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Zonder onderwerpscode: economie

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This paper specifies a general set of conditions under which the impacts of a policy can be identified using data generated under a different policy regime. We show that some of the policy impacts can be identified under relatively weak conditions on the data and structure of a model. Based on the identification results we develop estimators of policy impacts. We discuss a nonparametric method to implement the estimation but also discuss semiparametric methods in order to reduce the conditioning dimension. We then provide an empirical example of the impact of tuition subsidies using the ideas. While the framework used in this paper is fairly narrow, we believe this approach can be applied to a broad set of problems.

Autoregression (Statistics) --- Economic policy --- Education and state. --- Estimation theory --- Evaluation. --- Econometric models.

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This paper considers data quality issues for the analysis of consumption inequality exploiting two complementary datasets from the Consumer Expenditure Survey for the United States. The Interview sample follows survey households over four calendar quarters and consists of retrospectively collected information about monthly expenditures on durable and non-durable goods. The Diary sample interviews household for two consecutive weeks and includes detailed information about frequently purchased items (food, personal cares and household supplies). Most reliable information from each sample is exploited to derive a correction for the measurement error affecting observed measures of consumption inequality in the two surveys. We find that consumption inequality, as measured by the standard deviation of log non-durable consumption, has increased by roughly 5% points during the 1990s.