Ảnh hưởng của trí tuệ thông minh của con người đến tham nhũng tại các nước ASEAN
Nội dung chính của bài viết
Tóm tắt
Bài viết này nhằm phân tích ảnh hưởng của trí tuệ thông minh của con người đến tham nhũng ở các nước ASEAN. Nhóm tác giả sử dụng bộ dữ liệu của 10 nước ASEAN trong giai đoạn từ 1995 đến 2019 để tìm kiếm các bằng chứng thực nghiệm. Kết quả phân tích bằng phương pháp hồi quy tuyến tính Bayes trong trường hợp không có kiểm soát và có kiểm soát các yếu tố khác đã cho thấy có mối quan hệ phi tuyến giữa trí tuệ thông minh và tham nhũng. Cụ thể, kết quả của bài viết đã cung cấp bằng chứng mạnh mẽ ủng hộ mối quan hệ hình chữ U ngược giữa trí tuệ thông minh và tham nhũng tại các nước ASEAN. Phát hiện vẫn không thay đổi khi nhóm tác giả thay thế cách đo lường trí tuệ thông minh bằng nguồn dữ liệu khác. Từ góc độ chính sách, kết quả của bài viết cho thấy các nước ASEAN có trí tuệ thông minh trên điểm ngoặt cần khuyến khích đầu tư vào giáo dục và kỹ năng con người để có mức độ tham nhũng thấp hơn.
Chi tiết bài viết
Từ khóa
ASEAN, Hồi quy Bayes, Tham nhũng, Trí tuệ thông minh của con người
Tài liệu tham khảo
Alfada, A. (2019). Corruption and Economic Growth in ASEAN Member Countries. Economics and Finance in Indonesia, 65(2), 111-131. https://doi.org/10.47291/efi.v65i2.628
Anguera-Torrell, O. (2020). Entrepreneurship, trust and corruption. European Journal of Political Economy, 65, 101937. https://doi.org/10.1016/j.ejpoleco.2020.101937
Basyal, D. K., Poudyal, N., & Seo, J. W. (2018). Does E-government reduce corruption? Evidence from a heterogeneous panel data model. Transforming Government: People, Process and Policy, 12(2), 134-154. https://doi.org/10.1108/TG-12-2017-0073
Becker, D., & Rindermann, H. (2016). The relationship between cross-national genetic distances and IQ-differences. Personality and Individual Differences, 98, 300-310. https://doi.org/10.1016/j.paid.2016.03.050
Colom, R., Karama, S., Jung, R. E., & Haier, R. J. (2010). Human intelligence and brain networks. Dialogues in clinical neuroscience, 12(4), 489-501. https://doi.org/10.31887/DCNS.2010.12.4/rcolom
Damania, R., Fredriksson, P. G., & List, J. A. (2003). Trade liberalization, corruption, and environmental policy formation: theory and evidence. Journal of Environmental Economics and Management, 46(3), 490-512. https://doi.org/10.1016/S0095-0696(03)00025-1
Dee, T. S. (2004). Are there civic returns to education? Journal of Public Economics, 88(9), 1697-1720. https://doi.org/10.1016/j.jpubeco.2003.11.002
Derry, S. J., & Murphy, D. A. (1986). Designing Systems that Train Learning Ability: From Theory to Practice. Review of Educational Research, 56(1), 1-39. https://doi.org/10.3102/00346543056001001
Evrensel, A. Y. (2010). Corruption, growth, and growth volatility. International Review of Economics & Finance, 19(3), 501-514. https://doi.org/10.1016/j.iref.2009.08.002
Farooq, A., Shahbaz, M., Arouri, M., & Teulon, F. (2013). Does corruption impede economic growth in Pakistan? Economic Modelling, 35, 622-633. https://doi.org/10.1016/j.econmod.2013.08.019
Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian data analysis. CRC press.
Gelman, A., & Rubin, D. B. (1992). Inference from Iterative Simulation Using Multiple Sequences. Statistical Science, 7(4), 457-472, 416. https://doi.org/10.1214/ss/1177011136
Gokcekus, O., & Suzuki, Y. (2011). Business cycle and corruption. Economics Letters, 111(2), 138-140. https://doi.org/10.1016/j.econlet.2011.01.023
Jones, G. (2011). National IQ and National Productivity: The Hive Mind Across Asia. Asian Development Review, 28(1), 51-71.
Kanyama, I. K. (2014). Quality of institutions: Does intelligence matter? Intelligence, 42, 44-52. https://doi.org/10.1016/j.intell.2013.10.002
Kass, R. E., Carlin, B. P., Gelman, A., & Neal, R. M. (1998). Markov Chain Monte Carlo in Practice: A Roundtable Discussion. The American Statistician, 52(2), 93-100. https://doi.org/10.1080/00031305.1998.10480547
Kaufmann, D., & Siegelbaum, P. (1997). Privatization and Corruption in Transition Economies. Journal of International Affairs, 50(2), 419-458. http://www.jstor.org/stable/24357625
Kodila-Tedika, O., & Asongu, S. A. (2015). The effect of intelligence on financial development: A cross-country comparison. Intelligence, 51, 1-9. https://doi.org/10.1016/j.intell.2015.04.010
Kraemer, H. C. (2019). Is It Time to Ban the P Value? JAMA Psychiatry, 76(12), 1219-1220. https://doi.org/10.1001/jamapsychiatry.2019.1965
Kumar, A., & Kober, B. (2012). Urbanization, human capital, and cross-country productivity differences. Economics Letters, 117(1), 14-17. https://doi.org/10.1016/j.econlet.2012.04.072
Kyllonen, P. C., & Tirre, W. C. (1988). Individual differences in associative learning and forgetting. Intelligence, 12(4), 393-421. https://doi.org/10.1016/0160-2896(88)90004-9
Lv, Z. (2017). Intelligence and corruption: An empirical investigation in a non-linear framework. Journal of Behavioral and Experimental Economics, 69, 83-91. https://doi.org/10.1016/j.socec.2017.06.003
Lynn, R. (2018). The Intelligence of Nations. In R. J. Sternberg (Ed.), The Nature of Human Intelligence. Cambridge University Press. https://doi.org/10.1017/9781316817049.017
Lynn, R., & Vanhanen, T. (2002). IQ and the wealth of nations. Praeger Publishers/Greenwood Publishing Group.
Lynn, R., & Vanhanen, T. (2012). Intelligence: A unifying construct for the social sciences. Ulster Institute for Social Research.
Milligan, K., Moretti, E., & Oreopoulos, P. (2004). Does education improve citizenship? Evidence from the United States and the United Kingdom. Journal of Public Economics, 88(9), 1667-1695. https://doi.org/10.1016/j.jpubeco.2003.10.005
Nam, T. (2018). Examining the anti-corruption effect of e-government and the moderating effect of national culture: A cross-country study. Government Information Quarterly, 35(2), 273-282. https://doi.org/10.1016/j.giq.2018.01.005
Nguyen, D. V., & Duong, M. T. H. (2021). Shadow Economy, Corruption and Economic Growth: An Analysis of BRICS Countries. The Journal of Asian Finance, Economics and Business, 8(4), 665-672. https://doi.org/10.13106/jafeb.2021.vol8.no4.0665
Nguyễn Văn Điệp, Phạm Xuân Thu, & Nguyễn Hoàng Thi. (2021). Chính phủ điện tử, văn hóa quốc gia và tham nhũng: Bằng chứng từ tiếp cận Bayes. Tạp chí Kinh tế và Ngân hàng châu Á, 185, 5-20.
Oanh, T. T. K., Diep, N. V., Truyen, P. T., & Chau, N. X. B. (2022). The Impact of Public Expenditure on Economic Growth of Provinces and Cities in the Southern Key Economic Zone of Vietnam: Bayesian Approach. In N. Ngoc Thach, D. T. Ha, N. D. Trung, & V. Kreinovich (Eds.), Prediction and Causality in Econometrics and Related Topics (pp. 328-344). Springer International Publishing. https://doi.org/10.1007/978-3-030-77094-5_26
Park, C. H., & Kim, K. (2020). E-government as an anti-corruption tool: panel data analysis across countries. International Review of Administrative Sciences, 86(4), 691-707. https://doi.org/10.1177/0020852318822055
Permai, S. D., & Tanty, H. (2018). Linear regression model using bayesian approach for energy performance of residential building. Procedia Computer Science, 135, 671-677. https://doi.org/10.1016/j.procs.2018.08.219
Potrafke, N. (2012). Intelligence and corruption. Economics Letters, 114(1), 109-112. https://doi.org/10.1016/j.econlet.2011.09.040
Richey, S. (2010). The Impact of Corruption on Social Trust. American Politics Research, 38(4), 676-690. https://doi.org/10.1177/1532673x09341531
Rindermann, H. (2008). Relevance of education and intelligence at the national level for the economic welfare of people. Intelligence, 36(2), 127-142. https://doi.org/10.1016/j.intell.2007.02.002
Romer, P. M. (1990). Human capital and growth: Theory and evidence. Carnegie-Rochester Conference Series on Public Policy, 32, 251-286. https://doi.org/10.1016/0167-2231(90)90028-J
Roy, V. (2020). Convergence Diagnostics for Markov Chain Monte Carlo. Annual Review of Statistics and Its Application, 7(1), 387-412. https://doi.org/10.1146/annurev-statistics-031219-041300
Rustiarini, N. W. (2019). The role of e-government in reducing corruption: A systematic review. Jurnal Perspektif Pembiayaan dan Pembangunan Daerah, 7(3), 269-286.
Seligson, M. A. (2002). The Impact of Corruption on Regime Legitimacy: A Comparative Study of Four Latin American Countries. The Journal of Politics, 64(2), 408-433.
Serra, D. (2006). Empirical determinants of corruption: A sensitivity analysis. Public Choice, 126(1), 225-256. https://doi.org/10.1007/s11127-006-0286-4
Torsello, D. (2013). Introduction: Corruption and rationality. Human Affairs, 23(2), 119-123. https://doi.org/10.2478/s13374-013-0114-8
Trafimow, D. (2021). Philosophical or empirical incommensurability of frequentist versus Bayesian thinking. Ekonometria, 25(1), 25-48. https://doi.org/10.15611/eada.2021.1.02
Uslaner, E. M. (2013). Trust and corruption revisited: how and why trust and corruption shape each other. Quality & Quantity, 47(6), 3603-3608. https://doi.org/10.1007/s11135-012-9742-z
Vo, D. H., Ha, D. T. T., & Ly, T. H. (2015). Shadow Economy and Corruption in the ASEAN: Complement or Substitute? In H. G. Djajadikerta & Z. Zhang (Eds.), A New Paradigm for International Business. Springer Singapore.
Võ Văn Dứt, & Nguyễn Thị Phương Nga. (2015). Ảnh hưởng của tham nhũng đến dòng vốn đầu tư trực tiếp nước ngoài vào các quốc gia Châu Á. HCMCOUJS - Kinh tế và Quản trị kinh doanh, 10(5), 162-172.
Wasserstein, R. L., Schirm, A. L., & Lazar, N. A. (2019, 2019/03/29). Moving to a World Beyond “p < 0.05”. The American Statistician, 73(sup1), 1-19. https://doi.org/10.1080/00031305.2019.1583913
Zhao, H., Ahn, M. J., & Manoharan, A. P. (2017). E-government, corruption reduction and culture: a study based on panel data of 57 countries Proceedings of the 18th Annual International Conference on Digital Government Research, Staten Island, NY, USA.
Anguera-Torrell, O. (2020). Entrepreneurship, trust and corruption. European Journal of Political Economy, 65, 101937. https://doi.org/10.1016/j.ejpoleco.2020.101937
Basyal, D. K., Poudyal, N., & Seo, J. W. (2018). Does E-government reduce corruption? Evidence from a heterogeneous panel data model. Transforming Government: People, Process and Policy, 12(2), 134-154. https://doi.org/10.1108/TG-12-2017-0073
Becker, D., & Rindermann, H. (2016). The relationship between cross-national genetic distances and IQ-differences. Personality and Individual Differences, 98, 300-310. https://doi.org/10.1016/j.paid.2016.03.050
Colom, R., Karama, S., Jung, R. E., & Haier, R. J. (2010). Human intelligence and brain networks. Dialogues in clinical neuroscience, 12(4), 489-501. https://doi.org/10.31887/DCNS.2010.12.4/rcolom
Damania, R., Fredriksson, P. G., & List, J. A. (2003). Trade liberalization, corruption, and environmental policy formation: theory and evidence. Journal of Environmental Economics and Management, 46(3), 490-512. https://doi.org/10.1016/S0095-0696(03)00025-1
Dee, T. S. (2004). Are there civic returns to education? Journal of Public Economics, 88(9), 1697-1720. https://doi.org/10.1016/j.jpubeco.2003.11.002
Derry, S. J., & Murphy, D. A. (1986). Designing Systems that Train Learning Ability: From Theory to Practice. Review of Educational Research, 56(1), 1-39. https://doi.org/10.3102/00346543056001001
Evrensel, A. Y. (2010). Corruption, growth, and growth volatility. International Review of Economics & Finance, 19(3), 501-514. https://doi.org/10.1016/j.iref.2009.08.002
Farooq, A., Shahbaz, M., Arouri, M., & Teulon, F. (2013). Does corruption impede economic growth in Pakistan? Economic Modelling, 35, 622-633. https://doi.org/10.1016/j.econmod.2013.08.019
Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian data analysis. CRC press.
Gelman, A., & Rubin, D. B. (1992). Inference from Iterative Simulation Using Multiple Sequences. Statistical Science, 7(4), 457-472, 416. https://doi.org/10.1214/ss/1177011136
Gokcekus, O., & Suzuki, Y. (2011). Business cycle and corruption. Economics Letters, 111(2), 138-140. https://doi.org/10.1016/j.econlet.2011.01.023
Jones, G. (2011). National IQ and National Productivity: The Hive Mind Across Asia. Asian Development Review, 28(1), 51-71.
Kanyama, I. K. (2014). Quality of institutions: Does intelligence matter? Intelligence, 42, 44-52. https://doi.org/10.1016/j.intell.2013.10.002
Kass, R. E., Carlin, B. P., Gelman, A., & Neal, R. M. (1998). Markov Chain Monte Carlo in Practice: A Roundtable Discussion. The American Statistician, 52(2), 93-100. https://doi.org/10.1080/00031305.1998.10480547
Kaufmann, D., & Siegelbaum, P. (1997). Privatization and Corruption in Transition Economies. Journal of International Affairs, 50(2), 419-458. http://www.jstor.org/stable/24357625
Kodila-Tedika, O., & Asongu, S. A. (2015). The effect of intelligence on financial development: A cross-country comparison. Intelligence, 51, 1-9. https://doi.org/10.1016/j.intell.2015.04.010
Kraemer, H. C. (2019). Is It Time to Ban the P Value? JAMA Psychiatry, 76(12), 1219-1220. https://doi.org/10.1001/jamapsychiatry.2019.1965
Kumar, A., & Kober, B. (2012). Urbanization, human capital, and cross-country productivity differences. Economics Letters, 117(1), 14-17. https://doi.org/10.1016/j.econlet.2012.04.072
Kyllonen, P. C., & Tirre, W. C. (1988). Individual differences in associative learning and forgetting. Intelligence, 12(4), 393-421. https://doi.org/10.1016/0160-2896(88)90004-9
Lv, Z. (2017). Intelligence and corruption: An empirical investigation in a non-linear framework. Journal of Behavioral and Experimental Economics, 69, 83-91. https://doi.org/10.1016/j.socec.2017.06.003
Lynn, R. (2018). The Intelligence of Nations. In R. J. Sternberg (Ed.), The Nature of Human Intelligence. Cambridge University Press. https://doi.org/10.1017/9781316817049.017
Lynn, R., & Vanhanen, T. (2002). IQ and the wealth of nations. Praeger Publishers/Greenwood Publishing Group.
Lynn, R., & Vanhanen, T. (2012). Intelligence: A unifying construct for the social sciences. Ulster Institute for Social Research.
Milligan, K., Moretti, E., & Oreopoulos, P. (2004). Does education improve citizenship? Evidence from the United States and the United Kingdom. Journal of Public Economics, 88(9), 1667-1695. https://doi.org/10.1016/j.jpubeco.2003.10.005
Nam, T. (2018). Examining the anti-corruption effect of e-government and the moderating effect of national culture: A cross-country study. Government Information Quarterly, 35(2), 273-282. https://doi.org/10.1016/j.giq.2018.01.005
Nguyen, D. V., & Duong, M. T. H. (2021). Shadow Economy, Corruption and Economic Growth: An Analysis of BRICS Countries. The Journal of Asian Finance, Economics and Business, 8(4), 665-672. https://doi.org/10.13106/jafeb.2021.vol8.no4.0665
Nguyễn Văn Điệp, Phạm Xuân Thu, & Nguyễn Hoàng Thi. (2021). Chính phủ điện tử, văn hóa quốc gia và tham nhũng: Bằng chứng từ tiếp cận Bayes. Tạp chí Kinh tế và Ngân hàng châu Á, 185, 5-20.
Oanh, T. T. K., Diep, N. V., Truyen, P. T., & Chau, N. X. B. (2022). The Impact of Public Expenditure on Economic Growth of Provinces and Cities in the Southern Key Economic Zone of Vietnam: Bayesian Approach. In N. Ngoc Thach, D. T. Ha, N. D. Trung, & V. Kreinovich (Eds.), Prediction and Causality in Econometrics and Related Topics (pp. 328-344). Springer International Publishing. https://doi.org/10.1007/978-3-030-77094-5_26
Park, C. H., & Kim, K. (2020). E-government as an anti-corruption tool: panel data analysis across countries. International Review of Administrative Sciences, 86(4), 691-707. https://doi.org/10.1177/0020852318822055
Permai, S. D., & Tanty, H. (2018). Linear regression model using bayesian approach for energy performance of residential building. Procedia Computer Science, 135, 671-677. https://doi.org/10.1016/j.procs.2018.08.219
Potrafke, N. (2012). Intelligence and corruption. Economics Letters, 114(1), 109-112. https://doi.org/10.1016/j.econlet.2011.09.040
Richey, S. (2010). The Impact of Corruption on Social Trust. American Politics Research, 38(4), 676-690. https://doi.org/10.1177/1532673x09341531
Rindermann, H. (2008). Relevance of education and intelligence at the national level for the economic welfare of people. Intelligence, 36(2), 127-142. https://doi.org/10.1016/j.intell.2007.02.002
Romer, P. M. (1990). Human capital and growth: Theory and evidence. Carnegie-Rochester Conference Series on Public Policy, 32, 251-286. https://doi.org/10.1016/0167-2231(90)90028-J
Roy, V. (2020). Convergence Diagnostics for Markov Chain Monte Carlo. Annual Review of Statistics and Its Application, 7(1), 387-412. https://doi.org/10.1146/annurev-statistics-031219-041300
Rustiarini, N. W. (2019). The role of e-government in reducing corruption: A systematic review. Jurnal Perspektif Pembiayaan dan Pembangunan Daerah, 7(3), 269-286.
Seligson, M. A. (2002). The Impact of Corruption on Regime Legitimacy: A Comparative Study of Four Latin American Countries. The Journal of Politics, 64(2), 408-433.
Serra, D. (2006). Empirical determinants of corruption: A sensitivity analysis. Public Choice, 126(1), 225-256. https://doi.org/10.1007/s11127-006-0286-4
Torsello, D. (2013). Introduction: Corruption and rationality. Human Affairs, 23(2), 119-123. https://doi.org/10.2478/s13374-013-0114-8
Trafimow, D. (2021). Philosophical or empirical incommensurability of frequentist versus Bayesian thinking. Ekonometria, 25(1), 25-48. https://doi.org/10.15611/eada.2021.1.02
Uslaner, E. M. (2013). Trust and corruption revisited: how and why trust and corruption shape each other. Quality & Quantity, 47(6), 3603-3608. https://doi.org/10.1007/s11135-012-9742-z
Vo, D. H., Ha, D. T. T., & Ly, T. H. (2015). Shadow Economy and Corruption in the ASEAN: Complement or Substitute? In H. G. Djajadikerta & Z. Zhang (Eds.), A New Paradigm for International Business. Springer Singapore.
Võ Văn Dứt, & Nguyễn Thị Phương Nga. (2015). Ảnh hưởng của tham nhũng đến dòng vốn đầu tư trực tiếp nước ngoài vào các quốc gia Châu Á. HCMCOUJS - Kinh tế và Quản trị kinh doanh, 10(5), 162-172.
Wasserstein, R. L., Schirm, A. L., & Lazar, N. A. (2019, 2019/03/29). Moving to a World Beyond “p < 0.05”. The American Statistician, 73(sup1), 1-19. https://doi.org/10.1080/00031305.2019.1583913
Zhao, H., Ahn, M. J., & Manoharan, A. P. (2017). E-government, corruption reduction and culture: a study based on panel data of 57 countries Proceedings of the 18th Annual International Conference on Digital Government Research, Staten Island, NY, USA.