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Federal Reserve Bank of Chicago Trade Structure, Industrial Structure, and International Business Cycles Marianne Baxter and Michael A. Kouparitsas WP 2002-30 Trade Structure, Industrial Structure, and International Business Cycles Marianne Baxter* Boston University and NBER and Michael A. Kouparitsas Federal Reserve Bank of Chicago ABSTRACT This paper examines the extent to which the composition of a count ry’s production and trade differs among its trade partners. For example, does the US export the same bundle of goods to the UK as it does to Japan? If we find high dispersion in a country’s export and import bundles with its various trading partners, can this be linked to identifiable country characteristics? These findings are important for two reasons. First, they enrich our empirical understanding of the nature of trade. Second, they will stand as a guide for further development of economic theories of the international transmission of business cycles. 1. Introduction A widely held belief, among economists and policymakers alike, is that countries that are linked through international trade will also share business cycle fluctuations. For this reason, countries proceed slowly and carefully to adopt new arrangements (regional trading arrangements, for example) that are designed to increase trade with a particular group of countries. It is therefore surprising that we lack strong empirical evidence that increased trade, by itself, also increases the extent of business-cycle linkages.1 This paper takes a first step on a new line of research that is designed to evaluate the circumstances under which trading relationships between two countries will lead their business cycles to become more synchronized.2 Our starting point is the observation that most countries have several, even many, trading partners, and that the basket of goods traded with one country may be different from the basket traded with another country. Thus, we use a highly disaggregated dataset that includes information on the industrial structure of each country, as well as detailed information on the industry composition of trade. Our dataset includes information on manufacturing goods, which have been the focus of some past studies, but also includes data on non- manufacturing industries. In this paper, we examine the extent to which the composition of a country’s production and trade differs among its trade partners. For example, does the US export the same bundle of goods to the UK as it does to Japan? If we find high dispersion in a country’s export and import bundles with its various trading partners, can this be linked to identifiable country characteristics? These findings will be important for two reasons. First, they enrich our empirical understanding of the nature of trade. Second, they will stand as a guide for further development of economic theories of the international transmission of business cycles. 2. A Snapshot of the Relationship between Production and Trade This paper analyzes the trade flows and production structure of 164 countries. These data come from a number of sources. Trade flows are based on 4-digit standard international trade classification (SITC) data described in Robert Feenstra, et al. (2002). The data are converted to 2-digit standard industry classification (SIC) so that they can be more easily compared to industry data. Production data come from two sources. Disaggregated manufacturing data are from the United Nations Industrial Development Organization (UNIDO) reported at the 4-digit international standard industry classification (ISIC) and converted to 2-digit SIC level for comparison with trade data. Non- manufacturing trade data were supplied by Werner Antweiler and Daniel Trefler; these data were used in Antweiler and Trefler (2002). These are also reported at the 4-digit ISIC level. A country’s land endowment is measured as the quantity of arable land per capita from the World Bank’s World Development Indicators. Educational attainment is measured using Robert Barro and Jong-Wha Lee’s (1993) average years of schooling in the total population over the age of 15. Real per capita income data are from the Penn World Tables version 5.6. Each country’s capital endowment is measured as capital stock per worker from William Easterly and Ross Levine (2001). We use the International Monetary Fund’s International Financial Statistics Yearbook (2002) to classify countries as either developing or developed. We classify a country as being either a commodity, fuel, or manufactured-goods exporter according to which category has the largest net export share. To begin, we examine the dispersion in a country’s production and trade structure. To do this, we develop indexes of dispersion that are variants of a Herfindahl index. To measure country i’s dispersion from the rest of world (ROW) with respect to its production structure, we construct the dispersion index: dyi country i’s output, and syr o w,n = 2 = ∑ ( syin − syr o w, n ) where syin is sector n’s share of N row n =1 N y ÷ y ∑∑ jn where yjn is output of sector n in ∑ jn j ≠i n =1 j ≠i country j. We also want to study the relationship between production dispersion vis-a-vis the rest of the world, and production dispersion vis-a-vis a country’s trading partners. Thus, we define indexes that capture the extent to which country i’s production structure differs from its export partners and from its import partners. Letting α xij denote the share of total exports of country i that go to country j, and continuing to let n index a particular export good, our measure of country i’s dispersion in production relative to her export partners, weighted by export share, is dyi = ∑ α xij ∑ ( syin − sy jn ) . Our measure of country i’s dispersion in production relative to export J N j =1 n =1 2 her import partners, weighted by import shares, α mij , is dyi import = ∑ α mij ∑ ( syin − sy jn ) , where J N j =1 n =1 2 α mij now stands for denote the share of total imports of country i that come from country j. Finally, we construct indexes of dispersion in exports and imports to measure the extent of dispersion in the structure of a country’s exports to its various export partners. As for the production dispersion indexes, we weight each export partner by its contribution to country i’s total imports. Thus, our weighted index of export dispersion for country i is dxi = ∑ α xij ∑ ( sxin − sxijn ) , where sx in is good n’s share of country i’s exports, and sx ijn is J N j =1 n =1 2 good n’s share of country i’s exports to country j. We construct a similar measure the importshare-weighted dispersion of country i’s imports from its import partners, j, as dmi = ∑ α mij ∑ ( smin − smijn ) where sm in is sector n’s share of country i’s imports, and sm ijn is J N j =1 n =1 2 good n’s share of country i’s imports from country j. These dispersio n measures are shown in Table 1. However, given the large number of countries, we find that graphs are the best way to understand the relationships between the various measures and we will focus our discussions on the graphs. Table 1 can be used as a reference to identify particular countries on the graphs. The relationships among dispersion in production, exports, and imports are shown in Figure 1.3 Figure 1-A plots a scatter of dyirow (x-axis) vs. dxi where each data point is a particular country, i. This figure allows us to address two questions. First, how much does production dispersion differ among different types of countries? Second, how is dispersion in production vs. export partners related to production dispersion vs. the rest of the world? We find that developed countries (the squares) have low dispersion indexes for both output and exports, and that this does not seem to depend importantly on the developed country’s primary net export good. Further, the developed countries tend to be similar both to the rest of the world and to their export partners. Developing countries (the triangles) generally display greater dispersion in production compared both with the rest of the world and with their export partners. Within the group of developing countries, manufactured-goods-exporters have lower dispersion, while commodity and fuel exporters exhibit higher dispersion. Strikingly, every single country is more dissimilar in terms of production structure from their export partners than they are from the ROW. This may be interpreted as reflecting the “trade based on comparative advantage” that is central to traditional trade theory. We note that the gap between “ROW” and export partners wid ens as production dissimilarity widens, and is especially large for developing countries. Figure 1-B examines the same questions for import partners. The results are very similar to those for export partners. Industrialized countries show much less dissimilarity from the rest of the world and from their import partners. Developing countries have high dispersion measures, both vs. the rest of the world and for import partners. There are only two countries for which import dissimilarity is less than rest-of-world production dissimilarity: these are Malawi and Bangladesh. Again, these findings seem consistent with a generalized theory of trade based on comparative advantage. We also compared production dispersion relative to export partners and import partners; see Figure 1-C. For the industrialized-country commodity exporters, production dispersion relative to export partners is substantially higher than production dispersion relative to import partners. In fact, the positive association between dissimilarity from export partners and dissimilarity from import partners does not appear for these countries. Rather, dispersion relative to import partners is uniformly low for all these countries. For all other groups of countries, there was little difference in production dissimilarity between export and import partners. We now turn to a closer look at our measure of trade dispersion, which measures the extent to which a country’s trade baskets differ among her trading partners. To begin, Figure 2A examines the relationship between export dispersion and the production dispersion with export partners. For each country, the horizontal axis plots “export dispersion” -- the extent to which a country exports different baskets of goods to her export partners. The vertical axis measures dispersion of a country’s production vs. her trading partners. High dispersion means that a country’s production structure is very different from that of her export partners. Figure 2-B presents similar information for import dispersion and production dispersion vs. import partners. Figure 2-A illustrates that there is no link between export dispersion and production dispersion. While industrialized countries (squares) tend to have lower production and export dispersion than developing countries, the general impression from this figure is that one can infer little about dispersion in export baskets just from looking at differences in production structures. Turning to imports, Figure 2-B shows us that there is no obvious relationship between import dispersion and production dispersion vis-a-vis import partners. Again, these findings suggest that looking at production data for trading partners will tell us little or nothing about the bilateral composition of trade. 3. Factor Endowments, Country Characteristics and Trade Dispersion Traditional trade theory suggests a strong link between factor endowments, production, and trade. Dispersion in export bundles from one country to its trading partners would be understood as stemming from dispersion in factor endowments among the country’s trading partners. Similarly, dispersion in import bundles would be due to dispersion in factor endowments among the country’s import partners. The factors we consider are the following: (i) arable land per capita; (ii) capital stock per worker; and (iii) average years of schooling for the population aged 15 and older. In each case, dispersion on the export side is measured as the squared difference between country i’s endowment of a factor and the endowment of its export partners, where the contribution of each partner is weighted by that partner’s share in country i’s total exports. A similar measure is constructed for factor dispersion vs.import partners. Table 2, columns 2 and 3, presents correlations between factor dispersion and trade dispersion. Considering all countries in the world together, there is no strong evidence that land dispersion is important either for exports or for imports. The other two measures of factor inputs, capital and education, are positively related to trade dispersion, most strongly on the export side. The results are different when we consider just the G-7. For G-7 exports, the relationship between land and exports is strongly positive, while there is a negative relationship between capital and trade and for educatio n and trade. For G-7 imports, we find that each of land, capital, and education dispersion is strongly positively correlated with import dispersion. For all countries taken together however, the correlations are much weaker. The strongest correlation is for education dispersion. The last three columns of Table 2 show how factor dispersion relates to trade dispersion when we stratify by type of exporter. There is little consistency in these correlations across exporter type. The strongest correlations are again for education, which is positive for all export categories and for both exports and imports. Capital dispersion is also positively related to trade dispersion for fuel and manufacturing exporters. Land dispersion appears unrelated to trade dispersion for each exporter type. Because dispersion in the factors may be correlated, we regressed export dispersion on dispersion in land, capital, and education. We also included dummy variables for (a) whether a country is classified as ‘developing,’ and (b) the country’s major export good. The results are shown in Table 3. First, the developing-country dummy variable is positive and strongly significant in all specifications and for both exports and imports. We checked to see whether this was simply a proxy for “country size” – we found that including a measure of real GDP in the regressiondid not change the significance of the developing-country dummy variable. We also found that commodity exporters have significantly larger export dispersion, while fuel exporters have significantly smaller import dispersion. The factor dispersion measures were mostly insignificant. The one exception is the measure of education dispersion, which appears positively correlated with export dispersion in specifications 3 and 4. Finally, we note that the explanatory power of the regressions is higher for exports than for imports. In specification 4, the regression explains 37% of export dispersion and 21% of import dispersion. 4. Summary and Conclusion This paper analyze the extent to which the composition of a country’s production and trade differs among its trade partners. We found that industrialized countries have low dispersion for both output and trade. That is: an industrialized country’s production structure tends to be similar to that of the rest of the world, and her export and import baskets are similar among all trading partners. Developing countries, by contrast, show high dispersion in production and trade. When we studied the relationship between export dispersion and the production dispersion (vs. export partners), we failed to find a strong link. Looking at production structures is not sufficient to understand the structure of trade. Finally, we investigated whether dispersion in export and import bundles can be related to dispersion in the factor endowments of trading partners. We found weak evidence tha t capital and especially education dispersion may help explain trade dispersion. However, the most important determinants of trade dispersion were developing-country status and the major type of export good. References Antweiler, W. and D. Trefler. “Increasing returns and all that: A view from trade” American Economic Review, March 2002, 92(1), pp. 93-119. Barro, R.J. and J.W.Lee. “International comparison of educational attainment,.” Journal of Monetary Economics, December 1993, 32(3), pp. 363-394. Canova, Fabio and Harris Dellas. “Trade interdependence and the international business cycle.” Journal of International Economics, February 1993, 34(1-2), pp. 23-47. Easterly, W. and R. Levine. “It’s Not Factor Accumulation: Stylized Facts of Growth Models.” World Bank Economic Review, 2001, 15(2), pp. 177-219. Feenstra, R.C., J. Romalis and P. Schott. “US Imports, Exports, and Tariff Data, 1989-2001.” National Bureau of Economic Research Working Paper 9387, December 2002. Hummels, David, Jun Ishii and Kei-Mu Yi. “The Nature and Growth of Vertical Specialization in World Trade.” Journal of International Economics, June 2001, 54(1), pp. 75-96. Imbs, Jean. “Comovement.” Mimeo, London Business School, 1999. International Monetary Fund. International Financial Statistics Yearbook. 2002. Kose, A., E. Prasad and M. Terrones. “Globalization and Business Cycle Comovement.” Mimeo, International Monetary Fund, 2002. Schott, P.K. “Across-Product versus Within-Product Specialization in International Trade.” Mimeo, Yale School of Management, 2002. Footnotes * Marianne Baxter, Boston University, 270 Bay State Rd., Boston MA 02215; Michael A. Kouparitsas, Federal Reserve Bank of Chicago, 230 LaSalle Street, Chicago, IL 60604. We are grateful to Kei-Mu Yi for his insightful comments on our paper. All errors are our own. The views expressed herein are those of the authors and not necessarily those of the Federal Reserve Bank of Chicago or the Federal Reserve System. 1. This is a large and growing literature. The first paper in this literature was by Fabio Canova and Harris Dellas (1993), who found no link. More recently, Jean Imbs (1999) finds that cyclic comovement is explainable by production structure but not trade. A recent review is found in Ayhan Kose, et al., (2002). 2. Our paper shares a micro-trade focus with several related recent contributions, including those by Werner Antweiler and Daniel Trefler (2002), David Hummels, et al. (2001), and Peter Schott (2002). Table 1: Country Characteristics and Measures of Dispersion Production Dispersion vs: Country Name USA GERMANY JAPAN UNITED-KINGDOM FRANCE ITALY CANADA CHINA NETHERLANDS HONG-KONG BELGIUM-LUX SINGAPORE SPAIN KOREA-RP MEXICO TAIWAN SWITZERLAND AUSTRIA SWEDEN THAILAND AUSTRALIA MALAYSIA USSR SAUDI-ARABIA TURKEY INDONESIA BRAZIL DENMARK NORWAY PORTUGAL IRELAND ISRAEL ARGENTINA FINLAND PHILIPPINES UNTD-ARAB-EM GREECE SOUTH-AFRICA INDIA POLAND YUGOSLAVIA VENEZUELA HUNGARY IRAN Largest Net Export Good:1 M M M M M M C F C M M F M M F M M M M C C F F F C F M C F M M C C M C F C C M C M F C F Developing Rest of country world 0.006 0.017 0.014 0.008 0.003 Export partners (weighted) 0.050 0.071 0.065 0.059 0.066 0.007 0.017 0.014 0.073 0.157 0.055 0.008 0.012 0.025 0.072 0.113 0.210 0.142 0.103 0.062 0.041 0.009 0.007 0.469 0.015 0.061 0.036 0.041 0.557 0.073 0.117 0.120 0.143 0.020 0.021 0.034 0.649 0.053 0.159 0.187 0.112 0.047 0.061 0.725 0.071 0.429 0.026 0.081 0.494 0.055 0.120 0.127 0.014 0.207 0.172 0.062 0.249 0.055 0.085 X X X X X X X X X X X X X X X X X X X X X X X X Export Dispersion Import vs. Export partners Partners (weighted) (weighted) 0.049 0.026 0.071 0.016 0.071 0.038 0.050 0.024 0.056 0.016 0.024 0.020 0.045 0.039 0.067 0.016 0.107 0.053 0.202 0.042 0.118 0.077 0.069 0.034 0.042 0.054 0.038 0.078 0.031 0.042 0.035 0.024 0.041 0.036 0.556 0.085 0.051 0.106 0.113 0.098 0.089 0.040 0.160 0.114 0.186 0.097 0.092 0.081 0.052 0.048 0.055 0.083 0.728 0.044 0.068 0.044 0.127 0.502 0.100 0.059 0.057 0.121 0.081 0.046 0.178 0.095 0.047 0.108 0.254 0.123 0.085 0.072 0.076 0.071 0.060 0.030 Import Dispersion vs. Import Partners (weighted) 0.124 0.083 0.168 0.086 0.092 0.101 0.050 0.088 0.090 0.066 0.085 0.117 0.117 0.124 0.038 0.055 0.051 0.057 0.067 0.130 0.071 0.071 0.124 0.116 0.188 0.113 0.229 0.078 0.109 0.110 0.046 0.164 0.121 0.078 0.189 0.088 0.113 0.039 0.248 0.140 0.129 0.078 0.088 0.132 Production Dispersion vs: Country Name CZECHOSLOVAKIA CHILE PANAMA COLOMBIA PAKISTAN EGYPT NEW-ZEALAND MOROCCO ALGERIA ROMANIA NIGERIA TUNISIA KUWAIT LIBERIA LIBYA PERU VIETNAM DOMINICAN-RP OMAN JORDAN NETH-ANTILLES LEBANON CYPRUS SYRIA GUADELOUPE ECUADOR BANGLADESH URUGUAY BAHAMAS COSTA-RICA SRI-LANKA MALTA PARAGUAY GUATEMALA BULGARIA BRUNEI BAHRAIN JAMAICA REUNION YEMEN FRENCH-GUIANA EL-SALVADOR BOLIVIA HONDURAS TRINIDAD-TBG CUBA Largest Net Export Good:1 M C C F M F C C F M F F F C F C C M F C F C C F C F C C C C M M C C C F F C C F C M C C F C Developing Rest of country world X X 0.064 X 0.122 X 0.076 X 0.154 X 0.130 0.077 X 0.073 X X X 0.498 X 0.328 X X X X 0.080 X X 0.285 X X X X X X 0.311 X X 0.098 X 0.350 X 0.064 X X 0.097 X 0.184 X X X 0.333 X X X X 0.057 X X X X 0.416 X 0.200 X 0.170 X X Export partners (weighted) 0.115 0.161 0.104 0.201 0.161 0.130 0.101 0.513 0.415 0.107 0.362 0.377 0.113 0.382 0.161 0.146 0.226 0.336 0.105 0.377 0.288 0.224 Export Dispersion Import vs. Export partners Partners (weighted) (weighted) 0.057 0.132 0.124 0.166 0.222 0.103 0.163 0.191 0.180 0.163 0.190 0.112 0.114 0.102 0.192 0.048 0.142 0.541 0.022 0.413 0.204 0.116 0.390 0.048 0.133 0.177 0.270 0.346 0.074 0.020 0.214 0.144 0.234 0.160 0.352 0.232 0.066 0.123 0.147 0.336 0.200 0.166 0.145 0.325 0.125 0.111 0.219 0.312 0.189 0.256 0.381 0.138 0.138 0.041 0.171 0.105 0.138 0.097 0.071 0.164 0.445 0.170 0.246 0.426 0.191 0.166 0.208 0.282 Import Dispersion vs. Import Partners (weighted) 0.107 0.144 0.340 0.085 0.247 0.136 0.104 0.182 0.101 0.192 0.081 0.120 0.121 0.133 0.086 0.148 0.111 0.134 0.121 0.214 0.250 0.139 0.147 0.158 0.102 0.107 0.240 0.164 0.256 0.104 0.246 0.140 0.159 0.123 0.203 0.207 0.167 0.136 0.107 0.230 0.119 0.103 0.097 0.144 0.137 0.192 Production Dispersion vs: Country Name ZIMBABWE QATAR GHANA NEW-CALEDONIA COTE-D'IVOIRE ICELAND ST-KITTS-NEV KENYA KOREA-D-P-RP MYANMAR BERMUDA MAURITIUS SENEGAL ZAMBIA TANZANIA ANGOLA ETHIOPIA CAMBODIA CAMEROON GABON MOZAMBIQUE GIBRALTAR PAPUA-N-GUINEA SUDAN BENIN BARBADOS SURINAME CONGO CAYMAN-ISLDS ALBANIA ZAIRE GUINEA IRAQ NICARAGUA MAURITANIA NEPAL MADAGASCAR TOGO GUYANA MALAWI FIJI HAITI GREENLAND AFGHANISTAN MALI BELIZE Largest Net Export Good:1 C F M C C C C C C C M C C C C F C C F F C M C C F C F F C C F C F C C M C C C C C M C C C C Developing Rest of country world X 0.062 X X 0.300 X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X Export partners (weighted) 0.104 0.395 0.196 0.221 0.407 0.424 0.442 0.517 0.178 0.195 0.425 0.535 0.074 0.298 0.097 0.361 0.262 0.368 0.263 0.242 0.304 0.286 Export Dispersion Import vs. Export partners Partners (weighted) (weighted) 0.103 0.175 0.096 0.326 0.230 0.123 0.180 0.096 0.316 0.212 0.138 0.181 0.107 0.241 0.196 0.229 0.282 0.050 0.244 0.082 0.484 0.167 0.279 0.207 0.105 0.094 0.341 0.258 0.525 0.167 0.255 0.283 0.102 0.244 0.371 0.172 0.191 0.289 0.165 0.164 0.129 0.025 0.296 0.264 0.120 0.359 0.190 0.376 0.336 0.162 0.108 0.296 0.271 0.069 0.001 0.398 0.217 0.219 Import Dispersion vs. Import Partners (weighted) 0.109 0.156 0.115 0.129 0.096 0.128 0.145 0.198 0.144 0.150 0.247 0.171 0.178 0.122 0.140 0.113 0.195 0.324 0.104 0.091 0.211 0.320 0.113 0.221 0.219 0.120 0.186 0.133 0.212 0.138 0.082 0.105 0.146 0.257 0.196 0.214 0.247 0.194 0.216 0.198 0.125 0.152 0.080 0.225 0.102 0.102 Production Dispersion vs: Country Name LAOS-P-DEM-R DJIBOUTI GAMBIA NIGER UGANDA BURKINA-FASO SEYCHELLES GUINEA-BISSAU KIRIBATI MONGOLIA SIERRA-LEONE MALDIVES RWANDA SOMALIA COMOROS BURUNDI CHAD CENTRAL-AFR-REP SOLOMON-ISLDS EQ-GUINEA ST-PIERRE-MIQU TURKS-CAICOS-ISL ST-HELENA FALKLAND-ISL BHUTAN WESTERN-SAHARA BR-IND-OC-TR GERMAN-DM-RP AVERAGE: G-7 AVERAGE: NON-G7 AVERAGE WORLD Largest Net Export Good:1 C C C M C C C C C C C C C C M C C C C M C C C C C C M F Developing Rest of country world X X X X X X X X X X X X X X X X X X X X X X X X X X X X 0.009 0.170 0.155 Export partners (weighted) 0.055 0.218 0.203 Export Dispersion Import vs. Export partners Partners (weighted) (weighted) 0.107 0.167 0.400 0.048 0.094 0.210 0.345 0.325 0.179 0.200 0.349 0.218 0.145 0.130 0.221 0.114 0.103 0.378 0.289 0.071 0.044 0.289 0.242 0.227 0.191 0.090 0.358 0.080 0.053 0.027 0.209 0.157 0.195 0.152 Notes: 1. Largest Net Export Good: M=manufactured goods, C=Commodities, F=Fuels. Import Dispersion vs. Import Partners (weighted) 0.090 0.224 0.143 0.094 0.096 0.110 0.201 0.132 0.082 0.132 0.109 0.110 0.080 0.200 0.092 0.086 0.110 0.133 0.101 0.166 0.095 0.060 0.178 0.242 0.146 0.190 0.182 0.157 0.101 0.142 0.141 Table 2: Correlations between trade and factors Correlation A. Export Dispersion with dispersion in export All Commodity Fuel Manufacturin G-7 partners' : countries exporters exporters g Exporters Land -0.09 0.41 0.06 -0.08 -0.08 Capital 0.25 -0.21 0.10 0.26 0.70 Education 0.35 -0.34 0.40 0.17 0.13 Correlation B. Import Dispersion with dispersion in import All Commodity Fuel Manufacturin partners' : countries G-7 exporters exporters g Exporters Land -0.06 0.80 -0.05 0.03 -0.19 Capital 0.09 0.51 -0.02 0.48 0.18 Education 0.19 0.61 0.12 0.63 0.14 Note: all data for 1990. Table 3 A. dependent variable = weighted export dispersion, 1990 Specification Independent variable developing country commodity exporter fuel exporter Land dispersion capital dispersion education dispersion adjusted R2 1 0.11 ** -0.06 ** -0.22 ** -3.31e-07 2 0.10 ** 0.06 ** -0.01 3 0.09 ** 0.07 ** 0.00 1.35E-06 0.34 0.32 1.53e-04 * 0.35 4 0.09 ** 0.04 * -0.00 -4.29E-07 1.45E-06 2.16e-04 * 0.37 B. dependent variable = weighted import dispersion, 1990 Specification Independent variable developing country commodity exporter Fuel exporter land dispersion capital dispersion education dispersion adjusted R2 1 0.06 ** -0.00 -0.04 ** -1.68e-07 2 0.06 ** 0.01 -0.03 * 3 0.06 ** -0.00 -0.03 ** -7.80e-07 0.18 0.17 2.46e-06 0.19 Notes: 1. Coefficient estimates provided in table. 2. The symbol * denotes significance at 10% level 3. The symbol ** denotes significance at 5% level 4 0.06 ** -0.00 -0.04 ** -2.08e-07 -3.13e-06 9.18e-05 0.21 Prod'n. dispersion-Export partners Figure 1-A: Production dispersion: Rest of World vs. Export partners 0.50 0.40 0.30 0.20 Ind-Comm Ind-Fuel Ind-Man 0.10 0.00 0.00 0.10 0.20 0.30 Dev-Comm Dev-Fuel Dev-Man 0.40 Production dispersion-ROW 0.50 Prod'n. dispersion-Import partners Figure 1-B. Production dispersion: Rest of World vs. Import partners 0.50 0.40 0.30 0.20 Ind-Comm Ind-Fuel Ind-Man 0.10 0.00 0.00 0.10 0.20 0.30 0.40 Production dispersion-ROW Dev-Comm Dev-Fuel Dev-Man 0.50 Figure 1C. Production dissimilarity: Export partners vs.Import partners Production dissimilarity-Import partners 0.60 0.50 Ind-Comm Dev-Comm Ind-Fuel Ind-Man Dev-Fuel Dev-Man 0.40 0.30 0.20 0.10 0.00 0.00 0.10 0.20 0.30 0.40 0.50 Production dissimilarity-Export partners 0.60 Figure 2-A: Export dispersion vs. Production dispersion Production dispersion-Export partners 0.60 0.50 0.40 0.30 Ind-Comm Dev-Comm Ind-Fuel Dev-Fuel Ind-Man Dev-Man 0.20 0.10 0.00 0.00 0.10 0.20 0.30 Export dispersion 0.40 0.50 0.60 Figure 2-B: Import dispersion vs. Production dispersion Production dispersion-Import partners 0.60 0.50 0.40 0.30 Ind-Comm Dev-Comm 0.20 Ind-Fuel Dev-Fuel Ind-Man Dev-Man 0.10 0.00 0.00 0.10 0.20 0.30 Import dispersion 0.40 0.50 0.60 Working Paper Series A series of research studies on regional economic issues relating to the Seventh Federal Reserve District, and on financial and economic topics. 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Ruilin Zhou WP-99-15 A Theory of Merchant Credit Card Acceptance Sujit Chakravorti and Ted To WP-99-16 1 Working Paper Series (continued) Who’s Minding the Store? Motivating and Monitoring Hired Managers at Small, Closely Held Firms: The Case of Commercial Banks Robert DeYoung, Kenneth Spong and Richard J. Sullivan WP-99-17 Assessing the Effects of Fiscal Shocks Craig Burnside, Martin Eichenbaum and Jonas D.M. Fisher WP-99-18 Fiscal Shocks in an Efficiency Wage Model Craig Burnside, Martin Eichenbaum and Jonas D.M. Fisher WP-99-19 Thoughts on Financial Derivatives, Systematic Risk, and Central Banking: A Review of Some Recent Developments William C. Hunter and David Marshall WP-99-20 Testing the Stability of Implied Probability Density Functions Robert R. Bliss and Nikolaos Panigirtzoglou WP-99-21 Is There Evidence of the New Economy in the Data? Michael A. Kouparitsas WP-99-22 A Note on the Benefits of Homeownership Daniel Aaronson WP-99-23 The Earned Income Credit and Durable Goods Purchases Lisa Barrow and Leslie McGranahan WP-99-24 Globalization of Financial Institutions: Evidence from Cross-Border Banking Performance Allen N. Berger, Robert DeYoung, Hesna Genay and Gregory F. Udell WP-99-25 Intrinsic Bubbles: The Case of Stock Prices A Comment Lucy F. Ackert and William C. Hunter WP-99-26 Deregulation and Efficiency: The Case of Private Korean Banks Jonathan Hao, William C. Hunter and Won Keun Yang WP-99-27 Measures of Program Performance and the Training Choices of Displaced Workers Louis Jacobson, Robert LaLonde and Daniel Sullivan WP-99-28 The Value of Relationships Between Small Firms and Their Lenders Paula R. Worthington WP-99-29 Worker Insecurity and Aggregate Wage Growth Daniel Aaronson and Daniel G. Sullivan WP-99-30 Does The Japanese Stock Market Price Bank Risk? Evidence from Financial Firm Failures Elijah Brewer III, Hesna Genay, William Curt Hunter and George G. Kaufman WP-99-31 Bank Competition and Regulatory Reform: The Case of the Italian Banking Industry Paolo Angelini and Nicola Cetorelli WP-99-32 2 Working Paper Series (continued) Dynamic Monetary Equilibrium in a Random-Matching Economy Edward J. Green and Ruilin Zhou WP-00-1 The Effects of Health, Wealth, and Wages on Labor Supply and Retirement Behavior Eric French WP-00-2 Market Discipline in the Governance of U.S. Bank Holding Companies: Monitoring vs. Influencing Robert R. Bliss and Mark J. Flannery WP-00-3 Using Market Valuation to Assess the Importance and Efficiency of Public School Spending Lisa Barrow and Cecilia Elena Rouse Employment Flows, Capital Mobility, and Policy Analysis Marcelo Veracierto Does the Community Reinvestment Act Influence Lending? An Analysis of Changes in Bank Low-Income Mortgage Activity Drew Dahl, Douglas D. Evanoff and Michael F. Spivey WP-00-4 WP-00-5 WP-00-6 Subordinated Debt and Bank Capital Reform Douglas D. Evanoff and Larry D. Wall WP-00-7 The Labor Supply Response To (Mismeasured But) Predictable Wage Changes Eric French WP-00-8 For How Long Are Newly Chartered Banks Financially Fragile? Robert DeYoung WP-00-9 Bank Capital Regulation With and Without State-Contingent Penalties David A. Marshall and Edward S. Prescott WP-00-10 Why Is Productivity Procyclical? Why Do We Care? Susanto Basu and John Fernald WP-00-11 Oligopoly Banking and Capital Accumulation Nicola Cetorelli and Pietro F. Peretto WP-00-12 Puzzles in the Chinese Stock Market John Fernald and John H. Rogers WP-00-13 The Effects of Geographic Expansion on Bank Efficiency Allen N. Berger and Robert DeYoung WP-00-14 Idiosyncratic Risk and Aggregate Employment Dynamics Jeffrey R. Campbell and Jonas D.M. Fisher WP-00-15 Post-Resolution Treatment of Depositors at Failed Banks: Implications for the Severity of Banking Crises, Systemic Risk, and Too-Big-To-Fail George G. Kaufman and Steven A. Seelig WP-00-16 3 Working Paper Series (continued) The Double Play: Simultaneous Speculative Attacks on Currency and Equity Markets Sujit Chakravorti and Subir Lall WP-00-17 Capital Requirements and Competition in the Banking Industry Peter J.G. Vlaar WP-00-18 Financial-Intermediation Regime and Efficiency in a Boyd-Prescott Economy Yeong-Yuh Chiang and Edward J. Green WP-00-19 How Do Retail Prices React to Minimum Wage Increases? James M. MacDonald and Daniel Aaronson WP-00-20 Financial Signal Processing: A Self Calibrating Model Robert J. Elliott, William C. Hunter and Barbara M. Jamieson WP-00-21 An Empirical Examination of the Price-Dividend Relation with Dividend Management Lucy F. Ackert and William C. Hunter WP-00-22 Savings of Young Parents Annamaria Lusardi, Ricardo Cossa, and Erin L. Krupka WP-00-23 The Pitfalls in Inferring Risk from Financial Market Data Robert R. Bliss WP-00-24 What Can Account for Fluctuations in the Terms of Trade? Marianne Baxter and Michael A. Kouparitsas WP-00-25 Data Revisions and the Identification of Monetary Policy Shocks Dean Croushore and Charles L. Evans WP-00-26 Recent Evidence on the Relationship Between Unemployment and Wage Growth Daniel Aaronson and Daniel Sullivan WP-00-27 Supplier Relationships and Small Business Use of Trade Credit Daniel Aaronson, Raphael Bostic, Paul Huck and Robert Townsend WP-00-28 What are the Short-Run Effects of Increasing Labor Market Flexibility? Marcelo Veracierto WP-00-29 Equilibrium Lending Mechanism and Aggregate Activity Cheng Wang and Ruilin Zhou WP-00-30 Impact of Independent Directors and the Regulatory Environment on Bank Merger Prices: Evidence from Takeover Activity in the 1990s Elijah Brewer III, William E. Jackson III, and Julapa A. Jagtiani WP-00-31 Does Bank Concentration Lead to Concentration in Industrial Sectors? Nicola Cetorelli WP-01-01 On the Fiscal Implications of Twin Crises Craig Burnside, Martin Eichenbaum and Sergio Rebelo WP-01-02 4 Working Paper Series (continued) Sub-Debt Yield Spreads as Bank Risk Measures Douglas D. Evanoff and Larry D. Wall WP-01-03 Productivity Growth in the 1990s: Technology, Utilization, or Adjustment? Susanto Basu, John G. Fernald and Matthew D. Shapiro WP-01-04 Do Regulators Search for the Quiet Life? The Relationship Between Regulators and The Regulated in Banking Richard J. Rosen Learning-by-Doing, Scale Efficiencies, and Financial Performance at Internet-Only Banks Robert DeYoung The Role of Real Wages, Productivity, and Fiscal Policy in Germany’s Great Depression 1928-37 Jonas D. M. Fisher and Andreas Hornstein WP-01-05 WP-01-06 WP-01-07 Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy Lawrence J. Christiano, Martin Eichenbaum and Charles L. Evans WP-01-08 Outsourcing Business Service and the Scope of Local Markets Yukako Ono WP-01-09 The Effect of Market Size Structure on Competition: The Case of Small Business Lending Allen N. Berger, Richard J. Rosen and Gregory F. Udell WP-01-10 Deregulation, the Internet, and the Competitive Viability of Large Banks and Community Banks WP-01-11 Robert DeYoung and William C. Hunter Price Ceilings as Focal Points for Tacit Collusion: Evidence from Credit Cards Christopher R. Knittel and Victor Stango WP-01-12 Gaps and Triangles Bernardino Adão, Isabel Correia and Pedro Teles WP-01-13 A Real Explanation for Heterogeneous Investment Dynamics Jonas D.M. Fisher WP-01-14 Recovering Risk Aversion from Options Robert R. Bliss and Nikolaos Panigirtzoglou WP-01-15 Economic Determinants of the Nominal Treasury Yield Curve Charles L. Evans and David Marshall WP-01-16 Price Level Uniformity in a Random Matching Model with Perfectly Patient Traders Edward J. Green and Ruilin Zhou WP-01-17 Earnings Mobility in the US: A New Look at Intergenerational Inequality Bhashkar Mazumder WP-01-18 The Effects of Health Insurance and Self-Insurance on Retirement Behavior Eric French and John Bailey Jones WP-01-19 5 Working Paper Series (continued) The Effect of Part-Time Work on Wages: Evidence from the Social Security Rules Daniel Aaronson and Eric French WP-01-20 Antidumping Policy Under Imperfect Competition Meredith A. Crowley WP-01-21 Is the United States an Optimum Currency Area? An Empirical Analysis of Regional Business Cycles Michael A. Kouparitsas WP-01-22 A Note on the Estimation of Linear Regression Models with Heteroskedastic Measurement Errors Daniel G. Sullivan WP-01-23 The Mis-Measurement of Permanent Earnings: New Evidence from Social Security Earnings Data Bhashkar Mazumder WP-01-24 Pricing IPOs of Mutual Thrift Conversions: The Joint Effect of Regulation and Market Discipline Elijah Brewer III, Douglas D. Evanoff and Jacky So WP-01-25 Opportunity Cost and Prudentiality: An Analysis of Collateral Decisions in Bilateral and Multilateral Settings Herbert L. Baer, Virginia G. France and James T. Moser WP-01-26 Outsourcing Business Services and the Role of Central Administrative Offices Yukako Ono WP-02-01 Strategic Responses to Regulatory Threat in the Credit Card Market* Victor Stango WP-02-02 The Optimal Mix of Taxes on Money, Consumption and Income Fiorella De Fiore and Pedro Teles WP-02-03 Expectation Traps and Monetary Policy Stefania Albanesi, V. V. Chari and Lawrence J. Christiano WP-02-04 Monetary Policy in a Financial Crisis Lawrence J. Christiano, Christopher Gust and Jorge Roldos WP-02-05 Regulatory Incentives and Consolidation: The Case of Commercial Bank Mergers and the Community Reinvestment Act Raphael Bostic, Hamid Mehran, Anna Paulson and Marc Saidenberg WP-02-06 Technological Progress and the Geographic Expansion of the Banking Industry Allen N. Berger and Robert DeYoung WP-02-07 Choosing the Right Parents: Changes in the Intergenerational Transmission of Inequality Between 1980 and the Early 1990s David I. Levine and Bhashkar Mazumder WP-02-08 6 Working Paper Series (continued) The Immediacy Implications of Exchange Organization James T. Moser WP-02-09 Maternal Employment and Overweight Children Patricia M. Anderson, Kristin F. Butcher and Phillip B. Levine WP-02-10 The Costs and Benefits of Moral Suasion: Evidence from the Rescue of Long-Term Capital Management Craig Furfine WP-02-11 On the Cyclical Behavior of Employment, Unemployment and Labor Force Participation Marcelo Veracierto WP-02-12 Do Safeguard Tariffs and Antidumping Duties Open or Close Technology Gaps? Meredith A. Crowley WP-02-13 Technology Shocks Matter Jonas D. M. Fisher WP-02-14 Money as a Mechanism in a Bewley Economy Edward J. Green and Ruilin Zhou WP-02-15 Optimal Fiscal and Monetary Policy: Equivalence Results Isabel Correia, Juan Pablo Nicolini and Pedro Teles WP-02-16 Real Exchange Rate Fluctuations and the Dynamics of Retail Trade Industries on the U.S.-Canada Border Jeffrey R. Campbell and Beverly Lapham WP-02-17 Bank Procyclicality, Credit Crunches, and Asymmetric Monetary Policy Effects: A Unifying Model Robert R. Bliss and George G. Kaufman WP-02-18 Location of Headquarter Growth During the 90s Thomas H. Klier WP-02-19 The Value of Banking Relationships During a Financial Crisis: Evidence from Failures of Japanese Banks Elijah Brewer III, Hesna Genay, William Curt Hunter and George G. Kaufman WP-02-20 On the Distribution and Dynamics of Health Costs Eric French and John Bailey Jones WP-02-21 The Effects of Progressive Taxation on Labor Supply when Hours and Wages are Jointly Determined Daniel Aaronson and Eric French WP-02-22 Inter-industry Contagion and the Competitive Effects of Financial Distress Announcements: Evidence from Commercial Banks and Life Insurance Companies Elijah Brewer III and William E. Jackson III WP-02-23 7 Working Paper Series (continued) State-Contingent Bank Regulation With Unobserved Action and Unobserved Characteristics David A. Marshall and Edward Simpson Prescott WP-02-24 Local Market Consolidation and Bank Productive Efficiency Douglas D. Evanoff and Evren Örs WP-02-25 Life-Cycle Dynamics in Industrial Sectors. The Role of Banking Market Structure Nicola Cetorelli WP-02-26 Private School Location and Neighborhood Characteristics Lisa Barrow WP-02-27 Teachers and Student Achievement in the Chicago Public High Schools Daniel Aaronson, Lisa Barrow and William Sander WP-02-28 The Crime of 1873: Back to the Scene François R. Velde WP-02-29 Trade Structure, Industrial Structure, and International Business Cycles Marianne Baxter and Michael A. Kouparitsas WP-02-30 8
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