Araştırma Makalesi
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Is Income Inequality a Determinant of Energy Poverty in Developing Countries?

Yıl 2023, Cilt: 8 Sayı: 2, 371 - 384, 30.12.2023

Serap Barış , Derya Demir

Öz

This study aims to investigate the relationship between energy poverty and income inequality in developing countries. Econometric analysis was carried out by following the panel data analysis processes with the data of 14 developing countries for the period 2000-2019. Two separate models were created for energy poverty using two different indicators (access to electricity, access to clean fuels and technologies for cooking to the total population). Models were estimated with Parks-Kmenta and Beck-Katz, estimators that can produce robust standard errors. As a result of the research, it was seen that income inequality negatively affected energy poverty indicators in three of the four estimates. Accordingly, it can be said that income inequality increases energy poverty. Based on the findings, it is recommended that policy makers in 14 developing countries take income inequality into account in their energy poverty policies.

Anahtar Kelimeler

Energy poverty Income inequality Access to energy Panel data analysis

Kaynakça

  • Abdoulaye Sy, S., & Mokaddem, L. (2022). Energy Poverty in Developing Countries: A Review of the Concept and Its Measurements. Energy Research & Social Science, 89(102562),1-14.
  • Acheampong, A. O., Shahbaz, M., Dzator, J., & Jiao, Z. (2022). Effects of Income Inequality and Governance On Energy Poverty Alleviation: Implications for Sustainable Development Policy. Utilities Policy, 78(101403),1-30.
  • Asongu, S. A., & Odhiambo, N. M. (2021). Inequality and Renewable Energy Consumption in Sub-Saharan Africa: Implication for High Income Countries. Innovation. The European Journal of Social Science Research, 20 (094), 1-22.
  • Baltagi, B. (2004). Econometric Analysis of Panel Data. New York: John Wiley and Sons.
  • Baltagi, B.H., & P.X. Wu (1999). Unequally Spaced Panel Data Regressions With AR(1) Disturbances. Econometric Theory, 15 (6), 814-823.
  • Bardazzi, R., Bortolotti, L., & Pazienza, M. G. (2021). To Eat and not to Heat? Energy Poverty and Income Inequality in Italian Regions. Energy Research & Social Science, 73 (101946), 1-15.
  • Beck, N., & Katz, Jonathan N. (1995). What to Do (and not to Do) with Time-series Cross-Section Data. American Political Science Review, 89, 634-47, https://www.researchgate.net, Erişim Tarihi: 25.02.2022.
  • Bhargava, A., L. Franzini & W. Narendranathan (1982). Serial Correlation and Fixed Effects Model. Review of Economic Studies 49(4), 533-549
  • Blomquist, J., & Westerlund, J. (2013). Testing slope homogeneity in large panels with serial correlation. Economics Letters, 121: 374-378.
  • Breusch, T. S., & Pagan, A. R. (1980). The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics. The Review of Economic Studies, 47(1), 239-253.
  • Bouzarovski, S., & Tirado-Herrero, S. (2017). The Energy Divide: Integrating Energy Transitions, Regional Inequalities and Poverty Trends in the European Union. European Urban and Regional Studies, 24(1), 69-86.
  • Bouzarovski, S., & Petrova, S. (2015). A Global Perspective on Domestic Energy Deprivation: Overcoming the Energy Poverty-Fuel Poverty Binary. Energy Research & Social Science 10, 31-40.
  • Broughton, A., Green, M., Rickard, C., Swift, S., Eichhorst, W., Tobsch, V., Magda, I., Lewandowski, P., Keister, R., Jonaviciene, D., Ramos Martín, N.E., Valsamis, D., & Tros, F. (2016). Precarious Employment in Europe: Patterns, Trends and Policy Strategy. Study. (Employment and Social Affairs). European Parliament. Directorate-General for Internal Policies. Policy Department A: Economic and Scientific Policy.(Erişim: 23.01.2023), ://www.europarl.europa.eu/RegData/etudes/STUD/2016/587285/IPOL_STU(2016)587285_EN.pdf.
  • Brown, M. B., & Forsythe, A. B. (1974). The Small Sample Behavior of Some Statistics Which Test the Equality of Several Means. Technometrics, 16(1), 129- 132.
  • Churchill, S. A., Ivanovski, K., & Munyanyi, M.E. (2021). Income Inequality and Renewable Energy Consumption: Time-varying Non-parametric Evidence. Journal of Cleaner Production, 296 (126306), 1-11.
  • Dong, K., Dou, Y., & Jiang, Q. (2022). Income Inequality, Energy Poverty, and Energy Efficiency: Who Cause Who and How? Technological Forecasting and Social Change, 179 (121622), 1-15.
  • Dong, X. Y., & Hao, Y. (2018). Would Income Inequality Affect Electricity Consumption? Evidence from China. Energy, 142, 215-227.
  • Eke, E. U., & Ayrancı, E. (2018). Türkiye’de Elektrik Enerjisi Sektörünün Enerji Yoksulluğu Açısından Değerlendirilmesi. Politik Ekonomik Kuram Sosyal Bilimler Dergisi, 2 (2), 109-109.
  • Erdoğdu, S. (2020). Dünyada ve Türkiye’de Enerji Yoksulluğu Üzerine: Türkiye’nin Enerji Görünümü. Ankara: TMMOB, Yayın No: MMO/17, 29-47.
  • Galvin, R. (2019). Letting the Gini out of The Fuel Poverty Bottle? Correlating Cold Homes and Income Inequality in European Union Countries. Energy Research & Social Science, 58 (101255), 1-14.
  • Gaye, A. (2007). Human Development Report 2007/2008 Fighting Climate Change: Human Solidarity in a Divided World. Human Development Report Office Occasional Paper.1-21.
  • González-Eguino, M. (2015). Energy poverty: An overview. Renewable and Sustainable Energy Reviews, 47, 377-385.
  • Gujarati, D. (2016). Örneklerle Ekonometri. Nasip Bolatoğlu. (Çev.). Ankara: BB101 Yayınları.
  • IEA (2021). The Energy Progress Report. Tracking SDG7. (Erişim: 02.04.2023), www.worldbank.org.
  • IEA (2022a). Global Energy Crisis. (Erişim: 24.01.2023). https://www.iea.org/topics/global-energy-crisis.
  • IEA (2022b). The Energy Progress Report. Tracking SDG7. (Erişim: 02.04.2023), www.worldbank.org.
  • IEA, IRENA, UNSD, WB, WHO (2019). Tracking SDG 7: The Energy Progress Report 2019. (Erişim:03.01.2023), https://www.worldbank.org/en/news/feature/2018/04/18/access-energy-sustainable-development-goal-7.
  • EU (2022). Report From the Commıssıon to the European Parliament, the Council, the European Economic and Social Committee and The Committee of The Regions State of the Energy Union. Brussels, 18.10.2022 COM(2022) 547 Final. (Erişim:02.04.2023), https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52022DC0547.
  • Igawa, M., & Managi, S. (2022). Energy Poverty and Income Inequality: An Economic Analysis of 37 Countries, Applied Energy, 306 (118076), 1-18.
  • Jones, S. (2016). Social Causes and Consequences of Energy Poverty. In: Csiba, K. (Ed.), Energy Poverty Handbook (21-38). Brussels: European Union.
  • Kavukçu, F. O. (2022). Avrupa’nın Enerji Krizi ile İmtihanı, Kış Öncesi Tedbirler ve Türkiye’nin Muhtemel Katkıları. Seta Perspektif, 345, 1-8.
  • Kmenta, J. (1986). Elements of Econometrics. The University of Michigan Press, Second edition, New York.
  • Le, T.-H., Nguyen, C.P., Su, T.D., & Tran-Nam, B. (2020). The Kuznets Curve for Export Diversification and Income Inequality: Evidence from a Global Sample. Economic. Analysis and Policy, 65 (C), 21-39.
  • Levene, H. (1960). Robust tests for equality of variances. Contributions to probability and statistics, 1, 278-292
  • Makhlouf, Y. (2023). Trends in Income Inequality: Evidence from Developing and Developed Countries. Social Indicators Research, 165(1), 213-243.
  • Muhammad, I., Özcan, R., Jain, V., Ramos-Meza, C. S., & Chawla, C. (2022). Do Drivers of Renewable Energy Consumption Matter for BRICS Economies? Nexus Among Technological Innovation, Environmental Degradation, Economic Growth, and Income Inequality. Environmental Science and Pollution Research, 30, 1-11.
  • Murtaza, G., & Faridi, M. Z. (2015). Causality Linkages among Energy Poverty, Income Inequality, Income Poverty and Growth: A System Dynamic Modelling Approach. The Pakistan Development Review, 54 (4), Part II, 407-425.
  • Nagaj, R., & Korpysa, J. (2020). Impact of COVID-19 On The Level of Energy Poverty in Poland. Energies, 13(18), 4977, 1-18.
  • Nguyen, C. P., & Nasir, M. A. (2021). An Inquiry into the Nexus Between Energy Poverty and Income Inequality in the Light of Global Evidence. Energy Economics, 99 (105289), 1-14.
  • Parks, Richard W. (1967). Efficient Estimation of a System of Regression Equations When Disturbances Are Both Serially and Contemporaneously Correlated. Journal of the American Statistical Association, 318(62), 500-509.
  • Pesaran, H. (2004). General Diagnostic Tests for Cross Section Dependence in Panels. Cambridge: University of Cambridge Working Paper.
  • Pesaran, M. H., Ullah, A., & Yamagata, T. (2008). A Bias-adjusted LM Test of Error Cross-section Independence. Econometrics Journal, 11, 105127.
  • Pesaran, M. H., & Yamagata, T. (2008). Testing Slope Homogeneity in Large Panel. Journal of Econometrics, 142 (1), 50-93.
  • Pye, S., Dobbins, A., Baffert, C., Brajkovġc, J., Grgurev, I., De Miglio, R., & Deane, P. (2015). Energy Poverty and Vulnerable Consumers in the Energy Sector Across the EU: Analysis of Policies and Measures. (03.01.2023), Erişim: www.insightenergy.org.
  • Rafi, M., Naseef, M., & Prasad, S. (2021). Multidimensional Energy Poverty and Human Capital Development: Empirical Evidence from India. Energy Economics, 101(C), 105427.
  • Recaldea, M., Peraltab, A., Oliverasa, L., Tirado-Herrerof, S., Borrella, C., Palenciab, L., Gotsensb, M., Artazcoza, L., & Mari-Dell’Olmob, M. (2019). Structural Energy Poverty Vulnerability and Excess Winter Mortality in The European Union: Exploring The Association Between Structural Determinants and Health. Energy Policy, 133 (110869), 1-18.
  • Sarkodie, S. A., & Adams, S. (2020). Electricity Access, Human Development Index, Governance And Income Inequality in Sub-Saharan Africa, Energy Reports, 6, 455-466.
  • Sen, A., Nepal, R., & Jamasb, T. (2016). Reforming-Electricity Reforms Empirical Evidence from Asian Economies. The Oxford Institute for Energy Studies, OIES Paper: EL 18, 1-54.
  • Sharma, K.R., & Chan, G. (2016). Energy Poverty: Electrification and Well-being. Nature Energy, 1(11), 1-2.
  • Sharma, R., & Rajpurohit, S. S. (2022). Nexus Between Income Inequality and Consumption of Renewable Energy in India: A Nonlinear Examination. Economic Change and Restructuring, 55(4), 2337-2358.
  • Solt, F. (2016). The Standardized World Income Inequality Database. Social Science Quarterly, 97(5), 1267-1281.
  • Swamy, P. A. V. B. (1970). Efficient Inference in a Random Coefficient Regression Model. Econometrica, 38 (2), 311-323.
  • SWIID (2023). Standardized World Income Inequality Database. (Erişim: 03.01.2023), https://fsolt.org/swiid/.
  • Tekin, S., & Dolu, M. T. (2020). Güney-Güney İşbirliğinin İdeolojik Temelleri: Bağlantısızlar Hareketi ve Küresel Güney. Dicle Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (24), 65-81.
  • Thomson, H., Bouzarovski, S., & Snell, C. (2017) Rethinking The Measurement of Energy Poverty in Europe: A Critical Analysis of Indicators and Data. Indoor and Built Environment, 26(7) 879–901.
  • Thomson, H., & Snell, C. (2016). Definitions And Indicators Of Energy Poverty Across The Eu, In: Csiba, K. (Ed). Energy Poverty Handbook. (101-118), Brussels: European Union.
  • UNDP Türkiye (2023). Sürdürülebilir Kalkınma için Küresel Amaçlar. (Erişim: 18.01.2023). https://www.kureselamaclar.org/amaclar/erisilebilir-ve-temiz-enerji/.
  • Uzar, U. (2020). Is Income Inequality a Driver for Renewable Energy Consumption?. Journal of Cleaner Production, 255 (120287), 1-11.
  • Yerdelen Tatoğlu, F. (2016). Panel Veri Ekonometrisi. Beta Yayınları, 5. Baskı, İstanbul.
  • WDI (2023). World Development Indicators Databank. (Erişim: 12.01.2023), https://databank.worldbank.org/source/world-development-indicators.
  • Xu, Q., & Zhong, M. (2023). The Impact of Income Inequity on Energy Consumption: The Moderating Role of Digitalization. Journal of Environmental Management, 325 ( 116464), 215-227.

Gelişmekte Olan Ülkelerde Gelir Eşitsizliği Enerji Yoksulluğunun Belirleyicisi mi?

Yıl 2023, Cilt: 8 Sayı: 2, 371 - 384, 30.12.2023

Serap Barış , Derya Demir

Öz

Bu çalışma, gelişmekte olan ülkelerde enerji yoksulluğu ve gelir eşitsizliği ilişkisini araştırmayı amaçlamaktadır. Gelişmekte olan 14 ülkenin 2000-2019 dönemine ait verileri ile panel veri analiz süreçleri takip edilerek ekonometrik analiz gerçekleştirilmiştir. Enerji yoksulluğu iki farklı gösterge (elektriğe erişim ve yemek pişirmek için temiz yakıtlara ve teknolojilere erişim) ile temsil edilerek iki ayrı model oluşturulmuştur. Modeller, dirençli standart hatalar üretebilen tahmincilerden Parks-Kmenta ve Beck-Katz ile tahmin edilmiştir. Araştırma sonucunda, yapılan dört tahminin üçünde gelir eşitsizliğinin enerji yoksulluğu göstergelerini negatif yönde etkilediği görülmüştür. Buna göre, gelir eşitsizliğinin enerji yoksulluğunu artırdığı söylenebilir. Bu sonuç özelinde, gelişmekte olan 14 ülkede politika yapıcıların enerji yoksulluğu ile ilgili politikalarında gelir eşitsizliğini de dikkate almaları önerilir.

Anahtar Kelimeler

Enerji yoksulluğu Gelir eşitsizliği Enerjiye erişim Panel veri analizi

Kaynakça

  • Abdoulaye Sy, S., & Mokaddem, L. (2022). Energy Poverty in Developing Countries: A Review of the Concept and Its Measurements. Energy Research & Social Science, 89(102562),1-14.
  • Acheampong, A. O., Shahbaz, M., Dzator, J., & Jiao, Z. (2022). Effects of Income Inequality and Governance On Energy Poverty Alleviation: Implications for Sustainable Development Policy. Utilities Policy, 78(101403),1-30.
  • Asongu, S. A., & Odhiambo, N. M. (2021). Inequality and Renewable Energy Consumption in Sub-Saharan Africa: Implication for High Income Countries. Innovation. The European Journal of Social Science Research, 20 (094), 1-22.
  • Baltagi, B. (2004). Econometric Analysis of Panel Data. New York: John Wiley and Sons.
  • Baltagi, B.H., & P.X. Wu (1999). Unequally Spaced Panel Data Regressions With AR(1) Disturbances. Econometric Theory, 15 (6), 814-823.
  • Bardazzi, R., Bortolotti, L., & Pazienza, M. G. (2021). To Eat and not to Heat? Energy Poverty and Income Inequality in Italian Regions. Energy Research & Social Science, 73 (101946), 1-15.
  • Beck, N., & Katz, Jonathan N. (1995). What to Do (and not to Do) with Time-series Cross-Section Data. American Political Science Review, 89, 634-47, https://www.researchgate.net, Erişim Tarihi: 25.02.2022.
  • Bhargava, A., L. Franzini & W. Narendranathan (1982). Serial Correlation and Fixed Effects Model. Review of Economic Studies 49(4), 533-549
  • Blomquist, J., & Westerlund, J. (2013). Testing slope homogeneity in large panels with serial correlation. Economics Letters, 121: 374-378.
  • Breusch, T. S., & Pagan, A. R. (1980). The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics. The Review of Economic Studies, 47(1), 239-253.
  • Bouzarovski, S., & Tirado-Herrero, S. (2017). The Energy Divide: Integrating Energy Transitions, Regional Inequalities and Poverty Trends in the European Union. European Urban and Regional Studies, 24(1), 69-86.
  • Bouzarovski, S., & Petrova, S. (2015). A Global Perspective on Domestic Energy Deprivation: Overcoming the Energy Poverty-Fuel Poverty Binary. Energy Research & Social Science 10, 31-40.
  • Broughton, A., Green, M., Rickard, C., Swift, S., Eichhorst, W., Tobsch, V., Magda, I., Lewandowski, P., Keister, R., Jonaviciene, D., Ramos Martín, N.E., Valsamis, D., & Tros, F. (2016). Precarious Employment in Europe: Patterns, Trends and Policy Strategy. Study. (Employment and Social Affairs). European Parliament. Directorate-General for Internal Policies. Policy Department A: Economic and Scientific Policy.(Erişim: 23.01.2023), ://www.europarl.europa.eu/RegData/etudes/STUD/2016/587285/IPOL_STU(2016)587285_EN.pdf.
  • Brown, M. B., & Forsythe, A. B. (1974). The Small Sample Behavior of Some Statistics Which Test the Equality of Several Means. Technometrics, 16(1), 129- 132.
  • Churchill, S. A., Ivanovski, K., & Munyanyi, M.E. (2021). Income Inequality and Renewable Energy Consumption: Time-varying Non-parametric Evidence. Journal of Cleaner Production, 296 (126306), 1-11.
  • Dong, K., Dou, Y., & Jiang, Q. (2022). Income Inequality, Energy Poverty, and Energy Efficiency: Who Cause Who and How? Technological Forecasting and Social Change, 179 (121622), 1-15.
  • Dong, X. Y., & Hao, Y. (2018). Would Income Inequality Affect Electricity Consumption? Evidence from China. Energy, 142, 215-227.
  • Eke, E. U., & Ayrancı, E. (2018). Türkiye’de Elektrik Enerjisi Sektörünün Enerji Yoksulluğu Açısından Değerlendirilmesi. Politik Ekonomik Kuram Sosyal Bilimler Dergisi, 2 (2), 109-109.
  • Erdoğdu, S. (2020). Dünyada ve Türkiye’de Enerji Yoksulluğu Üzerine: Türkiye’nin Enerji Görünümü. Ankara: TMMOB, Yayın No: MMO/17, 29-47.
  • Galvin, R. (2019). Letting the Gini out of The Fuel Poverty Bottle? Correlating Cold Homes and Income Inequality in European Union Countries. Energy Research & Social Science, 58 (101255), 1-14.
  • Gaye, A. (2007). Human Development Report 2007/2008 Fighting Climate Change: Human Solidarity in a Divided World. Human Development Report Office Occasional Paper.1-21.
  • González-Eguino, M. (2015). Energy poverty: An overview. Renewable and Sustainable Energy Reviews, 47, 377-385.
  • Gujarati, D. (2016). Örneklerle Ekonometri. Nasip Bolatoğlu. (Çev.). Ankara: BB101 Yayınları.
  • IEA (2021). The Energy Progress Report. Tracking SDG7. (Erişim: 02.04.2023), www.worldbank.org.
  • IEA (2022a). Global Energy Crisis. (Erişim: 24.01.2023). https://www.iea.org/topics/global-energy-crisis.
  • IEA (2022b). The Energy Progress Report. Tracking SDG7. (Erişim: 02.04.2023), www.worldbank.org.
  • IEA, IRENA, UNSD, WB, WHO (2019). Tracking SDG 7: The Energy Progress Report 2019. (Erişim:03.01.2023), https://www.worldbank.org/en/news/feature/2018/04/18/access-energy-sustainable-development-goal-7.
  • EU (2022). Report From the Commıssıon to the European Parliament, the Council, the European Economic and Social Committee and The Committee of The Regions State of the Energy Union. Brussels, 18.10.2022 COM(2022) 547 Final. (Erişim:02.04.2023), https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52022DC0547.
  • Igawa, M., & Managi, S. (2022). Energy Poverty and Income Inequality: An Economic Analysis of 37 Countries, Applied Energy, 306 (118076), 1-18.
  • Jones, S. (2016). Social Causes and Consequences of Energy Poverty. In: Csiba, K. (Ed.), Energy Poverty Handbook (21-38). Brussels: European Union.
  • Kavukçu, F. O. (2022). Avrupa’nın Enerji Krizi ile İmtihanı, Kış Öncesi Tedbirler ve Türkiye’nin Muhtemel Katkıları. Seta Perspektif, 345, 1-8.
  • Kmenta, J. (1986). Elements of Econometrics. The University of Michigan Press, Second edition, New York.
  • Le, T.-H., Nguyen, C.P., Su, T.D., & Tran-Nam, B. (2020). The Kuznets Curve for Export Diversification and Income Inequality: Evidence from a Global Sample. Economic. Analysis and Policy, 65 (C), 21-39.
  • Levene, H. (1960). Robust tests for equality of variances. Contributions to probability and statistics, 1, 278-292
  • Makhlouf, Y. (2023). Trends in Income Inequality: Evidence from Developing and Developed Countries. Social Indicators Research, 165(1), 213-243.
  • Muhammad, I., Özcan, R., Jain, V., Ramos-Meza, C. S., & Chawla, C. (2022). Do Drivers of Renewable Energy Consumption Matter for BRICS Economies? Nexus Among Technological Innovation, Environmental Degradation, Economic Growth, and Income Inequality. Environmental Science and Pollution Research, 30, 1-11.
  • Murtaza, G., & Faridi, M. Z. (2015). Causality Linkages among Energy Poverty, Income Inequality, Income Poverty and Growth: A System Dynamic Modelling Approach. The Pakistan Development Review, 54 (4), Part II, 407-425.
  • Nagaj, R., & Korpysa, J. (2020). Impact of COVID-19 On The Level of Energy Poverty in Poland. Energies, 13(18), 4977, 1-18.
  • Nguyen, C. P., & Nasir, M. A. (2021). An Inquiry into the Nexus Between Energy Poverty and Income Inequality in the Light of Global Evidence. Energy Economics, 99 (105289), 1-14.
  • Parks, Richard W. (1967). Efficient Estimation of a System of Regression Equations When Disturbances Are Both Serially and Contemporaneously Correlated. Journal of the American Statistical Association, 318(62), 500-509.
  • Pesaran, H. (2004). General Diagnostic Tests for Cross Section Dependence in Panels. Cambridge: University of Cambridge Working Paper.
  • Pesaran, M. H., Ullah, A., & Yamagata, T. (2008). A Bias-adjusted LM Test of Error Cross-section Independence. Econometrics Journal, 11, 105127.
  • Pesaran, M. H., & Yamagata, T. (2008). Testing Slope Homogeneity in Large Panel. Journal of Econometrics, 142 (1), 50-93.
  • Pye, S., Dobbins, A., Baffert, C., Brajkovġc, J., Grgurev, I., De Miglio, R., & Deane, P. (2015). Energy Poverty and Vulnerable Consumers in the Energy Sector Across the EU: Analysis of Policies and Measures. (03.01.2023), Erişim: www.insightenergy.org.
  • Rafi, M., Naseef, M., & Prasad, S. (2021). Multidimensional Energy Poverty and Human Capital Development: Empirical Evidence from India. Energy Economics, 101(C), 105427.
  • Recaldea, M., Peraltab, A., Oliverasa, L., Tirado-Herrerof, S., Borrella, C., Palenciab, L., Gotsensb, M., Artazcoza, L., & Mari-Dell’Olmob, M. (2019). Structural Energy Poverty Vulnerability and Excess Winter Mortality in The European Union: Exploring The Association Between Structural Determinants and Health. Energy Policy, 133 (110869), 1-18.
  • Sarkodie, S. A., & Adams, S. (2020). Electricity Access, Human Development Index, Governance And Income Inequality in Sub-Saharan Africa, Energy Reports, 6, 455-466.
  • Sen, A., Nepal, R., & Jamasb, T. (2016). Reforming-Electricity Reforms Empirical Evidence from Asian Economies. The Oxford Institute for Energy Studies, OIES Paper: EL 18, 1-54.
  • Sharma, K.R., & Chan, G. (2016). Energy Poverty: Electrification and Well-being. Nature Energy, 1(11), 1-2.
  • Sharma, R., & Rajpurohit, S. S. (2022). Nexus Between Income Inequality and Consumption of Renewable Energy in India: A Nonlinear Examination. Economic Change and Restructuring, 55(4), 2337-2358.
  • Solt, F. (2016). The Standardized World Income Inequality Database. Social Science Quarterly, 97(5), 1267-1281.
  • Swamy, P. A. V. B. (1970). Efficient Inference in a Random Coefficient Regression Model. Econometrica, 38 (2), 311-323.
  • SWIID (2023). Standardized World Income Inequality Database. (Erişim: 03.01.2023), https://fsolt.org/swiid/.
  • Tekin, S., & Dolu, M. T. (2020). Güney-Güney İşbirliğinin İdeolojik Temelleri: Bağlantısızlar Hareketi ve Küresel Güney. Dicle Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (24), 65-81.
  • Thomson, H., Bouzarovski, S., & Snell, C. (2017) Rethinking The Measurement of Energy Poverty in Europe: A Critical Analysis of Indicators and Data. Indoor and Built Environment, 26(7) 879–901.
  • Thomson, H., & Snell, C. (2016). Definitions And Indicators Of Energy Poverty Across The Eu, In: Csiba, K. (Ed). Energy Poverty Handbook. (101-118), Brussels: European Union.
  • UNDP Türkiye (2023). Sürdürülebilir Kalkınma için Küresel Amaçlar. (Erişim: 18.01.2023). https://www.kureselamaclar.org/amaclar/erisilebilir-ve-temiz-enerji/.
  • Uzar, U. (2020). Is Income Inequality a Driver for Renewable Energy Consumption?. Journal of Cleaner Production, 255 (120287), 1-11.
  • Yerdelen Tatoğlu, F. (2016). Panel Veri Ekonometrisi. Beta Yayınları, 5. Baskı, İstanbul.
  • WDI (2023). World Development Indicators Databank. (Erişim: 12.01.2023), https://databank.worldbank.org/source/world-development-indicators.
  • Xu, Q., & Zhong, M. (2023). The Impact of Income Inequity on Energy Consumption: The Moderating Role of Digitalization. Journal of Environmental Management, 325 ( 116464), 215-227.
Toplam 61 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Uluslararası İktisat (Diğer)
Bölüm Araştırma Makalesi
Yazarlar

Serap Barış 0000-0003-3905-4746

Derya Demir 0000-0002-7355-1757

Erken Görünüm Tarihi 24 Ekim 2023
Yayımlanma Tarihi 30 Aralık 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 8 Sayı: 2

Kaynak Göster

APA Barış, S., & Demir, D. (2023). Gelişmekte Olan Ülkelerde Gelir Eşitsizliği Enerji Yoksulluğunun Belirleyicisi mi?. JOEEP: Journal of Emerging Economies and Policy, 8(2), 371-384.
 Kapak Resmi İndir

The sole purpose of JOEEP is to be a prestigious journal which contributes to scientific knowledge. In order to keep this purpose, JOEEP, adopts and follows the publication policies of world’s prestigious scientific journals. All original and qualified works which may contribute to the scientific knowledge, are evaluated through a rigorous editorial and peer review process. Hereby, JOEEP is a peer reviewed and scientific journal. It strictly depends on the scientific principles, rules and ethical framework that are required to this qualification.

JOEEP is published as two issues per year June and December and all publication policies and processes are conducted according to the international standards. JOEEP accepts and publishes the research articles in the fields of economics, political economy, fiscal economics, applied economics, business economics, labour economics and econometrics. JOEEP, without depending on any institution or organization, is a non-profit journal that has an International Editorial Board specialist on their fields. All “Publication Process” and “Writing Guidelines” are explained in the related title and it is expected from authors to Show a complete match to the rules. JOEEP is an open Access journal.