Contained in:
Book Chapter

Assessment of agricultural productivity change at country level: A stochastic frontier approach

  • Alessandro Magrini

In this paper, we estimate agricultural productivity change at country level based on the same data employed by the United States Department of Agriculture (USDA), the current reference data source, using a stochastic frontier model instead of the growth accounting method. The use of a stochastic frontier model is motivated by the opportunity to overcome the limitation of USDA estimates which rely on approximated and imputed input cost shares, and of the growth accounting method in general, which ignores technical inefficiency. We found that, in general, USDA estimates are higher in absolute value than ours but in substantial agreement, confirming the different theoretical foundations of the two methods and suggesting the empirical validity of both of them. Furthermore, our results show that the assumption of constant returns to scale made by many authors appears just a simplification and not a real property of the production processes of the various countries. This work has the value to provide, for the first time in the literature, a comparison between agricultural productivity changes estimated with different methodologies, and an additional data source that can be employed in a large variety of longitudinal economic analyses at country level.

  • Keywords:
  • agricultural TFP,
  • growth accounting,
  • Malmquist index,
  • technical efficiency,
  • translog production frontier,
+ Show More

Alessandro Magrini

University of Florence, Italy - ORCID: 0000-0002-7278-5332

  1. Battese, G.E., Coelli, T.J. (1995). A model for technical inefficiency effects in a stochastic frontier production function for panel data Empirical Economics, 20: 325-332.
  2. Charnes, A., Cooper, W.W., Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6): 429-444.
  3. Caves, D.W., Christensen, L.R., Diewert, W.E. (1982). The economic theory of index numbers and the measurement of input, output, and productivity. Econometrica, 50: 1393-1414.
  4. Coelli, T., Henningsen, A. (2020). frontier: stochastic frontier analysis. R package version 1.1-8. <https://CRAN.R-Project.org/package=frontier>.
  5. Fuglie, K.O. (2015). Accounting for growth in global agriculture. Bio-based and Applied Economics, 4(3): 221-254.
  6. Kryszak, L., Swierczynska, K., Staniszewski, J. (2021). Measuring total factor productivity in agriculture: A bibliometric review. International Journal of Emerging Markets, 16(5).
  7. Laureti, T. (2006). L’efficienza rispetto alla frontiera delle possibilit`a produttive: Modelli teorici ed analisi empiriche. Firenze University Press, Florence, IT.
  8. Magrini, A. (2021). A stochastic frontier model to assess agricultural eco-efficiency of European countries in 1990–2019. International Journal of Statistics and Probability, 10(4): 138-156.
  9. Orea, L. (2002). Parametric decomposition of a generalized Malmquist productivity index. Journal of Productivity Analysis, 18: 5-22.
  10. Schmidt, P., Sickles, R.C. (1984). Production frontiers and panel data. Journal of Business & Economic Statistics, 2(4): 299-326.
  11. United Nations (2020). World economic situation and prospects (WESP 2020). Department of Economic and Social Affairs, United Nations. <https://www.un.org/development/desa/publications/wesp-2020.html>.
  12. USDA (2019). International agricultural productivity. Economic Research Service (ERS), United States Department of Agriculture (USDA). <https://www.ers.usda.gov/data-products/international-agricultural-productivity/>.
PDF
  • Publication Year: 2021
  • Pages: 197-202
  • Content License: CC BY 4.0
  • © 2021 Author(s)

XML
  • Publication Year: 2021
  • Content License: CC BY 4.0
  • © 2021 Author(s)

Chapter Information

Chapter Title

Assessment of agricultural productivity change at country level: A stochastic frontier approach

Authors

Alessandro Magrini

Language

English

DOI

10.36253/978-88-5518-461-8.37

Peer Reviewed

Publication Year

2021

Copyright Information

© 2021 Author(s)

Content License

CC BY 4.0

Metadata License

CC0 1.0

Bibliographic Information

Book Title

ASA 2021 Statistics and Information Systems for Policy Evaluation

Book Subtitle

BOOK OF SHORT PAPERS of the on-site conference

Editors

Bruno Bertaccini, Luigi Fabbris, Alessandra Petrucci

Peer Reviewed

Publication Year

2021

Copyright Information

© 2021 Author(s)

Content License

CC BY 4.0

Metadata License

CC0 1.0

Publisher Name

Firenze University Press

DOI

10.36253/978-88-5518-461-8

eISBN (pdf)

978-88-5518-461-8

eISBN (xml)

978-88-5518-462-5

Series Title

Proceedings e report

Series ISSN

2704-601X

Series E-ISSN

2704-5846

174

Fulltext
downloads

248

Views

Export Citation

1,339

Open Access Books

in the Catalogue

2,191

Book Chapters

3,709,757

Fulltext
downloads

4,396

Authors

from 923 Research Institutions

of 65 Nations

64

scientific boards

from 348 Research Institutions

of 43 Nations

1,246

Referees

from 379 Research Institutions

of 38 Nations