Productivity and Producer Welfare in the Presence of Production Risk

Production risk is an inherent characteristic of agriculture and changes in production risk will affect the welfare of risk‐averse producers. Using standard concepts from the literature on uncertainty, we introduce a welfare measure which comprises total factor productivity (TFP), production risk and farmer risk preferences, and which reflects the impact on producer welfare of changes in production technology. An empirical application is carried out using data from a sample of Spanish dairy farms which shows how the positive impact of increases in TFP on welfare can be offset by increases in the risk premium (‘cost of risk’) to the point where welfare may decrease.     

Explaining Differences in Milk Quota Values: The Role of Economic Efficiency

This article explores the relationship between milk quota values and economic efficiency in order to analyze government interventions in quota allocations among producers. For this purpose, we estimate quota values using a panel of Spanish dairy farms. Quota values are then decomposed into economic efficiency, price, and scale effects in order to assess the relative influence of these factors. We find that efficiency is important in explaining quota values but is uncorrelated with observable farm characteristics. This casts doubts on the government's ability to allocate quotas to efficient farms.     

A Parametric Approach to Estimating Eco‐Efficiency

The concept of eco‐efficiency is becoming increasingly popular as a tool to capture economic and environmental aspects of agricultural production. The literature to date has exclusively used the Data Envelopment Analysis (DEA) approach to measure producers’ eco‐efficiency. We show that it can also be estimated using a Stochastic Frontier Analysis (SFA) approach. Our approach not only allows controlling for random noise in the data but also permits an analysis of the potential substitutability between environmental pressures. We provide an empirical application of our model to data on a sample of Spanish dairy farms.     

Choosing the Technical Efficiency Orientation to Analyze Firms' Technology: A Model Selection Test Approach

We focus on the importance of the assumptions regarding how inefficiency should be incorporated into the specification of the data generating process in an examination of a sector's production or efficiency. Drawing on the literature on non-nested hypothesis testing, we find that the model selection approach of Vuong (1989) is a potentially useful tool for identifying the best specification before carrying out such studies. We include an empirical application using panel data on Spanish dairy farms where we estimate cost frontiers under different specifications of how inefficiency enters the data generating process (in particular, efficiency is introduced as an input-oriented, output-oriented and hyperbolic parameter). Our results show that the different models yield very different pictures of the technology and the efficiency levels of the sector, illustrating the importance of choosing the most correct model before carrying out production and efficiency analyses. The Vuong test shows that the input-oriented model is the best among the models we use, whereas the output-oriented model is the worst. This is consistent with the fact that the input- and output-oriented models provide the most and least credible estimates of scale economies given the structure of the sector.     

Parametric Decomposition of a Generalized Malmquist Productivity Index

This paper provides a parametric decomposition of a generalized Malmquist productivity index which takes into account scale economies. Unlike Balk (2001), the contribution of scale economies to productivity change is evaluated without recourse to scale efficiency measures, which are neither bounded for globally increasing, decreasing, or constant returns to scale technologies nor for ray-homogeneous technologies. An empirical application using panel data from Spanish savings banks is included. This application shows the advantages of the suggested method compared to Balk's approach. The results show an increase of total factor productivity which can be mainly attributed to technical progress and the positive effect of returns to scale.     

Do we estimate an input or an output distance function? An application of the mixture approach to European railways

In this paper, we estimate parametric input and output distance functions and discuss how to estimate a mixture/latent class model (LCM) involving the output and input distance functions in the context of multi-input and multi-output production technology. The proposed technique is applied to a panel data on European Railways (1971–1994). This model allows us to identify determinants of the efficiency orientation, thereby providing useful information that can help researchers to choose between the input and the output-oriented approaches. In addition, we develop cross-indices that can be used to compute input (output) technical inefficiency from the estimates of output (input) distance function.

Interpreting and Testing the Scaling Property in Models where Inefficiency Depends on Firm Characteristics

Let u ≥ 0 be technical inefficiency, let z be a set of variables that affect u, and let δ be the parameters of this relationship. The model satisfies the scaling property if u(z, δ) can be written as a scaling function h(z, δ) times a random variable u* that does not depend on z. This property implies that changes in z affect the scale but not the shape of u(z,δ). This paper reviews the existing literature and identifies models that do and do not have the scaling property. It also discusses practical advantages of the scaling property. The paper shows how to test the hypothesis of scaling, and other interesting hypotheses, in the context of the model of Wang, Journal of Productivity Analysis, 2002. Finally, two empirical examples are given.     

Endogeneity and measurement errors when estimating demand functions with average prices: an example from the movie market

Due to a lack of information about the prices faced by consumers, demand functions are sometimes estimated using average prices, namely total revenue divided by the number of consumers. Examples of this type of estimation can be found for cinema, sporting events and the performing arts since box office revenue is frequently available, though it is also common in other industrial markets. We construct a straightforward theoretical model showing that this practice introduces a specific type of measurement error that generates a major source of endogeneity into empirical research. Our theoretical framework also allows us, however, to find proper instruments for the endogenous price variables. An empirical application is provided using Spanish data on cinema attendance to illustrate the validity of the strategy proposed here to address this sort of endogeneity in an instrumental variable framework.