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Modelling farm production decisions under an expenditure constraint

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  • Subal C. Kumbhakar
  • Raushan Bokusheva

Abstract

We use the indirect production function approach in the stochastic frontier framework to estimate separately the output losses due to the presence of a budget constraint and technical inefficiency. We develop a methodology for estimating the severity and testing the significance of the expenditure constraint at individual producer level. Our results, based on the farm data from three Russian regions from 1999 to 2003, show that the majority of the farms studied were expenditure-constrained during the study period. Expenditure constraints caused, on average, a potential output loss of 20 per cent. Output loss due to technical inefficiency, on average, is found to be around 13 per cent. Oxford University Press and Foundation for the European Review of Agricultural Economics 2009; all rights reserved. For permissions, please email journals.permissions@oxfordjournals.org, Oxford University Press.

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  • Subal C. Kumbhakar & Raushan Bokusheva, 2009. "Modelling farm production decisions under an expenditure constraint," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 36(3), pages 343-367, September.
    • Handle: RePEc:oup:erevae:v:36:y:2009:i:3:p:343-367
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    1. Raushan Bokusheva & Heinrich Hockmann, 2006. "Production risk and technical inefficiency in Russian agriculture," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 33(1), pages 93-118, March.
    2. Anjana Bhattacharyya & Subal C. Kumbhakar, 1997. "Market Imperfections and Output Loss in the Presence of Expenditure Constraint: A Generalized Shadow Price Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(3), pages 860-871.
    3. 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.
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    1. Obeng, K. & Sakano, R. & Naanwaab, C., 2016. "Understanding overall output efficiency in public transit systems: The roles of input regulations, perceived budget and input subsidies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 89(C), pages 133-150.
    2. 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.
    3. Viaggi, Davide & Raggi, Meri & Gomez y Paloma, Sergio, 2011. "Farm-household investment behaviour and the CAP decoupling: Methodological issues in assessing policy impacts," Journal of Policy Modeling, Elsevier, vol. 33(1), pages 127-145, January.
    4. Ioannis Skevas & Alfons Oude Lansink, 2020. "Dynamic Inefficiency and Spatial Spillovers in Dutch Dairy Farming," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(3), pages 742-759, September.
    5. Barbora Hřebíková & Lukáš Čechura, 2015. "An Analysis of the Impacts of Weather on Technical Efficiency in Czech Agriculture," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 63(5), pages 1645-1652.
    6. Jin, Man & Zhao, Shunan & Kumbhakar, Subal C., 2019. "Financial constraints and firm productivity: Evidence from Chinese manufacturing," European Journal of Operational Research, Elsevier, vol. 275(3), pages 1139-1156.
    7. Christian Stetter & Johannes Sauer, 2022. "Greenhouse Gas Emissions and Eco-Performance at Farm Level: A Parametric Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 81(3), pages 617-647, March.
    8. Melina Lamkowsky & Miranda P. M. Meuwissen & Harold A. B. van der Meulen & Frederic Ang, 2024. "How limiting is finance for Dutch dairy farms? A dynamic profit analysis," Journal of Agricultural Economics, Wiley Blackwell, vol. 75(1), pages 382-403, February.
    9. Marian Rizov & Jan Pokrivcak & Pavel Ciaian, 2013. "CAP Subsidies and Productivity of the EU Farms," Journal of Agricultural Economics, Wiley Blackwell, vol. 64(3), pages 537-557, September.
    10. Ioannis Skevas & Grigorios Emvalomatis & Bernhard Brümmer, 2018. "The effect of farm characteristics on the persistence of technical inefficiency: a case study in German dairy farming," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(1), pages 3-25.
    11. K. Obeng, 2011. "Indirect production function and the output effect of public transit subsidies," Transportation, Springer, vol. 38(2), pages 191-214, March.
    12. Moro, Daniele & Sckokai, Paolo, 2013. "The impact of decoupled payments on farm choices: Conceptual and methodological challenges," Food Policy, Elsevier, vol. 41(C), pages 28-38.
    13. Frýd, Lukáš & Sokol, Ondřej, 2021. "Relationships between technical efficiency and subsidies for Czech farms: A two-stage robust approach," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    14. Pokrivčák, Ján & Tóth, Marián, 2022. "Financing Gap of Agro-food Firms and the Role of Policies," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 14(3), September.
    15. Dzanku, F.M. & Osei, R.D., 2018. "Impact of pre– and post-harvest training reminders on crop losses and food poverty in Mali," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 275924, International Association of Agricultural Economists.
    16. Helen Pushkarskaya & Maria Marshall, 2010. "Family Structure, Policy Shocks, and Family Business Adjustment Choices," Journal of Family and Economic Issues, Springer, vol. 31(4), pages 414-426, December.

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