nhũng có thể có các phân bố hoàn toàn khác nhau. Khung phân tích của chúng tôi vừa mang tính chuẩn đoán vừa mang tính đề xuất: Nó chỉ ra nơi mà tham nhũng có khả năng xảy ra phổ biến trong các thị trường khác nhau và gợi ý rằng các chính sách chống tham nhũng khác nhau là cần thiết cho các quốc gia khác nhau.
Từ khóa
Tài liệu tham khảo
Scott, J.C.: Seeing Like a State: How Certain Schemes to Improve the Human Condition Have Failed. Yale University Press, New Haven (1998)
Pappalardo, L., Vanhoof, M., Gabrielli, L., Smoreda, Z., Pedreschi, D., Giannotti, F.: An analytical framework to nowcast well-being using mobile phone data. Int. J. Data Sci. Anal. 2(1–2), 75 (2016)
Kim, G.H., Trimi, S., Chung, J.H.: Big-data applications in the government sector. Commun. ACM 57(3), 78 (2014)
Mungiu-Pippidi, A.: The Quest for Good Governance: How Societies Develop Control of Corruption. Cambridge University Press, Cambridge (2015)
Rodríguez-Pose, A., Di Cataldo, M.: Quality of government and innovative performance in the regions of europe. J. Econ. Geogr. 15(4), 673 (2014)
Stockemer, D., LaMontagne, B., Scruggs, L.: Bribes and ballots: the impact of corruption on voter turnout in democracies. Int. Polit. Sci. Rev. 34(1), 74 (2013)
Gupta, S., Davoodi, H., Alonso-Terme, R.: Does corruption affect income inequality and poverty? Econ. Gov. 3(1), 23 (2002)
Hawken, A., Munck, G.L.: Do you know your data? Measurement validity in corruption research. Technical report, Working paper - School of Public Policy, Pepperdine University (2009)
Radermacher, W.J.: Official statistics in the era of big data opportunities and threats. Int. J. Data Sci. Anal. 6(3), 225 (2018)
OECD.Stat.: Government at a glance—2017 edition: public procurement. https://stats.oecd.org/Index.aspx?QueryId=78413. Accessed 08 Sept 2018 (2017)
Fazekas, M., Tóth, I.J.: From corruption to state capture: a new analytical framework with empirical applications from Hungary. Polit. Res. Q. 69(2), 320 (2016)
Klašnja, M.: Corruption and the incumbency disadvantage: theory and evidence. J. Polit. 77(4), 928 (2015)
Charron, N., Dahlström, C., Fazekas, M., Lapuente, V.: Careers, connections, and corruption risks: investigating the impact of bureaucratic meritocracy on public procurement processes. J. Polit. 79(1), 89 (2017)
Watts, J.: Operation car wash: is this the biggest corruption scandal in history. The Guardian 1(06), 2017 (2017)
Ribeiro, H.V., Alves, L.G., Martins, A.F., Lenzi, E.K., Perc, M.: The dynamical structure of political corruption networks. J. Complex Netw. 6, 989–1003 (2018)
Calderoni, F.: In: Third Annual Illicit Networks Workshop. (Équipe de recherche sur la délinquance en réseau, 2011), pp. 1–21
Krebs, V.E.: Mapping networks of terrorist cells. Connections 24(3), 43 (2002)
Saracco, F., Di Clemente, R., Gabrielli, A., Squartini, T.: Detecting early signs of the 2007–2008 crisis in the world trade. Sci. Rep. 6, 30286 (2016)
Hidalgo, C.A., Klinger, B., Barabási, A.L., Hausmann, R.: The product space conditions the development of nations. Science 317(5837), 482 (2007)
Mamei, M., Pancotto, F., De Nadai, M., Lepri, B., Vescovi, M., Zambonelli, F., Pentland, A.: Is social capital associated with synchronization in human communication? An analysis of italian call records and measures of civic engagement. EPJ Data Sci. 7(1), 25 (2018)
Stadtfeld, C.: The Micro–Macro Link in Social Networks. Emerging Trends in the Social and Behavioral Sciences: An Interdisciplinary, Searchable, and Linkable Resource, pp. 1–15 (2015)
Murdoch, T.B., Detsky, A.S.: The inevitable application of big data to health care. JAMA 309(13), 1351 (2013)
Sinatra, R., Wang, D., Deville, P., Song, C., Barabási, A.L.: Quantifying the evolution of individual scientific impact. Science 354(aaf6312), 5239 (2016)
Pappalardo, L., Pedreschi, D., Smoreda, Z., Giannotti, F.: In: 2015 IEEE International Conference on Big Data (Big Data). IEEE, pp. 871–878 (2015)
Szell, M.: Crowdsourced quantification and visualization of urban mobility space inequality. Urb. Plan. 3(1), 1 (2018)
Hilbert, M.: Big data for development: a review of promises and challenges. Dev. Policy Rev. 34(1), 135 (2016)
Connelly, R., Playford, C.J., Gayle, V., Dibben, C.: The role of administrative data in the big data revolution in social science research. Soc. Sci. Res. 59, 1 (2016)
Transparency International, Transparency international corruption perceptions index. Technical report. Data retrieved from https://www.transparency.org/research/cpi/overview
The World Bank. World bank worldwide governance indicators. Data retrieved from https://info.worldbank.org/governance/wgi/index.aspx#home
Heywood, P.M., Rose, J.: “close but no cigar”: the measurement of corruption. J. Public Policy 34(3), 507 (2014)
Coppedge, M., Gerring, J., Lindberg, S.I., Skaaning, S.E., Teorell, J., Altman, D., Andersson, F., Bernhard, M., Fish, M.S., Glynn, A. et al.: V-dem codebook v8 . Data retrieved from https://www.v-dem.net/en/reference/version-8-apr-2018/ (2017). Accessed 1 May 2019
Charron, N., Dijkstra, L., Lapuente, V.: Regional governance matters: quality of government within European Union member states. Reg. Stud. 48(1), 68 (2014)
Cameron, L., et al.: Propensities to engage in and punish corrupt behavior: experimental evidence from Australia, India, Indonesia and Singapore. J. Public Econ. 93(7–8), 843 (2009). https://doi.org/10.1016/j.jpubeco.2009.03.004
Weisel, O., Shalvi, S.: The collaborative roots of corruption. Proc. Natl. Acad. Sci. 112(34), 10651 (2015). https://doi.org/10.1073/pnas.1423035112
Olken, B.A.: Monitoring corruption: evidence from a field experiment in indonesia. J. Polit. Econ. 115(2), 200 (2007)
Goel, R.K., Nelson, M.A.: Measures of corruption and determinants of us corruption. Econ. Gov. 12(2), 155 (2011)
Kornberger, M., Meyer, R.E., Brandtner, C., Höllerer, M.A.: When bureaucracy meets the crowd: studying “open government” in the Vienna City Administration. Organ. Stud. 38(2), 179 (2017)
Bertot, J.C., Jaeger, P.T., Grimes, J.M.: Using icts to create a culture of transparency: E-government and social media as openness and anti-corruption tools for societies. Gov. Inf. Q. 27(3), 264 (2010)
Borisov, A., Goldman, E., Gupta, N.: The corporate value of (corrupt) lobbying. Rev. Financ. Stud. 29(4), 1039 (2015)
Garcia-Bernardo, J., Fichtner, J., Takes, F.W., Heemskerk, E.M.: Uncovering offshore financial centers: conduits and sinks in the global corporate ownership network. Sci. Rep. 7(1), 6246 (2017)
Prosperi, M., Buchan, I., Fanti, I., Meloni, S., Palladino, P., Torvik, V.I.: Kin of coauthorship in five decades of health science literature. Proc. Natl. Acad. Sci. 113(32), 8957 (2016)
Fazekas, M., Tóth, I.J., King, L.P.: An objective corruption risk index using public procurement data. Eur. J. Crim. Policy Res. 22(3), 369 (2016)
Bergh, A., Erlingsson, G., Gustafsson, A., Wittberg, E.: Municipally owned enterprises as danger zones for corruption? How politicians having feet in two camps may undermine conditions for accountability. Public Integr. 21(3), 320 (2019)
Wachs, J., Yasseri, T., Lengyel, B., Kertész, J.: Social capital predicts corruption risk in towns. R. Soc. Open Sci. 6(4), 182103 (2019)
Fazekas, M., Ferrali, R., Wachs, J.: Institutional quality, campaign contributions, and favouritism in us federal government contracting. GTI working paper series (1) (2018)
Popa, M.: Uncovering the structure of public procurement transactions. Bus. Polit. 21(3), 1–34 (2019)
Johnston, M.: Syndromes of Corruption: Wealth, Power, and Democracy. Cambridge University Press, Cambridge (2005)
Christen, P.: Data Matching: Concepts and Techniques for Record Linkage, Entity Resolution, and Duplicate Detection. Springer, Berlin (2012)
Gregg, F., Eder, D.: Dedupe. https://github.com/datamade/dedupe (2015). Accessed 3 Dec 2018
Wachs, J.: Network approaches to the study of corruption. Ph.D. thesis, Central European University (2019). http://www.etd.ceu.edu/2019/wachs_johannes.pdf
Attström, K., Kröber, R., Junclaus, M.: Review of the Function of the CPV Codes/System. Technical report, European Commission (2012)
European Court of Auditors, Fighting fraud in EU spending: action needed. Technical report (2019)
Mungiu-Pippidi, A., Dadašov, R.: Measuring control of corruption by a new index of public integrity. Eur. J. Crim. Policy Res. 22(3), 415 (2016)
Jordano, P., Bascompte, J., Olesen, J.M.: Invariant properties in coevolutionary networks of plant–animal interactions. Ecol. Lett. 6(1), 69 (2003)
Bustos, S., Gomez, C., Hausmann, R., Hidalgo, C.A.: The dynamics of nestedness predicts the evolution of industrial ecosystems. PLoS ONE 7(11), e49393 (2012)
Hernández, L., Vignes, A., Saba, S.: Trust or robustness? An ecological approach to the study of auction and bilateral markets. PLoS ONE 13(5), e0196206 (2018)
Robins, G., Alexander, M.: Small worlds among interlocking directors: network structure and distance in bipartite graphs. Comput. Math. Org. Theory 10(1), 69 (2004)
Axtell, R.: Firm sizes: facts, formulae, fables and fantasies. SSRN Electron. J. (2006). https://doi.org/10.2139/ssrn.1024813
Alstott, J., Bullmore, E., Plenz, D.: powerlaw: a python package for analysis of heavy-tailed distributions. PLoS ONE 9(1), e85777 (2014)
Csermely, P., London, A., Wu, L.Y., Uzzi, B.: Structure and dynamics of core/periphery networks. J. Complex Netw. 1(2), 93 (2013)
Batagelj, V., Zaversnik, M.: An o (m) algorithm for cores decomposition of networks. arXiv preprint cs/0310049 (2003)
Dorogovtsev, S.N., Goltsev, A.V., Mendes, J.F.F.: K-core organization of complex networks. Phys. Rev. Lett. 96(4), 040601 (2006)
Garas, A., Schweitzer, F., Havlin, S.: A k-shell decomposition method for weighted networks. New J. Phys. 14(8), 083030 (2012)
Persson, T., Tabellini, G.E.: Political Economics: Explaining Economic Policy. MIT Press, Cambridge (2002)
Evans, T.S., Lambiotte, R.: Line graphs of weighted networks for overlapping communities. Eur. Phys. J. B 77(2), 265 (2010)
Ahn, Y.Y., Bagrow, J.P., Lehmann, S.: Link communities reveal multiscale complexity in networks. Nature 466(7307), 761 (2010)
Blondel, V.D., Guillaume, J.L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. J. Stat. Mech. Theory Exp. 2008(10), P10008 (2008)
Monteiro, J., Martins, B., Pires, J.M.: A hybrid approach for the spatial disaggregation of socio-economic indicators. Int. J. Data Sci. Anal. 5(2–3), 189 (2018)
Fazekas, M., Skuhrovec, J., Wachs, J.: Corruption, government turnover, and public contracting market structure. GTI working paper series (2) (2017)
Sikdar, S., Ganguly, N., Mukherjee, A.: Time series analysis of temporal networks. Eur. Phys. J. B 89(1), 11 (2016)
Tsalouchidou, I., Baeza-Yates, R., Bonchi, F., Liao, K., Sellis, T.: Temporal betweenness centrality in dynamic graphs. Int. J. Data Sci. Anal. (2019). https://doi.org/10.1007/s41060-019-00189-x
Grossi, V., Rapisarda, B., Giannotti, F., Pedreschi, D.: Data science at sobigdata: the European research infrastructure for social mining and big data analytics. Int. J. Data Sci. Anal. 6(3), 205 (2018)
Podobnik, B., Horvatić, D., Kenett, D.Y., Stanley, H.E.: The competitiveness versus the wealth of a country. Sci. Rep. 2, 678 (2012)
Correa, J.C., Jaffe, K.: Corruption and wealth: unveiling a national prosperity syndrome in Europe. arXiv preprint arXiv:1604.00283 (2015)
Paulus, M., Kristoufek, L.: Worldwide clustering of the corruption perception. Physica A 428, 351 (2015)
Albeaik, S., Kaltenberg, M., Alsaleh, M., Hidalgo, C.A.: Improving the economic complexity index. arXiv preprint arXiv:1707.05826 (2017)