## _wp07292 - 1. Descriptive statistics: High-income countries.

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---

### Introduction and motivation
- Research question: What explains diverse export performance across countries, and in particular whether trade-related administrative barriers—number of signatures required for exporting (border barrier) and number of procedures to register a business (behind-the-border barrier)—reduce country exports and whether effects differ across differentiated versus homogeneous goods.
- Core hypothesis: Higher transaction costs from export signatures and business registration procedures reduce exports; the impact is stronger for differentiated (complex) products than for homogeneous (simple) goods.
- Key data constraint: Trading-across-borders variables from the World Bank Doing Business dataset are available only for 2005 (with some 2006 data noted but limited variation), so the empirical sample is effectively cross-sectional for 2004–2005 trade data.

### Theoretical model (structure and mechanisms)
- Trade costs modeled as ad valorem: importer faces price (1+τ_ij) p_j; exporter-specific trade costs captured by (1+η_j).
- Exporter must collect s_j signatures before shipment leaves port; signature fees are ad valorem on an official’s estimated price (ε + p_j) with fee rate θ(s) and θ′(s) > 0.
- Official’s price estimate deviation factor ε increases with product heterogeneity c (ε′(c) > 0); thus:
  - transaction costs increase with the number of required signatures;
  - differentiated products face higher transaction costs than homogeneous products;
  - an extra signature is costlier for differentiated products than for homogeneous goods.
- Behind-the-border barriers modeled via a country-specific efficiency parameter a: higher a reduces marginal costs in both sectors and reduces fixed costs F, increasing number of varieties N_i = S_i / F.
- Derived export/import value equations:
  - homogeneous goods: equation (11a)
  - differentiated goods: equation (11b)
- Comparative statics: ∂E/∂s is more negative for differentiated goods than for homogeneous goods; ∂E/∂a has a larger positive effect on differentiated goods.

### Estimation approach
- Baseline empirical specification: gravity equation (equation 12) for bilateral exports Ln E_ij including exporter signature count sign_j and business start procedures start_j, exporter GDP Y_j, exporter GDP per capita Ypc_j, importer tariffs tariff_ij, exporter remoteness remote_j, bilateral gravity controls Z_ij, and importer fixed effects D.
- Differential-effect identification:
  - Split exports into differentiated vs homogeneous using Rauch (1999) liberal classification (commodity and price-referenced combined as homogeneous).
  - Pooled regressions with interaction of trade-facilitation variables and differentiated dummy.
  - Separate regressions for each product type.
  - Difference-in-difference approach (equation 15) using log ratio Ln(E_ij,d/E_ij,h) and anchor country Belgium (B) to mitigate endogeneity.
- Endogeneity concerns addressed by:
  - Focusing on difference between differentiated and homogeneous exports (less likely to drive policy change that alters signatures differentially).
  - Difference-in-difference with an anchor country to eliminate importer-specific factors.

### Data sources and sample
- Bilateral import data at 4-digit product level: COMTRADE database (UN/World Bank WITS).
- Product classification: Rauch (1999) liberal scheme into commodity, price-referenced, and differentiated; commodity + price-referenced treated as homogeneous.
- Export-signature and trading-across-borders indicators: World Bank Doing Business in 2005 survey of freight forwarders and port/customs officials across 146 countries; signature count used as proxy for export facilitation.
- Business registration procedures (start): Doing Business indicator for number of procedures to start a business.
- Tariffs: applied bilateral import tariff rates from TRAINS via WITS at 6-digit level aggregated as weighted averages.
- Other data: 2004 GDP and GDP per capita from World Development Indicators; geographic and dummy variables from Andrew Rose’s dataset.
- Final sample: summary statistics presented for 140 exporters with complete data; income group definitions based on 2005 GNI per capita (Atlas method): low-income $875 or less; lower middle income $876-3,465; upper middle income $3,466-$10,725; high income $10,726 or more.

### Descriptive statistics — High-income countries (selected summary values preserved exactly as in source)
- Average GDP per capita: 30672
- Average Number of Signatures: 4147
- Average Time to export: 3212
- Average Number of procedures to start business: 530
- Average Exports/GDP (in percent): 30.09

### Main empirical results (key estimates and magnitudes)
- Aggregate exports (gravity regressions; Table 5):
  - Exporter Signature point estimates: -0.047, -0.061, -0.091, -0.042, -0.054, -0.08 (t-statistics: (-3.55)(-3.82)(-6.5)(-3.17)(-3.44)(-5.53)).
  - Exporter Registration point estimates: -0.033, -0.052, -0.047, -0.014, -0.025, -0.001 (t-statistics: (-1.29)(-1.87)(-1.4)(-0.55)(-0.93)(-0.04)).
  - Implied effect: one additional signature reduces country’s aggregate exports by about 4½ percent (central estimate reported as -0.047).
  - Importer tariff effect: a 1 percentage point increase in average tariff associated with about 0.8 percent reduction in exports.
  - Tariff-equivalent: one extra signature (≈ 4.2 percent lower exports in preferred specification) ≈ increasing importer’s tariff by about 5 percentage points.
  - Robustness: excluding oil/gas and products with stringent clearance yields stronger estimates: one extra signature associated with 6 percent lower exports; each business registration procedure associated with 5 percent lower exports (significant at 6 percent level).
  - Including exporter governance (average of regulatory quality, rule of law, control of corruption) renders start_j insignificant while sign_j remains significant with estimates -0.042 and -0.054 in some specifications.
  - Number of observations (as presented concatenated): 750174535792748274345787 (individual values include 7501, 7453, 5792, 7482, 7434, 5787).
  - R-squared reported: 0.729, 0.730, 0.580, 0.730, 0.730, 0.59.
- Homogeneous vs differentiated (pooled and separate regressions; Tables 6–7):
  - Pooled interacted estimates (Table 6): Exporter Signature on homogeneous goods = -0.016, interaction with differentiated = -0.068; total effect on differentiated goods = -0.084 in that specification (t-statistics: (-1.29) and (-6.92)).
  - Business registration: no impact on homogeneous goods; associated with ~10 percent lower differentiated exports in pooled specifications.
  - Separate regressions (Table 7): HOM Exporter Signature = -0.027 (t: (-2.35)); DIF = -0.075 (t: (-4.46)). Exporter Registration: HOM 0.011 (0.44), DIF -0.088 (-2.68).
  - Exporter Governance: 0.163 (0.94) for HOM and 0.609 (2.96) for DIF.
  - Number of observations (concatenated examples): 68127, 158680, 17142.
- Product-level regressions (4-digit products; Table 8):
  - One extra signature reduces homogeneous product exports by -0.013 and differentiated product exports by -0.065 (example column 1).
  - Exporter Signature reported sequence: -0.013, -0.017, -0.021, -0.012, -0.016, -0.021 (t-statistics: (-11.68)(-13.59)(-6.65)(-10.01)(-12.35)(-6.6)).
  - *Differentiated: -0.052, -0.049, -0.033, -0.052, -0.049, -0.033 (t-statistics: (-42.04)(-36.92)(-10)(-42.06)(-36.74)(-9.98)).
  - Number of Obs.: 8.09E+05, 7.48E+05, 1.09E+05, 8.09E+05, 7.48E+05, 1.09E+05.
  - R-squared: 0.43, 0.44, 0.41, 0.43, 0.44, 0.42.
- Difference-in-difference regressions (Table 9):
  - Exporter Signature estimates (example sequence): -0.054, -0.035, -0.032, -0.046, -0.029, -0.035 (t-statistics: (-4.85)(-2.64)(-1.49)(-4.06)(-2.13)(-1.65)).
  - Exporter Registration estimates (example sequence): -0.097, -0.088, -0.094, -0.068, -0.068, -0.108 (t-statistics: (-3.34)(-2.98)(-2.53)(-2.16)(-1.96)(-2.63)).
  - Preferred specification (column 4) controlling for exporter governance: an additional export signature reduces exports of differentiated products by 4.6 percentage points more than exports of homogeneous goods (reported as -0.046 in that column).
  - Differential impact of business registration: 6.8 percentage points greater reduction for differentiated relative to homogeneous goods in that specification (reported as -0.068).
  - Number of Obs. concatenated: 641762043717640861973716.
  - R-squared reported: 0.14, 0.12, 0.10, 0.15, 0.13, 0.10.
- Oil-exporter heterogeneity check (Table 10):
  - Sample split by oil-export share (cutoff mean oil share used): Exporter Signature for Oil exporters example coefficients: -0.036 (-1.78), -0.040 (-2.61), -0.026 (-1.3); Nonoil exporters example coefficient: 0.011 (0.7).
  - *Differentiated: -0.031 (-3.13), -0.091 (-5.02).
  - Exporter Registration and interaction with Differentiated: Exporter Registration -0.07 (-1.32), -0.019 (-0.57); *Differentiated -0.132 (-3.13), -0.058 (-1.35).
  - Number of Obs. concatenated: 149143, 272752, 8004.
  - R-squared: 0.65, 0.76, 0.60, 0.72.

### Robustness and sensitivity
- Multiple dependent-variable definitions: all products; excluding oil/gas and products subject to strict clearance; only goods meeting the Doing Business survey assumptions (SITC 07, 65, 84).
- Alternative specifications: inclusion of exporter governance index; pooled versus split regressions; product-level fixed effects; importer-product fixed effects; difference-in-difference with anchor country.
- Results robust across specifications: signature variable consistently associated with economically meaningful and statistically significant reductions in exports, especially for differentiated products; business registration evidence mixed in levels but stronger for differentiated goods in difference-in-difference.

### Policy-relevant conclusions and recommendations
- Administrative export formalities matter: the number of signatures required for exporting is a measurable and policy-controllable source of transaction costs that significantly reduces aggregate exports.
- Scale of impact:
  - Central estimate: each additional export signature ≈ 4.2 percent lower aggregate exports (reported central estimates around -0.047; preferred specifications produce effects in the 4–6 percent range).
  - Tariff-equivalent: one extra signature ≈ 5 percentage point increase in importer’s tariff (in terms of export volume effect).
  - Product-differentiation effect: each signature reduces exports of differentiated products by about 4–5 percent more than homogeneous goods (estimates vary by specification; some specifications show larger differentials up to ~8 percent).
- Policy implication: trade-facilitation reforms that reduce number of signatures and streamline export procedures are likely to disproportionately boost exports of differentiated, higher-value-added products; such reforms can be an effective complement to tariff reduction in promoting export diversification and development.
- Governance and behind-the-border reforms: exporter governance matters for exports; evidence on business registration procedures is mixed in levels but suggests larger negative effects on differentiated products when endogeneity is addressed—implying broader regulatory reforms that lower behind-the-border frictions (reduce start procedures, improve rule of law, reduce corruption) can further raise differentiated exports.

*Source: _wp07292 - 1. Descriptive statistics: High-income countries.*

### 1. Descriptive statistics: High-income countries. ....................................................................23

### _wp07292 - 1. Descriptive statistics: High-income countries. ....................................................................23

### Major contents (by section)

- 1. Descriptive statistics: High-income countries. ....................................................................23
- 2. Descriptive statistics: Upper-middle-income countries. ......................................................24
- 3. Descriptive statistics: Lower-middle-income countries.......................................................25
- 4. Descriptive statistics: Low-income countries. .....................................................................26
- 5. Regressions. Aggregate Bilateral Exports. ..........................................................................27
- 6. Regressions. Differentiated vs. Homogeneous Products: Pooled Data ...............................28
- 7. Regressions. Differentiated vs. Homogeneous Products: ....................................................29
- 8. Regressions. Differentiated vs. Homogeneous Products: ....................................................30
- 9. Regressions. Differentiated vs. Homogeneous Products: ....................................................31
- 10. Regressions. Oil and Nonoil Exporters..............................................................................32

*Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2007/_wp07292.pdf*

### References..............................................................................................................

### _wp07292 - References..............................................................................................................

### Introduction and motivation
- Research question: What explains diverse export performance across countries, and in particular whether trade-related administrative barriers—number of signatures required for exporting (border barrier) and number of procedures to register a business (behind-the-border barrier)—reduce country exports and whether effects differ across differentiated versus homogeneous goods.
- Core hypothesis: Higher transaction costs from export signatures and business registration procedures reduce exports; the impact is stronger for differentiated (complex) products than for homogeneous (simple) goods.
- Key data constraint: Trading-across-borders variables from the World Bank Doing Business dataset are available only for 2005 (with some 2006 data noted but limited variation), so the empirical sample is effectively cross-sectional for 2004–2005 trade data.

### Theoretical model (structure and mechanisms)
- Trade costs modeled as ad valorem: importer faces price (1+τ_ij) p_j; exporter-specific trade costs captured by (1+η_j).
- Exporter must collect s_j signatures before shipment leaves port; signature fees are ad valorem on an official’s estimated price (ε + p_j) with fee rate θ(s) and θ′(s) > 0.
- Official’s price estimate deviation factor ε increases with product heterogeneity c (ε′(c) > 0); thus:
  - transaction costs increase with the number of required signatures;
  - differentiated products face higher transaction costs than homogeneous products;
  - an extra signature is costlier for differentiated products than for homogeneous goods.
- Behind-the-border barriers modeled via a country-specific efficiency parameter a: higher a reduces marginal costs in both sectors and reduces fixed costs F (manufacturing), increasing number of varieties N_i = S_i / F.
- Derived export/import value equations:
  - homogeneous goods: equation (11a)
  - differentiated goods: equation (11b)
- Comparative statics: ∂E/∂s is more negative for differentiated goods than for homogeneous goods; ∂E/∂a has a larger positive effect on differentiated goods.

### Estimation approach
- Baseline empirical specification: gravity equation (equation 12) for bilateral exports Ln E_ij including exporter signature count sign_j and business start procedures start_j, exporter GDP Y_j, exporter GDP per capita Ypc_j, importer tariffs tariff_ij, exporter remoteness remote_j, bilateral gravity controls Z_ij, and importer fixed effects D.
- Differential-effect identification:
  - Split exports into differentiated vs homogeneous using Rauch (1999) liberal classification (commodity and price-referenced combined as homogeneous).
  - Pooled regressions with interaction of trade-facilitation variables and differentiated dummy.
  - Separate regressions for each product type.
  - Difference-in-difference approach (equation 15) using log ratio Ln(E_ij,d/E_ij,h) and anchor country Belgium (B) to mitigate endogeneity.
- Endogeneity concerns addressed by:
  - Focusing on difference between differentiated and homogeneous exports (less likely to drive policy change that alters signatures differentially).
  - Difference-in-difference with an anchor country to eliminate importer-specific factors.

### Data sources and sample
- Bilateral import data at 4-digit product level: COMTRADE database (UN/World Bank WITS).
- Product classification: Rauch (1999) liberal scheme into commodity, price-referenced, and differentiated; commodity + price-referenced treated as homogeneous.
- Export-signature and trading-across-borders indicators: World Bank Doing Business in 2005 survey of freight forwarders and port/customs officials across 146 countries; signature count used as proxy for export facilitation.
- Business registration procedures (start): Doing Business indicator for number of procedures to start a business.
- Tariffs: applied bilateral import tariff rates from TRAINS via WITS at 6-digit level aggregated as weighted averages.
- Other data: 2004 GDP and GDP per capita from World Development Indicators; geographic and dummy variables from Andrew Rose’s dataset.
- Final sample: summary statistics presented for 140 exporters with complete data; income group definitions based on 2005 GNI per capita (Atlas method): low-income $875 or less; lower middle income $876-3,465; upper middle income $3,466-$10,725; high income $10,726 or more.

### Main empirical results (key estimates and magnitudes)
- Aggregate exports (gravity regressions; Table 5):
  - Point estimate for export signatures (α) in first column: -0.047 (highly significant).
  - Business registration coefficient: -0.033 (statistically not different from zero in first specification).
  - Implied effect: one additional signature reduces country’s aggregate exports by about 4½ percent.
  - Importer tariff effect: a 1 percentage point increase in average tariff associated with about 0.8 percent reduction in exports.
  - Tariff-equivalent: one extra signature (≈ 4.2 percent lower exports in preferred specification) ≈ increasing importer’s tariff by about 5 percentage points.
  - Robustness: excluding oil/gas and products with stringent clearance (column 2) yields stronger estimates: one extra signature associated with 6 percent lower exports; each business registration procedure associated with 5 percent lower exports (significant at 6 percent level).
  - Including exporter governance (average of regulatory quality, rule of law, control of corruption) renders start_j insignificant while sign_j remains significant with estimates -0.042 and -0.054 in some specifications.
- Homogeneous vs differentiated (pooled and separate regressions; Tables 6–7):
  - Pooled interacted estimates (Table 6, column 1): sign_j coefficient on homogeneous goods = -0.016 (not statistically different from 0); interaction with differentiated dummy = -0.068; total effect on differentiated goods = -0.084 (i.e., each signature reduces differentiated exports by 8.4 percent in that spec).
  - Business registration: no impact on homogeneous goods; associated with ~10 percent lower differentiated exports in pooled specifications.
  - Separate regressions by product type (Table 7): exports of differentiated products are considerably more sensitive to signatures than homogeneous products; results hold with and without governance control.
- Product-level regressions (4-digit products; Table 8):
  - One extra signature reduces homogeneous product exports by 1.3 percent and differentiated product exports by 6.5 percent (column 1).
  - Controlling for exporter governance (column 4): an extra signature ≈ 1.3 percentage point increase in import tariff for homogeneous goods; for differentiated goods each signature ≈ 7.1 percentage point increase in import tariff.
- Difference-in-difference regressions (Table 9):
  - Robust support for main hypothesis; estimates consistent in magnitude and significance.
  - Preferred specification (column 4) controlling for exporter governance: an additional export signature reduces exports of differentiated products by 4.6 percentage points more than exports of homogeneous goods.
  - Differential impact of business registration: 6.8 percentage points greater reduction for differentiated relative to homogeneous goods in that specification.
  - Noted finding: an increase in a trading partner’s import tariff associated with higher ratio of differentiated-to-homogeneous exports.
- Oil-exporter heterogeneity check (Table 10):
  - Sample split by oil-export share: countries with oil share < 1 percent versus > 12.87 percent (mean oil share used as cutoff).
  - Signatures negatively affect differentiated goods more in both groups, but the differential magnitude is stronger in the non-oil-exporter sample, implying country characteristics also matter.

### Robustness and sensitivity
- Multiple dependent-variable definitions: all products; excluding oil/gas and products subject to strict clearance; only goods meeting the Doing Business survey assumptions (SITC 07, 65, 84).
- Alternative specifications: inclusion of exporter governance index; pooled versus split regressions; product-level fixed effects; importer-product fixed effects; difference-in-difference with anchor country.
- Results robust across specifications: signature variable consistently associated with economically meaningful and statistically significant reductions in exports, especially for differentiated products; business registration evidence mixed in levels but stronger for differentiated goods in difference-in-difference.

### Policy-relevant conclusions
- Administrative export formalities matter: the number of signatures required for exporting is a measurable and policy-controllable source of transaction costs that significantly reduces aggregate exports.
- Scale of impact:
  - Central estimate: each additional export signature ≈ 4.2 percent lower aggregate exports.
  - Tariff-equivalent: one extra signature ≈ 5 percentage point increase in importer’s tariff (in terms of export volume effect).
  - Product-differentiation effect: each signature reduces exports of differentiated products by about 4–5 percent more than homogeneous goods (estimates vary by specification; some specifications show larger differentials up to ~8 percent).
- Policy implication: trade-facilitation reforms that reduce number of signatures and streamline export procedures are likely to disproportionately boost exports of differentiated, higher-value-added products; such reforms can be an effective complement to tariff reduction in promoting export diversification and development.
- Governance and behind-the-border reforms: exporter governance matters for exports; evidence on business registration procedures is mixed in levels but suggests larger negative effects on differentiated products when endogeneity is addressed—implying broader regulatory reforms that lower behind-the-border frictions (reduce start procedures, improve rule of law, reduce corruption) can further raise differentiated exports.

*Source: _wp07292 - References (IMF working paper content unit)._

### References

### _wp07292 - References

### References cited
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- Ben-David, Dan (1993) “Equalizing Exchange: Trade Liberalization and Income Convergence.” Quarterly Journal of Economics, August, 108(3).
- Dollar, David; Micco, Alejandro, and Clark, Ximena (2002) “Maritime Transport Costs and Port Efficiency.” World Bank Working Paper No. 2781.
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- Feenstra, Robert C.; Markusen, James R., and Rose, Andrew K. (2001) “Using the Gravity Equation to Differentiate Among Alternative Theories of Trade.” Canadian Journal of Economics, May, 34(2).
- Fink, Carsten; Mattoo, Aaditya, and Neagu, Christina I. (2002a) “Trade in International Maritime Services: How Much Does Policy Matter?” World Bank Economic Review, June, 16(1).
- Fink, Carsten; Mattoo, Aaditya, and Neagu, Christina I. (2002b) “Assessing the Role of Communication Costs in International Trade.” World Bank Working Paper No. 2929.
- Francois, Joseph, and Manchin, Miriam (2006) “Institutional Quality, Infrastructure, and the Propensity to Export.” Mimeo.
- Frankel, Jeffrey A., and Romer, David (1999) "Does Trade Cause Growth?" American Economic Review, June, 89(3).
- Freund, Caroline L., and Weinhold, Diana (2000) “On the Effect of the Internet on International Trade.” International Finance Discussion Papers No. 693, Board of Governors of the Federal Reserve System.
- Head, Keith (2003) “Gravity for Beginners.” University of British Columbia, Mimeo.
- Hummels, David. (2001) “Time as a Trade Barrier.” GTAP Working Paper No. 18, Center for Global Trade Analysis, Purdue University.
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- Messerlin, Patrick A., and Zarrouk, Jamel (2000) “Trade Facilitation: Technical Regulation and Customs Procedures.” The World Economy, April, 23(4).
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### Descriptive statistics by income group (selected summary values preserved exactly as in source)
- High-income countries (Table 1)
  - Average GDP per capita: 30672
  - Average Number of Signatures: 4147
  - Average Time to export: 3212
  - Average Number of procedures to start business: 530
  - Average Exports/GDP (in percent): 30.09
- Upper-middle-income countries (Table 2)
  - Average GDP per capita: 5944
  - Average Number of Signatures: 6249
  - Average Time to export: 3711
  - Average Number of procedures to start business: 480
  - Average Exports/GDP (in percent): 0.12
- Lower-middle-income countries (Table 3)
  - Average GDP per capita: 1863
  - Average Number of Signatures: 1133
  - Average Time to export: 1123
  - Average Number of procedures to start business: 164
  - Average Exports/GDP (in percent): 00.18
- Low-income countries (Table 4)
  - Average GDP per capita: 420
  - Average Number of Signatures: 1849
  - Average Time to export: 1122
  - Average Number of procedures to start business: 128
  - Average Exports/GDP (in percent): 0.27

(Note: country-level rows in Tables 1–4 provide country-specific values for GDP per capita, Number of Signatures, Time to export, Number of procedures to start business, Exports/GDP (in percent), Petroleum&Gas/Exports (in percent), Diff. products / Exports (in percent), and Herfindahl Index.)

### Regression tables — reported coefficients, t-statistics, sample sizes, and R-squared
- Table 5. Regressions. Aggregate Bilateral Exports.
  - Dependent variable: Log Aggregate Bilateral Imports.
  - Key coefficients (examples preserved exactly):
    - Exporter Signature: -0.047, -0.061, -0.091, -0.042, -0.054, -0.08 (t-statistics in parentheses: (-3.55)(-3.82)(-6.5)(-3.17)(-3.44)(-5.53))
    - Exporter Registration: -0.033, -0.052, -0.047, -0.014, -0.025, -0.001 (t-statistics: (-1.29)(-1.87)(-1.4)(-0.55)(-0.93)(-0.04))
    - Exporter Governance: 0.296, 0.429, 0.727 (t-statistics: (1.86)(2.49)(2.85))
    - Log Exporter GDP: 1.264, 1.318, 1.195, 1.271, 1.329, 1.209 (t-statistics: (24.99)(25.48)(15.67)(25.05)(25.93)(16.99))
  - Number of observations: values include 7501, 7453, 5792, 7482, 7434, 5787 (as presented as concatenated No of Obs.750174535792748274345787)
  - R-squared: 0.729, 0.730, 0.580, 0.730, 0.730, 0.59
  - Notes: t-statistics in parenthesis; robust standard errors clustered by exporters; all regressions include importer fixed effects. Definitions for Export samples: 2/ Exports include SITC 07, 65, 84. 1/ Exports exclude SITC categories 00, 01, 02, 05, 08, 33, 34, 35, 54, 57, 94, 95, 96, 97.

- Table 6. Regressions. Differentiated vs. Homogeneous Products: Pooled Data.
  - Dependent variable: Log Bilateral Imports by Product Group.
  - Example coefficients:
    - Exporter Signature: -0.016, -0.030, -0.051, -0.010, -0.022, -0.041 (t-statistics: (-1.29)(-1.64)(-2.95)(-0.76)(-1.24)(-2.49))
    - *Differentiated: -0.068, -0.059, -0.056, -0.068, -0.059, -0.055 (t-statistics: (-6.92)(-5.06)(-3.43)(-6.88)(-5.05)(-3.41))
    - Exporter Governance: 0.388, 0.477, 0.713 (t-statistics: (2.49)(2.88)(2.98))
    - Log Exporter GDP: 1.236, 1.281, 1.114, 1.247, 1.295, 1.127 (t-statistics: (24.75)(25.26)(14.49)(25.56)(26.4)(15.93))
  - Number of observations: shown as 1397013701974913943136769743 (pooled presentation).
  - R-squared: 0.69, 0.68, 0.51, 0.69, 0.69, 0.52
  - Notes: t-statistics in parenthesis; robust standard errors clustered by exporters; all regressions include importer fixed effects; Export sample notes same as Table 5.

- Table 7. Regressions. Differentiated vs. Homogeneous Products: Individual Regressions.
  - Dependent variable: Log Bilateral Imports by Product Group.
  - Example coefficients:
    - HOM: Exporter Signature -0.027 (t: (-2.35)); DIF: -0.075 (t: (-4.46))
    - Exporter Registration: HOM 0.011 (0.44), DIF -0.088 (-2.68)
    - Exporter Governance: 0.163 (0.94) for HOM and 0.609 (2.96) for DIF
  - Number of Obs.: 68127, 158680, 17142 (as concatenated)
  - R-squared: 0.65, 0.74, 0.65, 0.74
  - Notes: t-statistics in parenthesis; robust standard errors clustered by exporters; all regressions include importer fixed effects.

- Table 8. Regressions. Commodity-Level Regressions Using Pooled Data.
  - Dependent variable: Log 4-digit Product-Level Bilateral Imports.
  - Example coefficients:
    - Exporter Signature: -0.013, -0.017, -0.021, -0.012, -0.016, -0.021 (t-statistics: (-11.68)(-13.59)(-6.65)(-10.01)(-12.35)(-6.6))
    - *Differentiated: -0.052, -0.049, -0.033, -0.052, -0.049, -0.033 (t-statistics: (-42.04)(-36.92)(-10)(-42.06)(-36.74)(-9.98))
    - Exporter Registration: 0.002, 0.006, 0.040, 0.021, 0.026, 0.051 (t-statistics: (1.48)(3.73)(7.4)(13)(14.54)(9.38))
    - Exporter Governance: 0.324, 0.331, 0.201 (t-statistics: (41.86)(41.26)(9.91))
    - Log Exporter GDP: 0.734, 0.762, 0.676, 0.741, 0.770, 0.679 (t-statistics: (361.56)(363.09)(133.44)(364.33)(366)(134.05))
  - Number of Obs.: 8.09E+05, 7.48E+05, 1.09E+05, 8.09E+05, 7.48E+05, 1.09E+05 (two sets presented)
  - R-squared: 0.43, 0.44, 0.41, 0.43, 0.44, 0.42
  - Notes: t-statistics in parenthesis; robust standard errors are clustered by exporters; all regressions include importer*product pair fixed effects.

- Table 9. Regressions. Difference-in-Difference Regressions.
  - Dependent variable: Log Ratio of Differentiated Imports to Homogenous Imports.
  - Example coefficients:
    - Exporter Signature: -0.054, -0.035, -0.032, -0.046, -0.029, -0.035 (t-statistics: (-4.85)(-2.64)(-1.49)(-4.06)(-2.13)(-1.65))
    - Exporter Registration: -0.097, -0.088, -0.094, -0.068, -0.068, -0.108 (t-statistics: (-3.34)(-2.98)(-2.53)(-2.16)(-1.96)(-2.63))
    - Exporter remoteness: -14.145, -11.473, -7.744, -14.789, -12.072, -7.522 (t-statistics: (-6.78)(-4.76)(-3)(-6.83)(-4.99)(-2.85))
  - Number of Obs.: 641762043717640861973716 (concatenated)
  - R-squared: 0.14, 0.12, 0.10, 0.15, 0.13, 0.10
  - Notes: t-statistics in parenthesis; robust standard errors are clustered by exporters. Definition of regressand: Ln (Eij,d /Eij,h) - Ln (EiB,d /EiB,h). Export sample notes as in prior tables.

- Table 10. Regressions. Oil and Nonoil Exporters.
  - Format: Columns for Oil exporters and Nonoil exporters; Dependent variables: Aggregate Imports and Imports by Product Category.
  - Example coefficients:
    - Exporter Signature: Oil exporters -0.036 (-1.78), -0.040 (-2.61), -0.026 (-1.3), Nonoil exporters 0.011 (0.7)
    - *Differentiated: -0.031 (-3.13), -0.091 (-5.02)
    - Exporter Registration and interaction with Differentiated: Exporter Registration -0.07 (-1.32), -0.019 (-0.57); *Differentiated -0.132 (-3.13), -0.058 (-1.35)
    - Log Exporter GDP: 1.287 (7.3), 1.295 (24.15), 1.207 (6.59), 1.273 (24.21)
  - Number of Obs.: 149143, 272752, 8004 (as concatenated)
  - R-squared: 0.65, 0.76, 0.60, 0.72
  - Notes: t-statistics in parenthesis; robust standard errors clustered by exporters; all regressions include importer fixed effects.

### Notes and regression annotations (as in source)
- t-statistics are reported in parenthesis.
- Robust standard errors are clustered by exporters.
- Many regressions include importer fixed effects or importer*product pair fixed effects as specified.
- Export sample definitions repeated across tables:
  - 2/ Exports include SITC 07 (coffee, tea, spices), 65 (textile yarns, fabrics), 84 (articles of apparel and clothing).
  - 1/ Exports exclude products in SITC 00, 01, 02, 05, 08, 33, 34, 35, 54, 57, 94, 95, 96, 97 categories (listed in source).

*Content derived from _wp07292 - References.*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2007/_wp07292.pdf_