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Finally, one should keep in mind that the applicability of fixed effects models is limited by the availability of data. For example, in a survey a student from the same family (e.g., a brother or a parent) will have the same treatment status as the student in question. Therefore, FE models are unlikely to identify wage effects for individuals with siblings or even for children of the respondents. Fixed effects individual slope (FEIS) models address this problem by detrending the data, which results in a reduction of the average individual effect from 1 to 0 for individuals with siblings and children (Brderl and Ludwig 2015, p. 337).
One of the most controversial topics in empirical economics is the estimation of price elasticities. The literature has identified several concerns regarding the estimation of the price elasticity. These concerns have led many economists to criticize the use of price elasticity estimates. The potential explanations for the lack of consensus in the literature are manifold. For example, one could argue that the use of price elasticities is in most cases not possible because either the product price or the quantity sold is unobservable or non-storable. This point is important, because it highlights the fact that the use of price elasticities is not only limited to drug consumption but could be found in a broad range of commodities. The literature has identified several approaches to estimate price elasticities such as the substitution effect, the income effect, the substitution effect among others. Here, we discuss the most important drawbacks regarding the estimation of price elasticity estimates.
Fixed effects estimators assume that the time trends of the treated and the untreated group do not differ. This means that the time trend of the treated group should be the same as that of the control group. Therefore, the fixed effects estimator can be considered a weighted average of the cross-sectional variation of the treated and the control group.
Some limitations of fixed effects estimations should be known. The authors' selection of explanatory variables might not be representative and might not be representative in time. Reverse causality might cause problems and could be more severe in FE estimations because FE estimations solely rely on intertemporal variation. 827ec27edc