IDEAS home Printed from https://ideas.repec.org/p/zbw/cauapw/wp202009.html
   My bibliography  Save this paper

Climate variability and farm inefficiency: A spatial stochastic frontier analysis of Senegalese agriculture

Author

Listed:
  • Adjin, K. Christophe
  • Henning, Christian H. C. A.

Abstract

This paper aimed to analyse Senegalese farmers' technical efficiency in the context of climate variability and spatial heterogeneity. To achieve this, firstly using simulated data, we evaluated the newly developed spatial stochastic frontier estimation technique based on skew-normal distributions. Secondly, using cross-sectional survey data we conducted an empirical analysis for 4423 Senegalese farm households. Simulation results show that the estimation approach used is appropriate and produces consistent results with large sample sizes, although it might suffer from a "starting values" problem. Empirical findings reveal that agricultural production in Senegal mostly depends on the allocated area and it is highly affected by climatic factors such as rainfall and temperature. Moreover, within a radius of 4 km, the technical efficiency of farms appears to be significantly affected by unobserved spatial features. Furthermore, this farm's technical efficiency can on average be increased by 20%, when accounting for spatial heterogeneity.

Suggested Citation

  • Adjin, K. Christophe & Henning, Christian H. C. A., 2020. "Climate variability and farm inefficiency: A spatial stochastic frontier analysis of Senegalese agriculture," Working Papers of Agricultural Policy WP2020-09, University of Kiel, Department of Agricultural Economics, Chair of Agricultural Policy.
  • Handle: RePEc:zbw:cauapw:wp202009
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/235901/1/1760765589.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Skevas, Ioannis, 2020. "Inference in the spatial autoregressive efficiency model with an application to Dutch dairy farms," European Journal of Operational Research, Elsevier, vol. 283(1), pages 356-364.
    2. Alexandra Schmidt & Ajax Moreira & Steven Helfand & Thais Fonseca, 2009. "Spatial stochastic frontier models: accounting for unobserved local determinants of inefficiency," Journal of Productivity Analysis, Springer, vol. 31(2), pages 101-112, April.
    3. Elisa Fusco & Francesco Vidoli, 2013. "Spatial stochastic frontier models: controlling spatial global and local heterogeneity," International Review of Applied Economics, Taylor & Francis Journals, vol. 27(5), pages 679-694, September.
    4. Abdoulaye Seck, 2017. "Fertiliser subsidy and agricultural productivity in Senegal," The World Economy, Wiley Blackwell, vol. 40(9), pages 1989-2006, September.
    5. Orea, Luis & Álvarez, Inmaculada C., 2019. "A new stochastic frontier model with cross-sectional effects in both noise and inefficiency terms," Journal of Econometrics, Elsevier, vol. 213(2), pages 556-577.
    6. António Carvalho, 2018. "Efficiency spillovers in Bayesian stochastic frontier models: application to electricity distribution in New Zealand," Spatial Economic Analysis, Taylor & Francis Journals, vol. 13(2), pages 171-190, April.
    7. Anselin, Luc & Bera, Anil K. & Florax, Raymond & Yoon, Mann J., 1996. "Simple diagnostic tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 26(1), pages 77-104, February.
    8. A. Azzalini & A. Capitanio, 1999. "Statistical applications of the multivariate skew normal distribution," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(3), pages 579-602.
    9. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    10. Francisco José Areal & Kelvin Balcombe & Richard Tiffin, 2012. "Integrating spatial dependence into Stochastic Frontier Analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 56(4), pages 521-541, October.
    11. Lavado, Rouselle F. & Barrios, Erniel B., 2010. "Spatial Stochastic Frontier Models," Discussion Papers DP 2010-08, Philippine Institute for Development Studies.
    12. Jaepil Han & Deockhyun Ryu & Robin Sickles, 2016. "How to Measure Spillover Effects of Public Capital Stock: A Spatial Autoregressive Stochastic Frontier Model," Advances in Econometrics, in: Spatial Econometrics: Qualitative and Limited Dependent Variables, volume 37, pages 259-294, Emerald Group Publishing Limited.
    13. Glass, Anthony J. & Kenjegalieva, Karligash & Sickles, Robin C., 2016. "A spatial autoregressive stochastic frontier model for panel data with asymmetric efficiency spillovers," Journal of Econometrics, Elsevier, vol. 190(2), pages 289-300.
    14. Sherlund, Shane M. & Barrett, Christopher B. & Adesina, Akinwumi A., 2002. "Smallholder technical efficiency controlling for environmental production conditions," Journal of Development Economics, Elsevier, vol. 69(1), pages 85-101, October.
    15. Areal, Francisco Jose & Balcombe, Kelvin & Tiffin, Richard, 2012. "Integrated spatial dependence into Stochastic Frontier Analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 56(4), pages 1-21, December.
    16. Glass, Anthony & Kenjegalieva, Karligash & Paez-Farrell, Juan, 2013. "Productivity growth decomposition using a spatial autoregressive frontier model," Economics Letters, Elsevier, vol. 119(3), pages 291-295.
    17. Valerien O. Pede & Francisco J. Areal & Alphonse Singbo & Justin McKinley & Kei Kajisa, 2018. "Spatial dependency and technical efficiency: an application of a Bayesian stochastic frontier model to irrigated and rainfed rice farmers in Bohol, Philippines," Agricultural Economics, International Association of Agricultural Economists, vol. 49(3), pages 301-312, May.
    18. Morakinyo Adetutu & Anthony Glass & Karligash Kenjegalieva & Robin Sickles, 2015. "The effects of efficiency and TFP growth on pollution in Europe: a multistage spatial analysis," Journal of Productivity Analysis, Springer, vol. 43(3), pages 307-326, June.
    19. Salvador Barrios & Luisito Bertinelli & Eric Strobl, 2010. "Trends in Rainfall and Economic Growth in Africa: A Neglected Cause of the African Growth Tragedy," The Review of Economics and Statistics, MIT Press, vol. 92(2), pages 350-366, May.
    20. Glass, Anthony & Kenjegalieva, Karligash & Sickles, Robin C., 2014. "Estimating efficiency spillovers with state level evidence for manufacturing in the US," Economics Letters, Elsevier, vol. 123(2), pages 154-159.
    21. Hughes, Neal & Lawson, Kenton & Davidson, Alistair & Jackson, Tom & Sheng, Yu, 2011. "Productivity pathways: climate-adjusted production frontiers for the Australian broadacre cropping industry," 2011 Conference (55th), February 8-11, 2011, Melbourne, Australia 100563, Australian Agricultural and Resource Economics Society.
    22. Jalloh, Abdulai & Nelson, Gerald C. & Thomas, Timothy S. & Zougmoré, Robert & Roy-Macauley, Harold, 2013. "West african agriculture and climate change: A comprehensive analysis:," Issue briefs 75, International Food Policy Research Institute (IFPRI).
    23. Reinaldo B. Arellano‐Valle & Adelchi Azzalini, 2006. "On the Unification of Families of Skew‐normal Distributions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(3), pages 561-574, September.
    24. Thomas Graaff, 2020. "On the estimation of spatial stochastic frontier models: an alternative skew-normal approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(2), pages 267-285, April.
    25. Efthymios G. Tsionas & Panayotis G. Michaelides, 2016. "A Spatial Stochastic Frontier Model with Spillovers: Evidence for Italian Regions," Scottish Journal of Political Economy, Scottish Economic Society, vol. 63(3), pages 243-257, July.
    26. Viliam Druska & William C. Horrace, 2004. "Generalized Moments Estimation for Spatial Panel Data: Indonesian Rice Farming," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(1), pages 185-198.
    27. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    28. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    29. Michee Arnold Lachaud & Boris E. Bravo-Ureta & Carlos E. Ludena, 2017. "Agricultural productivity in Latin America and the Caribbean in the presence of unobserved heterogeneity and climatic effects," Climatic Change, Springer, vol. 143(3), pages 445-460, August.
    30. Arellano-Valle, Reinaldo B. & Azzalini, Adelchi, 2008. "The centred parametrization for the multivariate skew-normal distribution," Journal of Multivariate Analysis, Elsevier, vol. 99(7), pages 1362-1382, August.
    31. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    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. Fei Jin & Lung-fei Lee, 2020. "Asymptotic properties of a spatial autoregressive stochastic frontier model," Journal of Spatial Econometrics, Springer, vol. 1(1), pages 1-40, December.
    2. Kassoum Ayouba, 2023. "Spatial dependence in production frontier models," Journal of Productivity Analysis, Springer, vol. 60(1), pages 21-36, August.
    3. Federico Belotti & Giuseppe Ilardi & Andrea Piano Mortari, 2019. "Estimation of Stochastic Frontier Panel Data Models with Spatial Inefficiency," CEIS Research Paper 459, Tor Vergata University, CEIS, revised 30 May 2019.
    4. Vidoli, Francesco & Cardillo, Concetta & Fusco, Elisa & Canello, Jacopo, 2016. "Spatial nonstationarity in the stochastic frontier model: An application to the Italian wine industry," Regional Science and Urban Economics, Elsevier, vol. 61(C), pages 153-164.
    5. Fusco, Elisa & Allegrini, Veronica, 2020. "The role of spatial interdependence in local government cost efficiency: An application to waste Italian sector," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    6. Thomas Graaff, 2020. "On the estimation of spatial stochastic frontier models: an alternative skew-normal approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(2), pages 267-285, April.
    7. Bao Hoang Nguyen & Zhichao Wang & Valentin Zelenyuk, 2023. "Efficiency of Queensland Public Hospitals via Spatial Panel Stochastic Frontier Models," CEPA Working Papers Series WP102023, School of Economics, University of Queensland, Australia.
    8. Yiorgos Gadanakis & Francisco José Areal, 2020. "Accounting for rainfall and the length of growing season in technical efficiency analysis," Operational Research, Springer, vol. 20(4), pages 2583-2608, December.
    9. Jacopo Canello & Francesco Vidoli, 2020. "Investigating space‐time patterns of regional industrial resilience through a micro‐level approach: An application to the Italian wine industry," Journal of Regional Science, Wiley Blackwell, vol. 60(4), pages 653-676, September.
    10. Orea, Luis & Álvarez, Inmaculada C., 2019. "Spatial Production Economics," Efficiency Series Papers 2019/06, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    11. Skevas, Ioannis, 2020. "Inference in the spatial autoregressive efficiency model with an application to Dutch dairy farms," European Journal of Operational Research, Elsevier, vol. 283(1), pages 356-364.
    12. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    13. Skevas, Ioannis & Skevas, Theodoros, 2021. "A generalized true random-effects model with spatially autocorrelated persistent and transient inefficiency," European Journal of Operational Research, Elsevier, vol. 293(3), pages 1131-1142.
    14. Sadick Mohammed & Awudu Abdulai, 2022. "Do Egocentric information networks influence technical efficiency of farmers? Empirical evidence from Ghana," Journal of Productivity Analysis, Springer, vol. 58(2), pages 109-128, December.
    15. Theodoros Skevas & Jasper Grashuis, 2020. "Technical efficiency and spatial spillovers: Evidence from grain marketing cooperatives in the US Midwest," Agribusiness, John Wiley & Sons, Ltd., vol. 36(1), pages 111-126, January.
    16. Orea, Luis & Álvarez, Inmaculada C., 2019. "A new stochastic frontier model with cross-sectional effects in both noise and inefficiency terms," Journal of Econometrics, Elsevier, vol. 213(2), pages 556-577.
    17. Kien C. Tran & Mike G. Tsionas, 2023. "Semiparametric estimation of a spatial autoregressive nonparametric stochastic frontier model," Journal of Spatial Econometrics, Springer, vol. 4(1), pages 1-28, December.
    18. Hou, Zhezhi & Zhao, Shunan & Kumbhakar, Subal C., 2023. "The GMM estimation of semiparametric spatial stochastic frontier models," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1450-1464.
    19. Bergantino, Angela Stefania & Intini, Mario & Volta, Nicola, 2020. "Spatial competition and efficiency: an investigation in the airport sector," The Warwick Economics Research Paper Series (TWERPS) 1287, University of Warwick, Department of Economics.
    20. Valerien O. Pede & Francisco J. Areal & Alphonse Singbo & Justin McKinley & Kei Kajisa, 2018. "Spatial dependency and technical efficiency: an application of a Bayesian stochastic frontier model to irrigated and rainfed rice farmers in Bohol, Philippines," Agricultural Economics, International Association of Agricultural Economists, vol. 49(3), pages 301-312, May.

    More about this item

    Keywords

    Climate variability; Farm efficiency; Spatial heterogeneity; Senegal;
    All these keywords.

    JEL classification:

    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:zbw:cauapw:wp202009. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/iakiede.html .

    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.