Abstract
Estimating the causal impact of sport or physical activity on health and well-being is an issue of great relevance in the sport and health literature. The increasing availability of individual level data has encouraged this interest. However, this analysis requires dealing with two types of simultaneity problem: (1) between exercise and response variables; and (2) across the different response variables. This note discusses how the previous literature has dealt with these two questions with particular attention paid to the use of seemingly aseptic econometric models proposed by some recent empirical papers. Regardless of the approach, identification necessarily requires the use of untestable hypotheses. We provide some recommendations based on analyzing the robustness of the estimation results to changes in the adopted identification assumptions.
Highlights
The purpose of this note is to discuss the use of systems of simultaneous equations in the empirical literature to estimate the impact of health behavior variables, such as sport and/or physical activity, on health and well-being
Dealing with simultaneity in cross-sectional databases is a difficult task which requires the use of untestable identification assumptions either in the choice of instruments or the direction of causality
When an exclusion restriction is not found, this problem can only be solved by a joint estimation of equations for each of the simultaneously observed variables if we have strong arguments to accept that health behavior affects health outcome but not the other way around
Summary
The purpose of this note is to discuss the use of systems of simultaneous equations in the empirical literature to estimate the impact of health behavior variables, such as sport and/or physical activity, on health and well-being. Recent years have witnessed the availability of surveys that allow for the observation of these variables together with other individual socio-economic characteristics. Recent years have witnessed the availability of surveys that allow for the observation of these variables together with other individual socio-economic characteristics This information has generated a burgeoning research literature aiming to estimate the main determinants of health and wellbeing, an important concern in this type of analysis regards the simultaneous observation of the different variables in the model. Contrary to the claims of previous papers in the literature, the estimation of a reduced form specification is generally not a valid alternative to deal with the simultaneity problem of response variables regardless of whether a seemingly unrelated regression (SUR ) strategy is used or not to account for the fact that errors in the different equations are potentially correlated This brief note does not attempt to discuss the main econometric properties of the estimators. Our main purpose is to discuss the theoretical implications of the use of simultaneous equation models to deal with endogeneity adopted by an important strand of the sport economic literature
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