Back Matter
  • 1 https://isni.org/isni/0000000404811396, International Monetary Fund

X. References

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Appendix

Figure A1.
Figure A1.

Share of Primary and Processed Goods in Total Exports

Citation: IMF Working Papers 2017, 044; 10.5089/9781475585537.001.A999

Source: UN Comtrade Export Volume, 2013

Sub-Saharan Africa (which has the least level of LPI compared to other regions) and the resource rich Middle East and North Africa mostly export primary goods, whereas, South Asia (with slightly higher LPI than Sub-Saharan Africa) mostly exports processed goods. With an LPI level around the world average, Latin America’s export composition between primary and processed goods is relatively balanced, and the rest of the high LPI regions, including East Asia and Pacific, Europe and Central Asia, and North America export relatively less primary goods. In fact, the share of processed goods in total exports of these high LPI regions are not significantly larger either compared to other middle level LPI regions such as Middle East and North Africa, and Latin America. This indicates that these high LPI regions export relatively more in products that are at a higher level of the value chains.

Figure A2.
Figure A2.

Country-Specific Weighted Average Direct Time Sensitivity of Products by LPI

Citation: IMF Working Papers 2017, 044; 10.5089/9781475585537.001.A999

Source: Measure of direct time sensitivity of products are extracted from computations in Hummels and Schaur (2013). Weights are share of a product in the total exports of a country. The measure of heaviness is the logarithm of weight over value ratio obtained from the UN Comtrade database, 2013.

Additional Analysis on Latin America

I examine additional impacts on the trade pattern arising due to improvement in timeliness in trade for Latin America. I particularly investigate if improvement in timeliness in trade due to transportation infrastructure reforms determine comparative advantage pattern in transportation intensive goods (such as heavy and upstream goods in addition to time-sensitive goods as examined earlier in the paper), and if such a comparative advantage pattern is stronger for processed goods than for primary goods. Below, I report the regression results and the analysis for Latin America, and how they compare to the rest of the world.

As expected, Table A1 shows that countries that have higher quality of transportation infrastructure have a comparative advantage in heavy goods and upstream goods in addition to time sensitive goods (as shown earlier). The results hold for Latin American countries as well. Moreover, we see that the comparative advantage pattern in heavy goods is particularly stronger for primary goods, whereas, comparative advantage pattern in upstream goods is particularly stronger for processed goods in Latin America. This result comes from the differences in product characteristics between primary and processed goods, on average.

Table A1.

Effects of Transport Infrastructure on Trade Pattern in Heavy and Upstream Products

article image
Note: Regressions were run separately for the two types of products (Heavy and upstream). Dependent variable is 2013 aggregate export volume. These regressions control for interactions of other factor endowments and factor intensities. Also, we include exporter and product fixed effects. A positive coefficient of the variable Heavy: ln(Qi) * heavyg implies a comparative advantage in products that are heavy; whereas, a positive coefficient of Upstreamness: ln(Qi) * upstreamg implies a comparative advantage in products that are upstream. The measure of heaviness is the logarithm of weight over value ratio obtained from the UN Comtrade database, 2013. The measure of upstreamness is the number of stages a product is far from its final demand, as computed in Fally (2012). Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1.

Primary goods are relatively heavier while processed goods are relatively more integrated in the global supply chain.

Table A2.

Effect of an 8.34% Improvement in the LPI of an Average Country in LAC

article image
Figure A3.
Figure A3.

Effect of an 8.34% Improvement in the LPI of an Average Country in LAC

Citation: IMF Working Papers 2017, 044; 10.5089/9781475585537.001.A999

Policy Shock: We introduce 8.34% improvement in the quality of transportation infrastructure (LPI) of Latin America. This conservative polic shock will increase the 2016 LPI level of Latin America (2.665) to the 2016 LPI level of Middle East and North Africa (2.887), which has th next best level of infrastructure quality after Latin American region. We use the coefficients obtained in Table 3, Latin America (Column 2).
Figure A4.
Figure A4.

Correlation Between Logistics Performance Index and Other Measures of Timeliness

Citation: IMF Working Papers 2017, 044; 10.5089/9781475585537.001.A999

Note: Index on infrastructure quality and timeliness are extracted from the components of the World Bank’s Logistics Performance Index Databas (2012). We use the inverse of time to export and time to import data from the World Bank’s Doing Business Survey, 2012. This confirms thi using LPI as a proxy for transportation infrastructure quality or the ability of a country to transport goods on time in this analysis is reasonable.
Table A3.

Measure for Factor Intensities Across Product Groups

article image
Source: Direct Factor Intensities are extracted from UNCTAD Revealed Factor Intensity Indices Database (2007). Indirect Factor Intensities across products are computed using the U.S. input-output table and direct factor intensities following the procedure carried out in Nunn (2007).
1

Prepared by Suprabha Baniya, a PhD student in the Department of Economics at Purdue University (email: sbaniya@purdue.edu). This paper was prepared as a background study for the Western Hemisphere Department’s Cluster Report on Trade Integration in Latin America and the Caribbean.

2

I would like to thank my dissertation committee members at Purdue University: Dr. David Hummels, Dr. Thomas Hertel, Dr. Chong Xiang and Dr. Dominique van der Mensbrugghe for their valuable suggestions and comments.

3

I would also like to thank Dr. Michele Ruta (Lead Economist, World Bank) and Dr. Nadia Rocha (Senior Economist, World Bank) for providing me a research internship opportunity at the World Bank to apply this work to study the trade and comparative advantage impacts of the Belt and Road Initiative of China.

4

I would like to thank Dr. Valerie Cerra (Assistant Director; Western Hemisphere Department, International Monetary Fund) for supervising me on the application of this work to Latin America.

5

This work is extended to the newly developed firm-heterogeneity CGE model in GTAP (Akgul et al., 2015) to examine the effects of timeliness in trade via transportation infrastructure reform on the export participation and composition. To do this, a two-part econometric model is incorporated to establish the relations in the CGE model between timeliness in trade and technical changes that reduce the fixed cost of entering into the export market and the variable cost of exporting. The paper compares the trade implications across sectors that vary by indirect time sensitivity and across importers using a policy experiment for low income South and East Asia region. This extension is co-authored with Dr. Zeynep Akgul (Visiting Scholar, U.S. International Trade Commission).

6

See Appendix (Figure 9) for shares of primary and processed goods in total commodity exports by region in 2013 for the sample of countries and products used in this paper.

7

The summary statistics includes only those countries and products that are in the sample used in this paper. The sample contains all the available countries in UN Comtrade database (2013) and all the available products in Hummels and Schaur’s time sensitivity computation.

8

See Figure 5, 6 and 10.

Effects of Timeliness on the Trade Pattern between Primary and Processed Goods
Author: Suprabha Baniya
  • View in gallery

    Share of Primary and Processed Goods in Total Exports

  • View in gallery

    Country-Specific Weighted Average Direct Time Sensitivity of Products by LPI

  • View in gallery

    Effect of an 8.34% Improvement in the LPI of an Average Country in LAC

  • View in gallery

    Correlation Between Logistics Performance Index and Other Measures of Timeliness