Kako sociodemografski faktori utiču na rast zelenih finansija?
Glavni sadržaj članka
Apstrakt
Ovaj rad istražuje uticaj sociodemografskih faktora na rast zelenih finansija u 21 evropskoj zemlji u periodu od 2000. do 2021. godine. Kvantitativni nalazi predstavljeni u ovom radu ukazuju na pozitivan i statistički značajan odnos između svih posmatranih sociodemografskih indikatora i rasta zelenih finansija.
Prvo, stopa nezaposlenosti pozitivno utiče na rast zelenih finansija. Ovaj nalaz sugeriše kontraintuitivan, ali pozitivan odnos između viših stopa nezaposlenosti i rasta zelenih finansija. Ekonomski padovi, karakterisani višom nezaposlenošću, često podstiču političke intervencije usmerene ka ekonomskom oporavku. Tokom ovih perioda može doći do prelaska na održive prakse kao deo ekonomskog restrukturiranja. Ovi rezultati su u skladu sa nalazima u literaturi koji naglašavaju da investicije u zelenu infrastrukturu tokom visoke nezaposlenosti mogu stvoriti radna mesta i stimulisati ekonomski rast. Drugo, gustina naseljenosti ima pozitivan dugoročni efekat na rast zelenih finansija. Ovi nalazi impliciraju da urbanizacija igra ključnu ulogu u unapređenju zelenih finansija kroz nekoliko sinergetskih mehanizama. Urbana područja sa većom gustinom naseljenosti odlikuju se efikasnijom upotrebom resursa. Takođe, socijalna dinamika u gusto naseljenim područjima, u kojima je veća izloženost ekološkim problemima, dovodi do povećane svesti o životnoj sredini, što dodatno podstiče zelene investicije. Nadalje, kao posledica ekonomije obima, urbana područja sa velikom gustinom naseljenosti povezuju se sa većim rastom zelenih finansija usled smanjenih troškova za implementaciju zelenih projekata.
Treće, povećanje udela izdataka za obrazovanje u odnosu na BDP povezano je sa rastom zelenih finansija na duži rok. Ovaj rezultat naglašava ključnu ulogu obrazovanja u unapređenju ekološke svesti i podsticanju potražnje za održivim finansijskim proizvodima. Viši nivoi obrazovanja su generalno povezani sa boljim razumevanjem ekoloških problema, što za posledicu ima jaču podršku zelenim finansijskim inicijativama. Četvrto, rodni odnos je povezan sa rastom zelenih finansija na duži rok. Ovaj značajan pozitivan odnos ukazuje da rodni paritet, posebno uključivanje žena u liderske uloge, može unaprediti inicijative u oblasti zelenih finansija. Žene na liderskim pozicijama često su ekološki svesnije, što dovodi do usvajanja sveobuhvatnih i efikasnih strategija zelenih finansija. Peto, utvrđen je pozitivan odnos između starosti i rasta zelenih finansija. Ova snažna pozitivna korelacija može biti pripisana nekolicini socio-ekonomskih faktora. Stariji slojevi populacije teže stabilnim i održivim investicijama, a njihova akumulirana novčana sredstva često se ulažu u zelene finansijske inicijative. Takođe, povećana ekološka svest među starijim generacijama, vođena brigom za buduće generacije i zdravstvene benefite, dodatno podstiče investicije u zelene inicijative.
Na kraju, rast Ginijevog koeficijenta povezan je sa povećanjem zelenih finansija na duži rok. Ova značajna pozitivna korelacija može se objasniti specifičnim socioekonomskim dinamikama. Rani usvojitelji zelenih proizvoda često imaju veću kupovnu moć, što im omogućava da priušte inicijalno skuplje zelene tehnologije i proizvode. Njihova spremnost da investiraju u ove proizvode pomaže u pokretanju inovacija, dok ekonomija obima na duži rok čini zelene tehnologije priuštivijim i drugim dohodovnim grupama stanovništva.
U zaključku, studija ističe značaj sociodemografskih faktora u kreiranju politika zelenih finansija. Rezultati istraživanja naglašavaju potrebu za daljim ispitivanjem dodatnih sociodemografskih faktora i kvalitativnih aspekata razvoja zelenih finansija kako bi se stvorile efikasnije strategije za promovisanje održivog razvoja.
Preuzimanja
Detalji članka
Centar za demografska istraživanja Instituta društvenih nauka
Reference
Abuatwan, N. (2023). The impact of green finance on the sustainability performance of the banking sector in Palestine: The moderating role of female presence. Economies, 11(10), 247. https://doi.org/10.3390/economies11100247 DOI: https://doi.org/10.3390/economies11100247
Al Mamun, M., Boubaker, S., Hossain, M. Z., & Manita, R. (2024). Female political empowerment and green finance. Energy Economics, 131, 107370. https://doi.org/10.1016/j.eneco.2024.107370 DOI: https://doi.org/10.1016/j.eneco.2024.107370
An, Y., & Madni, G. R. (2023). Factors affecting the green investment and assessing sustainable performance of firms in China. PLOS ONE, 18(12), e0296099. https://doi.org/10.1371/journal.pone.0296099 DOI: https://doi.org/10.1371/journal.pone.0296099
Arpad, T. (2018) Willing to pay to save the planet? Evaluating support for increased spending on sustainable development and environmentally friendly policies in five countries. PLoS ONE 13 (11): e0207862. https://doi.org/10.1371/journal.pone.0207862 DOI: https://doi.org/10.1371/journal.pone.0207862
Barbieri, N., Consoli, D., Marin, G., & Perruchas, F. (2023). Green technology and income inequality: an empirical analysis of US metro areas. Regional Studies, 1–14. https://doi.org/10.1080/00343404.2023.2171378 DOI: https://doi.org/10.1080/00343404.2023.2171378
Berrou, R., Ciampoli, N., & Marini, V. (2019). Defining Green Finance: Existing Standards and Main Challenges. In: M., Migliorelli, & P., Dessertine, (Eds.) The Rise of Green Finance in Europe. (pp. 31-51) Palgrave Studies in Impact Finance. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-22510-0_2 DOI: https://doi.org/10.1007/978-3-030-22510-0_2
Bowen, A., & Kuralbayeva, K. (2015). Looking for green jobs: The impact of green growth on employment. Grantham Research Institute on Climate Change and the Environment. https://www.lse.ac.uk/granthaminstitute/wp-content/uploads/2015/03/Looking-for-green-jobs_the-impact-of-green-growth-on-employment.pdf
Barra, C., & Ruggiero, N. (2019). Are Green Energies Employment Friendly? Empirical Evidence for Some OECD Countries over the 1985–2013 Period. Sustainability, 11(14), 3963. https://doi.org/10.3390/su11143963 DOI: https://doi.org/10.3390/su11143963
Blankenberg, A.-K., & Alhusen, H. (2019). On the Determinants of Pro-Environmental Behavior: A Literature Review and Guide for the Empirical Economist. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3473702 DOI: https://doi.org/10.2139/ssrn.3473702
Choi, I. (2001). Unit root tests for panel data. Journal of International Money and Finance, 20, 249–272. https://doi.org/10.1016/S0261-5606(00)00048-6 DOI: https://doi.org/10.1016/S0261-5606(00)00048-6
Cui, Y., Wang, G., Irfan, M., Wu, D., & Cao, J. (2022). The effect of green finance and unemployment rate on carbon emissions in China. Frontiers in Environmental Science, 10, 887341. https://doi.org/10.3389/fenvs.2022.887341 DOI: https://doi.org/10.3389/fenvs.2022.887341
Das, N., Gangopadhyay, P., Alam, M. M., Mahmood, H., Bera, P., Khudoykulov, K., … Hossain, Md. E. (2023). Does greenwashing obstruct sustainable environmental technologies and green financing from promoting environmental sustainability? Analytical evidence from the Indian economy. Sustainable Development, 32(1), 1069-1080. https://doi.org/10.1002/sd.2722 DOI: https://doi.org/10.1002/sd.2722
Debrah, C., Chan, A. P. C., & Darko, A. (2022). Green finance gap in green buildings: A scoping review and future research needs. Building and Environment, 207, 108443. https://doi.org/10.1016/j.buildenv.2021.108443 DOI: https://doi.org/10.1016/j.buildenv.2021.108443
Engle, R.F., & Granger, C. W. J. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica, 55(2), 251–276. https://doi.org/10.2307/1913236 DOI: https://doi.org/10.2307/1913236
Gör, Y., & Tekin, B. (2023). The determinants of green finance and effect on the banking sector. Financial Internet Quarterly, 19(4), 80–96. https://doi.org/10.2478/fiqf-2023-0028 DOI: https://doi.org/10.2478/fiqf-2023-0028
Gray, S. G., Raimi, K. T., Wilson, R., & Árvai, J. (2019). Will Millennials save the world? The effect of age and generational differences on environmental concern. Journal of Environmental Management, 242, 394–402. https://doi.org/10.1016/j.jenvman.2019.04.071 DOI: https://doi.org/10.1016/j.jenvman.2019.04.071
Guillochon, J. (2022). The role of media, policy and regional heterogeneity in renewable energy project crowdfunding. Energy Economics, 115, 106349. https://doi.org/10.1016/j.eneco.2022.106349 DOI: https://doi.org/10.1016/j.eneco.2022.106349
Hamurcu, Ç. (2023). Relationship between the green finance index, CO2 emission, and GDP. Financial Internet Quarterly, 19(1), 66–77. https://doi.org/10.2478/fiqf-2023-0007 DOI: https://doi.org/10.2478/fiqf-2023-0007
Hotak, S., Islam, M., Kakinaka, M., & Kotani, K. (2020). Carbon emissions and carbon trade balances: International evidence from panel ARDL analysis. Environmental Science and Pollution Research, 27, 24115–24128. https://doi.org/10.1007/s11356-020-08478-w DOI: https://doi.org/10.1007/s11356-020-08478-w
Hsu, A., Johnson, L., & Lloyd, A. (2013). Measuring progress: A practical guide from the developers of the Environmental Performance Index (EPI). Yale Center for Environmental Law & Policy. https://datadrivenlab.org/wp-content/uploads/2019/10/Measuring_Prgoress_2013.pdf
Im, K.S., Pesaran, M.H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1), 53–74. https://doi.org/10.1016/S0304-4076(03)00092-7 DOI: https://doi.org/10.1016/S0304-4076(03)00092-7
Jaffe, A. B., Newell, R. G., & Stavins, R. N. (2005). A tale of two market failures: Technology and environmental policy. Ecological Economics, 54(2–3), 164–174. https://doi.org/10.1016/j.ecolecon.2004.12.027 DOI: https://doi.org/10.1016/j.ecolecon.2004.12.027
Kao, C. (1999). Spurious regression and residual-based tests for cointegration in panel data. Journal of Econometrics, 90 (1), 1–44. https://doi.org/10.1016/S0304-4076(98)00023-2 DOI: https://doi.org/10.1016/S0304-4076(98)00023-2
Kumar, S., Sharma, D., Rao, S., Lim, W. M., & Mangla, S. K. (2022). Past, present, and future of sustainable finance: insights from big data analytics through machine learning of scholarly research. Annals of Operations Research. https://doi.org/10.1007/s10479-021-04410-8 DOI: https://doi.org/10.1007/s10479-021-04410-8
Lee, K. H., & Min, B. (2015). Green R&D for eco-innovation and its impact on carbon emissions and firm performance. Journal of Cleaner Production, 108, 534-542. https://doi.org/10.1016/j.jclepro.2015.05.114 DOI: https://doi.org/10.1016/j.jclepro.2015.05.114
Levin, A., Lin, C-F., & Chu, J. C-S. (2002). Unit root tests in panel data: asymptotic and finite-sample properties. Journal of Econometrics, 108(1), 1–24. https://doi.org/10.1016/S0304-4076(01)00098-7 DOI: https://doi.org/10.1016/S0304-4076(01)00098-7
Lin, K., & Zhao, H. (2022). The Impact of Green Finance on the Ecologicalization of Urban Industrial Structure —— Based on GMM Model of Dynamic Panel System. Journal of Artificial Intelligence and Technology, 2(3), 123–129. https://doi.org/10.37965/jait.2022.0115 DOI: https://doi.org/10.37965/jait.2022.0115
Liang, Y., Zhou, H., Zeng, J., & Wang, C. (2024). Do natural resources rent increase green finance in developing countries? The role of education. Resources Policy, 91, 104838. https://doi.org/10.1016/j.resourpol.2024.104838 DOI: https://doi.org/10.1016/j.resourpol.2024.104838
Ma, W. (2022). Research on the coupling and coordination of green finance, higher education, and green economic growth. Environmental Science and Pollution Research, 29, 59145–59158. https://doi.org/10.1007/s11356-022-20026-2 DOI: https://doi.org/10.1007/s11356-022-20026-2
Maddala, G. S., & Wu, S. (1999). A comparative study of unit root tests with panel data and a new simple test. Oxford Bullettin of Economics and Statistics, 61(S1), 631–652. https://doi.org/10.1111/1468-0084.0610s1631 DOI: https://doi.org/10.1111/1468-0084.61.s1.13
Murshed, M., Nurmakhanova, M., Elheddad, M., & Ahmed, R. (2020). Value addition in the services sector and its heterogeneous impacts on CO2 emissions: revisiting the EKC hypothesis for the OPEC using panel spatial estimation techniques. Environmental Science and Pollution Research, 27, 38951–38973. https://doi.org/10.1007/s11356-020-09593-4 DOI: https://doi.org/10.1007/s11356-020-09593-4
Naqvi, S., Wang, J., & Ali, R. (2021). Towards a green economy in Europe: does renewable energy production has asymmetric effects on unemployment? Environmental Science and Pollution Research, 29(13), 18832–18839. https://doi.org/10.1007/s11356-021-17093-2 DOI: https://doi.org/10.1007/s11356-021-17093-2
Niamir, L., Ivanova, O., & Filatova, T. (2020). Economy-wide impacts of behavioral climate change mitigation: Linking agent-based and computable general equilibrium models. Environmental Modelling and Software, 134, 104839. https://doi.org/10.1016/j.envsoft.2020.104839 DOI: https://doi.org/10.1016/j.envsoft.2020.104839
Olumekor, M. & Oke, A. (2024). Support for sustainable finance and investment in Europe. Journal of Cleaner Production, 449, 1-10. https://doi.org/10.1016/j.jclepro.2024.141769 DOI: https://doi.org/10.1016/j.jclepro.2024.141769
Owen, R., Brennan, G., & Lyon, F. (2018). Enabling investment for the transition to a low carbon economy: government policy to finance early stage green innovation. Current Opinion in Environmental Sustainability, 31, 137–145. https://doi.org/10.1016/j.cosust.2018.03.004 DOI: https://doi.org/10.1016/j.cosust.2018.03.004
Pedroni, P. (2004). Panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis. Economic Theory, 20(3), 597–625. https://doi.org/10.1017/S0266466604203073 DOI: https://doi.org/10.1017/S0266466604203073
Pesaran, M. H., & Smith, R. (1995). Estimating long-run relationships from dynamic heterogeneous panels. Journal of Econometrics, 68(1), 79–113. https://doi.org/10.1016/0304-4076(94)01644-F DOI: https://doi.org/10.1016/0304-4076(94)01644-F
Pesaran, M.H., Shin, Y., Smith, R.P., & Hashem, M. (1999). Pooled mean group estimation of dynamic heterogeneous panels. Journal of the American Statistical Association, 94(446), 621–634. https://doi.org/10.1080/01621459.1999.10474156 DOI: https://doi.org/10.1080/01621459.1999.10474156
Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels. University of Cambridge, Faculty of Economics, Cambridge Working Papers in Economics No. 0435. https://docs.iza.org/dp1240.pdf DOI: https://doi.org/10.2139/ssrn.572504
Popp, D. (2019). Environmental Policy and Innovation: A Decade of Research. National Bureau of Economic Research. (Working Paper 25631) https://doi.org/10.3386/w25631 DOI: https://doi.org/10.3386/w25631
Schroeder, F. & Havers, J. (2021). Closing the trillion dollar gap to keep 1.5 degrees within reach. E3G Report. https://www.e3g.org/wp-content/uploads/Closing-the-trillion-dollar-gap-to-keep-1.5-degrees-within-reach_E3G-report.pdf
Semieniuk, G., & Mazzucato, M. (2019). Financing green growth. In: R. Fouquet (Ed.), Handbook on green growth, (pp. 240-259). https://doi.org/10.4337/9781788110686.00019 DOI: https://doi.org/10.4337/9781788110686.00019
Sheng, J., Ding, R., & Yang, H. (2024). Corporate green innovation in an aging population: Evidence from Chinese listed companies. Technological Forecasting and Social Change, 202, 123307. https://doi.org/10.1016/j.techfore.2024.123307 DOI: https://doi.org/10.1016/j.techfore.2024.123307
Vona, F., & Patriarca, F. (2011). Income inequality and the development of environmental technologies. Ecological Economics, 70(11), 2201–2213. https://doi.org/10.1016/j.ecolecon.2011.06.027 DOI: https://doi.org/10.1016/j.ecolecon.2011.06.027
Zhao, J., Dong, K., & Taghizadeh-Hesary, F. (2023). Moving Towards Sustainable Development: Can Narrowing Income Inequality Facilitate Green Growth in China? Journal of Environmental Assessment Policy and Management, 25(2), 2350011. https://doi.org/10.1142/S1464333223500114 DOI: https://doi.org/10.1142/S1464333223500114