Essays in time series econometrics
| dc.contributor.advisor | Jentsch, Carsten | |
| dc.contributor.author | Reichold, Karsten | |
| dc.contributor.referee | Wagner, Martin | |
| dc.contributor.referee | Demetrescu, Matei | |
| dc.date.accepted | 2023-07-05 | |
| dc.date.accessioned | 2023-07-18T06:52:33Z | |
| dc.date.available | 2023-07-18T06:52:33Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | This cumulative dissertation consists of three self-contained papers all contributing to the cointegrating regression literature. The first chapter is devoted to classical linear cointegrating regressions, i.e., regressions that contain integrated processes as regressors. It combines traditional and self-normalized Wald-type test statistics with a vector autoregressive sieve bootstrap to reduce size distortions of hypothesis tests on the cointegrating vector. The second chapter focuses on panels of cointegrating polynomial regressions, i.e., panels of regressions that include an integrated process and its powers as regressors. It derives the asymptotic properties of a group-mean fully modified OLS estimator and hypothesis tests based upon it in a fixed cross-section and large time series dimension. The third chapter is devoted to testing for a cointegrating relationship between a fixed number of integrated processes. In particular, it derives asymptotic theory for an existing nonparametric variance ratio unit root test (originally proposed to test for an unit root in an observed univariate time series) when applied to regression residuals. | en |
| dc.identifier.uri | http://hdl.handle.net/2003/42002 | |
| dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-23838 | |
| dc.language.iso | en | de |
| dc.subject | Bootstrap | en |
| dc.subject | Cointegration | en |
| dc.subject | Estimation | en |
| dc.subject | Inference | en |
| dc.subject.ddc | 310 | |
| dc.subject.rswk | Regressionsanalyse | de |
| dc.subject.rswk | Kointegration | de |
| dc.subject.rswk | Bootstrap-Statistik | de |
| dc.title | Essays in time series econometrics | de |
| dc.type | Text | de |
| dc.type.publicationtype | PhDThesis | de |
| dcterms.accessRights | open access | |
| eldorado.secondarypublication | false | de |