at Google ScholarTitle data
Borchert, Ingo ; Larch, Mario ; Shikher, Serge ; Yotov, Yoto V.:
The International Trade and Production Database for Estimation (ITPD-E).
In: International Economics.
Vol. 166
(2021)
.
- pp. 140-166.
ISSN 2110-7017
DOI: https://doi.org/10.1016/j.inteco.2020.08.001
Abstract in another language
This paper introduces and describes the new International Trade and Production Database that can be used for statistical estimation (ITPD-E). The ITPD-E contains consistent data on international and domestic trade for 243 countries, 170 industries, and 17 years. The data are constructed at the industry level covering agriculture, mining, energy, manufacturing, and services, so that the ITPD-E describes nearly completely the traded sectors of each economy. The time period covered commences in 2000 and extends to 2016. The ITPD-E is constructed using reported administrative data and intentionally does not include information estimated by statistical techniques. This feature and the unprecedented coverage of industries and countries with consistent international and domestic trade data renders the ITPD-E well suited for estimation of economic models, e.g., the gravity model of trade. We demonstrate the usefulness of the ITPD-E by running standard gravity regressions.
Further data
| Item Type: | Article in a journal |
|---|---|
| Refereed: | Yes |
| Institutions of the University: | Faculties > Faculty of Law, Business and Economics Faculties > Faculty of Law, Business and Economics > Department of Economics Faculties > Faculty of Law, Business and Economics > Department of Economics > Chair Economics VI: Empirical Economic Research Faculties > Faculty of Law, Business and Economics > Department of Economics > Chair Economics VI: Empirical Economic Research > Chair Economics VI: Empirical Economic Research - Univ.-Prof. Dr. Mario Larch Faculties |
| Result of work at the UBT: | Yes |
| DDC Subjects: | 300 Social sciences > 330 Economics |
| Date Deposited: | 02 Jun 2022 06:33 |
| Last Modified: | 02 Jun 2022 06:33 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/69891 |