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İnternet Kullanımı Yolsuzluğu Azaltır mı? BİT Çerçevesinde Panel Veri Analizi

Yıl 2020, Cilt: 21 Sayı: 3, 41 - 61, 30.09.2020

Öz

Çalışmada internet kullanımının yolsuzluk üzerinde azaltıcı bir etkiye sahip olup olmadığını 164 ülke için 2012-2018 yıllarını kapsayan dönemde dinamik panel veri analizi ile test etmek amaçlanmaktadır. Ana bağımsız değişken olan internet kullanımın yanı sıra kişi başına düşen gelir, Dünya Bankası küresel yönetişim göstergelerinden ifade özgürlüğü ve hesap verilebilirlik, politik istikrar ve şiddetsizlik ve hukukun üstünlüğü bağımsız değişkenlerinin de yolsuzluk üzerindeki etkileri analiz edilmiştir. Bu amaç doğrultusunda yöntem olarak sistem GMM analizi tercih edilmiştir. Çalışmadan elde edilen ampirik sonuçlar internet kullanımının yolsuzluğu azalttığı yönündeki hipotezi destekler niteliktedir.

Kaynakça

  • Acaravcı, A., Artan, S., Hayaloğlu, P., & Erdoğan, S. (2016). Yüksek ve Orta Gelir Grubu Ülkelerde İnternet Kullanımı, Dışa Açıklık, Gelir ve Yolsuzluk Arasındaki Nedensel İlişkiler. 2. International Congress on Economics and Business (s. 1168-1179). ICEB'16.
  • Acemoğlu, D., & Verdier, T. (1998). Property Rights, Corruption and the Allocation of Talent: A General Equilibrium Approach. The Economic Journal, 108(450), 1381-1403.
  • Ades, A., & Di Tella, R. (1997). The New Economics of Corruption: A Survey and Some New Results. Political Studies, XLV, 496-515.
  • Akçay, S. (2000). Yolsuzluk, Ekonomik Özgürlükler ve Demokrasi. Muğla Üniversitesi SBE Dergisi, 1(1), 1-15.
  • Ali, N., Cullen, G., & Gasbarro, D. (2010). The Coexistence of Corruption and Economic Growth in East Asia: Miracle or Alarm? Murdoch Business School. http://www.apeaweb.org/confer/hk10/papers/ali_n.pdf adresinden alındı
  • Andersen, T. B. (2009). E-Government as an anti-corruption strategy. Information Economics and Policy, 21, 201-210.
  • Andersen, T. B., & RAND, J. (2006). Does E-Government Reduce Corruption? University of Copenhagen, Department of Economics, Working Paper.
  • Andersen, T. B., Bentzen, J., Dalgaard, C.-J., & Selaya, P. (2011). Does the Internet Reduce Corruption? Evidence from U.S. States and across Countries. The World Bank Economic Review, 25(3), 387-417.
  • Andvig, J. C., Fjeldstad, O.-H., Amundsen, I., Sissener, T., & Soreide, T. (2000). Research on Corruption. A Policy Oriented Survey. CHR. Michelsen Institute.
  • Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte carlo evidence and an application to employment equations. The Review of Economic Studies, 58(2), 277–297.
  • Arellano, M., & Bover, O. (1995). Another look at the instrumental variable estimation of error-components model. Journal of Econometrics, 68, 29-51.
  • Arpit, B. (2012). E-government and Social Media as Openness and Anti-corruption Strategy. Research Journal of Management Sciences, 1(1), 48-52.
  • Ata, A. Y., & Arvas, M. (2011). Determinants of Economic Corruption: A Cross-Country Data Analysis. International Journal of Business and Social Science, 161-169.
  • Baltagi, B. H. (2005). Econometric analysis of panel data (3. b.). England: John Wiley & Sons Ltd.
  • Barreto, R. (2001). Endogenous Corruption, Inequality and Growth: Econometric Evidence, Working Paper 01-2. Australia: School of Economics Adelaide University.
  • Bertot, J. C., Jaeger, P., & Grimes, J. (2010). Using ICTs to create a culture of transparency: E-government and social media as openness and anti-corruption tools for societies. Government Information Quarterly, 27, 264-271.
  • Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87, 115-143.
  • Blundell, R., Bond, S., & Windmeijer, F. (2000). Estimation in dynamic panel data models: improving on the performance of the standard GMM estimator. IFS Working Papers W00/12. Institute for Fiscal Studies.
  • Braun, M., & Di Tella, R. (2004). Inflation, Inflation Variability and Corruption. Economics and Politics, 16(1), 77-100.
  • Chang, E. C., & Golden, M. (2004). Electoral Systems, District Magnitude and Corruption. British Journal of Political Science, 37(1).
  • Charoensukmongkol, P., & Moqbel, M. (2014). Does Investment in ICT Curb or Create More Corruption? A Cross-Country Analysis. Public Organization Review, 14(1), 51-63.
  • Controlling Corruption: A Parliamentarian's Handbook. (2005). World Bank Institute .
  • Damania, R., Fredriksson , P., & Mani , M. (2004). The Persistence of Corruption and Regulatory Compliance Failures: Theory and Evidence. Public Choice, 121, 363–390.
  • ELBAHNASAWY, N. G. (2014). E-Government, Internet Adoption, and Corruption: An Empirical Investigation. World Development, 57, 114-126.
  • Ghalwash, T. (2014). Corruption and Economic Growth: Evidence from Egypt. Modern Economy, 5, 1001-1009.
  • Goel, R. K., & Nelson, M. A. (2011). Measures of corruption and determinants of US corruption. Economics of Governance, 12, 155-176.
  • Goel, R. K., Nelson, M., & Naretta, M. (2012). The internet as an indicator of corruption awareness. European Journal of Political Economy, 28, 64-75.
  • Hsiao, C. (2003). Analysis of Panel Data (2. b.). New York: Cambridge University Press.
  • HUŇADY, J., & ORVISKÁ, M. (2015). DOES THE INTERNET USAGE REDUCE THE CORRUPTION IN PUBLIC SECTOR? THE SHORT RUN AND LONG RUN CAUSALITY. Acta Aerarii Publici, 12(1), 22-43.
  • Iliman, T., & Tekeli, R. (2016). Dünya’da ve Türkiye’de Yolsuzluk Algısı. Adnan Menderes Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 3(2), 62-84.
  • Inuwa, I., Kah, M. M., & Ononiwu, C. (2019). Understanding How the Traditional and Information Technology Anti-Corruption Strategies intertwine to Curb Public Sector Corruption: A Systematic Literature Review. Conference: Pacific Asia Conference on Information Systems (PACIS). Xi'an, China.
  • ITU. (2020). International Telecommunication Union/Statistics. https://www.itu.int/en/ITU-D/Statistics/Pages/default.aspx adresinden alındı
  • Jin, S., & Cho, C. M. (2015). Is ICT a New Essential for National Economic Growth in An Information Society? Government Information Quarterly, 32(3), 253-260.
  • Johnston, M. (1998). What can be done about entrenched corruption? In B. Pleskovic, & J. Stiglitz (Ed.), Annual world bank conference on development economics 1997 (pp. 69-90). Washington: World Bank.
  • Jung, H., & Kwon, H. U. (2007). An Alternative System GMM Estimation in Dynamic Panel Models. Hi-Stat Discussion Paper Series. Institute of Economic Research, Hitotsubashi University.
  • KANYAM, D. A., KOSTANDINI, G., & FERREIRA, S. (2017). The Mobile Phone Revolution: Have Mobile Phones and the Internet Reduced Corruption in Sub-Saharan Africa? World Development, 99, 271-284.
  • Karluk, S. R., & Ünal, U. (2017). TÜRKİYE EKONOMİSİNDE YOKSULLUK, YOLSUZLUK VE GELİR DAĞILIMI İLİŞKİSİ. F. Şenses, M. Koyuncu, H. Mıhcı, & E. Yeldan içinde, Geçmişten geleceğe Türkiye ekonomisi : Fikret Şenses'e armağan. İstanbul: İletişim Yayınları.
  • Keyifli, N. (2016). E-Devletin Yolsuzluğu Azaltıcı Etkisi: Ampirik Bir Analiz. Küresel İktisat ve İşletme Çalışmaları Dergisi, 8(16), 196-206.
  • Khan, M. H. (1996). The efficiency implications of corruption. Journal of International Development, 8(5), 683-696.
  • Koyuncu, C., & Ünver, M. (2017). Information and Communication Technologies (ICTs) and Corruption Level: Empirical Evidence from Panel Data Analysis. The Journal of International Scientific Researches, 2(6).
  • Lee, M.-H., & Lio, M.-C. (2016). The Impact Of Information and Communication Technology on Public Governance and Corruption in China. Information Development, 32(2), 127-141.
  • Leff, N. H. (1964). Economic Development Through Bureaucratic Corruption. American Behavioral Scientist, 8(3), 8–14.
  • Linhartová, V. (2017). THE ROLE OF E-GOVERNMENT IN MITIGATING CORRUPTION. Scientific Papers of the University of Pardubice - Series D, Faculty of Economics and Administration, 40, 120-131.
  • Lio, M.-C., Liu, M.-C., & Ou, Y.-P. (2011). Can the internet reduce corruption? A cross-country study based on dynamic panel data models. Government Information Quarterly, 28, 47-53.
  • Mimbi, L., & Bankole, F. (2016). Factors Influencing ICT Service Efficiency in Curbing Corruption in Africa: A Bootstrap Approach. SAICSIT '16: Proceedings of the Annual Conference of the South African Institute of Computer Scientists and Information Technologists.
  • Oktar, S. (2003). Yolsuzluk Ekonomisi. Marmara Üniversitesi İ.İ.B.F. Dergisi, 18(1), 13-27. Retrieved Nisan 3, 2019, from http://www.sbb.gov.tr/kalkinma-planlari/
  • Paldam, M. (2002). The cross-country pattern of corruption: economics, culture and the seesaw dynamics. European Journal of Political Economy, 18(2), 215-240.
  • Paul, B. P. (2010). Does corruption foster growth in Bangladesh? International Journal of Development Issues, 9(3), 246-262.
  • Sandholtz, W., & Koetzle, W. (2000). Accounting for Corruption: Economic Structure, Democracy and Trade. International Studies Quarterly, 44(1), 31-50.
  • Sassi, S., & Ali, M. S. (2017). Corruption in Africa: What role does ICT diffusion play. Telecommunications Policy, 41, 662-669.
  • Seldadyo, H., & Haan, J. (2006). The Determinants of Corruption a Literature Survey and New Evidence. Paper Prepared for the 2006 EPCS Conference.
  • Shim, D. C., & Eom, T. (2008). E-Government and Anti-Corruption: Empirical Analysis of International Data. International Journal of Public Administration, 31(3), 298-316.
  • Shrivastava, U., & Bhattacherjee, A. (2014). ICT Development and Corruption: An Empirical Study. Twentieth Americas Conference on Information Systems, (s. 1-9).
  • Soto, M. (2009). System GMM Estimation with a Small Sample. Barselona Economics Working Paper Series. Working Paper No 395. Mayıs 5, 2020 tarihinde https://www.researchgate.net/publication/229054201_System_GMM_Estimation_with_a_Small_Sample adresinden alındı
  • Swaleheen, M. (2011). Economic growth with endogenous corruption: an empirical study. Public Choice, 146, 23–41.
  • Tanzi, V. (1998). Corruption Around The World: Causes, Consequences, Scope, and Cures. Staff Paper, 45(4). https://www.imf.org/en/Publications/WP/Issues/2016/12/30/Corruption-Around-the-World-Causes-Consequences-Scope-and-Cures-2583 adresinden alındı
  • The Worldwide Governance Indicators. (2020). https://info.worldbank.org/governance/wgi/ adresinden alındı
  • Transparency International. (2020). 2020 tarihinde Transparency International: https://www.transparency.org/ adresinden alındı
  • Van Rijckeghem, C., & Weder, B. (1997). Corruption and the Rate of Temptation: Do Low Wages in the Civil Service Cause Corruption? IMF Working Paper WP/ 97/ 73. Washington: International Monetary Fund.
  • Vinod, H. D. (1999). Statistical Analysis of Corruption Data and Using the Internet to Reduce Corruption . Journal of Asian Economics.
  • Wu, W.-C. (2011). Internet Technology and its Impact on Corruption. San Diego: A Senior Honors Thesis, University of California.
  • Yakışık, H., & Çetin, A. (2014). Yolsuzlukların Sosyoekonomik Belirleyicileri: Yatay Kesit Veri Analizi. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 28(3), 205-224.
  • Yardımcıoğlu, F. (2013). Türk Cumhuriyetlerinde Demokrasi ve Yolsuzluk İlişkisi: Panel Veri Analizi. Abant İzzet Baysal Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 13(2), 437-457.

Does the internet usage mitigate corruption? A panel data analysis through ICTs

Yıl 2020, Cilt: 21 Sayı: 3, 41 - 61, 30.09.2020

Öz

The study aims to test whether internet usage has a reducing impact on corruption or not for 164 countries in the period of 2012-2018 by dynamic panel data analysis. Also, per capita income, voice and accountability, political stability and absence of violence and the rule of law are added to the model as independent variable and their effects on corruption are analysed. In parallel with this purpose, system GMM is preferred. The empirical results obtained from the study support the hypothesis that internet usage reduces corruption.

Kaynakça

  • Acaravcı, A., Artan, S., Hayaloğlu, P., & Erdoğan, S. (2016). Yüksek ve Orta Gelir Grubu Ülkelerde İnternet Kullanımı, Dışa Açıklık, Gelir ve Yolsuzluk Arasındaki Nedensel İlişkiler. 2. International Congress on Economics and Business (s. 1168-1179). ICEB'16.
  • Acemoğlu, D., & Verdier, T. (1998). Property Rights, Corruption and the Allocation of Talent: A General Equilibrium Approach. The Economic Journal, 108(450), 1381-1403.
  • Ades, A., & Di Tella, R. (1997). The New Economics of Corruption: A Survey and Some New Results. Political Studies, XLV, 496-515.
  • Akçay, S. (2000). Yolsuzluk, Ekonomik Özgürlükler ve Demokrasi. Muğla Üniversitesi SBE Dergisi, 1(1), 1-15.
  • Ali, N., Cullen, G., & Gasbarro, D. (2010). The Coexistence of Corruption and Economic Growth in East Asia: Miracle or Alarm? Murdoch Business School. http://www.apeaweb.org/confer/hk10/papers/ali_n.pdf adresinden alındı
  • Andersen, T. B. (2009). E-Government as an anti-corruption strategy. Information Economics and Policy, 21, 201-210.
  • Andersen, T. B., & RAND, J. (2006). Does E-Government Reduce Corruption? University of Copenhagen, Department of Economics, Working Paper.
  • Andersen, T. B., Bentzen, J., Dalgaard, C.-J., & Selaya, P. (2011). Does the Internet Reduce Corruption? Evidence from U.S. States and across Countries. The World Bank Economic Review, 25(3), 387-417.
  • Andvig, J. C., Fjeldstad, O.-H., Amundsen, I., Sissener, T., & Soreide, T. (2000). Research on Corruption. A Policy Oriented Survey. CHR. Michelsen Institute.
  • Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte carlo evidence and an application to employment equations. The Review of Economic Studies, 58(2), 277–297.
  • Arellano, M., & Bover, O. (1995). Another look at the instrumental variable estimation of error-components model. Journal of Econometrics, 68, 29-51.
  • Arpit, B. (2012). E-government and Social Media as Openness and Anti-corruption Strategy. Research Journal of Management Sciences, 1(1), 48-52.
  • Ata, A. Y., & Arvas, M. (2011). Determinants of Economic Corruption: A Cross-Country Data Analysis. International Journal of Business and Social Science, 161-169.
  • Baltagi, B. H. (2005). Econometric analysis of panel data (3. b.). England: John Wiley & Sons Ltd.
  • Barreto, R. (2001). Endogenous Corruption, Inequality and Growth: Econometric Evidence, Working Paper 01-2. Australia: School of Economics Adelaide University.
  • Bertot, J. C., Jaeger, P., & Grimes, J. (2010). Using ICTs to create a culture of transparency: E-government and social media as openness and anti-corruption tools for societies. Government Information Quarterly, 27, 264-271.
  • Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87, 115-143.
  • Blundell, R., Bond, S., & Windmeijer, F. (2000). Estimation in dynamic panel data models: improving on the performance of the standard GMM estimator. IFS Working Papers W00/12. Institute for Fiscal Studies.
  • Braun, M., & Di Tella, R. (2004). Inflation, Inflation Variability and Corruption. Economics and Politics, 16(1), 77-100.
  • Chang, E. C., & Golden, M. (2004). Electoral Systems, District Magnitude and Corruption. British Journal of Political Science, 37(1).
  • Charoensukmongkol, P., & Moqbel, M. (2014). Does Investment in ICT Curb or Create More Corruption? A Cross-Country Analysis. Public Organization Review, 14(1), 51-63.
  • Controlling Corruption: A Parliamentarian's Handbook. (2005). World Bank Institute .
  • Damania, R., Fredriksson , P., & Mani , M. (2004). The Persistence of Corruption and Regulatory Compliance Failures: Theory and Evidence. Public Choice, 121, 363–390.
  • ELBAHNASAWY, N. G. (2014). E-Government, Internet Adoption, and Corruption: An Empirical Investigation. World Development, 57, 114-126.
  • Ghalwash, T. (2014). Corruption and Economic Growth: Evidence from Egypt. Modern Economy, 5, 1001-1009.
  • Goel, R. K., & Nelson, M. A. (2011). Measures of corruption and determinants of US corruption. Economics of Governance, 12, 155-176.
  • Goel, R. K., Nelson, M., & Naretta, M. (2012). The internet as an indicator of corruption awareness. European Journal of Political Economy, 28, 64-75.
  • Hsiao, C. (2003). Analysis of Panel Data (2. b.). New York: Cambridge University Press.
  • HUŇADY, J., & ORVISKÁ, M. (2015). DOES THE INTERNET USAGE REDUCE THE CORRUPTION IN PUBLIC SECTOR? THE SHORT RUN AND LONG RUN CAUSALITY. Acta Aerarii Publici, 12(1), 22-43.
  • Iliman, T., & Tekeli, R. (2016). Dünya’da ve Türkiye’de Yolsuzluk Algısı. Adnan Menderes Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 3(2), 62-84.
  • Inuwa, I., Kah, M. M., & Ononiwu, C. (2019). Understanding How the Traditional and Information Technology Anti-Corruption Strategies intertwine to Curb Public Sector Corruption: A Systematic Literature Review. Conference: Pacific Asia Conference on Information Systems (PACIS). Xi'an, China.
  • ITU. (2020). International Telecommunication Union/Statistics. https://www.itu.int/en/ITU-D/Statistics/Pages/default.aspx adresinden alındı
  • Jin, S., & Cho, C. M. (2015). Is ICT a New Essential for National Economic Growth in An Information Society? Government Information Quarterly, 32(3), 253-260.
  • Johnston, M. (1998). What can be done about entrenched corruption? In B. Pleskovic, & J. Stiglitz (Ed.), Annual world bank conference on development economics 1997 (pp. 69-90). Washington: World Bank.
  • Jung, H., & Kwon, H. U. (2007). An Alternative System GMM Estimation in Dynamic Panel Models. Hi-Stat Discussion Paper Series. Institute of Economic Research, Hitotsubashi University.
  • KANYAM, D. A., KOSTANDINI, G., & FERREIRA, S. (2017). The Mobile Phone Revolution: Have Mobile Phones and the Internet Reduced Corruption in Sub-Saharan Africa? World Development, 99, 271-284.
  • Karluk, S. R., & Ünal, U. (2017). TÜRKİYE EKONOMİSİNDE YOKSULLUK, YOLSUZLUK VE GELİR DAĞILIMI İLİŞKİSİ. F. Şenses, M. Koyuncu, H. Mıhcı, & E. Yeldan içinde, Geçmişten geleceğe Türkiye ekonomisi : Fikret Şenses'e armağan. İstanbul: İletişim Yayınları.
  • Keyifli, N. (2016). E-Devletin Yolsuzluğu Azaltıcı Etkisi: Ampirik Bir Analiz. Küresel İktisat ve İşletme Çalışmaları Dergisi, 8(16), 196-206.
  • Khan, M. H. (1996). The efficiency implications of corruption. Journal of International Development, 8(5), 683-696.
  • Koyuncu, C., & Ünver, M. (2017). Information and Communication Technologies (ICTs) and Corruption Level: Empirical Evidence from Panel Data Analysis. The Journal of International Scientific Researches, 2(6).
  • Lee, M.-H., & Lio, M.-C. (2016). The Impact Of Information and Communication Technology on Public Governance and Corruption in China. Information Development, 32(2), 127-141.
  • Leff, N. H. (1964). Economic Development Through Bureaucratic Corruption. American Behavioral Scientist, 8(3), 8–14.
  • Linhartová, V. (2017). THE ROLE OF E-GOVERNMENT IN MITIGATING CORRUPTION. Scientific Papers of the University of Pardubice - Series D, Faculty of Economics and Administration, 40, 120-131.
  • Lio, M.-C., Liu, M.-C., & Ou, Y.-P. (2011). Can the internet reduce corruption? A cross-country study based on dynamic panel data models. Government Information Quarterly, 28, 47-53.
  • Mimbi, L., & Bankole, F. (2016). Factors Influencing ICT Service Efficiency in Curbing Corruption in Africa: A Bootstrap Approach. SAICSIT '16: Proceedings of the Annual Conference of the South African Institute of Computer Scientists and Information Technologists.
  • Oktar, S. (2003). Yolsuzluk Ekonomisi. Marmara Üniversitesi İ.İ.B.F. Dergisi, 18(1), 13-27. Retrieved Nisan 3, 2019, from http://www.sbb.gov.tr/kalkinma-planlari/
  • Paldam, M. (2002). The cross-country pattern of corruption: economics, culture and the seesaw dynamics. European Journal of Political Economy, 18(2), 215-240.
  • Paul, B. P. (2010). Does corruption foster growth in Bangladesh? International Journal of Development Issues, 9(3), 246-262.
  • Sandholtz, W., & Koetzle, W. (2000). Accounting for Corruption: Economic Structure, Democracy and Trade. International Studies Quarterly, 44(1), 31-50.
  • Sassi, S., & Ali, M. S. (2017). Corruption in Africa: What role does ICT diffusion play. Telecommunications Policy, 41, 662-669.
  • Seldadyo, H., & Haan, J. (2006). The Determinants of Corruption a Literature Survey and New Evidence. Paper Prepared for the 2006 EPCS Conference.
  • Shim, D. C., & Eom, T. (2008). E-Government and Anti-Corruption: Empirical Analysis of International Data. International Journal of Public Administration, 31(3), 298-316.
  • Shrivastava, U., & Bhattacherjee, A. (2014). ICT Development and Corruption: An Empirical Study. Twentieth Americas Conference on Information Systems, (s. 1-9).
  • Soto, M. (2009). System GMM Estimation with a Small Sample. Barselona Economics Working Paper Series. Working Paper No 395. Mayıs 5, 2020 tarihinde https://www.researchgate.net/publication/229054201_System_GMM_Estimation_with_a_Small_Sample adresinden alındı
  • Swaleheen, M. (2011). Economic growth with endogenous corruption: an empirical study. Public Choice, 146, 23–41.
  • Tanzi, V. (1998). Corruption Around The World: Causes, Consequences, Scope, and Cures. Staff Paper, 45(4). https://www.imf.org/en/Publications/WP/Issues/2016/12/30/Corruption-Around-the-World-Causes-Consequences-Scope-and-Cures-2583 adresinden alındı
  • The Worldwide Governance Indicators. (2020). https://info.worldbank.org/governance/wgi/ adresinden alındı
  • Transparency International. (2020). 2020 tarihinde Transparency International: https://www.transparency.org/ adresinden alındı
  • Van Rijckeghem, C., & Weder, B. (1997). Corruption and the Rate of Temptation: Do Low Wages in the Civil Service Cause Corruption? IMF Working Paper WP/ 97/ 73. Washington: International Monetary Fund.
  • Vinod, H. D. (1999). Statistical Analysis of Corruption Data and Using the Internet to Reduce Corruption . Journal of Asian Economics.
  • Wu, W.-C. (2011). Internet Technology and its Impact on Corruption. San Diego: A Senior Honors Thesis, University of California.
  • Yakışık, H., & Çetin, A. (2014). Yolsuzlukların Sosyoekonomik Belirleyicileri: Yatay Kesit Veri Analizi. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 28(3), 205-224.
  • Yardımcıoğlu, F. (2013). Türk Cumhuriyetlerinde Demokrasi ve Yolsuzluk İlişkisi: Panel Veri Analizi. Abant İzzet Baysal Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 13(2), 437-457.
Toplam 63 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Ekonomi
Bölüm Araştırma Makalesileri
Yazarlar

Cemre Nur Çetin 0000-0002-7396-7859

Yayımlanma Tarihi 30 Eylül 2020
Gönderilme Tarihi 21 Ağustos 2020
Yayımlandığı Sayı Yıl 2020 Cilt: 21 Sayı: 3

Kaynak Göster

APA Çetin, C. N. (2020). İnternet Kullanımı Yolsuzluğu Azaltır mı? BİT Çerçevesinde Panel Veri Analizi. Anadolu Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 21(3), 41-61.

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