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of selection) in matching, instrumental variable and control functions methods. (2) It contrasts the roles of exclusion … restrictions in matching and selection models. (3) It characterizes the sensivity of matching to the choice of conditioning …. (4) It demonstrates the problem of choosing the conditioning variables in matching and the failure of conventional model …
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matching estimators. As an illustration of the applicability of the theory, we derive the asymptotic distribution of a matching …Matching estimators are widely used in statistical data analysis. However, the distribution of matching estimators has … matching estimators. This representation allows the use of martingale limit theorems to derive the asymptotic distribution of …
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Data on the number of people who have committed suicide tends to be reported with a substantial time lag of around two years. We examine whether online activity measured by Google searches can help us improve estimates of the number of suicide occurrences in England before official figures are...
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This chapter discusses the formal and informal techniques that are commonly used to give quantitative answers in the field of distributional analysis. To this end, it covers subjects including inequality, poverty, and the modeling of income distributions. It also deals with parametric and...
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A Bayesian approach is used to estimate the covariance matrix of Gaussian data. Ideas from Gaussian graphical models and model selection are used to construct a prior for the covariance matrix that is a mixture over all decomposable graphs. For this prior the probability of each graph size is...
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