IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v16y2023i5p265-d1140881.html
   My bibliography  Save this article

The Impact of Socioeconomic and Environmental Indicators on Economic Development: An Interdisciplinary Empirical Study

Author

Listed:
  • Antonio Pacifico

    (Department of Economics and Law, University of Macerata, Piazza Strambi 1, 62100 Macerata, Italy)

Abstract

This paper aims to investigate the effects of environmental sources and health statistics on economic growth and other development indicators of interest. With population growth, urbanization, and industrialization of economies, the built environment for human health has emerged as an important and growing driver in interdisciplinary research and evidence-based policy development, improving a country’s growth prospects and the standard of living. A compressed structural Panel Vector Autoregression is used to address these issues. Methodologically, a hierarchical semiparametric Bayesian approach is involved to reduce the dimensionality, overtake variable selection problems, and model stochastic volatility. Policy-relevant strategies are also addressed to investigate causal relationships between sustainability indicators and economic growth.

Suggested Citation

  • Antonio Pacifico, 2023. "The Impact of Socioeconomic and Environmental Indicators on Economic Development: An Interdisciplinary Empirical Study," JRFM, MDPI, vol. 16(5), pages 1-16, May.
    • Handle: RePEc:gam:jjrfmx:v:16:y:2023:i:5:p:265-:d:1140881
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/16/5/265/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1911-8074/16/5/265/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stock, James H & Watson, Mark W, 1988. "Variable Trends in Economic Time Series," Journal of Economic Perspectives, American Economic Association, vol. 2(3), pages 147-174, Summer.
    2. Faber, Malte, 2008. "How to be an ecological economist," Ecological Economics, Elsevier, vol. 66(1), pages 1-7, May.
    3. Harvey James, 2010. "From the editor," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 27(4), pages 385-386, December.
    4. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    5. Harvey James, 2010. "From the editor," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 27(3), pages 257-258, September.
    6. Charles L. Baum & William F. Ford, 2004. "The wage effects of obesity: a longitudinal study," Health Economics, John Wiley & Sons, Ltd., vol. 13(9), pages 885-899, September.
    7. Bowsher, Clive G., 2002. "On testing overidentifying restrictions in dynamic panel data models," Economics Letters, Elsevier, vol. 77(2), pages 211-220, October.
    8. Kaddour Hadri, 2000. "Testing for stationarity in heterogeneous panel data," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 148-161.
    9. Harvey James, 2010. "From the editor," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 27(1), pages 1-2, March.
    10. Antonio Pacifico, 2021. "Robust open Bayesian analysis: Overfitting, model uncertainty, and endogeneity issues in multiple regression models," Econometric Reviews, Taylor & Francis Journals, vol. 40(2), pages 148-176, February.
    11. Antonio Pacifico, 2021. "Structural Panel Bayesian VAR with Multivariate Time-Varying Volatility to Jointly Deal with Structural Changes, Policy Regime Shifts, and Endogeneity Issues," Econometrics, MDPI, vol. 9(2), pages 1-35, May.
    12. Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
    13. Christian Kroll, 2011. "Different Things Make Different People Happy: Examining Social Capital and Subjective Well-Being by Gender and Parental Status," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 104(1), pages 157-177, October.
    14. Harvey James, 2010. "From the editor," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 27(2), pages 117-118, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Magdalena Kachniewska & Anna Para, 2023. "Feminine vs. Masculine: Expectations of Leadership Styles in Hotels during the COVID-19 Pandemic," Sustainability, MDPI, vol. 15(13), pages 1-24, July.
    2. Michael LaCour-Little & Eric Rosenblatt & Vincent Yao, 2010. "Home Equity Extraction by Homeowners: 2000-2006," Journal of Real Estate Research, American Real Estate Society, vol. 32(1), pages 23-46.
    3. Harvey James, 2012. "From the editor," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 29(1), pages 1-2, March.
    4. Caruso, Alberto & Reichlin, Lucrezia & Ricco, Giovanni, 2019. "Financial and fiscal interaction in the Euro Area crisis: This time was different," European Economic Review, Elsevier, vol. 119(C), pages 333-355.
    5. Mumtaz, Haroon & Theodoridis, Konstantinos, 2017. "Common and country specific economic uncertainty," Journal of International Economics, Elsevier, vol. 105(C), pages 205-216.
    6. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2020. "Choosing Prior Hyperparameters: With Applications to Time-Varying Parameter Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 124-136, January.
    7. Salzmann, Leonard, 2020. "The Impact of Uncertainty and Financial Shocks in Recessions and Booms," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224588, Verein für Socialpolitik / German Economic Association.
    8. Gary Koop & Dimitris Korobilis, 2019. "Forecasting with High‐Dimensional Panel VARs," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(5), pages 937-959, October.
    9. Davide Pettenuzzo & Francesco Ravazzolo, 2016. "Optimal Portfolio Choice Under Decision‐Based Model Combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1312-1332, November.
    10. Scott Brave & R. Andrew Butters & Alejandro Justiniano, 2016. "Forecasting Economic Activity with Mixed Frequency Bayesian VARs," Working Paper Series WP-2016-5, Federal Reserve Bank of Chicago.
    11. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian Vector Autoregressions," The Warwick Economics Research Paper Series (TWERPS) 1159, University of Warwick, Department of Economics.
    12. Miescu, Mirela & Rossi, Raffaele, 2021. "COVID-19-induced shocks and uncertainty," European Economic Review, Elsevier, vol. 139(C).
    13. Alessandri, Piergiorgio & Mumtaz, Haroon, 2019. "Financial regimes and uncertainty shocks," Journal of Monetary Economics, Elsevier, vol. 101(C), pages 31-46.
    14. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.
    15. Haroon Mumtaz & Konstantinos Theodoridis, 2017. "US financial shocks and the distribution of income and consumption in the UK," Working Papers 845, Queen Mary University of London, School of Economics and Finance.
    16. Anastasios Evgenidis & Apostolos Fasianos, 2019. "Monetary Policy and Wealth Inequalities in Great Britain: Assessing the role of unconventional policies for a decade of household data," Papers 1912.09702, arXiv.org.
    17. Richard K. Crump & Stefano Eusepi & Domenico Giannone & Eric Qian & Argia M. Sbordone, 2021. "A Large Bayesian VAR of the United States Economy," Staff Reports 976, Federal Reserve Bank of New York.
    18. Andrea Carriero & George Kapetanios & Massimiliano Marcellino, 2011. "Forecasting large datasets with Bayesian reduced rank multivariate models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(5), pages 735-761, August.
    19. Anttonen, Jetro, 2018. "Nowcasting the Unemployment Rate in the EU with Seasonal BVAR and Google Search Data," ETLA Working Papers 62, The Research Institute of the Finnish Economy.
    20. Bratsiotis, George J. & Theodoridis, Konstantinos, 2022. "Precautionary liquidity shocks, excess reserves and business cycles," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jjrfmx:v:16:y:2023:i:5:p:265-:d:1140881. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.