Technical efficiency in farming: a meta-regression analysis

By B. Bravo-Ureta, D. Solís, Víctor H. Moreira López, José Maripani, A. Thiam, Teodoro E. Rivas. 2007

534 citations recorded by the source corpus.

Subfields: Environmental Chemistry, General Agricultural and Biological Sciences, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/57e77ef7cab7d1c3fbe5687f1d7da6119b62a2c3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Chemistry

In General Agricultural and Biological Sciences

In Management Science and Operations Research

Citations in the corpus

Determining water use efficiency for wheat and cotton: A meta-regression analysis (2016, unknown): “For instance, Bravo-Ureta et al. (2007) meta-analyzed the farm level technical efficiency using 167 studies conducted around the world and found that varying estimates of the technical efficiency obtained were due to the differences of empirical models employed and variations at the country and…”
Using least squares and tobit in second stage DEA efficiency analyses (2009, methodology): “Researchers who have used tobit at stage 2 include Bravo-Ureta et al. (2007), Latruffe et al. (2004), Fethi et al. (2002), Vestergaard et al. (2002), Ruggiero and Vitaliano (1999), Chilingerian (1995), Oum and Yu (1994) and Bjurek et al. (1992).”
Whether crop diversification is a desired strategy for agricultural growth in Bangladesh (2009, background): “TE can be interpreted as a relative measure of managerial ability for a given level of technology, whereas TC evaluates the effect on productivity arising from the adoption of new or improved production processes (Bravo-Ureta et al., 2007).”
Modern Rice Technologies and Productivity in the Philippines: Disentangling Technology from Managerial Gaps (2015, methodology): “As indicated above, we follow the approach of Greene (2010) and Bravo-Ureta et al. (2012) where the PSM and SPF approaches are combined in order to correct biases from both observed and unobserved characteristics.”
Technical Efficiency among Peasant Farmers Participating in Natural Resource Management Programmes in Central America (2009, result): “It is worth noting that the average level of efficiency obtained here is comparable with the averages presented by Bravo-Ureta et al. (2007) in their meta-regression analysis of TE in agriculture.”
Women's labour contribution to productivity and efficiency in agriculture: empirical evidence from Bangladesh. (2010, unknown): “…frontier analysis by Aigner, Lovell and Schmidt (1977), a large number of studies followed which typically place farming efficiency of developing country farmers in the range of 60% to 82% (e.g., Bravo-Ureta et al., 2007; Rahman, 2003; Coelli et al., 2002; Ali and Flinn, 1989; Wang et al., 1996).”
Can Technology Deliver on the Yield Challenge to 2050 (2009, background): “Besides, developing countries will increasingly depend on imports of cereals (and oilseeds) from industrial countries, Eastern Europe (including Russia), and Brazil and Argentina.”
Technical efficiency analysis correcting for biases from observed and unobserved variables: an application to a natural resource management project (2012, background): “A contribution of this article is to narrow the gap between significant methodological advances that have been made in the estimation of SPF models (Greene 2008), which has lead to a sizable number of farm level TE studies (Bravo-Ureta et al. 2007), and the rapidly evolving impact evaluation literat”
Technical efficiency and metatechnology ratios for dairy farms in three southern cone countries: a stochastic meta-frontier model (2010, unknown): “The average TE estimates for the preferred country specific SPF models are 87.0, 84.9 and 81.1%, respectively, for Argentina, Chile and Uruguay, which are consistent with TE values for dairy farms reported in the literature (Bravo-Ureta et al. 2007).”