dc.contributor.author | KAPETANIOS, George | |
dc.contributor.author | KHALAF, Lynda | |
dc.contributor.author | MARCELLINO, Massimiliano | |
dc.date.accessioned | 2016-03-09T10:07:24Z | |
dc.date.available | 2016-03-09T10:07:24Z | |
dc.date.issued | 2016 | |
dc.identifier.citation | Journal of applied econometrics, 2016, Vol. 31, No. 5, pp. 821–842 | |
dc.identifier.uri | https://hdl.handle.net/1814/39321 | |
dc.description.abstract | Robust methods for instrumental variable inference have received considerable attention recently. Their analysis has raised a variety of problematic issues such as size/power trade-offs resulting from weak or many instruments. We show that information reduction methods provide a useful and practical solution to this and related problems. Formally, we propose factor-based modifications to three popular weak-instrument-robust statistics, and illustrate their validity asymptotically and in finite samples. Results are derived using asymptotic settings that are commonly used in both the factor and weak-instrument literature. For the Anderson–Rubin statistic, we also provide analytical finite-sample results that do not require any underlying factor structure. An illustrative Monte Carlo study reveals the following. Factor-based tests control size regardless of instruments and factor quality. All factor-based tests are systematically more powerful than standard counterparts. With informative instruments and in contrast to standard tests: (i) power of factor-based tests is not affected by k even when large; and (ii) weak factor structure does not cost power. An empirical study on a New Keynesian macroeconomic model suggests that our factor-based methods can bridge a number of gaps between structural and statistical modeling. | |
dc.relation.ispartof | Journal of applied econometrics | |
dc.title | Factor based identification-robust inference in IV regressions | |
dc.type | Article | |
dc.identifier.doi | 10.1002/jae.2466 | |
dc.identifier.volume | 31 | |
dc.identifier.startpage | 821 | |
dc.identifier.endpage | 842 | |
eui.subscribe.skip | true | |
dc.identifier.issue | 5 | |