Time and causality: A Monte Carlo assessment of the timing-of-events approach |
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Authors: | Simen Gaure,Knut Rø ed,Tao Zhang |
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Affiliation: | 1. The Ragnar Frisch Centre for Economic Research, Gaustadalléen 21, 0349 Oslo, Norway;2. Centre for Information Technology Services, University of Oslo, Oslo, Norway |
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Abstract: | We present new Monte Carlo evidence regarding the feasibility of separating causality from selection within non-experimental duration data, by means of the non-parametric maximum likelihood estimator (NPMLE). Key findings are: (i) the NPMLE is extremely reliable, and it accurately separates the causal effects of treatment and duration dependence from sorting effects, almost regardless of the true unobserved heterogeneity distribution; (ii) the NPMLE is normally distributed, and standard errors can be computed directly from the optimally selected model; and (iii) unjustified restrictions on the heterogeneity distribution, e.g., in terms of a pre-specified number of support points, may cause substantial bias. |
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Keywords: | C14 C15 C41 |
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