There are two primary treatment alternatives available to those with mild to moderate depression or anxiety: psychotherapy and medication. The medical literature and our analysis suggests that in many cases psychotherapy, or a combination of therapy and medication, is more curative than medication alone. However, few individuals choose to use psychotherapy. We develop and estimate a dynamic model in which individuals make sequential medical treatment and labor supply decisions while jointly managing mental health and human capital. The results shed light on the relative importance of several drawbacks to psychotherapy that explain patients’ reluctance to use it: (1) therapy has high time costs, which vary with an individual’s opportunity cost of time and flexibility of the work schedule; (2) therapy is less standardized than medication, which results in uncertainty about it’s productivity for a given individual; and (3) therapy is expensive. The estimated model is used to simulate the impacts of counterfactual policies that alter the costs associated with psychotherapy.
This handbook-style article describes various longitudinal methods used commonly in program impact evaluation. We discuss the advantages of each method, the assumptions required for implementation, and provide programming examples in STATA using data from Indonesia and Malawi.
The following program can be used to determine which of 11 parametric distributions best fits the empirical (conditional or unconditional) distribution of a variable of interest. The distributions mimic those used in Jones, Lomas, and Rice (2014), which are chosen to fit a healthcare expenditure distribution that is characterized by a long right tail. I have attached an edited (publicly available) data file from the 1996 Medical Expenditure Panel Survey (MEPS) as an example of how the code works.