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Technical Annex: Mathematical Proofs for "Quantile Cointegration in the Autoregressive Distributed-Lag Modelling Framework"
| Content Provider | Semantic Scholar |
|---|---|
| Author | Kim, Tae-Hwan Shin, Yong-Cheol |
| Copyright Year | 2014 |
| Abstract | Recently, Xiao (2009) develops a novel estimation technique for quantile cointegrated time series in a static regression by extending the semiparametric approach by Phillips and Hansen (1990) and the parametrically augmented approach by Saikkonen (1991). This paper aims to extend the autoregressive distributed-lag approach of Pesaran and Shin (1998) into the quantile regression framework. This QARDL extension enables us to jointly analyse the short-run dynamics and the long-run cointegrating relationship across a range of quantiles. We derive the asymptotic distribution of QARDL estimators, and provide a general package in which the model can be estimated and tested within and across quantiles. Monte Carlo simulation results provide strong support for theoretical predictions. The main utilities of QARDL are demonstrated through the empirical application to the dividend policy in the U.S. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://web.yonsei.ac.kr/jinseocho/JSCHO_qardl_Nov22.pdf |
| Alternate Webpage(s) | http://web.yonsei.ac.kr/jinseocho/JSCHO_08_01_14_qardl_appendix.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
