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Modeling Unobserved Heterogeneity in New York Dairy Farms: One-Stage versus Two-Stage Models

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  • Alvarez, Antonio
  • del Corral, Julio
  • Tauer, Loren W.

Abstract

Agricultural production estimates have often differentiated and estimated different technologies within a sample of farms. The common approach is to use observable farm characteristics to split the sample into groups and subsequently estimate different functions for each group. Alternatively, unique technologies can be determined by econometric procedures such as latent class models. This paper compares the results of a latent class model with the use of a priori information to split the sample using dairy farm data. Latent class separation appears to be a superior method of separating heterogeneous technologies and suggests that technology differences are multifaceted.

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  • Alvarez, Antonio & del Corral, Julio & Tauer, Loren W., 2012. "Modeling Unobserved Heterogeneity in New York Dairy Farms: One-Stage versus Two-Stage Models," Agricultural and Resource Economics Review, Cambridge University Press, vol. 41(3), pages 275-285, December.
  • Handle: RePEc:cup:agrerw:v:41:y:2012:i:03:p:275-285_00
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    Cited by:

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    2. Lajos Baráth & Imre Fertő & Štefan Bojnec, 2020. "The Effect of Investment, LFA and Agri‐environmental Subsidies on the Components of Total Factor Productivity: The Case of Slovenian Farms," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(3), pages 853-876, September.
    3. Lajos Baráth & Imre Fertő & Štefan Bojnec, 2018. "Are farms in less favored areas less efficient?," Agricultural Economics, International Association of Agricultural Economists, vol. 49(1), pages 3-12, January.
    4. Vidoli, Francesco & Pignataro, Giacomo & Benedetti, Roberto, 2022. "Identification of spatial regimes of the production function of Italian hospitals through spatially constrained cluster-wise regression," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    5. K Hervé Dakpo & Laure Latruffe & Yann Desjeux & Philippe Jeanneaux, 2022. "Modeling heterogeneous technologies in the presence of sample selection: The case of dairy farms and the adoption of agri‐environmental schemes in France," Agricultural Economics, International Association of Agricultural Economists, vol. 53(3), pages 422-438, May.
    6. repec:blg:reveco:v:69:y:2017:i:6:p:7-17 is not listed on IDEAS
    7. K Hervé Dakpo & Laure Latruffe & Yann Desjeux & Philippe Jeanneaux, 2021. "Latent Class Modelling for a Robust Assessment of Productivity: Application to French Grazing Livestock Farms," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(3), pages 760-781, September.
    8. Niskanen, Olli & Heikkilä, Anna-Maija, 2015. "The Impact of Parcel Structure on the Efficiency of Finnish Dairy Farms," Agricultural and Resource Economics Review, Cambridge University Press, vol. 44(1), pages 65-77, April.
    9. Elizabeth Ahikiriza & Jef Meensel & Xavier Gellynck & Ludwig Lauwers, 2021. "Heterogeneity in frontier analysis: does it matter for benchmarking farms?," Journal of Productivity Analysis, Springer, vol. 56(2), pages 69-84, December.
    10. Marta Arbelo-Pérez & Pilar Pérez-Gómez & Antonio Arbelo, . "Profit efficiency and its determinants in the agricultural sector: A Bayesian approach," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 0.
    11. Vladimír Kostlivý & Zuzana Fuksová & Tamara Rudinskaya, 2020. "Drivers of farm performance in Czech crop farms," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 66(7), pages 297-306.
    12. A. G. Billé & C. Salvioni & R. Benedetti, 2018. "Modelling spatial regimes in farms technologies," Journal of Productivity Analysis, Springer, vol. 49(2), pages 173-185, June.
    13. Heesun, Jang & Xiaodong, Du, 2014. "Spatiotemporal Analysis of Dairy Farm Productivity, Size, and Entry-Exit in the US," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169824, Agricultural and Applied Economics Association.
    14. Lajos Barath & Heinrich Hockmann, 2016. "Technological differences, theoretically consistent frontiers and technical efficiency: a Random parameter application in the Hungarian crop producing farms," IEHAS Discussion Papers 1636, Institute of Economics, Centre for Economic and Regional Studies.
    15. Marta Arbelo-Pérez & Pilar Pérez-Gómez & Antonio Arbelo, 2023. "Profit efficiency and its determinants in the agricultural sector: A Bayesian approach," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 69(11), pages 436-445.
    16. John Bailey Jones & Sangeeta Pratap, 2020. "An Estimated Structural Model of Entrepreneurial Behavior," American Economic Review, American Economic Association, vol. 110(9), pages 2859-2898, September.
    17. Juan Cabas Monje & Bouali Guesmi & Amer Ait Sidhoum & José María Gil, 2023. "Measuring technical efficiency of Spanish pig farming: Quantile stochastic frontier approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 67(4), pages 688-703, October.
    18. Habtamu ALEM, 2017. "Source Of Total Factor Productivity Change: An Empirical Analysis Of Grain Producing Regions In Norway," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 69(6), pages 8-18, December.
    19. Martinez Cillero, Maria & Breen, James & Thorne, Fiona & Wallace, Michael & Hennessy, Thia, 2016. "Technical efficiency and technology heterogeneity of beef farms: a latent class stochastic frontier approach," 90th Annual Conference, April 4-6, 2016, Warwick University, Coventry, UK 236351, Agricultural Economics Society.
    20. Garcia, Luis & Laepple, Doris & Dillon, Emma & Thorne, Fiona, 2020. "The role of hired labor in transient and persistent technical efficiency on Irish dairy farms," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304395, Agricultural and Applied Economics Association.
    21. Fertő, Imre & Baráth, Lajos, 2013. "Heterogenitás és technikai hatékonyság - a magyar specializált szántóföldi növénytermesztő üzemek esete [Heterogeneity and technical efficiency - the case of Hungarys specialized arable crop produc," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(6), pages 650-669.
    22. Zoltán Bakucs & Imre Fertő & Enikő Vígh, 2020. "Crop Productivity and Climatic Conditions: Evidence from Hungary," Agriculture, MDPI, vol. 10(9), pages 1-12, September.

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