Template-type: ReDIF-Paper 1.0
Author-Name: Celbis, Mehmet Güney
Author-Email: celbis@merit.unu.edu
Author-Workplace-Name: UNU-MERIT / MGSoG, Maastricht University 
Author-Name: Nijkamp, Peter
Author-Email: p.nijkamp@vu.nl
Author-Workplace-Name: Vrije Universiteit Amsterdam
Author-Name: Poot, Jacques
Author-Email: jpoot@waikato.ac.nz
Author-Workplace-Name: University of Waikato 
Title: How big is the impact of infrastructure on trade? Evidence from meta-analysis
Abstract: Low levels of infrastructure quality and quantity can create trade 
	 impediments through increased transport costs. Since the late 1990s an 
	 increasing number of trade studies have taken infrastructure into 
	 account. The purpose of the present paper is to quantify the importance 
	 of infrastructure for trade by means of meta-analysis and 
	 meta-regression techniques that synthesize various studies. The type of 
	 infrastructure that we focus on is mainly public infrastructure in 
	 transportation and communication. We examine the impact of 
	 infrastructure on trade by means of estimates obtained from 36 primary 
	 studies that yielded 542 infrastructure elasticities of trade. We 
	 explicitly take into account that infrastructure can be measured in 
	 various ways and that its impact depends on the location of the 
	 infrastructure. We estimate several meta-regression models that control 
	 for observed heterogeneity in terms of variation across different 
	 methodologies, infrastructure types, geographical areas and their 
	 economic features, model specifications, and publication 
	 characteristics. Additionally, random effects account for between-study 
	 unspecified heterogeneity, while publication bias is explicitly 
	 addressed by means of the Hedges model. After controlling for all these 
	 issues we find that a 1 per cent increase in own infrastructure 
	 increases exports by about 0.6 per cent and imports by about 0.3 per 
	 cent. Such elasticities are generally larger for developing countries, 
	 land infrastructure, IV or panel data estimation, and macro-level 
	 analyses. They also depend on the inclusion or exclusion of various 
	 common covariates in trade regressions 
Classification-JEL: O18, F10, H54, R53, C10, F19, R49
Keywords: Infrastructure, Trade, Transportation, Communication, Public Capital,
	 Public Goods, Meta-Analysis
Series: UNU-MERIT Working Papers
Creation-Date: 2013
Number: 032
File-URL: http://www.merit.unu.edu/publications/wppdf/2013/wp2013-032.pdf
File-Format: application/pdf
File-Size: 275 Kb
Handle: RePEc:unm:unumer:2013032