An empirical analysis of night-time light data based on the gravity model
Linyue Li,
Zhixian Sun and
Xiang Long
Applied Economics, 2019, vol. 51, issue 8, 797-814
Abstract:
This article aims to explore the feasibility of applying night-time light data to the study of trade. Based on 61 countries’ panel data from 1995 to 2012, this research used night-time light data, as the substitute for GDP, to study trade development based on the traditional gravity model. The method of ordinary least squares, Poisson pseudo-maximum-likelihood and two-stage least squares were used. The results show that geographical distance, country borders and regional agreements have a significant effect on China’s trade with other Belt and Road countries, which verifies the validity of trade research based on night-time light data analysis. Additionally, comparisons reveal the trade trends predicted by night-time light data from 1996 to 2012, were highly consistent with the actual data. This article stands as the first study to apply night-time light data to the gravity model in the research on trade between China and other Belt and Road countries. Breaking new ground, this research uses night-time light data as an economic indicator to study trade, in combination with micro foundations and the latest findings of the gravity model. Thus, this article deepens the understanding of trade analysis and contributing to the field of related researches.
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1080/00036846.2018.1523612 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:applec:v:51:y:2019:i:8:p:797-814
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20
DOI: 10.1080/00036846.2018.1523612
Access Statistics for this article
Applied Economics is currently edited by Anita Phillips
More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().