Is climate change a source of economic disparities between regions in Benin? Evidence from the spatial effects analysis method
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Author(s)Hortensia Acacha-AcakpoLink to ORCID Index: https://orcid.org/0000-0003-2406-4458
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Denis Acclassato HouensouLink to ORCID Index: https://orcid.org/0000-0002-7237-5069
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Christian Duhamel LogozoLink to ORCID Index: https://orcid.org/0009-0004-7468-0122
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Sylvain HekponhoueLink to ORCID Index: https://orcid.org/0000-0001-5306-3943
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DOIhttp://dx.doi.org/10.21511/ee.15(2).2024.07
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Article InfoVolume 15 2024, Issue #2, pp. 93-107
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21 Downloads
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Creative Commons Attribution 4.0 International License
Despite numerous studies on the impacts of climate change in developing economies, scarce research focuses on these spatial effects in the internal regions of these countries. To shed light on this concern, this study aims to analyze the spatial effect of climate change on regional economic disparities in the context of Benin. The secondary data are extracted from the World Bank’s Climate Knowledge Portal and a Beninese local finance database covering the period from 2010 to 2019. A random-effects panel model and a dynamic spatial Durbin model of endogenous growth are used. The results reveal that, in the absence of spatial effects, average temperature reinforces economic disparities by 4.4 points within regions. A one-point increase in precipitation increases economic disparities by 0.001 points. The spatial model reveals both short- and long-term positive spatial externalities. Thus, a one-point positive variation in precipitation in neighboring regions leads to a 0.005% increase in a given region’s own revenue per capita. Similarly, a one-point increase in precipitation in a given region induces a 0.004% rise in own revenues in neighboring regions. Damage caused by climate change in one area encourages positive economic dynamics in neighboring areas. These spatial interactions reinforce economic differences and maintain economic disparities between Benin’s regions.
- Keywords
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JEL Classification (Paper profile tab)O44, Q54, R11
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References44
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Tables8
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Figures3
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- Figure 1. Trends in per capita revenues by department
- Figure 2. Spatial distribution of mean temperature and precipitation
- Figure 3. Spatial distribution of the average Gini index within departments
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- Table 1. Explanatory variables and expected signs
- Table 2. Descriptive statistics for own-source revenues per capita (in FCFA*)
- Table 3. Gini index of own revenues per capita in departments
- Table 4. Moran index
- Table 5. Effect of climate change on regional economic disparities using the random-effects model
- Table 6. Effect of climate change on regional economic disparities using the dynamic panel SDM model
- Table A1. SDM estimation in fixed-effect panel
- Table A2. Pairwise correlations
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- Aho, N., Aho, S., Agbokou, I., Kaffo, B., Seni, S., & Loconon, D. (2018). Introduction à la résilience aux changements climatiques en Afrique de l’Ouest : Répertoire des dates prédéterminées des saisons pluvieuses dans les villages et quartiers de ville du Bénin [Introduction to resilience to climate change in West Africa: Directory of predetermined dates of rainy seasons in villages and city districts of Benin] Ministère de l’Energie, de l’Eau et des Mines – PNUD Bénin, Cotonou (In French).
- Ahsan, F., Chandio, A. A., & Fang, W. (2020). Climate change impacts on cereal crops production in Pakistan: Evidence from cointegration analysis. International Journal of Climate Change Strategies and Management, 12(2), 257-269.
- Anselin, L. (2010) Thirty years of spatial econometrics. Papers in Regional Science, 89(1), 3-25.
- Anyanwu, J. C., Erhijakpor, A. E. O., & Obi, E. (2016). Empirical analysis of the key drivers of income inequality in West Africa. African Development Review, 28(1), 18-38.
- Asfaw, S., Pallante, G., & Palma, A. (2020). Distributional impacts of soil erosion on agricultural productivity and welfare in Malawi. Ecological Economics, 177, Article 106764.
- Azariadis, C., & Stachurski, J. (2005). Poverty traps. In Ph. Aghion & S. N. Durlauf (Eds.), Handbook of Economic Growth (vol.1, pp. 295-384). Elsevier.
- Bălan, M., Uzlǎu, C., Spânulescu, G.-A., & Bǎlan, M. (2020). Statistical analysis of the regional disparities. International Journal of Research in Commerce and Management Studies, 2(02).
- Beguerang, T. (2023). Trois essais sur l’impact socio-économique du changement climatique en Afrique subsaharienne [Three essays on the socio-economic impact of climate change in sub-Saharan Africa] (Doctoral Thesis). Université Clermont Auvergne. (In French).
- Benhamed, A., Osman, Y., Ben-Salha, O., & Jaidi, Z. (2023). Unveiling the spatial effects of climate change on economic growth: International evidence. Sustainability, 15(10), Article 8197.
- Berlemann, M., & Wenzel, D. (2018). Hurricanes, economic growth and transmission channels: Empirical evidence for countries on differing levels of development. World Development, 105, 231-247.
- Bourdin, S. (2013). Une mesure spatiale locale de la sigma-convergence pour évaluer les disparités régionales dans l’union européenne [A local spatial measure of sigma-convergence to assess regional disparities in the European Union]. Région et Développement, 37, 1-18. (In French).
- Capello, R. (2009). Théories sur la croissance régionale et le développement local: évolution des concepts en 50 ans de science régionale [Theories of regional growth and local development: Evolution of concepts in 50 years of regional science]. Geographie Economie Societe, 11(1), 9-21. (In French).
- Cappelli, F., Costantini, V., & Consoli, D. (2021). The trap of climate change-induced “natural” disasters and inequality. Global Environmental Change, 70, Article 102329.
- Chen, X., & Yang, L. (2019). Temperature and industrial output: Firm-level evidence from China. Journal of Environmental Economics and Management, 95, 257-274.
- De Siano, R., Leone Sciabolazza, V., & Sapio, A. (2020). Economic resilience and regional disparities: The value added of spatial analysis. In Regional Resilience to Climate and Environmental Shocks (pp. 7-29). Cham: Springer.
- Debarsy, N., Ertur, C., & LeSage, J. P. (2012). Interpreting dynamic space-time panel data models. Statistical Methodology, 9(1-2), 158-171.
- Dehn, J., & Collier, P. (2001). Aid, shocks, and growth policy (Policy Research Working Paper Series No. 2688). The World Bank.
- Dell, M., Jones, B., & Olken, B. (2008). Climate change and economic growth: Evidence from the last half century (Working Paper No. 14132). National Bureau of Economic Research.
- Direction de la Statistique Agricole (DSA). (2021). Recensement national de l’agriculture [National agricultural census]. (In French).
- Dubé, L., & Legros, D. (2014). Econométrie spatiale appliquée des microdonnées [Applied spatial econometrics of microdata]. ISTE Group. (In French).
- Dupuy, C. (2011). Inégalités territoriales [Territorial inequalities]. In D. R. Pasquier, S. Guigner, & A. Cole (Eds.), Dictionnaire Des Politiques Territoriales [Dictionary of Territorial Policies]. Paris: Presses de La Fondation Nationale des Sciences Politiques. (In French).
- Fujita, M., Krugman, P., & Venables, A. (2001). The spatial economy: Cities, regions and international trade (Chapters 4, 5, and 14). MIT Press.
- Hallegatte, S., & Rozenberg, J. (2017). Climate change through a poverty lens. Nature Climate Change, 7(4), 250-256.
- Hallegatte, S., Fay, M., & Barbier, E. B. (2018). Poverty and climate change: Introduction. Environment and Development Economics, 23(3), 217-233.
- He, W., Cheng, Y., Zhang, H., Guo, F., & Yu, H. (2021). The microeconomic effects of temperature changes. Journal of Cleaner Production, 326, Article 129389.
- Hountondji, F. (2022). Evaluation des plans, politiques et directives liées à la gestion à long terme des inondations et de la sécheresse dans la portion béninoise du bassin de la volta [Assessment of plans, policies and guidelines for long-term flood and drought management in the Benin section of the Volta basin]. (In French).
- Lazar, A., Eva, M., Bourdin, S., & Iatu, S. (2021). Analyse multicritère des disparités régionales en Roumanie (2000–2016) [Multi-criteria analysis of regional disparities in Romania (2000–2016)]. In Revue Roumaine de Géographie – Romanian Journal of Geography, 65(1), 21-34. (In French).
- LeSage, J., & Pace, R. K. (2009). Introduction to spatial econometrics (1st ed.). Chapman and Hall/CRC.
- Lybbert, T. J., & Barrett, C. B. (2011). Risk-taking behavior in the presence of nonconvex asset dynamics. Economic Inquiry, 49(4), 982-988.
- Ministère du Cadre de Vie et du Développement Durable (MCVDD). (2022). Communication relative à l’adaptation du Bénin au titre de la Convention-cadre des Nations unies sur les changements climatiques [Communication on Benin’s adaptation to the United Nations Framework Convention on Climate Change]. (In French).
- Montador, L. (2022). Le changement climatique et ses conséquences é.onomiques [Climate change and its economic consequences]. Annales Des Mines – Responsabilité et Environnement, 106(2), 59-64. (In French).
- Muhammad Ali, N. (2018). Impact of climate change and natural catastrophe on the occupational changes in the coastal areas of Bangladesh: An empirical study. Environmental Economics, 9(1), 22-37.
- Ostermeyer, V. (2023). Local multipliers and the growth of services: Evidence from late nineteenth century USA, Great Britain, and Sweden. European Review of Economic History, 27(1), 70-90.
- Oţil, M. D., Miculescu, A., & Cismaş, L. M. (2015). Disparities in regional economic development in Romania. Analele Stiintifice Ale Universitatii Al I Cuza Din Iasi – Sectiunea Stiinte Economice, 62(s1), 37-51.
- Paglialunga, E., Coveri, A., & Zanfei, A. (2022). Climate change and within-country inequality: New evidence from a global perspective. World Development, 159, Article 106030.
- Sawada, Y., & Takasaki, Y. (2017). Natural disaster, poverty, and development: An introduction. World Development, 94, 2-15.
- Shi, L., & Varuzzo, A. M. (2020). Surging seas, rising fiscal stress: Exploring municipal fiscal vulnerability to climate change. Cities, 100, Article 102658.
- Soumaoro, T. (2021). Assessment of climate change impacts on agriculture in Mali. International Journal of Scientific Research and Management, 9(1), 313-329.
- Torre, A. (2015). Théorie du développement territorial [Territorial development theory]. Geographie, Economie, Societe – Geography, Economy, Society, 17(3), 273-288. (In French).
- Torre, A., & Chia, E. (2017). Nouvelles controverses du développement territorial : Quelle gouvernance et quelles innovations ? [New controversies in territorial development: What governance and what innovations?]. Association Canadienne Des Sciences Régionales – Canadian Regional Science Association, 40(2), 91-102. (In French).
- Warsame, A. A., Sheik-Ali, I. A., Ali, A. O., & Sarkodie, S. A. (2021). Climate change and crop production nexus in Somalia: An empirical evidence from ARDL technique. Environmental Science and Pollution Research, 28(16), 19838-19850.
- Yang, X., & Tang, W. (2022). Climate change and regional inequality: The effect of high teperatures on fiscal stress. Urban Climate, 43, Article 101167.
- Yu, J., & Lee, L.-F. (2012). Convergence: A spatial dynamic panel data approach. Global Journal of Economics, 01(01), Article 1250006.
- Zhang, P., Deschenes, O., Meng, K., & Zhang, J. (2018). Temperature effects on productivity and factor reallocation: Evidence from a half million Chinese manufacturing plants. Journal of Environmental Economics and Management, 88, 1-17.
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The effect of innovation and technological specialization on income inequality
Muhammad Yorga Permana ,
Donald Crestofel Lantu ,
Yulianto Suharto
doi: http://dx.doi.org/10.21511/ppm.16(4).2018.05
Problems and Perspectives in Management Volume 16, 2018 Issue #4 pp. 51-63 Views: 2066 Downloads: 298 TO CITE АНОТАЦІЯUsing a panel of 28 European Union countries for the period 2003–2014, the authors provide empirical evidence for the relationship between innovation, technological specialization, and income inequality. The results of the fixed effect panel regressions show two important findings. Firstly, the positive link was found between innovation, as measured by patenting activities, and income inequality as measured by Gini index and the top 10% income shares of the richest. Secondly, the authors also found the positive correlation between technological specialization, as measured by the Coefficient of Variances (CV) of Revealed Technological Advantage Index, and income inequality. Overall, the study enriches the previous literature suggesting that innovation may increase the gap of income distribution through the mechanism of Skill-Biased Technical Change (SBTC) and the Schumpeterian view of entrepreneurial rent. More importantly, this study is the first which found that not only the level of innovation does matter to the income distribution, but also how the innovation activities are specialized or diversified. Concentrating the activities into few narrow sectors (i.e., increase technological specialization) may also lead to the increase of income inequality.
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A guarantor in the quality management system of educational programs: a case of Ukrainian universities
Oleksandr Velychko 
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Liudmyla Velychko ,
Svitlana Khalatur ,
Hynek Roubík
doi: http://dx.doi.org/10.21511/ppm.18(4).2020.14
Problems and Perspectives in Management Volume 18, 2020 Issue #4 pp. 153-166 Views: 787 Downloads: 288 TO CITE АНОТАЦІЯDevelopment of the system of ensuring quality in higher education of Ukraine grounded the creation of such management subject as a guarantor of the educational program. However, a formal understanding of the role and uncertainty of the guarantor’s status in the contemporary area of managing higher education institutions became the widespread consequence of those innovations. Considering the stated above, various models of managing the quality of educational programs with the help of the guarantor have been developed in the research, and conditions for efficient application of such models in Ukrainian universities have been grounded. The research is based on the application of the strategic analysis method GAP for identifying issues and features of organizing management in systems of internal quality assurance in universities, and methods of modeling and graphical analysis method for creating alternative management systems in educational programs with and without such professional educational-scientific structural subdivisions as departments. As a result, the developed models include the rational organization of management of educational programs under the conditions of centralized and decentralized systems of internal educational quality assurance provision. For instance, it could create favorable conditions for decreasing bureaucracy and repetition of functions in the management system of universities and lead to the realization of the individual potential of guarantors as managers-experts in educational programs.
Acknowledgment
To the National Agency for Higher Education Quality Assurance for the possibility to take part in accreditation expertise and consulting evaluation of educational programs in universities of Ukraine. The research was carried out also within the context of the tasks of Ukrainian-American international project “Program of professional development of them managerial staff in Ukrainian universities,” which was initiated by the investment company “Rayter Inc.” (The USA). In addition, we are thankful to the Czech Development Cooperation support, which allowed this scientific cooperation to start (through projects: “Strengthening scientific capacities and cooperation of Ukrainian universities in AgriSciences” and “Interuniversity cooperation as a tool to improve the quality of selected universities in Ukraine”). -
Assessment of the relationship between inequality, income and economic growth in the regions of Kazakhstan
Karina Turkebayeva ,
Makpal Bekturganova ,
Orazaly Sabden ,
Galiya Dauliyeva ,
Gaukhar Kenzhegulova
doi: http://dx.doi.org/10.21511/ppm.20(2).2022.42
Problems and Perspectives in Management Volume 20, 2022 Issue #2 pp. 511-521 Views: 589 Downloads: 178 TO CITE АНОТАЦІЯThis paper aims to analyze various indicators to explain the impact of inequality and income on economic growth at the regional level of Kazakhstan. The data collected from the Bureau of National Statistics from 1995 to 2020 examined the impact of country, interregional, and market inequality indices and real income/wage on the GRP of different regions. Applying the methods such as analysis of unique statistical data covering 16 regions of Kazakhstan and log-linear multivariate regression analysis, which was carried out using the STATA software package, evidence was provided on the influence of interregional, country inequality, and income on economic growth. The analysis showed the differential impact of inequality and income. It was found at the first stage that the gap between interregional inequality and country inequality is insignificant. It was identified at the second stage that in models with real incomes, an increase in income has a negative impact on the development of the economy of Kazakhstan. All the models obtained are consistent and have (although not very high) significant explanatory power and confirm the relationship between inequality and economic growth. The findings can help policymakers, regionalists, economists, and governmental bodies understand the importance of income inequality and which areas can contribute to the formation of effective regional policy.
Acknowledgments
The study was carried out within the framework of program targeted IRN OR11465433 funding by the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan “Development of the concept and mechanisms of balanced territorial development of the economy and society of Kazakhstan”.
