Application of Econometrics in Agricultural Production

This Special Issue on “Applications of Econometrics in Agricultural Production” has aimed to rebuild and extend the approach to agricultural production analysis by including econometric methods for (a) developing a new paradigm for agricultural production analysis that acknowledges and models the relevance of the combined economic and agronomic aspects of the production processes; (b) defining output and input demand and supply in agricultural production from a technical perspective, with the use of production function/or production frontier models; and (c) understanding agricultural market exchange and market distortions and failures from a quantitative perspective.

The Special Issue has voluntarily selected and included very different and differentiated papers. The contributions, in fact, vary in many aspects and dimensions. Those include socio-economic and macroeconomic milieu, spanning from developed [1,2] to developing countries [3] and a plethora of agricultural issues and problems related to biotic threats treatment [3], land allocation [4], sector productivity [5,6], technological change and innovation [7,8,9], commercialization, market fluctuations and price trends [6,9,10,11], economic and technological efficiency [6,8,9,10], soil productivity and climate change-induced aridification and desertification [3], and different types of agricultural input, with a focus on banana [4], sugarcane [10], rice [7], palm oil [6], and grains [9].

In addition, the papers are distinguished among each other for the very different types of econometric and empirical methods adopted to address the issues. We remind the reader that econometrics (from the ancient Greek oikonomia, i.e., management/economics, and metron, measurement) is the statistical diagnostics of economic phenomena and systems. Econometrics represents a crucial technical tool for retrieving causal relationships among key economic variables and indicators, explaining economic phenomena, quantifying the impacts, and offering estimates and predictions.

In this perspective, the selected contributions adopt both parametric for the exploration of cause–effect phenomena and non-parametric analysis for the creation of a complex indicator [2,7]. Most contributions make use of dichotomous, limited dependent variable models [3,10] and time series analysis [1,5,9]. Other methods refer to endogenous switching regressors [4,11], stochastic frontier models [6], and sensitivity analysis [8].

Obviously, the choice of technical econometric instrument depends on many variables, including data availability and research questions that address the use of the methods and their complexity. Econometrics aims at measuring deterministic and stochastic relationships with a view to predicting.

In this perspective, therefore, despite the variance in applications and methods, the use of econometrics (superbly represented in the paper selections in this Special Issue) has embodied a fundamental technical instrument for understanding and explaining agricultural dynamics, including agricultural production, for both efficient industrial strategy and effective policy design.

The fil rouge and commonalities of the selected papers are strong problem-oriented and policy/industrial strategy objectives, spanning from biotic threats to production efficiency, from EU subsidies management to agriculture to grain price fluctuations, to name a few examples. The theory and approach developed and applied are therefore used to address aspects of environmental and economic sustainability of agricultural production and provide sound and firm strategy/policy design context and applicability.

In fact, we cannot manage what we cannot measure.