The Role of Economic Freedom in Interpreting Corruption Perception
Keywords:
Downloads
Abstract
The main purpose of the study is to examine the nexus between corruption and economic freedom to determine the most influencing factors to be focused on to reduce corruption. With this aim, two different machine learning algorithms are performed to find out the single effect, two-way, and three-way interaction effects of factors affecting corruption. As a result of the analysis, tax burden, government integrity, and government spending are the main indicators to be focused on to improve corruption steadily. Besides, critical thresholds of the tax burden, government integrity, and government spending are 83.3, 50.9, and 40.6, respectively. Since there are a limited number of studies to predict corruption by machine learning algorithms in the extant literature, this research provides highly detailed information to policy-makers where they can focus on reducing corruption perception.
Downloads
References
Adam, A., Kammas, P., & Lapatinas, A. (2015). Income inequality and the tax structure: evidence from developed and developing countries, Journal of Comparative Economics, 43(1), 138-154. https://doi.org/10.1016/j.jce.2014.05.006
Google Scholar CrossrefAndvig, J., & Fjeldstad, O.-H. (2001). Corruption: A review of contemporary research. CMI Report R 2001:7. Chr. Michelsen Institute.
Google Scholar CrossrefAstafurova. O. A., Borisova. A. S., Golomanchuk. E. V., & Yagotinsteva. T. Y. (2020). Use of Modern Information Technologies for Countering Corruption in the Executive Authorities. International Journal of Information and Education Technology, 10(3), 209-214. https://doi.org/10.18178/ijiet.2020.10.3.1365
Google Scholar CrossrefAugustine, A.A., & Enyi, E. (2020). Control of Corruption, Trust in Government, and Voluntary Tax Compliance in South-West, Nigeria. Management Studies, 8(1), 84-97. https://doi.org/10.17265/2328-2185/2020.01.011
Google Scholar CrossrefBauhr, M., Czibik, A., Licht, J. F., & Fazekas, M. (2019). Lights on the shadows of public procurement: Transparency as an antidote to corruption, Governance, 33(3), 495-523. https://doi.org/10.1111/gove.12432
Google Scholar CrossrefBillger. S. M., & Goel. R. K. (2009). Do Existing Corruption Levels Matter in Controlling Corruption?: Cross-country Quantile Regression Estimates, Journal of Development Economics, 90(2), 299-305. https://doi.org/10.1016/j.jdeveco.2008.07.006
Google Scholar CrossrefBudsaratragoon, P., & Jitmaneeroj, B. (2020). A critique on the Corruption Perceptions Index: An interdisciplinary approach, Socio-Economic Planning Sciences, 70, 100768. https://doi.org/10.1016/j.seps.2019.100768
Google Scholar CrossrefCarden. A., & Verdon. L. (2010). When is corruption a substitute for economic freedom? Law and Development Review, 3, 40-63. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1132751
Google Scholar CrossrefCAF (2019). RED 2019. Integridad en las políticas públicas: claves para prevenir la corrupción. http://scioteca.caf.com/handle/123456789/1503
Google Scholar CrossrefChen, C., & Neshkova, M.I. (2019). The effect of fiscal transparency on corruption: A panel cross‐country analysis. Public Administration, 98(1), 226-243. https://doi.org/10.1111/padm.12620
Google Scholar CrossrefChowdhury. S. (2004). The effect of democracy and press freedom on corruption: An empirical test. Economics Letters, 85, 93-101. https://doi.org/10.1016/j.econlet.2004.03.024
Google Scholar CrossrefChristos, P., Eleni, K., Dimitrios, K., Zacharias, D., Athanasios, A., & Panagiotis, L. (2018). Corruption Perception Index (CPI), as an Index of Economic Growth for European Countries. Theoretical Economics Letters, 8(3), 82541. https://doi.org/10.4236/tel.2018.83037
Google Scholar CrossrefCooray, A., Jha, C.K., & Panda, B. (2020). Corruption and assortative matching of partners in international trade, WIDER Working Paper Series wp-2020-114, World Institute for Development Economic Research (UNU-WIDER).
Google Scholar CrossrefCortes. C., & Vapnik. V. (1995). Support-Vector Networks. Machine Learning, 20, 273-297.
Google Scholar CrossrefCuadrado-Ballesteros. B., & Pena-Miguel. N. (2020). Corruption Perception Following Privatization Reforms: The Moderating Role of the Quality of Governance. Revista De Contabilidad. 23(1), 127-137. https://doi.org/10.6018/rcsar.361041
Google Scholar CrossrefÇelikay, F. (2020). Dimensions of tax burden: a review on OECD countries. Journal of Economics, Finance and Administrative Science, 25(49), 27-43.
Google Scholar CrossrefDamayanti, T.W., Prabowo, R., Sucahyo, U.S., & Supramano, S. (2020). The Relationship between Gender, Tax Burdens, Corruption Practices, and Tax Compliance. Journal of Southwest Jiaotong University, 55(3), 1-12. https://doi.org/10.35741/issn.0258-2724.55.3.54
Google Scholar Crossrefde Jong. E., & Bogmans. C. (2011). Does corruption discourage international trade? European Journal of Political Economy, 27, 385-398. https://doi.org/10.1016/j.ejpoleco.2010.11.005
Google Scholar CrossrefDebski, J., Jetter, M., Mösle, S., & Stadelmann, D. (2018). Gender and corruption: the neglected role of culture. European Journal of Political Economy, 55(December), 526-537.
Google Scholar CrossrefDelavallade, C. (2006). Corruption and distribution of public spending in developing countries. Journal of Economics and Finance, 30, 222-239. https://link.springer.com/article/10.1007/BF02761488
Google Scholar CrossrefDepren, Ö., Kartal, M.T., & Kılıç Depren, S. (2021). Recent Innovation in Benchmark Rates (BMR): Evidence from Influential Factors on Turkish Lira Overnight Reference Interest Rate with Machine Learning Algorithms. Financial Innovation, 7(44), 1-20. https://doi.org/10.1186/s40854-021-00245-1
Google Scholar CrossrefDong, B., & Torgler, B. (2011). Corruption and Social Interaction: Evidence from China. Dong, Bin and Torgler, Benno, Corruption and Social Interaction: Evidence from China (February 7, 2011). FEEM Working Paper No. 9.2011. https://ssrn.com/abstract=1756843
Google Scholar CrossrefDzhumashev, R. (2013). The two-way relationship between government spending and corruption and its effects on economic growth. Contemporary Economic Policy, 32(2), 403-419. https://doi.org/10.1111/coep.12025
Google Scholar CrossrefFazira, D.R., & Cahyadin, M. (2018). The Impact of Interest Rate, Corruption Perception Index, and Economic Growth on Foreign Direct Investment in ASEAN-6. Jurnal Keuangan dan Perbankan, 22(4), 707-713.
Google Scholar CrossrefFriedman. J. H. (1991). Multivariate Adaptive Regression Splines. The Annals of Statistics, 19(1), 1-67.
Google Scholar CrossrefGoel. R., & Nelson. M. (2007). Are corrupt acts contagious? Evidence from the United States. Journal of Policy Modeling, 29, 839-850. https://doi.org/10.1016/j.jpolmod.2007.09.002
Google Scholar CrossrefGroenendijk, N. (1997). A principal-agent model of corruption. Crime. Law and Social Change, 27(3-4), 207-229.
Google Scholar CrossrefGwartney. J., Lawson. R., Hall. J., Murphy. R., Bennett. D. L., Fike. R., & Nikolaev. B. (2019). Economic Freedom of the World: 2019 Annual Report. Vancouver. Fraser Institute.
Google Scholar CrossrefHallward-Driemeier, M. (2013). Who Survives? The Impact of Corruption, Competition and Property Rights Across Firms. Policy Research Working Papers, World Bank. https://doi.org/10.1596/1813-9450-5084
Google Scholar CrossrefHashem, A.H. (2014). The Effects of Corruption on Government Expenditures: Arab Countries Experience. Journal of Economics and Sustainable Development, 5(4), 120-130.
Google Scholar CrossrefHuang, C-H. (2016). Is corruption bad for economic growth? Evidence from Asia-Pacific countries. The North American Journal of Economics and Finance, 35, 247-256. https://doi.org/10.1016/j.najef.2015.10.013
Google Scholar CrossrefJajkowicz, O., & Drobiszová, A. (2015). The Effect of Corruption on Government Expenditure Allocation in OECD Countries. ACTA Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 63(138), 1251-1259.
Google Scholar CrossrefKeyifli. N. (2019). E-government and corruption: an empiric analysis. Global Journal of Economics and Business Studies, 8(16), 196-206. https://doi.org/10.1080/01900690701590553
Google Scholar CrossrefKohler, J.C., & Dimancesco, D. (2020). The risk of corruption in public pharmaceutical procurement: How anti-corruption, transparency and accountability measures may reduce this risk. Global Health Action, 13(1), 1-10. https://doi.org/10.1080/16549716.2019.1694745
Google Scholar CrossrefKonu. A., & Ata. A. Y. (2016). Yolsuzluk ve Ekonomik Özgürlükler İlişkisi: AB Ülkeleri Üzerine Yatay Kesit Analizi. Niğde Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 9(1), 195-207.
Google Scholar CrossrefLaw, T., & Shawe-Taylor, J. (2017). Practical bayesian support vector regression for financial time series prediction and market condition change detection. Quantitative Finance, 17(9), 1403-1416.
Google Scholar CrossrefLe, D.T., Malesky, E., & Pham, A. (2020). The impact of local corruption on business tax registration and compliance: Evidence from Vietnam. Journal of Economic Behavior & Organization, 177, 762-786. https://doi.org/10.1016/j.jebo.2020.07.002
Google Scholar CrossrefLee. T.-S., & Chen. I.-F. (2005). A two-stage hybrid credit scoring model using artificial neural networks and multivariate adaptive regression splines. Expert Systems with Applications, 28(4), 743-752. https://doi.org/10.1016/j.eswa.2004.12.031
Google Scholar CrossrefLima. M.S.M., & Delen. D. (2020). Predicting and Explaining Corruption Across Countries: A Machine Learning Approach. Government Information Quarterly, 37(1), 1-15. https://doi.org/10.1016/j.giq.2019.101407
Google Scholar CrossrefLin, J., Cheng, C-T., & Chau, K-W. (2006). Using Support Vector Machines for Long-Term Discharge Prediction. Hydrological Sciences Journal, 51 (4), 599-612. https://doi.org/10.1623/hysj.51.4.599
Google Scholar CrossrefMarquette, H., & Peiffer, C. (2015). Corruption and Collective Actions. U4 Anti-Corruption Resource Centre, Chr. Michelsen Institute.
Google Scholar CrossrefMauro, P. (1998). Corruption and the composition of government expenditure. Journal of Public Economics, 69, 263–279. https://ideas.repec.org/a/eee/pubeco/v69y1998i2p263-279.html
Google Scholar CrossrefMondal, P. (2021). Contribution of Foreign Trade to Economic Growth. Your Article library. https://www.yourarticlelibrary.com/foreign-trade/contribution-of-foreign-trade-to-economic-growth/40276
Google Scholar CrossrefMyles, G.D., & Yousefi, H. (2020). Corruption as an Occupational Choice: Endogenous Corruption and Tax Policy. Southern Economic Journal, 86, 1446-1474. https://doi.org/10.1002/soej.12421
Google Scholar CrossrefPeisakhin, L.V. (2012). Transparency and Corruption: Evidence from India. The Journal of Law and Economics, 55(1), 129–149. https://doi.org/10.1086/663727
Google Scholar CrossrefPersson, A., Rothstein, B., & Teorell, J. (2013). Why Anticorruption Reforms fail: Systemic corruption as a collective action problem. Governance, 26(3), 449-471.
Google Scholar CrossrefPieroni. L., & d'Agostino. G. (2013). Corruption and The Effects of Economic Freedom. European Journal of Political Economy, 29, 54-72. https://doi.org/10.1016/j.ejpoleco.2012.08.002
Google Scholar CrossrefQaiser, B., Nadeem, S., Siddiqi, M.U., & Siddiqui, A.F. (2017). Relationship of Social Progress Index (SPI) with Gross Domestic Product (GDP PPP per capita): The Moderating Role of Corruption Perception Index (CPI). Pakistan Journal of Engineering, Technology & Science, 7(1), 61-76. http://dx.doi.org/10.22555/pjets.v7i1.2083
Google Scholar CrossrefQureshi, F., Qureshi, S., Vo, X.V., & Junejo, I. (2020). Revisiting the nexus among foreign direct investment, corruption and growth in developing and developed markets. Borsa Istanbul Review. https://doi.org/10.1016/j.bir.2020.08.001
Google Scholar CrossrefSafari. M. J. (2019). Decision tree (DT), generalized regression neural network (GR) and multivariate adaptive regression splines (MARS) models for sediment transport in sewer pipes. Water Science & Technology, 79(6), 1113-1122. https://doi.org/10.2166/wst.2019.106
Google Scholar CrossrefSaha. S., Gounder. R., & Su. J. (2009). The interaction effect of economic freedom and democracy on corruption: A panel cross-country analysis. Economics Letters, 105, 173-176. https://doi.org/10.1016/j.econlet.2009.07.010
Google Scholar CrossrefSharda. V. N., Prasher. S. O., Patel. R. M., Ojasvi. P. R., & Prakash. C. (2008). Performance of Multivariate Adaptive Regression Splines (MARS) in predicting runoff in mid-Himalayan micro-watersheds with limited data. Hydrological Sciences Journal, 53(6), 1165-1175. https://doi.org/10.1623/hysj.53.6.1165
Google Scholar CrossrefShirazi, M.A. (2020). The Impact of Corruption on International Trade. Denver Journal of International Law & Policy, 40(1), 435-446. https://doi.org/10.1111/j.1467-9701.2012.01436.x
Google Scholar CrossrefSmidova, Z. (2020). Building the evidence for OECD integrity and anti-corruption agenda: The current situation and avenues for future analysis. OECD Economics Department Working Papers, No: 1614. https://doi.org/10.1787/80ebe6e6-en
Google Scholar CrossrefStensöta, H., Svensson, R., & Wängnerud, L. (2015). Gender and Corruption: the mediating power of institutional logics. Governance: An international Journal of Policy, Administration, and Institutions, 28(4), 475-496.
Google Scholar CrossrefStephen, J. (2018). Corruption is costing the global economy $3.6 trillion dollars every year. The World Economic Forum. https://www.weforum.org/agenda/2018/12/the-global-economy-loses-3-6-trillion-to-corruption-each-year-says-u-n
Google Scholar CrossrefStoean. C., & Stoean. R. (2014). Support vector machines and evalutionary algorithms for classification. Springer-Verlag.
Google Scholar CrossrefThach, N. N., & Ngoc, B.H. (2021). Impact of Economic Freedom on Corruption Revisited in ASEAN Countries: A Bayesian Hierarchical Mixed-Effects Analysis. Economies, 9(3), 1-16.
Google Scholar CrossrefTransparency International (2020, June 04). What-is-corruption. Transparency International Website. https://www.transparency.org/en/what-is-corruption
Google Scholar CrossrefTreisman. D. (2007). What have we learned about the causes of corruption from ten years of cross-national empirical research? Annual Reviews Political Science, 10, 211-244. https://www.annualreviews.org/doi/abs/10.1146/annurev.polisci.10.081205.095418
Google Scholar CrossrefVapnik, V. (2010). The Nature of Statistical Learning Theory. Springer-Verlag.
Google Scholar CrossrefVendrell-Herrero, F., Darko, C., & Vaillant, Y. (2020). Firm productivity and government contracts: The moderating role of corruption. Socio-Economic Planning Sciences. https://doi.org/10.1016/j.seps.2020.100899
Google Scholar CrossrefZheng, B., & Xiao, J. (2020). Corruption and Investment: Theory and Evidence from China. Journal of Economic Behavior & Organization, 175, 40-54. https://doi.org/10.1016/j.jebo.2020.03.018
Google Scholar CrossrefDownloads
Published
Metrics
Almetric
Dimensions
How to Cite
Issue
Section
License
Copyright (c) 2021 International and Multidisciplinary Journal of Social Sciences
This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles are published under Creative Commons copyright (CC BY). Authors hold the copyright and retain publishing rights without restrictions, but authors allow anyone to download, reuse, reprint, modify, distribute, and/or copy articles as the original source is cited.
