Decomposing agricultural productivity growth using a random-parameters stochastic production frontier

Abstract

This study makes two key contributions to the agricultural productivity literature. First, it demonstrates, using US agricultural state-level data, how a random-parameters stochastic frontier model can be used to account for environmental heterogeneity across decision-making units. Second, it uses the estimated parameters of the model to compute and decompose a productivity index that satisfies several key axioms from index theory. Because the decomposition explicitly accounts for both observed and unobserved environmental effects, we are able to obtain a more realistic and flexible assessment of productivity growth. We find substantial differences between productivity results generated using a model with random slope parameters and those generated using a more conventional model with constant slope parameters.

Agricultural productivity growth in Latin America and the Caribbean: an analysis of climatic effects, catch‐up and convergence*

“…(2017) and Njuki et al . (2019). The TRP‐SPF estimates are then used to calculate and decompose CATFP.…”

“…Accounting for the effect of climatic variables on output is essential so that reliable productivity measures can be derived (Njuki et al . 2019; Chambers and Pieralli, 2020). In addition, the exclusion of climatic variables in the production function, something that has been quite common, is a classic example of omitted variables (Griliches, 1957).…”

Creation of climate‐smart and energy‐efficient agriculture in the European Union: Pathways based on the frontier analysis

“…The analysis of agricultural productivity growth is an important research avenue due to the role of agriculture in the economy. Njuki, Bravo‐Ureta, and O'Donnell (2019) presented a parametric framework for analysis of the total factor productivity growth based on the random parameters frontier. Skevas (2020) and Baráth, Fertő, and Bojnec (2020) applied the random parameters frontier for efficiency and productivity analysis.…”

Technological Differences, Theoretical Consistency, and Technical Efficiency: The Case of Hungarian Crop-Producing Farms

“…However, this does not mean that there is less need to take account of parameter heterogeneity [15]. The number of papers that applied RPM in agricultural context is very limited (e.g., references [16][17][18][19][20][21]).…”