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In many applications of econometrics and economics, a large proportion of the questions of interest are identification. An economist may be interested in uncovering the true signal when the data could be very noisy, such as time-series spurious regression and weak instruments problems, to name a few. In this book, High Dimensional Econometrics and Identification, we illustrate the true signal and, hence, identification can be recovered even with noisy data in high-dimensional data, e.g., large panels. High-dimensional data in econometrics is the rule rather than the exception. One of the tools to analyze large, high-dimensional data is the panel data model. High Dimensional Econometrics and Identification grew out of research work on the identification and high-dimensional econometrics that we have collaborated on over the years, and it aims to provide an up-to-date presentation of the issues of identification and high-dimensional econometrics, as well as insights into the use of these results in empirical studies. This book is designed for high-level graduate courses in econometrics and statistics, as well as used as a reference for researchers.
| Autorius: | Chihwa Kao & Long Liu |
| Leidėjas: | World Scientific |
| Išleidimo metai: | 2019 |
| Knygos puslapių skaičius: | 180 |
| ISBN-10: | 9811200157 |
| ISBN-13: | 9789811200151 |
| Formatas: | 235 x 157 x 14 mm. Knyga kietu viršeliu |
| Kalba: | Anglų |
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