Efficiency in agricultural production: the case of peasant farmers in eastern Paraguay

This paper contributes to the productivity literature in developing country agriculture by quantifying the level of efficiency for a sample of peasant farmers from Eastern Paraguay. A stochastic efficiency decomposition methodology is used to derive technical, allocative and economic efficiency measures separately for cotton and cassava. An average economic efficiency of 40.1% for cotton and of 52.3% for cassava is found, which suggests considerable room for productivity gains for the farms in the sample through better use of available resources given the state of technology. Gains in output through productivity growth have become increasingly important to Paraguay as the opportunities to bring additional virgin lands into cultivation have significantly diminished in recent years. No clear strategy to improve farm productivity could be gleaned from an examination of the relationship between efficiency and various socioeconomic variables. One possible explanation for this finding is the existence of a stage of development threshold below which there is no consistent relationship between socioeconomic variables and productivity. If this is the case, then our results suggest that this sample of Paraguayan peasants are yet to reach such a threshold. Hence, improvements in educational and extension services, for example, would be needed to go beyond this threshold. Once this is accomplished, additional productivity gains would be obtained by further investments in human capital and related factors.     

ALTERNATIVE PRODUCTION FRONTIER METHODOLOGIES AND DAIRY FARM EFFICIENCY

This paper estimates technical efficiency (TE) measures using four alternative production frontier models, and evaluates the sensitivity of the results to the choice of methodology. The Cobb-Douglas functional form along with data for 1982 and 1983 from 404 dairy farms located throughout six northeastern states in the US are used in the estimation. A general conclusion is that, broadly speaking, frontier function models are neutrally upwardly scaled versions of the OLS or average model. A second conclusion is that different models yield markedly different efficiency levels across firms. However, the correlation between the indexes from the various methods is high, which implies that the ordinal ranking of firms according to their measured level of technical efficiency appears to be independent of the method used for a given year. By comparison, the correlation between efficiency indexes for the same method across time, although positive, is much lower than the previous set of correlations. Correlation analysis of efficiency versus farm size and of efficiency versus returns over variable costs, based on the alternative models, yielded consistent results.     

Technical efficiency analysis correcting for biases from observed and unobserved variables: an application to a natural resource management project

This article brings together the stochastic frontier framework with impact evaluation methodology to compare technical efficiency (TE) across treatment and control groups using cross-sectional data associated with the MARENA Program in Honduras. A matched group of beneficiaries and control farmers is determined using propensity score matching techniques to mitigate biases stemming from observed variables. In addition, possible self-selection arising from unobserved variables is addressed using a selectivity correction model for stochastic frontiers recently introduced by Greene (J Prod Anal 34:15?C24, 2010). The results reveal that average TE is consistently higher for beneficiary farmers than the control group while the presence of selectivity bias cannot be rejected. TE ranges from 0.67 to 0.75 for beneficiaries and from 0.40 to 0.65 for the control depending on whether biases were controlled or not. The TE gap between beneficiaries and control farmers decreases by implementing the matching technique and the sample selection framework decreases this gap even further. The analysis also suggests that beneficiaries do not only exhibit higher TE but also higher frontier output.     

Technical efficiency and metatechnology ratios for dairy farms in three southern cone countries: a stochastic meta-frontier model

This paper compares technical efficiency (TE) and metatechnology ratios (MTR) for dairy farms from Argentina, Chile and Uruguay using the meta-frontier (MF) approach. The estimated average MTRs for Argentina, Chile and Uruguay are 83.8, 79.6 and 91.4%, respectively, and these results are significantly different from each other. The TEs estimated with respect to the MF are 72.8, 65.8 and 73.4% for Argentina, Chile and Uruguay, respectively. The average TEs for Argentina and Uruguay are not significantly different from each other but are significantly higher than the value for Chile. The production frontiers for Argentina and Uruguay are relatively close to the MF, which suggests that these two countries might need to increase investments to promote local research to generate new technologies and/or search for technologies to adapt from more distant areas. By contrast, Chile could benefit from adaptive research, designed to make borrowed technology from Argentina and/or Uruguay applicable to local conditions, which could be a cost effective way to improve dairy farm performance.     

Agricultural productivity,shadow wages and off-farm labor decisions in Nicaragua

The objective of this study is to analyze the decision to work off-farm by male and female farmers in Nicaragua using a three-year unbalanced panel dataset. Shadow income and shadow wages are also estimated. Moreover, to mitigate biases from unobserved individual and farm time-invariant characteristics as well as from sample selection, we apply a semiparametric approach for panel data. Our main findings suggest that shadow wages play a major role in off-farm labor decisions for both males and females. This implies that less labor is allocated to off-farm activities as the opportunity cost for agricultural work goes up. In addition, as the on-farm marginal productivity of households (i.e., shadow income) rises, both males and females reduce the hours they allocate to off-farm activities.     

Plot-level technical efficiency accounting for farm-level effects: Evidence from Chilean wine grape producers

This paper applies alternative panel data models to a cross-sectional dataset that contains observations at the plot level for a sample of wine-grape farms in Central Chile. The input–output data as well as key attributes of the production system are at the plot level, at which individualized management exists. However, plots belonging to a particular farm are also subject to overall centralized (farm-level) management. Thus, this data configuration offers the possibility of analyzing technical efficiency (TE) both across plots and across farms. A Generalized True Random Effects model, which permits the separate identification of farm-level and plot-level inefficiency while controlling for unobserved farm-level heterogeneity, shows that TE varies across farms but not among plots within the same farm. Geographical location also affects grape production and agro-climatic conditions influence production levels, with grape farms located on cooler zones producing significantly less than their counterparts in warmer zones, as expected. The analysis underscores the value of using recent methodologies typically applied to panel data when cross-sectional information is available for individual plots within a farm unit or in similar settings.     

A Growth Accounting Analysis of Cost Efficiency in Milk Production for Six Northern States in the United States

This paper reports on the use of a growth accounting approach to calculate and decompose cost efficiency indices into technical change, regional competitive advantage stemming from spatial effects, and economies of size. Dairy farm data for Connecticut, Maine, Vermont, Michigan, New York and Pennsylvania for the years 1968, 1970, 1977, 1980 and 1988 are utilized in the analysis. The results show that technological change yielded a 1.8% average annual rate of cost reduction over the period studied. In addition, medium and large farms were, on average, 12% to 20% more efficient than small farms. Pennsylvania had a distinct competitive advantage (13.8%), while Maine exhibited a clear competitive disadvantage (−18.2%) in producing milk relative to New York.     

Technical efficiency measures for dairy farms using panel data: A comparison of alternative model specifications

This article examines the impact of fixed effects production functions vis-à-vis stochastic production frontiers on technical efficiency measures. An unbalanced panel consisting of 96 Vermont dairy farmers for the 1971–1984 period was used in the analysis. The models examined incorporated both time-variant and time-invariant technical efficiency. The major source of variation in efficiency levels across models stemmed from the assumption made concerning the distribution of the one-sided term in the stochastic frontiers. In general, the fixed effects technique was found superior to the stochastic production frontier methodology. Despite the fact that the results of various statistical tests revealed the superiority of some specifications over others, the overall conclusion of the study is that the efficiency analysis was fairly consistent throughout all the models considered.     

Technical efficiency in farming: a meta-regression analysis

A meta-regression analysis including 167 farm level technical efficiency (TE) studies of developing and developed countries was undertaken. The econometric results suggest that stochastic frontier models generate lower mean TE (MTE) estimates than non-parametric deterministic models, while parametric deterministic frontier models yield lower estimates than the stochastic approach. The primal approach is the most common technological representation. In addition, frontier models based on cross-sectional data produce lower estimates than those based on panel data whereas the relationship between functional form and MTE is inconclusive. On average, studies for animal production show a higher MTE than crop farming. The results also suggest that the studies for countries in Western Europe and Oceania present, on average, the highest levels of MTE among all regions after accounting for various methodological features. In contrast, studies for Eastern European countries exhibit the lowest estimate followed by those from Asian, African, Latin American, and North American countries. Additional analysis reveals that MTEs are positively and significantly related to the average income of the countries in the data set but this pattern is broken by the upper middle income group which displays the lowest MTE.