Productivity is a key factor for the growth of production outcomes and the development of industries. While data and methodologies are demanding, many insightful conclusions can be derived from cross sectional estimations, especially with micro data. This paper does a literature review of the most important methodologies for the estimation of cross-sectional productivity and the proper treatment of granular data in such estimations. Taking advantage of a rich dataset of agricultural production at farm level, the paper shows a practical example of the methodologies exposed and recommended data treatment. Although the results shows common directions on the productivity estimations, we conclude that the assumptions underlying each methodology will determine the context in which the estimations would have a better fit.


  • Henry Gómez Ramírez
  • Nicolás Garcés Rodríguez

Palabras clave:

  • Cross-Sectional Data
  • Production Unit Level A nalysis
  • Productivity


  • Proyecto 3
  • Documentos de trabajo