IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i24p6970-d295010.html
   My bibliography  Save this article

Weather Volatility and Production Efficiency

Author

Listed:
  • Denitsa Angelova

    (School of Management, Technical University of Munich, Arcisstraße 21, 80333 Munich, Germany)

  • Jan Käbel

    (School of Life Sciences Weihenstephan, Technical University of Munich, Alte Akademie 8, 85354 Freising, Germany)

Abstract

We formulate a stochastic production frontier model to estimate the production efficiency scores while correcting for technical progress and weather effects in the form of temperature and precipitation levels and volatility. We econometrically estimate a model for European agriculture. Our results indicate that average temperature, unlike average precipitation levels, significantly influences aggregate agricultural output. We estimate that a marginal increase in temperature would decrease aggregate European agricultural output by about 1.6% percent. Further estimation results indicate a slight increase in output associated with marginal increases of precipitation and temperature volatilities.

Suggested Citation

  • Denitsa Angelova & Jan Käbel, 2019. "Weather Volatility and Production Efficiency," Sustainability, MDPI, vol. 11(24), pages 1-12, December.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:24:p:6970-:d:295010
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/24/6970/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/24/6970/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Binder, Michael & Hsiao, Cheng & Pesaran, M. Hashem, 2005. "Estimation And Inference In Short Panel Vector Autoregressions With Unit Roots And Cointegration," Econometric Theory, Cambridge University Press, vol. 21(4), pages 795-837, August.
    2. Maria Belyaeva & Raushan Bokusheva, 2018. "Will climate change benefit or hurt Russian grain production? A statistical evidence from a panel approach," Climatic Change, Springer, vol. 149(2), pages 205-217, July.
    3. repec:adr:anecst:y:1999:i:55-56:p:11 is not listed on IDEAS
    4. Olivier Deschênes & Michael Greenstone, 2012. "The Economic Impacts of Climate Change: Evidence from Agricultural Output and Random Fluctuations in Weather: Reply," American Economic Review, American Economic Association, vol. 102(7), pages 3761-3773, December.
    5. Clive W. J. Granger & Namwon Hyung, 1999. "Spurious Stochastics in a Short Time-Series Panel Data," Annals of Economics and Statistics, GENES, issue 55-56, pages 299-315.
    6. Sun Ling Wang & Eldon Ball & Richard Nehring & Ryan Williams & Truong Chau, 2018. "Impacts of Climate Change and Extreme Weather on US Agricultural Productivity: Evidence and Projection," NBER Chapters, in: Agricultural Productivity and Producer Behavior, pages 41-75, National Bureau of Economic Research, Inc.
    7. Marco Letta & Richard S. J. Tol, 2019. "Weather, Climate and Total Factor Productivity," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(1), pages 283-305, May.
    8. Zhangqi Zhong & Yiqin Hu & Lei Jiang, 2019. "Impact of Climate Change on Agricultural Total Factor Productivity Based on Spatial Panel Data Model: Evidence from China," Sustainability, MDPI, vol. 11(6), pages 1-17, March.
    9. Bernard Oury, 1965. "Allowing for Weather in Crop Production Model Building," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 47(2), pages 270-283.
    10. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    11. Eric Njuki & Boris E Bravo-Ureta & Christopher J O’Donnell, 2018. "A new look at the decomposition of agricultural productivity growth incorporating weather effects," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-21, February.
    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. Viktoriya Galushko & Samuel Gamtessa, 2022. "Impact of Climate Change on Productivity and Technical Efficiency in Canadian Crop Production," Sustainability, MDPI, vol. 14(7), pages 1-21, April.
    2. Li Chen & Bin Jiang & Chuan Wang, 2023. "Climate change and urban total factor productivity: evidence from capital cities and municipalities in China," Empirical Economics, Springer, vol. 65(1), pages 401-441, July.
    3. Augustus J. Panton, 2020. "Climate hysteresis and monetary policy," CAMA Working Papers 2020-76, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Bannor, Frank & Dikgang, Johane & Gelo, Dambala, 2021. "Agricultural total factor productivity growth, technical efficiency, and climate variability in sub-Saharan Africa," EconStor Preprints 231310, ZBW - Leibniz Information Centre for Economics.
    5. Tao Xiang & Tariq H. Malik & Jack W. Hou & Jiliang Ma, 2022. "The Impact of Climate Change on Agricultural Total Factor Productivity: A Cross-Country Panel Data Analysis, 1961–2013," Agriculture, MDPI, vol. 12(12), pages 1-20, December.
    6. Sun Ling Wang & Eldon Ball & Richard Nehring & Ryan Williams & Truong Chau, 2018. "Impacts of Climate Change and Extreme Weather on US Agricultural Productivity: Evidence and Projection," NBER Chapters, in: Agricultural Productivity and Producer Behavior, pages 41-75, National Bureau of Economic Research, Inc.
    7. Majid Khan & Abdul Rashid, 2022. "(A)symmetry effects of climate changes on economic growth: a panel data analysis," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 69(4), pages 571-607, December.
    8. Arturas Juodis, 2013. "Cointegration Testing in Panel VAR Models Under Partial Identification and Spatial Dependence," UvA-Econometrics Working Papers 13-08, Universiteit van Amsterdam, Dept. of Econometrics.
    9. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, March.
    10. Tom Kompas & Tuong Nhu Che & R. Quentin Grafton, 2004. "Technical efficiency effects of input controls: evidence from Australia's banana prawn fishery," Applied Economics, Taylor & Francis Journals, vol. 36(15), pages 1631-1641.
    11. Lundgren, Tommy & Marklund, Per-Olov & Zhang, Shanshan, 2016. "Industrial energy demand and energy efficiency – Evidence from Sweden," Resource and Energy Economics, Elsevier, vol. 43(C), pages 130-152.
    12. Daniel Solís & Boris E. Bravo‐Ureta & Ricardo E. Quiroga, 2009. "Technical Efficiency among Peasant Farmers Participating in Natural Resource Management Programmes in Central America," Journal of Agricultural Economics, Wiley Blackwell, vol. 60(1), pages 202-219, February.
    13. Andriakopoulos, Konstantinos & Ladas, Augoustinos & Andriakopoulos, Panagiotis, 2020. "Bank efficiency and leasing in U.S.A. banking system," MPRA Paper 112645, University Library of Munich, Germany.
    14. Koetter Michael, 2008. "An Assessment of Bank Merger Success in Germany," German Economic Review, De Gruyter, vol. 9(2), pages 232-264, May.
    15. Giovanni Calice & Levent Kutlu & Ming Zeng, 2021. "Understanding US firm efficiency and its asset pricing implications," Empirical Economics, Springer, vol. 60(2), pages 803-827, February.
    16. Fofack, Hippolyte, 2008. "Technology trap and poverty trap in Sub-Saharan Africa," Policy Research Working Paper Series 4582, The World Bank.
    17. António Afonso & Ana Patricia Montes & José M. Domínguez, 2024. "Measuring Tax Burden Efficiency in OECD Countries: An International Comparison," CESifo Working Paper Series 11333, CESifo.
    18. Barros, Carlos Pestana & Williams, Jonathan, 2013. "The random parameters stochastic frontier cost function and the effectiveness of public policy: Evidence from bank restructuring in Mexico," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 98-108.
    19. Ligia Alba Melo-Becerra & Luis E. Arango & Oscar Iván Ávila-Montealegre & Jhorland Ayala-García & Leonardo Bonilla-Mejía & Jesús Alonso Botero-García & Carolina Crispin-Fory & Manuela Cardona & Daniel, 2023. "Aspectos financieros y fiscales del sistema de salud en Colombia," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, issue 106, pages 1-92, October.
    20. Khanal, Aditya & Koirala, Krishna & Regmi, Madhav, 2016. "Do Financial Constraints Affect Production Efficiency in Drought Prone Areas? A Case from Indonesian Rice Growers," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230087, Southern Agricultural Economics Association.

    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:jsusta:v:11:y:2019:i:24:p:6970-:d:295010. 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.