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Ekonomik Risk, Ekonomik Özgürlük İndeksi, Yolsuzluk Algısı İndeksi ve İnsani Gelişim İndeksi’nin Mekânsal Analizi

Yıl 2024, , 213 - 241, 30.07.2024
https://doi.org/10.17233/sosyoekonomi.2024.03.11

Öz

Bu çalışmanın amacı 163 ülkenin ekonomik risk (ER), ekonomik özgürlük indeksi (EÖİ), yolsuzluk algısı indeksi (YAİ) ve insani gelişim indeksi (İGİ) açısından mekânsal (komşuluk) ilişkilerini incelemektir. Mekânsal analiz için Moran I, Coğrafi Ağırlıklı Regresyon (GWR) ve Çok Ölçekli Coğrafi Ağırlıklı Regresyon (MGWR) yöntemleri kullanılmıştır. MGWR modelleri, dünya genelinde ülkelerin komşu ülkeleriyle ER, EÖİ ve YAİ açısından güçlü mekânsal ilişkilere sahip olduğunu fakat İGİ açısından anlamlı olmadığını göstermiştir. Bu sonuç ER, EÖİ ve YAİ göstergelerinin daha çok ülke ekonomisiyle ilgili olması ve günümüzde ülkelerin ekonomik yönden birbirine bağımlı hale gelmesiyle açıklanabilir. İGİ ise insan yaşam kalitesine odaklanması ve ülkeler arasındaki sosyal-kültürel farklılıkların varlığı anlamlı mekânsal ilişkilerin olmamasına sebep olabilir.

Kaynakça

  • Afi, H. et al. (2022), “Do Foreign Investment and Economic Freedom Matter For Behavioral Entrepreneurship? Comparing Opportunity Versus Necessity Entrepreneurs”, Social Change, 181, 121761.
  • Altay, H. & F. Çelebioğlu (2011), “Spatial Analysis of Relations Among Democracy, Economic Freedom And Economic Growth: A Research on the European Countries”, Suleyman Demirel University the Journal of Faculty of Economics and Administrative Sciences, 16(2), 219-234.
  • Amin, S. et al. (2022), “Fishing grounds footprint and economic freedom indexes: Evidence from Asia-Pacific”, Plos One, 17(4), e0263872.
  • Anavatan, A. (2021), “ABD’de Gelir Eşitsizliği: Çok Ölçekli Coğrafi Ağırlıklı Regresyon Modeli Yaklaşımı”, içinde: Z. Yıldırım (ed.), Ekonometrik Modeller-I: Açıklamalı Uygulama Anlatımlı (1-18), Ankara: Gazi Kitabevi.
  • Anselin, L. (1988), Spatial Econometrics: Methods and Models, Dordrecht: Springer Science+Business Media.
  • Aral, N. & H. Bakır (2023), “A Spatial Analysis of Happiness”, Panoeconomicus, 71(1), 135-151.
  • ArcGIS (2022), Interpreting GWR Result, <https://desktop.arcgis.com/en/arcmap/latest/tools/spatial-statistics-toolbox/interpreting-gwr-results.htm>, 13.01.2023.
  • ArcGIS Pro (2021), Data Classification Methods, <https://pro.arcgis.com/en/pro-app/latest/help/mapping/layer-properties/data-classification-methods.htm>, 10.01.2023.
  • Ashraf, J. (2022), “The Spillover Effects of Political Risk, Financial Risk, And Economic Freedom On Ecological Footprint: Empirical Evidence From Belt And Road Initiative Countries”, Borsa Istanbul Review, 22(5), 873-885.
  • Aydın, O. vd. (2018), “Mekânsal Veri Analizi Teknikleriyle Türkiye’de Toplam Doğurganlık Hızının Dağılımı ve Modellenmesi”, Journal of Geography, 37, 27-45.
  • Bhimani, A. et al. (2022), “Do National Development Factors Affect Cryptocurrency Adoption?”, Technological Forecasting and Social Change, 181, 121739.
  • Bologna, J. (2014), “A Spatial Analysis of Entrepreneurship and Institutional Quality: Evidence from U.S. Metropolitan Areas”, Journal of Regional Analysis and Policy, 44(1), 109-131.
  • Brkić, I. et al. (2020), “The Impact of Economic Freedom on Economic Growth? New European Dynamic Panel Evidence”, Journal of Risk and Financial Management, 13(2), 26.
  • Brunsdon, C. et al. (1996), “Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity”, Geographical Analysis, 28, 281-298.
  • Buchholz, M. & L. Tonzer (2016), “Sovereign Credit Risk Co-Movements in the Eurozone: Simple Interdependence or Contagion?”, International Finance, 19, 246-268.
  • Chen, S. et al. (2023), “The Measurements and Analysis of Spatial-Temporal Variations of Human Development Index Based on Planetary Boundaries in China: Evidence from Provincial-Level Data”, Land, 12(3), 691.
  • Chih, Y-Y. et al. (2023), “A Spatial Analysis of Local Corruption on Foreign Direct Investment: Evidence from Chinese Cities”, European Journal of Political Economy, 79, 102443.
  • Ciftci, C. & D. Durusu-Ciftci (2022), “Economic Freedom, Foreign Direct Investment, and Economic Growth: The Role of Sub-Components of Freedom”, The Journal of International Trade & Economic Development, 31(2), 233-254.
  • Cima, E.G. et al. (2021), “A Spatial Analysis of Western Paraná: Scenarios for Regional Development”, Revista Brasileira de Gestão e Desenvolvimento Regional, 17(2), 151-164.
  • Darsyah, M.Y. et al. (2018), “Spatial Modeling for Human Development Index in Central Java”, South East Asia Journal of Contemporary Business, Economics and Law, 16(5), 36-41.
  • Debarsy, N. et al. (2018), “Measuring Sovereign Risk Spillovers and Assessing the Role of Transmission Channels: A Spatial Econometrics Approach”, Journal of Economic Dynamics and Control, 87(C), 21-45.
  • Dell’Erba, S. et al. (2013), “Spatial Spillovers in Emerging Market Spreads”, Empirical Economics, 45, 735-756.
  • Deng, W. et al. (2022), “Economic Performance and Natural Resources: Evaluating The Role of Economic Risk”, Resources Policy, 78, 102840.
  • Djokoto, J. G. (2022), “The Investment Development Path and Human Development: Is There A Nexus?”, Research in Globalization, 4, 100079.
  • Doğan, Ö. & Y. Kılıç (2022), “BRICS-T Ülke Piyasalarında Risk Ayrıştırma”, Gaziantep University Journal of Social Sciences, 21(4), 2175-2186.
  • Domashova, J. & A. Politova (2021). “The Corruption Perception Index: Analysis of Dependence on Socio-Economic Indicators”, Procedia Computer Science, 190, 193-203.
  • Elhorst, J.P. (2014), Spatial Econometrics: From Cross-Sectional Data to Spatial Panels, Berlin/Heidelberg: Springer.
  • Farber, S. & A. Páez (2007), “A Systematic Investigation of Cross-Validation in GWR Model Estimation: Empirical Analysis and Monte Carlo Simulations”, Journal of Geographical Systems, 9, 371-396.
  • Fischer, M. & A. Getis (2010), Handbook of Applied Spatial Analysis, Berlin/Heidelberg: Springer- Verlag.
  • Fotheringham, A.S. et al. (2002), Geographically Weighted Regression, England: John Wiley & Sons Ltd.
  • Fotheringham, A.S. et al. (2017), “Multi-scale Geographically Weighted Regression (MGWR)”, Annals of the American Association of Geographers, 107(6), 1247-1265.
  • Fotheringham, A.S. et al. (2019), “Examining the Influences of Air Quality in China's Cities Using Multi-Scale Geographically Weighted Regression”, Transactions in GIS, 23(6), 1444-1464.
  • Garcia-Portilla, J. (2021), “Diagnosing Corruption and Prosperity in Europe and the Americas (A)”, in: Ye Shall Know Them by Their Fruits (29-32), Contributions to Economics. Springer, Cham.
  • Geary, R.C. (1954), “The Contiguity Ratio and Statistical Mapping”, The Incorporated Statistician, 5(3), 115-146.
  • Goel, R.K. & J.W. Saunoris (2022), “Corrupt Thy Neighbor? New Evidence of Corruption Contagion From Bordering Nations”, Journal of Policy Modeling, 44(3), 635-652.
  • Gouvea, R. et al. (2022), “Does Transitioning To A Digital Economy Imply Lower Levels of Corruption?”, Thunderbird International Business Review, 64( 3), 221-233.
  • Griffith, D.A. (2008), “Spatial-Filtering-Based Contributions to a Critique of Geographically Weighted Regression (GWR)”, Environment and Planning A: Economy and Space, 40(11), 2751-2769.
  • Hassan, T. et al. (2022), “International Trade and Consumption-Based Carbon Emissions: Evaluating The Role of Composite Risk For RCEP Economies”, Environmental Science and Pollution Research, 29, 3417-3437.
  • Isiksal, A.Z. & A.F. Assi (2022), “Determinants of Sustainable Energy Demand in The European Economic Area: Evidence From The PMG-ARDL Model”, Social Change, 183, 121901.
  • Kaewnern, H. et al. (2023), “Investigating The Role of Research Development and Renewable Energy on Human Development: An Insight from The Top Ten Human Development Index Countries”, Energy, 262(B), 125540.
  • Kalesnikaite, V. et al. (2022), “Parsing The Impact of E-Government on Bureaucratic Corruption”, Governance, 36(3), 827-842.
  • Karabchuk, T. et al. (2022), “Life Satisfaction and Desire to Emigrate: What Does The Cross-National Analysis Show?”, International Migration, 61(3), 349-372.
  • Lee, C.-C. et al. (2022), “Financial Aid and Financial Inclusion: Does Risk Uncertainty Matter?”, Pacific-Basin Finance Journal, 71(42), 101700.
  • LeSage, J. & R.K. Pace (2009), Introduction to Spatial Econometrics, Boca Raton, FL: Chapman & Hall/CRC Taylor & Francis Group.
  • Li, Z., et al. (2020), “Measuring Bandwidth Uncertainty in Multiscale Geographically Weighted Regression Using Akaike Weights”, Annals of the American Association of Geographers, 110(5), 1500-1520.
  • Lian, X. et al. (2023), “Analysis of Spatial Differences in Global Regional Human Development Index Under Planetary Pressure and Decomposition Study of Driving Factors”, Journal of Environmental Management, 348, 119292.
  • Liu, P. & W.-Q. Huang (2023), “Spatial Analysis of Sovereign Risk From the Perspective of EPU Spillovers”, International Review of Economics & Finance, 89, 427-443.
  • Mahmood, M.T. et al. (2022), “The Relevance of Economic Freedom For Energy, Environment, And Economic Growth in Asia-Pacific Region”, Environmental Science and Pollution Research, 29, 5396-5405.
  • Mallek, R.S. et al. (2022), “Herding Behaviour Heterogeneity Under Economic and Political Risks: Evidence From GCC”, Economic Analysis and Policy, 75, 345-361.
  • Marti, L. et al. (2022), “Analysis of The Nexus Between Country Risk, Environmental Policies, and Human Development”, Energy Research & Social Science, 92, 102767.
  • Masduki, U. et al. (2022), “How can Quality Regional Spending Reduce Poverty and Improve Human Development Index?”, Journal of Asian Economics, 82, 101515.
  • Mendoza-Macías, M.M. (2019), “Higher Education, Social Welfare, and Corruption: Some Challenges for Universities in Guayaquil, Ecuador”, in: S. Nair & J. Saiz-Álvarez (eds.), Handbook of Research on Ethics, Entrepreneurship, and Governance in Higher Education (54-78), IGI Global.
  • Miranda-Lescano, R. et al. (2022), “Human Development and Decentralization: The Importance of Public Health Expenditure”, Annals of Public and Cooperative Economics, 94(1), 191- 219.
  • Mohammadi, H. et al. (2022), “Does Freedom Matter for Sustainable Economic Development? New Evidence from Spatial Econometric Analysis”, Mathematics, 11(1), 145.
  • Moran, P.A.P. (1948), “The Interpretation of Statistical Maps”, Journal of the Royal Statistical Society. Series B (Methodological), 10(2), 243-251.
  • Moran, P.A.P. (1950), “Notes on Continuous Stochastic Phenomena”, Biometrika, 37(1/2), 17-23.
  • Musonera, E. (2008), “Country Risk Factors: An Empirical Study of FDI Determinants in SSA”, Journal of International Management Studies, 3(1), 1-9.
  • Nairobi, N. & N. Amelia (2022), “Political Stability, Index Perception of Corruption and Direct Foreign Investment in Southeast Asia”, E-Jurnal Ekonomi dan Bisnis Universitas Udayana, 11(2), 187-196.
  • Noumba, I. et al. (2022), “Do Globalization and Resource Rents Matter For Human Well-Being? Evidence From African Countries”, International Economics, 170, 49-65.
  • Okunev, I. & E. Zakharova (2023), “The Neighborhood Effect on Perceptions of Corruption: Comparative Spatial Autocorrelation Analysis”, International Trends, 21(2), 103-119.
  • Oshan, T.M. & A.S. Fotheringham (2018), “A Comparison of Spatially Varying Regression Coefficient Estimates Using Geographically Weighted and Spatial-Filter-Based Techniques”, Geographical Analysis, 50, 53-75.
  • Oshan, T.M. et al. (2019), “A Comment on Geographically Weighted Regression with Parameter-Specific Distance Metrics”, International Journal of Geographical Information Science, 33(7), 1289-1299.
  • Padilla, A. & N. Cachanosky (2022), “Immigration and Economic Freedom of The US States: Does The Institutional Quality of Immigrants' Origin Countries Matter?”, Contemporary Economic Policy, 41(3), 489-512.
  • Paelinck, J. & L. Klaassen (1979), Spatial Econometrics, Saxon House: Farnborough, Hants.
  • Páez, A. et al. (2011), “A Simulation-Based Study of Geographically Weighted Regression as a Method for Investigating Spatially Varying Relationships”, Environment and Planning A: Economy and Space, 43(12), 2992-3010.
  • Penska, A. (2015), “Determinants of Corruption in Ukrainian Regions: Spatial Analysis”, Ekonomia, 42, 135-160.
  • Pereira, M.M. & P. Fernandez-Vazquez (2022), “Does Electing Women Reduce Corruption? A Regression Discontinuity Approach”, Legislative Studies Quarterly, 48(4), 731-763.
  • Piribauer, P. et al. (2023), “Beyond Distance: The Spatial Relationships of European Regional Economic Growth”, Journal of Economic Dynamics and Control, 155, 104735.
  • Pirvan, C. & I. Nıșulescu (2022), “Poverty and Inequality As Predictors of Corruption”, CECCAR Business Review, 3(4), 66-72.
  • Pratama, A.D. & U. Ciptawaty (2022), “Economic Spatial Patterns and Human Development Index Districts and Cities in Five Southern Sumatera Provinces,” Jurnal Pembangunan Wilayah dan Kota, 18(2), 192-208.
  • Priya, P. & C. Sharma (2022), “Do Financial Constraints and Corruption Limit Firms' Innovation Capability? Evidence From Developing Economies”, Managerial and Decision Economics, 44(4), 1935-1961.
  • Resce, G. (2022), “Wealth-Adjusted Human Development Index”, Journal of Cleaner Production, 318, 128587.
  • Romo, C.M. & X. Romero-Vidal (2022), “In the Eyes of the Beholder? Understanding Policymakers' Perceptions of Corruption”, Legislative Studies Quarterly, 48(3), 535-559.
  • Sadiq, M. et al. (2022), “Does Nuclear Energy Consumption Contribute to Human Development? Modeling The Effects of Public Debt and Trade Globalization in an OECD Heterogeneous Panel”, Journal of Cleaner Production, 375(1), 133965.
  • Sultana, N. et al. (2022), “The Effect of the Informal Sector on Sustainable Development: Evidence from Developing Countries”, Business Strategy & Development, 5(4), 437-451.
  • Tag, M.N. & S. Degirmen (2022), “Economic Freedom and Foreign Direct Investment: Are They Related?”, Economic Analysis and Policy, 73, 737-752.
  • The Heritage Foundation (2023), About The Index, <https://www.heritage.org/index/about>, 18.01.2023.
  • The Human Development Reports (2023), What Is Human Development?, <https://hdr.undp.org/about/human-development>, 18.01.2023.
  • Tobler, W.R. (1970), “A Computer Movie Simulating Urban Growth in The Detroit Region”, Economic Geography, 46, 234-240.
  • Transparency International (2023), What Is Corruption?, <https://www.transparency.org/en/what-is-corruption>, 18.01.2023.
  • Wang, Q. et al. (2022), “Renewable Energy and Economic Growth: New Insight From Country Risks”, Energy, 238(C), 122018.
  • Wheeler, D. & M. Tiefelsdorf (2005), “Multicollinearity and Correlation Among Local Regression Coefficients in Geographically Weighted Regression”, Journal of Geographical Systems, 7, 161-187.
  • Wolf, L.J. et al. (2018). “Single and Multiscale Models of Process Spatial Heterogeneity”, Geographical Analysis, 50(3), 223-246.
  • Yang, Q. et al. (2018), “County-Scale Migration Attractivity And Factors Analysis”, 26th International Conference on Geoinformatics (1-7), Piscataway, NJ: IEEE.
  • Yu, H. et al. (2020), “On the Measurement of Bias in Geographically Weighted Regression Models”, Spatial Statistics, 38, 100453.
  • Yulianti, S. et al. (2021), “Spatial Panel Data Model on Human Development Index at Central Java”, Journal of Physics: Conference Series, 1722(1), 012090.
  • Zallé, O. (2017), “Spatial Effect of Political Risk on Economic Growth in Africa”, Modern Economy, 8, 1383-1399.
  • Zhao, J. et al. (2022), “Do Good Intentions Bring Bad Results? Climate Finance and Economic Risks”, Finance Research Letters, 48, 103003.

Spatial Analysis of Economic Risk, Economic Freedom Index, Corruption Perceptions Index and Human Development Index

Yıl 2024, , 213 - 241, 30.07.2024
https://doi.org/10.17233/sosyoekonomi.2024.03.11

Öz

This study aims to examine the spatial (neighbourhood) relations of 163 countries in terms of economic risk (ER), economic freedom index (EFI), corruption perception index (CPI) and human development index (HDI). Moran I, Geographically Weighted Regression (GWR) and Multiscale Geographically Weighted Regression (MGWR) methods were used for spatial analysis. The MGWR models demonstrated that countries globally have strong spatial relationships with their neighbouring countries regarding ER, EFI, and CPI but are not significant regarding HDI. This result can be explained by the fact that ER, EFI and CPI indicators are mostly related to the country's economy and that countries have become economically interdependent today. However, HDI may not have resulted in significant spatial relationships due to its focus on human quality of life and social-cultural differences among countries.

Kaynakça

  • Afi, H. et al. (2022), “Do Foreign Investment and Economic Freedom Matter For Behavioral Entrepreneurship? Comparing Opportunity Versus Necessity Entrepreneurs”, Social Change, 181, 121761.
  • Altay, H. & F. Çelebioğlu (2011), “Spatial Analysis of Relations Among Democracy, Economic Freedom And Economic Growth: A Research on the European Countries”, Suleyman Demirel University the Journal of Faculty of Economics and Administrative Sciences, 16(2), 219-234.
  • Amin, S. et al. (2022), “Fishing grounds footprint and economic freedom indexes: Evidence from Asia-Pacific”, Plos One, 17(4), e0263872.
  • Anavatan, A. (2021), “ABD’de Gelir Eşitsizliği: Çok Ölçekli Coğrafi Ağırlıklı Regresyon Modeli Yaklaşımı”, içinde: Z. Yıldırım (ed.), Ekonometrik Modeller-I: Açıklamalı Uygulama Anlatımlı (1-18), Ankara: Gazi Kitabevi.
  • Anselin, L. (1988), Spatial Econometrics: Methods and Models, Dordrecht: Springer Science+Business Media.
  • Aral, N. & H. Bakır (2023), “A Spatial Analysis of Happiness”, Panoeconomicus, 71(1), 135-151.
  • ArcGIS (2022), Interpreting GWR Result, <https://desktop.arcgis.com/en/arcmap/latest/tools/spatial-statistics-toolbox/interpreting-gwr-results.htm>, 13.01.2023.
  • ArcGIS Pro (2021), Data Classification Methods, <https://pro.arcgis.com/en/pro-app/latest/help/mapping/layer-properties/data-classification-methods.htm>, 10.01.2023.
  • Ashraf, J. (2022), “The Spillover Effects of Political Risk, Financial Risk, And Economic Freedom On Ecological Footprint: Empirical Evidence From Belt And Road Initiative Countries”, Borsa Istanbul Review, 22(5), 873-885.
  • Aydın, O. vd. (2018), “Mekânsal Veri Analizi Teknikleriyle Türkiye’de Toplam Doğurganlık Hızının Dağılımı ve Modellenmesi”, Journal of Geography, 37, 27-45.
  • Bhimani, A. et al. (2022), “Do National Development Factors Affect Cryptocurrency Adoption?”, Technological Forecasting and Social Change, 181, 121739.
  • Bologna, J. (2014), “A Spatial Analysis of Entrepreneurship and Institutional Quality: Evidence from U.S. Metropolitan Areas”, Journal of Regional Analysis and Policy, 44(1), 109-131.
  • Brkić, I. et al. (2020), “The Impact of Economic Freedom on Economic Growth? New European Dynamic Panel Evidence”, Journal of Risk and Financial Management, 13(2), 26.
  • Brunsdon, C. et al. (1996), “Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity”, Geographical Analysis, 28, 281-298.
  • Buchholz, M. & L. Tonzer (2016), “Sovereign Credit Risk Co-Movements in the Eurozone: Simple Interdependence or Contagion?”, International Finance, 19, 246-268.
  • Chen, S. et al. (2023), “The Measurements and Analysis of Spatial-Temporal Variations of Human Development Index Based on Planetary Boundaries in China: Evidence from Provincial-Level Data”, Land, 12(3), 691.
  • Chih, Y-Y. et al. (2023), “A Spatial Analysis of Local Corruption on Foreign Direct Investment: Evidence from Chinese Cities”, European Journal of Political Economy, 79, 102443.
  • Ciftci, C. & D. Durusu-Ciftci (2022), “Economic Freedom, Foreign Direct Investment, and Economic Growth: The Role of Sub-Components of Freedom”, The Journal of International Trade & Economic Development, 31(2), 233-254.
  • Cima, E.G. et al. (2021), “A Spatial Analysis of Western Paraná: Scenarios for Regional Development”, Revista Brasileira de Gestão e Desenvolvimento Regional, 17(2), 151-164.
  • Darsyah, M.Y. et al. (2018), “Spatial Modeling for Human Development Index in Central Java”, South East Asia Journal of Contemporary Business, Economics and Law, 16(5), 36-41.
  • Debarsy, N. et al. (2018), “Measuring Sovereign Risk Spillovers and Assessing the Role of Transmission Channels: A Spatial Econometrics Approach”, Journal of Economic Dynamics and Control, 87(C), 21-45.
  • Dell’Erba, S. et al. (2013), “Spatial Spillovers in Emerging Market Spreads”, Empirical Economics, 45, 735-756.
  • Deng, W. et al. (2022), “Economic Performance and Natural Resources: Evaluating The Role of Economic Risk”, Resources Policy, 78, 102840.
  • Djokoto, J. G. (2022), “The Investment Development Path and Human Development: Is There A Nexus?”, Research in Globalization, 4, 100079.
  • Doğan, Ö. & Y. Kılıç (2022), “BRICS-T Ülke Piyasalarında Risk Ayrıştırma”, Gaziantep University Journal of Social Sciences, 21(4), 2175-2186.
  • Domashova, J. & A. Politova (2021). “The Corruption Perception Index: Analysis of Dependence on Socio-Economic Indicators”, Procedia Computer Science, 190, 193-203.
  • Elhorst, J.P. (2014), Spatial Econometrics: From Cross-Sectional Data to Spatial Panels, Berlin/Heidelberg: Springer.
  • Farber, S. & A. Páez (2007), “A Systematic Investigation of Cross-Validation in GWR Model Estimation: Empirical Analysis and Monte Carlo Simulations”, Journal of Geographical Systems, 9, 371-396.
  • Fischer, M. & A. Getis (2010), Handbook of Applied Spatial Analysis, Berlin/Heidelberg: Springer- Verlag.
  • Fotheringham, A.S. et al. (2002), Geographically Weighted Regression, England: John Wiley & Sons Ltd.
  • Fotheringham, A.S. et al. (2017), “Multi-scale Geographically Weighted Regression (MGWR)”, Annals of the American Association of Geographers, 107(6), 1247-1265.
  • Fotheringham, A.S. et al. (2019), “Examining the Influences of Air Quality in China's Cities Using Multi-Scale Geographically Weighted Regression”, Transactions in GIS, 23(6), 1444-1464.
  • Garcia-Portilla, J. (2021), “Diagnosing Corruption and Prosperity in Europe and the Americas (A)”, in: Ye Shall Know Them by Their Fruits (29-32), Contributions to Economics. Springer, Cham.
  • Geary, R.C. (1954), “The Contiguity Ratio and Statistical Mapping”, The Incorporated Statistician, 5(3), 115-146.
  • Goel, R.K. & J.W. Saunoris (2022), “Corrupt Thy Neighbor? New Evidence of Corruption Contagion From Bordering Nations”, Journal of Policy Modeling, 44(3), 635-652.
  • Gouvea, R. et al. (2022), “Does Transitioning To A Digital Economy Imply Lower Levels of Corruption?”, Thunderbird International Business Review, 64( 3), 221-233.
  • Griffith, D.A. (2008), “Spatial-Filtering-Based Contributions to a Critique of Geographically Weighted Regression (GWR)”, Environment and Planning A: Economy and Space, 40(11), 2751-2769.
  • Hassan, T. et al. (2022), “International Trade and Consumption-Based Carbon Emissions: Evaluating The Role of Composite Risk For RCEP Economies”, Environmental Science and Pollution Research, 29, 3417-3437.
  • Isiksal, A.Z. & A.F. Assi (2022), “Determinants of Sustainable Energy Demand in The European Economic Area: Evidence From The PMG-ARDL Model”, Social Change, 183, 121901.
  • Kaewnern, H. et al. (2023), “Investigating The Role of Research Development and Renewable Energy on Human Development: An Insight from The Top Ten Human Development Index Countries”, Energy, 262(B), 125540.
  • Kalesnikaite, V. et al. (2022), “Parsing The Impact of E-Government on Bureaucratic Corruption”, Governance, 36(3), 827-842.
  • Karabchuk, T. et al. (2022), “Life Satisfaction and Desire to Emigrate: What Does The Cross-National Analysis Show?”, International Migration, 61(3), 349-372.
  • Lee, C.-C. et al. (2022), “Financial Aid and Financial Inclusion: Does Risk Uncertainty Matter?”, Pacific-Basin Finance Journal, 71(42), 101700.
  • LeSage, J. & R.K. Pace (2009), Introduction to Spatial Econometrics, Boca Raton, FL: Chapman & Hall/CRC Taylor & Francis Group.
  • Li, Z., et al. (2020), “Measuring Bandwidth Uncertainty in Multiscale Geographically Weighted Regression Using Akaike Weights”, Annals of the American Association of Geographers, 110(5), 1500-1520.
  • Lian, X. et al. (2023), “Analysis of Spatial Differences in Global Regional Human Development Index Under Planetary Pressure and Decomposition Study of Driving Factors”, Journal of Environmental Management, 348, 119292.
  • Liu, P. & W.-Q. Huang (2023), “Spatial Analysis of Sovereign Risk From the Perspective of EPU Spillovers”, International Review of Economics & Finance, 89, 427-443.
  • Mahmood, M.T. et al. (2022), “The Relevance of Economic Freedom For Energy, Environment, And Economic Growth in Asia-Pacific Region”, Environmental Science and Pollution Research, 29, 5396-5405.
  • Mallek, R.S. et al. (2022), “Herding Behaviour Heterogeneity Under Economic and Political Risks: Evidence From GCC”, Economic Analysis and Policy, 75, 345-361.
  • Marti, L. et al. (2022), “Analysis of The Nexus Between Country Risk, Environmental Policies, and Human Development”, Energy Research & Social Science, 92, 102767.
  • Masduki, U. et al. (2022), “How can Quality Regional Spending Reduce Poverty and Improve Human Development Index?”, Journal of Asian Economics, 82, 101515.
  • Mendoza-Macías, M.M. (2019), “Higher Education, Social Welfare, and Corruption: Some Challenges for Universities in Guayaquil, Ecuador”, in: S. Nair & J. Saiz-Álvarez (eds.), Handbook of Research on Ethics, Entrepreneurship, and Governance in Higher Education (54-78), IGI Global.
  • Miranda-Lescano, R. et al. (2022), “Human Development and Decentralization: The Importance of Public Health Expenditure”, Annals of Public and Cooperative Economics, 94(1), 191- 219.
  • Mohammadi, H. et al. (2022), “Does Freedom Matter for Sustainable Economic Development? New Evidence from Spatial Econometric Analysis”, Mathematics, 11(1), 145.
  • Moran, P.A.P. (1948), “The Interpretation of Statistical Maps”, Journal of the Royal Statistical Society. Series B (Methodological), 10(2), 243-251.
  • Moran, P.A.P. (1950), “Notes on Continuous Stochastic Phenomena”, Biometrika, 37(1/2), 17-23.
  • Musonera, E. (2008), “Country Risk Factors: An Empirical Study of FDI Determinants in SSA”, Journal of International Management Studies, 3(1), 1-9.
  • Nairobi, N. & N. Amelia (2022), “Political Stability, Index Perception of Corruption and Direct Foreign Investment in Southeast Asia”, E-Jurnal Ekonomi dan Bisnis Universitas Udayana, 11(2), 187-196.
  • Noumba, I. et al. (2022), “Do Globalization and Resource Rents Matter For Human Well-Being? Evidence From African Countries”, International Economics, 170, 49-65.
  • Okunev, I. & E. Zakharova (2023), “The Neighborhood Effect on Perceptions of Corruption: Comparative Spatial Autocorrelation Analysis”, International Trends, 21(2), 103-119.
  • Oshan, T.M. & A.S. Fotheringham (2018), “A Comparison of Spatially Varying Regression Coefficient Estimates Using Geographically Weighted and Spatial-Filter-Based Techniques”, Geographical Analysis, 50, 53-75.
  • Oshan, T.M. et al. (2019), “A Comment on Geographically Weighted Regression with Parameter-Specific Distance Metrics”, International Journal of Geographical Information Science, 33(7), 1289-1299.
  • Padilla, A. & N. Cachanosky (2022), “Immigration and Economic Freedom of The US States: Does The Institutional Quality of Immigrants' Origin Countries Matter?”, Contemporary Economic Policy, 41(3), 489-512.
  • Paelinck, J. & L. Klaassen (1979), Spatial Econometrics, Saxon House: Farnborough, Hants.
  • Páez, A. et al. (2011), “A Simulation-Based Study of Geographically Weighted Regression as a Method for Investigating Spatially Varying Relationships”, Environment and Planning A: Economy and Space, 43(12), 2992-3010.
  • Penska, A. (2015), “Determinants of Corruption in Ukrainian Regions: Spatial Analysis”, Ekonomia, 42, 135-160.
  • Pereira, M.M. & P. Fernandez-Vazquez (2022), “Does Electing Women Reduce Corruption? A Regression Discontinuity Approach”, Legislative Studies Quarterly, 48(4), 731-763.
  • Piribauer, P. et al. (2023), “Beyond Distance: The Spatial Relationships of European Regional Economic Growth”, Journal of Economic Dynamics and Control, 155, 104735.
  • Pirvan, C. & I. Nıșulescu (2022), “Poverty and Inequality As Predictors of Corruption”, CECCAR Business Review, 3(4), 66-72.
  • Pratama, A.D. & U. Ciptawaty (2022), “Economic Spatial Patterns and Human Development Index Districts and Cities in Five Southern Sumatera Provinces,” Jurnal Pembangunan Wilayah dan Kota, 18(2), 192-208.
  • Priya, P. & C. Sharma (2022), “Do Financial Constraints and Corruption Limit Firms' Innovation Capability? Evidence From Developing Economies”, Managerial and Decision Economics, 44(4), 1935-1961.
  • Resce, G. (2022), “Wealth-Adjusted Human Development Index”, Journal of Cleaner Production, 318, 128587.
  • Romo, C.M. & X. Romero-Vidal (2022), “In the Eyes of the Beholder? Understanding Policymakers' Perceptions of Corruption”, Legislative Studies Quarterly, 48(3), 535-559.
  • Sadiq, M. et al. (2022), “Does Nuclear Energy Consumption Contribute to Human Development? Modeling The Effects of Public Debt and Trade Globalization in an OECD Heterogeneous Panel”, Journal of Cleaner Production, 375(1), 133965.
  • Sultana, N. et al. (2022), “The Effect of the Informal Sector on Sustainable Development: Evidence from Developing Countries”, Business Strategy & Development, 5(4), 437-451.
  • Tag, M.N. & S. Degirmen (2022), “Economic Freedom and Foreign Direct Investment: Are They Related?”, Economic Analysis and Policy, 73, 737-752.
  • The Heritage Foundation (2023), About The Index, <https://www.heritage.org/index/about>, 18.01.2023.
  • The Human Development Reports (2023), What Is Human Development?, <https://hdr.undp.org/about/human-development>, 18.01.2023.
  • Tobler, W.R. (1970), “A Computer Movie Simulating Urban Growth in The Detroit Region”, Economic Geography, 46, 234-240.
  • Transparency International (2023), What Is Corruption?, <https://www.transparency.org/en/what-is-corruption>, 18.01.2023.
  • Wang, Q. et al. (2022), “Renewable Energy and Economic Growth: New Insight From Country Risks”, Energy, 238(C), 122018.
  • Wheeler, D. & M. Tiefelsdorf (2005), “Multicollinearity and Correlation Among Local Regression Coefficients in Geographically Weighted Regression”, Journal of Geographical Systems, 7, 161-187.
  • Wolf, L.J. et al. (2018). “Single and Multiscale Models of Process Spatial Heterogeneity”, Geographical Analysis, 50(3), 223-246.
  • Yang, Q. et al. (2018), “County-Scale Migration Attractivity And Factors Analysis”, 26th International Conference on Geoinformatics (1-7), Piscataway, NJ: IEEE.
  • Yu, H. et al. (2020), “On the Measurement of Bias in Geographically Weighted Regression Models”, Spatial Statistics, 38, 100453.
  • Yulianti, S. et al. (2021), “Spatial Panel Data Model on Human Development Index at Central Java”, Journal of Physics: Conference Series, 1722(1), 012090.
  • Zallé, O. (2017), “Spatial Effect of Political Risk on Economic Growth in Africa”, Modern Economy, 8, 1383-1399.
  • Zhao, J. et al. (2022), “Do Good Intentions Bring Bad Results? Climate Finance and Economic Risks”, Finance Research Letters, 48, 103003.
Toplam 88 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Ekonomi
Bölüm Makaleler
Yazarlar

Yusuf Kalkan 0000-0003-4246-8624

Erken Görünüm Tarihi 21 Temmuz 2024
Yayımlanma Tarihi 30 Temmuz 2024
Gönderilme Tarihi 15 Şubat 2023
Yayımlandığı Sayı Yıl 2024

Kaynak Göster

APA Kalkan, Y. (2024). Ekonomik Risk, Ekonomik Özgürlük İndeksi, Yolsuzluk Algısı İndeksi ve İnsani Gelişim İndeksi’nin Mekânsal Analizi. Sosyoekonomi, 32(61), 213-241. https://doi.org/10.17233/sosyoekonomi.2024.03.11
AMA Kalkan Y. Ekonomik Risk, Ekonomik Özgürlük İndeksi, Yolsuzluk Algısı İndeksi ve İnsani Gelişim İndeksi’nin Mekânsal Analizi. Sosyoekonomi. Temmuz 2024;32(61):213-241. doi:10.17233/sosyoekonomi.2024.03.11
Chicago Kalkan, Yusuf. “Ekonomik Risk, Ekonomik Özgürlük İndeksi, Yolsuzluk Algısı İndeksi Ve İnsani Gelişim İndeksi’nin Mekânsal Analizi”. Sosyoekonomi 32, sy. 61 (Temmuz 2024): 213-41. https://doi.org/10.17233/sosyoekonomi.2024.03.11.
EndNote Kalkan Y (01 Temmuz 2024) Ekonomik Risk, Ekonomik Özgürlük İndeksi, Yolsuzluk Algısı İndeksi ve İnsani Gelişim İndeksi’nin Mekânsal Analizi. Sosyoekonomi 32 61 213–241.
IEEE Y. Kalkan, “Ekonomik Risk, Ekonomik Özgürlük İndeksi, Yolsuzluk Algısı İndeksi ve İnsani Gelişim İndeksi’nin Mekânsal Analizi”, Sosyoekonomi, c. 32, sy. 61, ss. 213–241, 2024, doi: 10.17233/sosyoekonomi.2024.03.11.
ISNAD Kalkan, Yusuf. “Ekonomik Risk, Ekonomik Özgürlük İndeksi, Yolsuzluk Algısı İndeksi Ve İnsani Gelişim İndeksi’nin Mekânsal Analizi”. Sosyoekonomi 32/61 (Temmuz 2024), 213-241. https://doi.org/10.17233/sosyoekonomi.2024.03.11.
JAMA Kalkan Y. Ekonomik Risk, Ekonomik Özgürlük İndeksi, Yolsuzluk Algısı İndeksi ve İnsani Gelişim İndeksi’nin Mekânsal Analizi. Sosyoekonomi. 2024;32:213–241.
MLA Kalkan, Yusuf. “Ekonomik Risk, Ekonomik Özgürlük İndeksi, Yolsuzluk Algısı İndeksi Ve İnsani Gelişim İndeksi’nin Mekânsal Analizi”. Sosyoekonomi, c. 32, sy. 61, 2024, ss. 213-41, doi:10.17233/sosyoekonomi.2024.03.11.
Vancouver Kalkan Y. Ekonomik Risk, Ekonomik Özgürlük İndeksi, Yolsuzluk Algısı İndeksi ve İnsani Gelişim İndeksi’nin Mekânsal Analizi. Sosyoekonomi. 2024;32(61):213-41.