Trade Facilitation and Manufactured Exports: Is Africa Different?

Iwanow, Tomasz; Kirkpatrick, Colin

doi:10.1016/j.worlddev.2008.09.014

Cited by 140 publications

(93 citation statements)

References 23 publications

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“…Iwanow and Kirkpatrick (2009) Zaki (2014) shows that the time to import (export) is equivalent to a mean ad valorem tax of 34.2% (17.6%) for developing countries. A study by Hummels and Schaur (2013) shows that each day in transit is worth 0.6%-2% of the value of the 2 Their preferred specification explains 80.8% of the variation in trade costs.…”

Section: Literaturementioning

confidence: 99%

Export Diversification Effects of the WTO Trade Facilitation Agreement

2015

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We estimate the effects of trade facilitation on export diversification, as measured by two extensive margins: the number of products exported by destination and the number of export destinations served by product. To address the issue of causality, we employ an identification strategy whereby only exports of new products, or exports to new destinations, are taken into account when computing the respective margins of trade. We find a positive impact of trade facilitation on the extensive margins of trade. The results are robust to alternative definitions of extensive margins, different sets of controls and various estimation methods. Simulation results suggest substantial extensive margin gains from trade facilitation reform in SubSaharan Africa and Latin America and the Caribbean.

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Section: Literaturementioning

confidence: 99%

Export Diversification Effects of the WTO Trade Facilitation Agreement

2015

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“…The term 'trade facilitation' has been used frequently in recent studies, although Other researchers such as Iwanow and Kirkpatrick (2009) adopt the same definition applied to manufacturers' exports from Africa, also concluding that trade facilitation reform could help to improve trade flows. More recently, Moïsé et al (2011) constructed 12 indicators for the main WTO political areas of negotiation, to estimate the impact of such interventions on the trade of a given country.…”

Section: Literature Reviewmentioning

confidence: 99%

The importance of the Logistics Performance Index in international trade

Martí¹,

Puertas²,

Garcia³

2014

Applied Economics

217

123

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Logistics and transport are becoming increasingly important in international trade relations. Logistic Performance Index (LPI) analyses the differences between countries, providing a general picture of customs procedures, logistics costs and the quality of the infrastructure necessary for overland and maritime transport. The aim of this article is to analyse the impact that each of the components that make up the LPI has on emerging countries' trade, employing a gravity model. Furthermore, the study also aims to detect possible advances in logistics in these countries, which are grouped into five regions (Africa, South America, Far East, Middle East and Eastern Europe) by comparing the first LPI data published in 2007 with the most recent data, released in 2012. The results obtained reveal that improvements in any of the components of the index cause the country to increase its volume of trade. Specifically, LPI components are becoming increasingly important for the countries in Africa, South America and Eastern Europe.

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“…Among the studies that contributed to both MRAs, the REML soundly describes the studies of Raballand (2003), Grigoriou (2007), Bandyopadhyay (1999), Carrere (2006) and Brun et al (2005). On the other hand, studies by Iwanow, Kirkpatrick (2009) Kurmanalieva, Parpiev (2008) 0.002 Brun et al (2005) 0.005 Raballand (2003) 0.023 Bandyopadhyay (1999) 0.043 Persson (2007) 0. 053 Carrere (2006) 0.058 Nordas, Piermartini (2004) 0.063 Elbadawi (1999) 0.087 Francois, Manchin (2007) 0.111 Grigoriou (2007) 0.…”

Section: Model Predictionmentioning

confidence: 99%

“…969 Bouet et al (2008) 2.013 Elbadawi et al (2006) 7.348 Granato (2008) 7.727 Raballand (2003) 0.000 Grigoriou (2007) 0.006 Bandyopadhyay (1999) 0.012 Carrere (2006) 0.012 Jansen, Nordås (2004) 0.014 Brun et al (2005) 0.016 Martinez-Zarzoso, Nowak-Lehmann (2003) 0.02 Wilson et al (2004) 0.026 Nordas, Piermartini (2004) 0.067 Kurmanalieva, Parpiev (2008) 0.116 Persson (2007) 0.118 De (2007) 0. 147 Njinkeu et al (2008) 0.149 Iwanow, Kirkpatrick (2009) 0.461 Fujimura, Edmonds (2006) 0.541 Marquez-Ramos, Martinez-Zarzoso (2005) 0.541 Lawless (2010) 0.672…”

Section: Model Predictionmentioning

confidence: 99%

Infrastructure and Trade: A Meta-Analysis

Celbiş

Nijkamp²,

Poot

2015

REGION

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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 these issues, we find that a 1 percent increase in own infrastructure increases exports by about 0.6 percent and imports by about 0.3 percent. 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.JEL classification: F10, H54, R53, C10, F1, R4

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Trade Facilitation and Manufactured Exports: Is Africa Different?

Cited by 140 publications

References 23 publications

Export Diversification Effects of the WTO Trade Facilitation Agreement

Export Diversification Effects of the WTO Trade Facilitation Agreement

The importance of the Logistics Performance Index in international trade

Infrastructure and Trade: A Meta-Analysis

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