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jA Meta-Analysis of the Price Elasticity of Meat: Evidence of Regional Differences - IntroductionMany studies estimate the price elasticity of meat utilizing various data and estimation methods, which several qualitative literature reviews, such as Kuznets, Tomek, Smallwood et al., and Asche et al., suggest contribute to differences in reported elasticity estimates. Yet qualitative literature reviews can be sensitive to the subjective decision of the reviewer to emphasize particular study characteristics over others, and so meta-analysis has been increasingly used as a tool to quantitatively survey literature. In a typical meta-analysis, a parameter commonly estimated in the literature, such as the price elasticity, is regressed on a series of dummy variables controlling for study characteristics. By utilizing regression techniques, the subjective decision of the reviewer is thus replaced by statistical tests, the results of which shed light on the statistical influence of study characteristics on the parameter estimate. Examples of such analyses include Espey, Dalhuisen et al., Gallet and List, Johnston et al., Gallet, and Gallet.
Concerning the demand for meat, Gallet reports results of a meta-analysis of the price elasticity. In his study, 4120 estimates of the price elasticity of meat, collected from 419 studies, were regressed on variables that control for the type of meat, demand specification, nature of the data used to estimate demand, estimation method, publication outlet, and demand location. He finds beef, lamb, and fish demand are more responsive to price, while poultry demand is less responsive to price. Also, although the price elasticity of meat is particularly sensitive to a number of specification, estimation, and publication characteristics, data issues and the location of demand have less influence on the price elasticity.
A typical meta-analysis constructs a meta-data set by compiling information from studies across multiple regions. For example, Gallet’s meta-data includes studies of meat demand in North America, Asia, and Europe, as well as a few other regions. Although meta-analyses often control for regional differences by including region dummy variables in the meta- regressions, this holds the marginal effects constant across regions. With respect to Gallet, while he finds some regional differences in the price elasticity of meat, the rank order of the price elasticity across study characteristics is held constant in each region. Yet there may not only be regional differences in the price elasticity of meat, but also regional differences in the impact of each study characteristic on the price elasticity, and so this study extends Gallet by reporting the results from estimating separate meta-regressions of the price elasticity for North America, Europe, and Asia, the three regions most commonly studied in the literature.
Although there are a number of similarities in the meta-regression results across the three regions, we do find regional differences in the pattern of the price elasticity of meat. For example, the price elasticities of beef, lamb, and fish in North America are significantly higher in absolute value compared to poultry, but significant differences in the price elasticity across meat products drop off for Asia and Europe. Furthermore, demand specification plays a more prominent role in determining the price elasticity of meat in Europe, compared to North America and Asia. In the sections that follow, Section 2 presents the data and meta-regression model. This is followed in Section 3 with a discussion of the estimation results. A conclusion is provided in Section 4.