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Kamu Harcamaları, Kamu İstihdamı ve Kamusal Etkililiğin Yozlaşma Üzerindeki Etkisi

Yıl 2024, Cilt: 9 Sayı: 1, 112 - 123

Semra Aydoğdu Bağcı

Öz

Bu çalışmanın amacı; kamu harcamalarının, kamu istihdamının ve kamusal etkililiğin yozlaşma üzerindeki etkisini araştırmaktır. 33 OECD ülkesinin 2007-2021 dönemine ait yıllık verilerini kapsayan bu çalışmada bağımlı değişken olan yolsuzluk algı endeksine ait veriler Uluslararası Şeffaflık Örgütü resmi internet sayfasından alınmıştır. Bağımsız değişken olan kamu harcamalarının Gayri Safi Yurtiçi Hasıla (GSYH) içindeki payı ve kamu istihdamının toplam istihdam içindeki payı değişkenlerine ait veriler OECD resmi internet sayfasından alınmıştır. Diğer bağımsız değişken olan kamusal etkililik değişkeni ise Dünya Bankası resmi internet sayfasından temin edilmiştir. Panel-ARDL yönteminin kullanıldığı analiz sonucunda kamu etkililiğindeki artışın yolsuzluk algı endeksini artırdığı ve böylece yozlaşmayı azalttığı tespit edilmiştir. Bunun yanında kamu istihdamındaki artışın yolsuzluk algı endeksini azalttığı ve bu bağlamda yozlaşmayı artırdığı saptanmıştır.

Anahtar Kelimeler

Kamu Harcamaları Kamu İstihdamı Kamusal Etkililik Yozlaşma Panel-ARDL.

Kaynakça

  • Amin, M. & Soh, Y. C. (2022). Financial Constraints and the Impact of Corruption on Employment Growth. Journal of International Development, 34 (3), 612–635.
  • Balestra, P. & Nerlove, M. (1966). Pooling Cross Section and time series Data in the Estimation of a Dynamic Model: The Demand for Natural Gas. Econometrica, 34(3), 585-612.
  • Beltrán, A. (2016). Does Corruption Increase or Decrease Employment in Firms?. Applied Economics Letters, 23(5), 361–364.
  • Bouzid, B. N. (2016). Dynamic Relationship between Corruption and Youth Unemployment: Empirical Evidences from a System GMM Approach. World Bank Policy Research Working Paper, 7842, 1-23.
  • Breitung, J. (2000). The Local Power of Some Unit Root Tests for Panel Data, in Advances in Econometrics, Vol. 15: Nonstationarity Panels, and Dynamic Panels, Baltagi, B.H. (ed.), 161-177, JAI Press, Amsterdam.
  • Breusch, T. S. & Pagan, A. (1980). The Lagrange Multiplier and its Applications to Model Specification in Econometrics. Review of Economic Research, 47(1), 239-253.
  • Cooray, A. & Dzhumashev, R. (2018). The Effect of Corruption on Labour Market Outcomes. Economic Modelling, 74, 207-218.
  • Cordis, A. S. (2014). Corruption and the Composition of Public Spending in the United States. Public Finance Review, 42(6) 745-773.
  • Grunfeld, Y. & Griliches, Z. (1960). Is Aggregation Necessarily Bad?. Review of Economics and Statistics, 42(1), 1-13.
  • Güriş, S. (2015). Panel Veri Modelleri. S. Güriş (Ed.), Stata ile Panel Veri Modelleri içinde (ss. 3-38). İstanbul: Der Yayınları.
  • Gürler Hazman, G. (2021). Yozlaşma, Kamusal Etkililik ve Ekonomik Büyüme: OECD Ülkeleri Üzerinde Bir Araştırma. Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 13(4), 75-82.
  • Harris, R. & Tzavalis, E. (1999). Inference for Unit Roots in Dynamic Panels Where the Time Dimension is Fixed. Journal of Econometrics, 91(2), 201-226.
  • Hildreth, C. (1950). Combining Cross-Section Data and Time Series. Cowles Commission Discussion Paper, No. 347.
  • Hoyos, R. D. & Sarafidis, V. (2006). Stata Module to Test for Cross-Sectional Dependence in Panel Data Models. The Stata Journal, 6(4), 482-496.
  • Im, K., Pesaran, H. & Shin, Y. (2003). Testing for Unit Roots in Heterogeneous Panels. Journal of Econometrics, 115(1), 53-74.
  • Kaufmann, D., Kraay, A. & Mastruzzi, M. (2014). World Governance Indicators Project. World Bank.
  • Kaufmann, D., A. Kraay & M. Mastruzzi. (2010). The Worldwide Governance Indicators: Methodology and Analytical Issues. World Bank Policy Research Working Paper, 5430, 1-29.
  • Laureti, L., Costantiello, A. & Leogrande, A. (2022). The Fight against Corruption at Global Level. A Metric Approach. Munich Personal RePEc Archive, 115837, 1-29.
  • Lee, J. & Liu, C. (2022). Public Corruption and Government Management Capacity. Public Performance & Management Review, 45(2), 397-427.
  • Levin, A., Lin, C.-F. & Chu, C.- S. J. (2002). Unit Root Tests in Panel Data: Asymptotic and Finite-Sample Properties. Journal of Econometrics, 108(1), 1-24.
  • Liu, C. & Mikesell, J. L. (2014). The Impact of Public Officials’ Corruption on the Size and Allocation of U.S. State Spending Public Administration Review, 74(3), 346–359.
  • Malyniak, B., Martyniuk, O., & Kyrylenko, O. (2019). Corruption and Efficiency of Public Spending in States with Various Public Management Types. Economic Annals-XXI, 178(7-8), 17-27.
  • Mamun, M. A., Sohog, K. & Akhter, A. (2013). A Dynamic Panel Analysis of CSR in Bangladeshi Banking Industry. Asian Economic and Financial Review, 3(5), 560-578.
  • Min, K. S. (2023).The Impact of Corruption on Government Performance: Evidence from South Korea. Crime, Law and Social Change, 79, 319-345.
  • Mocetti, S. & Orlando, T. (2019). Corruption, Workforce Selection And Mismatch in the Public Sector. European Journal of Political Economy, 60, 101809, 1-21.
  • Montes, G. C. & Paschoal, P. C. (2016). Corruption: What are the Effects on Government Effectiveness? Empirical Evidence considering Developed and Developing Countries. Applied Economics Letters, 23(2), 146-150.
  • Kuh, E. (1959). The Validity of Cross-Sectionally Estimated Behaviour Equations in Time Series Applications. Econometrica, 27, 197-214.
  • OECD. (2023). Government at a Glance 2023. (Erişim: 29.01.2024). https://www.oecd-ilibrary.org/employment-in-general-government_b85007f1en.pdf?itemId =%2Fcontent%2Fcomponent%2Fb85007f1-en&mimeType=pdf.
  • Qadar, M., Ibrar, M., Shah Waqas, M., Liaqat, A., Afzal, I. & Israr, M. (2014). The Effects of Corruption on Employment (A Perception of Rural Educated Youth). IOSR Journal of Humanities and Social Science, 19(1), 75-79.
  • Pesaran, M. H. (2004). General Diagnostic Tests for Cross Section Dependence in Panels. Cambridge Working Papers in Econometrics, 435, 1-39.
  • Pesaran, M. H. & Shin, Y. (1995). An Autoregressive Distributed Lag Modelling Approach to Cointegration Analysis. Cambridge Working Papers in Econometrics, 9514.
  • Pesaran, M. H., Shin, Y. & Smith, R. P. (2001). Bounds Testing Approaches to the Analysis of Level Relationships. Journal of Applied Econometrics, 16, 289-326.
  • Pesaran M. H., Ullah, A. & Yamagata, T. (2008), A Bias-Adjusted LM Test of Error Cross Section Independence. Econometrics Journal, 11, 105-127.
  • Sedgo, H. & Omgba, L.-D. (2022). Corruption and Distortion of Public Expenditures: Evidence from Africa, International Tax and Public Finance, 30, 419–452.
  • Setyaningrum, D.,Wardhani, R. & Syakhroza, A. (2017). Good Public Governance, Corruption and Public Service Quality: Indonesia Evidence. International Journal of Applied Business and Economic Research, 15(19), 327-338.
  • Sevüktekin, M., Nargeleçekenler, M. & Giray, F. (2010). A Cross-Country Comparison of Corruption and Public Expenditures: A Panel Data Approach. International Journal of Public Administration, 33(3), 140-150.
  • Swaleheena, M., Ben Ali, M. S. & Temimib, A. (2019). Corruption and Public Spending on Education and Health. Applied Economics Letters, 26(4), 321-325.
  • Swamy, P. A. (1970). Efficient Inference in a Random Coefficient Regression Model. Econometrica, 38(2), 311-322.
  • Tanzi, V. & Davoodi, H. (1997). Corruption, Public Investment and Growth. IMF Working Papers, 97139, 1-23.
  • Ullah, B. (2020). Financial Constraints, Corruption, and SME Growth in Transition Economies. The Quarterly Review of Economics and Finance, 75 (C), 120-132.
  • Worldbank (2020). Anticorruption Fact Sheet. (Erişim: 05.12.2023), https://www.worldbank.org/en/news/factsheet/2020/02/19/anticorruption-fact-sheet.
  • Yamak, R. & Erdem, H. F. (2018). Türkiye Ekonomisinde Armey Eğrisi Geçerli midir?. International Journal of Economic and Administrative Studies Prof Dr. Harun Terzi Özel Sayısı, 335-346.
  • Yerdelen Tatoğlu, F. (2020). Panel Zaman Serileri Analizi. İstanbul: Beta Yayınları.
  • Yerdelen Tatoğlu, F. (2018). Panel Veri Ekonometrisi Stata Uygulamalı. İstanbul: Beta Basım Yayım Dağıtım A.Ş
  • Yerdelen Tatoğlu, F. (2013). İleri Panel Veri Analizi Stata Uygulamalı. İstanbul: Beta Basım Yayım Dağıtım A.Ş.
  • Transparency International. (2023). Corruption Perceptions Index. (Erişim: 13.10.2023), https://www.transparency.org/en/cpi/2022?gclid=CjwKCAiAk9itBhASEiwA1my_66Yg8Oo2pcdGH-M2PU5Lm_IGQ1lX7IFOYODnP_3usmGDPZw__5uf1BoC_4oQAvD_BwE&gad_source=1.
  • Transparency International. (2023). The Global Coalition against Corruption. Why Corruption Matters. (Erişim: 04.12.2023), https://www.transparency.org.uk/why-corruption-matters.
  • Zellner, A. (1962). An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias. Journal of American Statistical Association, 57, 348-368.

The Impact of Public Expenditures, Public Employment and Public Effectiveness on Corruption

Yıl 2024, Cilt: 9 Sayı: 1, 112 - 123

Semra Aydoğdu Bağcı

Öz

The purpose of this study is to investigate the impact of public expenditures, public employment and public effectiveness on corruption. In this study, which covers the annual data of 33 OECD countries for the period 2007-2021, the data on the corruption perception index, which is the dependent variable, was taken from the official website of Transparency International. Data on the independent variables, the ratio of public expenditures to Gross Domestic Product (GDP) and the share of public employment in total employment, were taken from the OECD official website. The other independent variable, the public effectiveness variable, was obtained from the World Bank official website. As a result of the analysis using the Panel-ARDL method, it was determined that the increase in public effectiveness increased the corruption perception index and thus reduced corruption. In addition, it has been determined that the increase in public employment reduces the corruption perception index and, in this context, increases corruption.

Anahtar Kelimeler

Public Expenditure Public Employment Public Effectiveness Corruption Panel-ARDL

Kaynakça

  • Amin, M. & Soh, Y. C. (2022). Financial Constraints and the Impact of Corruption on Employment Growth. Journal of International Development, 34 (3), 612–635.
  • Balestra, P. & Nerlove, M. (1966). Pooling Cross Section and time series Data in the Estimation of a Dynamic Model: The Demand for Natural Gas. Econometrica, 34(3), 585-612.
  • Beltrán, A. (2016). Does Corruption Increase or Decrease Employment in Firms?. Applied Economics Letters, 23(5), 361–364.
  • Bouzid, B. N. (2016). Dynamic Relationship between Corruption and Youth Unemployment: Empirical Evidences from a System GMM Approach. World Bank Policy Research Working Paper, 7842, 1-23.
  • Breitung, J. (2000). The Local Power of Some Unit Root Tests for Panel Data, in Advances in Econometrics, Vol. 15: Nonstationarity Panels, and Dynamic Panels, Baltagi, B.H. (ed.), 161-177, JAI Press, Amsterdam.
  • Breusch, T. S. & Pagan, A. (1980). The Lagrange Multiplier and its Applications to Model Specification in Econometrics. Review of Economic Research, 47(1), 239-253.
  • Cooray, A. & Dzhumashev, R. (2018). The Effect of Corruption on Labour Market Outcomes. Economic Modelling, 74, 207-218.
  • Cordis, A. S. (2014). Corruption and the Composition of Public Spending in the United States. Public Finance Review, 42(6) 745-773.
  • Grunfeld, Y. & Griliches, Z. (1960). Is Aggregation Necessarily Bad?. Review of Economics and Statistics, 42(1), 1-13.
  • Güriş, S. (2015). Panel Veri Modelleri. S. Güriş (Ed.), Stata ile Panel Veri Modelleri içinde (ss. 3-38). İstanbul: Der Yayınları.
  • Gürler Hazman, G. (2021). Yozlaşma, Kamusal Etkililik ve Ekonomik Büyüme: OECD Ülkeleri Üzerinde Bir Araştırma. Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 13(4), 75-82.
  • Harris, R. & Tzavalis, E. (1999). Inference for Unit Roots in Dynamic Panels Where the Time Dimension is Fixed. Journal of Econometrics, 91(2), 201-226.
  • Hildreth, C. (1950). Combining Cross-Section Data and Time Series. Cowles Commission Discussion Paper, No. 347.
  • Hoyos, R. D. & Sarafidis, V. (2006). Stata Module to Test for Cross-Sectional Dependence in Panel Data Models. The Stata Journal, 6(4), 482-496.
  • Im, K., Pesaran, H. & Shin, Y. (2003). Testing for Unit Roots in Heterogeneous Panels. Journal of Econometrics, 115(1), 53-74.
  • Kaufmann, D., Kraay, A. & Mastruzzi, M. (2014). World Governance Indicators Project. World Bank.
  • Kaufmann, D., A. Kraay & M. Mastruzzi. (2010). The Worldwide Governance Indicators: Methodology and Analytical Issues. World Bank Policy Research Working Paper, 5430, 1-29.
  • Laureti, L., Costantiello, A. & Leogrande, A. (2022). The Fight against Corruption at Global Level. A Metric Approach. Munich Personal RePEc Archive, 115837, 1-29.
  • Lee, J. & Liu, C. (2022). Public Corruption and Government Management Capacity. Public Performance & Management Review, 45(2), 397-427.
  • Levin, A., Lin, C.-F. & Chu, C.- S. J. (2002). Unit Root Tests in Panel Data: Asymptotic and Finite-Sample Properties. Journal of Econometrics, 108(1), 1-24.
  • Liu, C. & Mikesell, J. L. (2014). The Impact of Public Officials’ Corruption on the Size and Allocation of U.S. State Spending Public Administration Review, 74(3), 346–359.
  • Malyniak, B., Martyniuk, O., & Kyrylenko, O. (2019). Corruption and Efficiency of Public Spending in States with Various Public Management Types. Economic Annals-XXI, 178(7-8), 17-27.
  • Mamun, M. A., Sohog, K. & Akhter, A. (2013). A Dynamic Panel Analysis of CSR in Bangladeshi Banking Industry. Asian Economic and Financial Review, 3(5), 560-578.
  • Min, K. S. (2023).The Impact of Corruption on Government Performance: Evidence from South Korea. Crime, Law and Social Change, 79, 319-345.
  • Mocetti, S. & Orlando, T. (2019). Corruption, Workforce Selection And Mismatch in the Public Sector. European Journal of Political Economy, 60, 101809, 1-21.
  • Montes, G. C. & Paschoal, P. C. (2016). Corruption: What are the Effects on Government Effectiveness? Empirical Evidence considering Developed and Developing Countries. Applied Economics Letters, 23(2), 146-150.
  • Kuh, E. (1959). The Validity of Cross-Sectionally Estimated Behaviour Equations in Time Series Applications. Econometrica, 27, 197-214.
  • OECD. (2023). Government at a Glance 2023. (Erişim: 29.01.2024). https://www.oecd-ilibrary.org/employment-in-general-government_b85007f1en.pdf?itemId =%2Fcontent%2Fcomponent%2Fb85007f1-en&mimeType=pdf.
  • Qadar, M., Ibrar, M., Shah Waqas, M., Liaqat, A., Afzal, I. & Israr, M. (2014). The Effects of Corruption on Employment (A Perception of Rural Educated Youth). IOSR Journal of Humanities and Social Science, 19(1), 75-79.
  • Pesaran, M. H. (2004). General Diagnostic Tests for Cross Section Dependence in Panels. Cambridge Working Papers in Econometrics, 435, 1-39.
  • Pesaran, M. H. & Shin, Y. (1995). An Autoregressive Distributed Lag Modelling Approach to Cointegration Analysis. Cambridge Working Papers in Econometrics, 9514.
  • Pesaran, M. H., Shin, Y. & Smith, R. P. (2001). Bounds Testing Approaches to the Analysis of Level Relationships. Journal of Applied Econometrics, 16, 289-326.
  • Pesaran M. H., Ullah, A. & Yamagata, T. (2008), A Bias-Adjusted LM Test of Error Cross Section Independence. Econometrics Journal, 11, 105-127.
  • Sedgo, H. & Omgba, L.-D. (2022). Corruption and Distortion of Public Expenditures: Evidence from Africa, International Tax and Public Finance, 30, 419–452.
  • Setyaningrum, D.,Wardhani, R. & Syakhroza, A. (2017). Good Public Governance, Corruption and Public Service Quality: Indonesia Evidence. International Journal of Applied Business and Economic Research, 15(19), 327-338.
  • Sevüktekin, M., Nargeleçekenler, M. & Giray, F. (2010). A Cross-Country Comparison of Corruption and Public Expenditures: A Panel Data Approach. International Journal of Public Administration, 33(3), 140-150.
  • Swaleheena, M., Ben Ali, M. S. & Temimib, A. (2019). Corruption and Public Spending on Education and Health. Applied Economics Letters, 26(4), 321-325.
  • Swamy, P. A. (1970). Efficient Inference in a Random Coefficient Regression Model. Econometrica, 38(2), 311-322.
  • Tanzi, V. & Davoodi, H. (1997). Corruption, Public Investment and Growth. IMF Working Papers, 97139, 1-23.
  • Ullah, B. (2020). Financial Constraints, Corruption, and SME Growth in Transition Economies. The Quarterly Review of Economics and Finance, 75 (C), 120-132.
  • Worldbank (2020). Anticorruption Fact Sheet. (Erişim: 05.12.2023), https://www.worldbank.org/en/news/factsheet/2020/02/19/anticorruption-fact-sheet.
  • Yamak, R. & Erdem, H. F. (2018). Türkiye Ekonomisinde Armey Eğrisi Geçerli midir?. International Journal of Economic and Administrative Studies Prof Dr. Harun Terzi Özel Sayısı, 335-346.
  • Yerdelen Tatoğlu, F. (2020). Panel Zaman Serileri Analizi. İstanbul: Beta Yayınları.
  • Yerdelen Tatoğlu, F. (2018). Panel Veri Ekonometrisi Stata Uygulamalı. İstanbul: Beta Basım Yayım Dağıtım A.Ş
  • Yerdelen Tatoğlu, F. (2013). İleri Panel Veri Analizi Stata Uygulamalı. İstanbul: Beta Basım Yayım Dağıtım A.Ş.
  • Transparency International. (2023). Corruption Perceptions Index. (Erişim: 13.10.2023), https://www.transparency.org/en/cpi/2022?gclid=CjwKCAiAk9itBhASEiwA1my_66Yg8Oo2pcdGH-M2PU5Lm_IGQ1lX7IFOYODnP_3usmGDPZw__5uf1BoC_4oQAvD_BwE&gad_source=1.
  • Transparency International. (2023). The Global Coalition against Corruption. Why Corruption Matters. (Erişim: 04.12.2023), https://www.transparency.org.uk/why-corruption-matters.
  • Zellner, A. (1962). An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias. Journal of American Statistical Association, 57, 348-368.
Toplam 48 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Kamu Maliyesi
Bölüm Araştırma Makalesi
Yazarlar

Semra Aydoğdu Bağcı 0000-0001-8078-5626

Erken Görünüm Tarihi 4 Mayıs 2024
Yayımlanma Tarihi
Gönderilme Tarihi 29 Ocak 2024
Kabul Tarihi 2 Mayıs 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 9 Sayı: 1

Kaynak Göster

APA Aydoğdu Bağcı, S. (2024). Kamu Harcamaları, Kamu İstihdamı ve Kamusal Etkililiğin Yozlaşma Üzerindeki Etkisi. JOEEP: Journal of Emerging Economies and Policy, 9(1), 112-123.
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