## _wp10218 - Appendix Table

## Source details

**Canonical URL:** [_wp10218 - Appendix Table](https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2010/_wp10218.pdf)

## Other formats

- [Markdown version](/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2010/_wp10218.pdf.md)
- [Structured JSON version](/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2010/_wp10218.pdf.json)

---

### I. INTRODUCTION — context and motivation
- The second half of the 20th century saw one of the greatest increases in trade openness in world history, driven by significant declines in tariffs and transportation costs.
- Cross-country and theoretical literature provide mixed and limited evidence on how trade liberalization affects within-country income distribution; mechanisms remain understudied.
- Standard Heckscher-Ohlin theory predicts gains to abundant factors (e.g., unskilled labor in developing countries), but recent models and empirical work show trade liberalization can reduce wages of unskilled labor even in labor-abundant countries.
- Adjustment costs and the speed of factor reallocation across sectors are important features in models where trade liberalization can harm the poor; empirical micro-evidence documents such adjustment costs in developing countries.

### Research focus and scope
- The paper examines the effect of trade liberalization on poverty in India using the sudden and extensive change in India’s trade policy in 1991.
- Extensions relative to previous work (Topalova (2007)) include:
  - Inclusion of non-tariff barriers (NTBs) in the measure of liberalization exposure.
  - Measurement of how loss of trade protection affected household consumption across the entire income distribution.
  - Robustness checks addressing potential endogeneity of pre-liberalization employment composition and confounding concurrent reforms, including dismantling of NTBs.

### Identification strategy (summary)
- Differential exposure: districts had different industrial composition in 1991; tariffs for industries were cut by varying levels and times, creating cross-district variation in exposure to liberalization.
- Difference-in-difference approach measures relative effects across districts more or less exposed to tariff reductions; it does not measure the overall level effect of liberalization on India as a whole.
- The approach captures aggregate (district-level) outcomes to reflect general equilibrium impacts within regions rather than only industry-level effects.

### Background: trade reform in India
- Post–Second World War strategy: import substitution and heavy government intervention; trade restrictions included high tariff and non-tariff barriers, complex import licensing, actual user requirement, canalization, and government purchase preferences.
- As late as 1989/90 only 12 percent of manufactured products could be imported under an open general license; the average tariff was greater than 90 percent.
- 1991 crisis led to IMF Stand-By Arrangement and conditional macroeconomic stabilization and structural reforms (industrial and import licenses, financial sector, tax, and trade policy).
- Tariff and NTB changes 1987–1997:
  - Share of goods subject to quantitative restrictions fell from 87 to 45 percent (period 1987–1994).
  - Average nominal tariff fell from 80 percent in 1990 to 37 percent in 1996.
  - Trade openness: ratio of total trade in manufactures to GDP rose from a base of 13 percent in the 1980s to nearly 19 percent of GDP in 1999/2000.
- Timing and nature of reforms: sudden, externally imposed “shock therapy” in 1991; reforms were implemented rapidly and largely unanticipated.

### Data and measurement
- Household data: NSS “thick” rounds in 1983, 1987–88, 1993–94 and 1999–2000; repeated cross-sections used to create district-level (rural) and region-level (urban) panels. Roughly 75,000 rural and 45,000 urban households per round.
- Geographic units: roughly 450 districts and 77 NSS regions in India.
- Poverty measures: headcount ratio using Deaton poverty lines and adjustments for 1999/2000 recall changes.
- Tariffs: detailed six-digit HS tariff data for ~5,000 product lines matched to NIC codes; district tariff exposure computed as 1991 employment-weighted average nominal ad-valorem tariff.
- Non-tariff barriers (NTB): share of products within a production sector importable without license; NTB data for 1997 collected, pre-1991 NTBs from Aksoy (1992).
- Auxiliary data sources: Annual Survey of Industries (ASI) 1982–1997 for registered manufacturing; WPI product prices; district agricultural wages (Duflo and Pande); Census 1991/2001.

### Empirical strategy
- Identification exploits cross-district variation in 1991 employment composition combined with exogenous tariff cuts 1987–1997.
- Baseline difference-in-differences: outcome dt y (poverty, consumption) regressed on dt Tariff interacted with Post indicator, with district fixed effects and year indicator.
- Address endogeneity of scaled tariff (Tariff) because of non-traded sector shares by instrumenting with non-scaled traded-tariff (TrTariff) and interactions with pre-reform unscaled tariffs.
- Focus on long difference 1987–1997 (exclude 1993 ambiguity); tariff data use 1987 pre and 1997 post measures.

### Main findings — magnitudes and distributional patterns
- Rural India:
  - OLS estimate (column (1)) for poverty: -0.24; IV with traded tariff (column (3)) gives -0.71 (significant at 1 percent).
  - Interpretation: a district experiencing the average decline in scaled tariffs of 5.5 percentage points had a relative poverty increase of about 3.9 percentage points.
  - Absolute comparisons: overall decline in poverty from 1987 to 1999 about 13 percentage points. A rural district with no tariff change experienced a 14 percentage point decline in poverty; a district with average exposure saw an 11–12 percentage point decline.
  - Average consumption: districts with average exposure experienced approximately 3–4 percentage point lower consumption growth relative to unexposed rural districts.
  - Effects concentrated among the poorest: largest consumption decline at the bottom of the distribution (10th and 20th percentiles), effects decline and become insignificant moving up the distribution (Table 6; region-level bottom 10th estimate 1.5 significant at 1 percent).
- Urban India:
  - Point estimates similar in magnitude but much less precise; urban results sensitive to inclusion of controls for pre-trends and other reforms and often statistically indistinguishable from zero.
- Robustness:
  - Results robust to controlling for NTBs; inclusion of NTB does not overturn tariff-poverty link and NTB coefficients statistically insignificant or pointing same direction in rural sample.
  - Controlling for concurrent reforms (industrial delicensing, FDI openness, number of bank branches per capita) leaves rural results essentially unchanged; urban coefficients attenuate substantially.
  - Falsification test (1983–1987 pre-trend vs. 1987–1997 tariff change) shows no correlation in rural sample; urban sample shows pre-reform trend correlation, undermining causal interpretation in urban areas.

### Mechanisms and interpretation
- Limited factor mobility:
  - Findings are inconsistent with standard trade theory assuming perfect mobility of factors across regions and industries.
  - There is almost no geographical or cross-sectoral migration in rural India, and no upward trend in mobility after the 1991 reforms.
- Role of institutions and labor-market flexibility:
  - The trade-consumption link is strongest among groups and sectors that are least geographically mobile (the bottom of the consumption distribution).
  - States with inflexible labor laws—where reallocation of labor across sectors may have been impeded—experienced the largest adverse impacts of trade opening on poverty.
  - States with flexible labor laws, faster manufacturing growth, and greater movement of capital and labor mitigated the shock from relative price changes.
- Price and wage adjustment:
  - Adjustment to trade reform occurred through changes in prices.
  - Wages and wage premia absorbed the effect of trade-induced relative price changes.
  - Results are consistent with a specific-factor model of trade: inability of labor to reallocate away from sectors that lost protection is the most likely explanation for the observed relationship between liberalization and poverty in rural districts.

### Mechanisms and channels — empirical evidence
- Factor mobility:
  - Geographic mobility: lifetime migration substantial (23 percent rural, 33 percent urban), but short-run migration across districts in past 10 years is low (3–4 percent rural), and migration for employment reasons is very low (<0.5 percent rural, 4 percent urban); migration flows are not correlated with district tariff changes (Table 5).
  - Sectoral reallocation: measures of structural change, excess job reallocation and net employment change from ASI show no post-1991 increase; structural change in India (0.04–0.1 percentage points) much lower than comparative estimate ~0.35 pp across 20 developing countries.
  - Industry-level regressions: lagged tariffs not significantly correlated with changes in employment share, capital share, output, or employment (Table 7, Panel A).
- Price and factor return adjustment:
  - Tariff cuts pass through to domestic prices: significant negative relation between tariff cuts and WPI product prices (Table 7, Panel B, column (1)); larger tariff cuts → lower domestic prices.
  - Industry wages: ASI-based average industry wage positively and significantly correlated with industry tariffs; a 10 percent drop in tariffs leads to a 0.8 percent decrease in industry wages (Table 7, Panel B, column (2)).
  - Sectoral wage premia: production sector premia positively correlated with lagged tariffs in urban sample (point estimates ~0.13–0.14); average sector tariff decline ~65 percentage points 1991–1997 → ~9 percentage points decrease in real wage premium (0.14 * 0.65); largest declines (180 percentage points) → ~25 percentage points decrease.
  - Agricultural wages: district-level agricultural wages positively and significantly correlated with district-level tariff protection; average rural district 5.5 percentage point decline in scaled tariffs between 1987 and 1999 implies a 5.7 percentage point relative decrease in agricultural wage (1.034 * 5.5) (Table 7, Panel B, column (5)).
- Institutional heterogeneity:
  - Labor law flexibility moderates impact: tariff cuts had substantially less adverse effect on poverty and consumption in states with flexible labor laws (interaction of Tariff with Flexible Labor Law reverses coefficient sign and magnitude, Table 8).
  - Interpretation: inflexible labor laws impede intersectoral reallocation, forcing adjustment through sector-specific wage declines and amplifying poverty impact.

### Policy implications and recommendations
- A flexible institutional environment (labor market flexibility) mitigates adverse distributional impacts of trade liberalization by facilitating factor reallocation and faster growth in higher-wage sectors.
- Where labor mobility and institutional flexibility are limited, complementary policies are needed to redistribute gains and cushion losers:
  - Implement programs to compensate or support workers and households adversely affected by trade shocks (targeted redistribution, safety nets).
  - Encourage reforms that enhance labor mobility and reduce sectoral protection of specific rents to allow reallocation (labor law reforms, improve investment climate).
  - Strengthen mechanisms that facilitate worker adjustment (skills, retraining, credit access, mobility-enhancing infrastructure).
- Policy sequencing: without flexible institutions and reallocation channels, trade liberalization can produce heterogeneous outcomes and increase poverty incidence in exposed regions; mitigation measures increase political feasibility of reform.

### Key statistics and figures (preserved exactly)
- 12 percent (manufactured products importable under open general license in 1989/90)
- average tariff >90 percent (pre-1991)
- average tariff fell from 80 percent in 1990 to 37 percent in 1996
- share of goods subject to quantitative restrictions fell from 87 to 45 percent (1987–1994)
- ratio of total trade in manufactures to GDP: from 13 percent (1980s base) to nearly 19 percent in 1999/2000
- districts/regions: roughly 450 districts and 77 regions
- NSS rounds: 1983, 1987–88, 1993–94, 1999–2000
- NSS sample size per round: approximately 75,000 rural and 45,000 urban households
- average decline in scaled tariffs cited: 5.5 percentage points
- IV estimate: Tariff → poverty coefficient -0.71 (significant at 1 percent)
- estimated relative poverty increase ≈ 3.9 percentage points for average 5.5 pp tariff decline
- overall decline in poverty from 1987 to 1999: about 13 percentage points
- rural district with no tariff change: 14 percentage point decline in poverty; with average exposure: 11–12 percentage points
- relative consumption growth lower by approximately 3–4 percentage points for average-exposure districts
- migration: 23 percent rural lifetime, 33 percent urban lifetime; short-run migration (past 10 years) 3–4 percent rural; migration for employment reasons <0.5 percent rural, 4 percent urban
- average sector tariff decline ~65 percentage points (1991–1997) → ~9 percentage point decrease in real wage premium (0.14*0.65)
- India average structural change 0.04–0.1 percentage points (versus ~0.35 pp in Wacziarg and Wallack (2004))
- ASI employment growth: near nil registered manufacturing employment growth during period except a sharp rise in 1996
- Table and figure references preserved as described in the source (Tables 1–8, Figures 1–3).

*Source: Appendix Table; I. INTRODUCTION; Section VI concludes; and REFERENCES from the provided content unit _wp10218.*

### Appendix Table .........................................................................................................

### _wp10218 - Appendix Table ................................................................................................

### I. INTRODUCTION — context and motivation
- The second half of the 20th century saw one of the greatest increases in trade openness in world history, driven by significant declines in tariffs and transportation costs.
- Cross-country and theoretical literature provide mixed and limited evidence on how trade liberalization affects within-country income distribution; mechanisms remain understudied.
- Standard Heckscher-Ohlin theory predicts gains to abundant factors (e.g., unskilled labor in developing countries), but recent models and empirical work show trade liberalization can reduce wages of unskilled labor even in labor-abundant countries.
- Adjustment costs and the speed of factor reallocation across sectors are important features in models where trade liberalization can harm the poor; empirical micro-evidence documents such adjustment costs in developing countries.

### Research focus and scope
- The paper examines the effect of trade liberalization on poverty in India using the sudden and extensive change in India’s trade policy in 1991.
- Extensions relative to previous work (Topalova (2007)) include:
  - Inclusion of non-tariff barriers (NTBs) in the measure of liberalization exposure.
  - Measurement of how loss of trade protection affected household consumption across the entire income distribution.
  - Robustness checks addressing potential endogeneity of pre-liberalization employment composition and confounding concurrent reforms, including dismantling of NTBs.

### Identification strategy (summary)
- Differential exposure: districts had different industrial composition in 1991; tariffs for industries were cut by varying levels and times, creating cross-district variation in exposure to liberalization.
- Difference-in-difference approach measures relative effects across districts more or less exposed to tariff reductions; it does not measure the overall level effect of liberalization on India as a whole.
- The approach captures aggregate (district-level) outcomes to reflect general equilibrium impacts within regions rather than only industry-level effects.

### Key empirical findings — magnitudes and distributional patterns
- Poverty impact in rural India:
  - Compared to a rural district experiencing no change in tariffs, a district experiencing the mean level of tariff changes saw:
    - a 2 percentage points increase in poverty incidence, and
    - a 0.6 percentage points increase in poverty depth.
  - This setback represents about 15 percent of India's progress in poverty reduction over the 1990s.
- Consumption and distributional effects:
  - Average real per capita expenditure in districts concentrated in industries exposed to larger tariff cuts grew relatively more slowly.
  - The adverse effect was most pronounced among the poorest households in affected districts, with estimated impacts declining in magnitude and becoming statistically indistinguishable from zero at the upper end of the consumption distribution.

### Mechanisms and interpretation
- Limited factor mobility:
  - Findings are inconsistent with standard trade theory assuming perfect mobility of factors across regions and industries.
  - There is almost no geographical or cross-sectoral migration in rural India, and no upward trend in mobility after the 1991 reforms.
- Role of institutions and labor-market flexibility:
  - The trade-consumption link is strongest among groups and sectors that are least geographically mobile (the bottom of the consumption distribution).
  - States with inflexible labor laws—where reallocation of labor across sectors may have been impeded—experienced the largest adverse impacts of trade opening on poverty.
  - States with flexible labor laws, faster manufacturing growth, and greater movement of capital and labor mitigated the shock from relative price changes.
- Price and wage adjustment:
  - Adjustment to trade reform occurred through changes in prices.
  - Wages and wage premia absorbed the effect of trade-induced relative price changes.
  - Results are consistent with a specific-factor model of trade: inability of labor to reallocate away from sectors that lost protection is the most likely explanation for the observed relationship between liberalization and poverty in rural districts.

### Contributions and relation to literature
- Re-assesses and extends Topalova (2007) debate on rural poverty effects of Indian liberalization; addresses contrasting findings in Hasan, Mitra and Ural (2007) by incorporating NTBs and district-level variation.
- Complements other work using similar identification strategies:
  - Links to studies finding short-run adjustment costs affected schooling and child labor decisions (Edmonds, Pavcnik and Topalova).
- Emphasizes importance of factor mobility and institutional settings in determining distributional consequences of trade liberalization.

*Source: Appendix Table and I. INTRODUCTION from the provided content unit.*

### Section VI concludes.

### _wp10218 - Section VI concludes.

### Background: trade reform in India
- Post–Second World War strategy: import substitution and heavy government intervention; trade restrictions included high tariff and non-tariff barriers, complex import licensing, actual user requirement, canalization, and government purchase preferences.
- As late as 1989/90 only 12 percent of manufactured products could be imported under an open general license; the average tariff was greater than 90 percent.
- 1991 crisis led to IMF Stand-By Arrangement and conditional macroeconomic stabilization and structural reforms (industrial and import licenses, financial sector, tax, and trade policy).
- Tariff and NTB changes 1987–1997:
  - Share of goods subject to quantitative restrictions fell from 87 to 45 percent (period 1987–1994).
  - Average nominal tariff fell from 80 percent in 1990 to 37 percent in 1996.
  - Trade openness: ratio of total trade in manufactures to GDP rose from a base of 13 percent in the 1980s to nearly 19 percent of GDP in 1999/2000.
- Timing and nature of reforms: sudden, externally imposed “shock therapy” in 1991; reforms were implemented rapidly and largely unanticipated.

### Data and measurement
- Household data: NSS “thick” rounds in 1983, 1987–88, 1993–94 and 1999–2000; repeated cross-sections used to create district-level (rural) and region-level (urban) panels. Roughly 75,000 rural and 45,000 urban households per round.
- Geographic units: roughly 450 districts and 77 NSS regions in India.
- Poverty measures: headcount ratio using Deaton poverty lines and adjustments for 1999/2000 recall changes.
- Tariffs: detailed six-digit HS tariff data for ~5,000 product lines matched to NIC codes; district tariff exposure computed as 1991 employment-weighted average nominal ad-valorem tariff.
- Non-tariff barriers (NTB): share of products within a production sector importable without license; NTB data for 1997 collected, pre-1991 NTBs from Aksoy (1992).
- Auxiliary data sources: Annual Survey of Industries (ASI) 1982–1997 for registered manufacturing; WPI product prices; district agricultural wages (Duflo and Pande); Census 1991/2001.

### Empirical strategy
- Identification exploits cross-district variation in 1991 employment composition combined with exogenous tariff cuts 1987–1997.
- Baseline difference-in-differences: outcome dt y (poverty, consumption) regressed on dt Tariff interacted with Post indicator, with district fixed effects and year indicator.
- Address endogeneity of scaled tariff (Tariff) because of non-traded sector shares by instrumenting with non-scaled traded-tariff (TrTariff) and interactions with pre-reform unscaled tariffs.
- Focus on long difference 1987–1997 (exclude 1993 ambiguity); tariff data use 1987 pre and 1997 post measures.

### Main findings
- Rural India:
  - OLS estimate (column (1)) for poverty: -0.24; IV with traded tariff (column (3)) gives -0.71 (significant at 1 percent).
  - Interpretation: a district experiencing the average decline in scaled tariffs of 5.5 percentage points had a relative poverty increase of about 3.9 percentage points.
  - Absolute comparisons: overall decline in poverty from 1987 to 1999 about 13 percentage points (Table 1). A rural district with no tariff change experienced a 14 percentage point decline in poverty; a district with average exposure saw an 11–12 percentage point decline.
  - Average consumption: districts with average exposure experienced approximately 3–4 percentage point lower consumption growth relative to unexposed rural districts.
  - Effects concentrated among the poorest: largest consumption decline at the bottom of the distribution (10th and 20th percentiles), effects decline and become insignificant moving up the distribution (Table 6; region-level bottom 10th estimate 1.5 significant at 1 percent).
- Urban India:
  - Point estimates similar in magnitude but much less precise; urban results sensitive to inclusion of controls for pre-trends and other reforms and often statistically indistinguishable from zero.
- Robustness:
  - Results robust to controlling for NTBs; inclusion of NTB does not overturn tariff-poverty link and NTB coefficients statistically insignificant or pointing same direction in rural sample.
  - Controlling for concurrent reforms (industrial delicensing, FDI openness, number of bank branches per capita) leaves rural results essentially unchanged; urban coefficients attenuate substantially.
  - Falsification test (1983–1987 pre-trend vs. 1987–1997 tariff change) shows no correlation in rural sample; urban sample shows pre-reform trend correlation, undermining causal interpretation in urban areas.

### Mechanisms and channels
- Factor mobility:
  - Geographic mobility: lifetime migration substantial (23 percent rural, 33 percent urban), but short-run migration across districts in past 10 years is low (3–4 percent rural), and migration for employment reasons is very low (<0.5 percent rural, 4 percent urban); migration flows are not correlated with district tariff changes (Table 5).
  - Sectoral reallocation: measures of structural change, excess job reallocation and net employment change from ASI show no post-1991 increase; structural change in India (0.04–0.1 percentage points) much lower than comparative estimate ~0.35 pp across 20 developing countries.
  - Industry-level regressions: lagged tariffs not significantly correlated with changes in employment share, capital share, output, or employment (Table 7, Panel A).
- Price and factor return adjustment:
  - Tariff cuts pass through to domestic prices: significant negative relation between tariff cuts and WPI product prices (Table 7, Panel B, column (1)); larger tariff cuts → lower domestic prices.
  - Industry wages: ASI-based average industry wage positively and significantly correlated with industry tariffs; a 10 percent drop in tariffs leads to a 0.8 percent decrease in industry wages (Table 7, Panel B, column (2)).
  - Sectoral wage premia: production sector premia positively correlated with lagged tariffs in urban sample (point estimates ~0.13–0.14); average sector tariff decline ~65 percentage points 1991–1997 → ~9 percentage points decrease in real wage premium (0.14 * 0.65); largest declines (180 percentage points) → ~25 percentage points decrease.
  - Agricultural wages: district-level agricultural wages positively and significantly correlated with district-level tariff protection; average rural district 5.5 percentage point decline in scaled tariffs between 1987 and 1999 implies a 5.7 percentage point relative decrease in agricultural wage (1.034 * 5.5) (Table 7, Panel B, column (5)).
- Institutional heterogeneity:
  - Labor law flexibility moderates impact: tariff cuts had substantially less adverse effect on poverty and consumption in states with flexible labor laws (interaction of Tariff with Flexible Labor Law reverses coefficient sign and magnitude, Table 8).
  - Interpretation: inflexible labor laws impede intersectoral reallocation, forcing adjustment through sector-specific wage declines and amplifying poverty impact.

### Policy implications and recommendations
- A flexible institutional environment (labor market flexibility) mitigates adverse distributional impacts of trade liberalization by facilitating factor reallocation and faster growth in higher-wage sectors.
- Where labor mobility and institutional flexibility are limited, complementary policies are needed to redistribute gains and cushion losers:
  - Implement programs to compensate or support workers and households adversely affected by trade shocks (targeted redistribution, safety nets).
  - Encourage reforms that enhance labor mobility and reduce sectoral protection of specific rents to allow reallocation (labor law reforms, improve investment climate).
  - Strengthen mechanisms that facilitate worker adjustment (skills, retraining, credit access, mobility-enhancing infrastructure).
- Policy sequencing: without flexible institutions and reallocation channels, trade liberalization can produce heterogeneous outcomes and increase poverty incidence in exposed regions; mitigation measures increase political feasibility of reform.

### Key statistics and figures (preserved exactly)
- 12 percent (manufactured products importable under open general license in 1989/90)
- average tariff >90 percent (pre-1991)
- average tariff fell from 80 percent in 1990 to 37 percent in 1996
- share of goods subject to quantitative restrictions fell from 87 to 45 percent (1987–1994)
- ratio of total trade in manufactures to GDP: from 13 percent (1980s base) to nearly 19 percent in 1999/2000
- districts/regions: roughly 450 districts and 77 regions
- NSS rounds: 1983, 1987–88, 1993–94, 1999–2000
- NSS sample size per round: approximately 75,000 rural and 45,000 urban households
- average decline in scaled tariffs cited: 5.5 percentage points
- IV estimate: Tariff → poverty coefficient -0.71 (significant at 1 percent)
- estimated relative poverty increase ≈ 3.9 percentage points for average 5.5 pp tariff decline
- overall decline in poverty from 1987 to 1999: about 13 percentage points
- rural district with no tariff change: 14 percentage point decline in poverty; with average exposure: 11–12 percentage points
- relative consumption growth lower by approximately 3–4 percentage points for average-exposure districts
- migration: 23 percent rural lifetime, 33 percent urban lifetime; short-run migration (past 10 years) 3–4 percent rural; migration for employment reasons <0.5 percent rural, 4 percent urban
- average sector tariff decline ~65 percentage points (1991–1997) → ~9 percentage point decrease in real wage premium (0.14*0.65)
- India average structural change 0.04–0.1 percentage points (versus ~0.35 pp in Wacziarg and Wallack (2004))
- ASI employment growth: near nil registered manufacturing employment growth during period except a sharp rise in 1996
- Table and figure references preserved as described in the source (Tables 1–8, Figures 1–3).

*Source: _wp10218 - Section VI concludes.*

### REFERENCES

### _wp10218 - REFERENCES

### Labor market regulation, employment, and social insurance
- Agarwala, Ramgopal, and Zafar Khan, 2001, “Labor Market and Social Insurance Policy in India: A Case of Losing on Both Competitiveness and Caring,” International Bank for Reconstruction and Development/World Bank, Stock Number 37168.  
- Ahsan, Ahmad, and Carmen Pages, 2007, “Are All Labor Regulations Equal? Assessing the Effects of Job Security, Labor Dispute and Contract Labor Laws in India,” World Bank Policy Research Working Paper 4259.  
- Basu, Kaushik, Gary Fields, and Shub Debgupta, 2009, “Labor Retrenchment Laws and their Effect on Wages and Employment: A Theoretical,” In New and Enduring Themes in Development Economics, ed. Bhaskar Dutta, Tridip Ray, and E. Sommanathan, 181–206. Singapore: World Scientific Publishers.  
- Besley, Timothy, and Robin Burgess, 2004, ”Can Labor Regulation Hinder Economic Performance? Evidence from India,” Quarterly Journal of Economics, 119(1): 91–134.  
- Caballero, Ricardo, Kevin Cowan, Eduardo Engel, and Alejandro Micco, 2004, “Effective Labor Regulation and Microeconomic Flexibility,” National Bureau of Economic Research Working Paper 10744.  
- Datta Chaudhuri, Mrinal, 1996, “Labor Markets as Social Institutions in India,” Center for Institutional Reform and the Informal Sector, India Working Paper 10.  
- Menon, Nidhiya, and Paroma Sanyal, 2005, “Labor Disputes and the Economics of Firm Geography: A Study of Domestic Investment in India,” Economic Development and Cultural Change, 53(4): 825–54.  
- Rama, Martin, 2003, “Globalization and the Labor Market.” World Bank Research Observer, 18(2): 159–186.  
- Goldar, Bishwanath, 2002, “Trade Liberalization and Manufacturing Employment,” International Labor Organization Employment Paper 2002/34.  
- Hasan, Rana, Devashish Mitra, and K. V. Ramaswamy, 2007, “Trade Reforms, Labor Regulations and Labor Demand Elasticities: Empirical Evidence from India,” Review of Economics and Statistics, 89(3): 466–81.  
- Hasan, Rana, Devashish Mitra, and Beyza Ural, 2007, “Trade Liberalization, Labor-Market Institutions and Poverty Reduction: Evidence from Indian States,” India Policy Forum, 3: 71–122.  

### Trade liberalization, wages, inequality, and poverty
- Aghion, Philippe, Robin Burgess, Stephen Redding, and Fabrizio Zilibotti, 2008, “The Unequal Effects of Liberalization: Theory and Evidence from India,” American Economic Review, 94 (4): 1397–1412.  
- Attanasio, Orazio, Pinelopi Goldberg, and Nina Pavcnik, 2004, “Trade Reforms and Wage Inequality in Colombia,” Journal of Development Economics, 74(2): 331–366.  
- Bhagwati, Jagdish, 1993, India in Transition: Freeing the Economy, Oxford University Press.  
- Currie, Janet, and Ann Harrison, 1997, “Sharing the Costs: The Impact of Trade Reform on Capital and Labor in Morocco,” Journal of Labor Economics, 15(3), Part 2: 44–71.  
- Davidson, Carl, Lawrence Martin and Steven Matusz, 1999, “Trade and search generated unemployment,” Journal of International Economics, 48: 271–99.  
- Davis, Donald, 1996, “Trade Liberalization and Income Distribution,” National Bureau of Economic Research Working Paper 5693.  
- Edwards, Sebastian, 1998, “Openness, Productivity and Growth. What Do We Really Know?,” Economic Journal, 108(447): 383–98.  
- Feenstra, Robert, and Gordon Hanson, 1997, “Foreign Direct Investment and Relative Wages: Evidence from Mexico's Maquiladoras,” Journal of International Economics, 42(2): 371–93.  
- Feliciano, Zadia, 2001, “Workers and Trade Liberalization: The Impact of Trade Reforms in Mexico on Wages and Employment,” Industrial and Labor Relations Review, 55(1): 95–115.  
- Goldberg, Pinelopi, and Nina Pavcnik, 2005, “Trade, Wages, and the Political Economy of Trade Protection: Evidence from the Colombian Trade Reforms,” Journal of International Economics, 66(1): 75–105.  
- Goldberg, Pinelopi, and Nina Pavcnik, 2007a, “Distributional Effects of Globalization in Developing Countries,” Journal of Economic Literature, 45(1): 39–82.  
- Goldberg, Pinelopi, and Nina Pavcnik, 2007b. “The Effects of the Colombian Trade Liberalization on Urban Poverty.” In Globalization and Poverty, ed. Ann Harrison, 241–90. The University of Chicago Press.  
- Hanson, Gordon, 2007, “Globalization, Labor Income, and Poverty in Mexico,” In Globalization and Poverty, ed. Ann Harrison, 417–56. The University of Chicago Press.  
- Hanson, Gordon, and Ann Harrison, 1999, “Trade and wage inequality in Mexico,” Industrial and Labor Relations Review, 52(2): 271–88.  
- Harrison, Ann, and Gordon Hanson, 1999, “Who Gains From Trade Reform? Some Remaining Puzzles,” Journal of Development Economics, 59(1): 125–54.  
- Porto, Guido, 2006, “Using Survey Data to Assess the Distributional Effect of Trade Policy,” Journal of International Economics, 70(1): 140–60.  
- Revenga, Ana, 1997, “Employment and Wage Effects of Trade Liberalization: The Case of Mexican Manufacturing.” Journal of Labor Economics, 15(3): 20–43.  
- Topalova, Petia, 2004, “The Effect of Trade Liberalization on Productivity: The Case of India.” IMF Working Paper 04/28.  
- Topalova, Petia, 2005, “Factor Immobility and Regional Impacts of Trade Liberalization: Evidence on Poverty and Inequality from India.” Unpublished.  
- Topalova, Petia, 2007, “Trade Liberalization, Poverty and Inequality: Evidence from Indian Districts.” In Globalization and Poverty, ed. Ann Harrison, 291–336. The University of Chicago Press.  
- Wacziarg, Romain, and Jessica Wallack, 2004, “Trade Liberalization and Intersectoral Labor Movements.” Journal of International Economics, 64(2): 411–39.  

### India-focused empirical studies and policy assessments
- Ahluwalia, Montek, 1999, “India's Economic Reforms. An Appraisal” In India in the Era of Economic Reforms, ed. Jeffrey Sachs, Ashutosh Varshney and Nirupam Bajpai, 26–80, Delhi: Oxford University Press.  
- Ahluwalia, Montek, 2002, “State-Level Performance Under Economic Reforms in India?” In Economic Policy Reforms and the Indian Economy, ed. Ann Krueger, 91–122. USA: University of Chicago Press.  
- Bhagwati, Jagdish, 1993, India in Transition: Freeing the Economy, Oxford University Press.  
- Cerra, Valerie, and Sweta Saxena, 2000, “What Caused the 1991 Currency Crisis in India?,” International Monetary Fund Working Paper No. 00/157.  
- Chopra, Ajai, Charles Collyns, Richard Hemming, Karen Parker, Woosik Chu, and Oliver Fratzscher, 1995, “India: Economic Reform and Growth,” International Monetary Fund Occasional Paper No. 134.  
- Datt, Gaurav, and Martin Ravallion, 2002, “Is India's Economic Growth Leaving the Poor Behind,” Journal of Economic Perspectives, 16(3): 89–108.  
- Deaton, Angus, 2003a, “Adjusted Indian Poverty Estimates for 1999–2000,” Economic and Political Weekly, pp. 322–326.  
- Deaton, Angus, 2003b, “Prices and Poverty in India, 1987–2000.” Economic and Political Weekly, pp. 362–368.  
- Goswami, O., A.K. Arun, S. Gantakolla, V. More, A. Mookherjee, D. Dollar, T. Mengistae, M. Hallward-Driemier, and G. Iarossi, 2002, “Competitiveness of Indian Manufacturing. Results From a Firm-Level Survey,” Confederation of Indian Industry and World Bank, 2002.  
- Goyal, S.K. 1996, “Political Economy of India's Economic Reforms,” Institute for Studies in Industrial Development (ISID) Working Paper, October 1996.  
- Hasan, Rana, 2002, “The Impact of Imported and Domestic Technologies on the Productivity of Firms: Panel Data Evidence From Indian Manufacturing Firms,” Journal of Development Economics, 69(1): 23–49.  
- Rajan, Ramikeshen S, 2002, “Trade Liberalization and Poverty: Revisiting the Age-Old Debate.” University of Adelaide, Australia, mimeo.  
- Varshney, Ashutosh, 1999, “Mass Politics or Elite Politics? India's Economic Reforms in Comparative Perspective.” In India in the Era of Economic Reforms, ed. Jeffrey Sachs, Ashutosh Varshney and Nirupam Bajpai, 222–60. Delhi: Oxford University Press.  

### Theoretical foundations, methods, and cross-country evidence
- Blanchard, Olivier, and Justin Wolfers, 2000, “The Role of Shocks and Institutions in the Rise of European Unemployment: the Aggregate Evidence,” Economic Journal, 110: 1–33.  
- Corden, Max W, 1966, “The Structure of a Tariff System and the Effective Protective Rate,” Journal of Political Economy, 74, (June): 221–237.  
- Davis, Steven, John Haltiwanger, and Scott Schuh, 1996, Job Creation and Destruction. Cambridge, MA: MIT Press.  
- Deaton, Angus, (various), 2003a and 2003b, on Indian poverty and prices in Economic and Political Weekly.  
- Dollar, David, and Aart Kraay, 2002, “Growth is Good for the Poor.” Journal of Economic Growth, 7(3): 195–225.  
- Dollar, David, Guiseppe Iarossi, and Taye Mengistae, 2002, “Investment Climate and Economic Performance: Some Firm Level Evidence from India,” Center for Research on Economic Development and Policy Reform Working Paper 143.  
- Edwards, Sebastian, 1998, “Openness, Productivity and Growth. What Do We Really Know?,” Economic Journal, 108(447): 383–98.  
- Grossman, Gene, 1984, International Competition and the Unionized Sector, Canadian Journal of Economics, 17(3): 541–56.  
- Grossman, Gene, 1986, “Imports as a Cause of Injury: The Case of the U.S. Steel Industry,” Journal of International Economics, 20(3–4): 201–23.  
- Grossman, Gene, and Elhanan Helpman, 2002, Interest Group and Trade Policy, Princeton University Press.  
- Krueger, Alan, and Lawrence Summers, 1988, “Efficiency Wages and the Inter-Industry Wage Structure,” Econometrica, 56(2): 259–93.  
- Lundberg, Mattias, and Lyn Squire, 2003, “The Simultaneous Evolution of Growth and Inequality,” Economic Journal, 113(487): 326–44.  
- Mayer, Wolfgang, 1974, “Short-Run and Long-Run Equilibrium for a Small Open Economy,” Journal of Political Economy, 82(5): 955–67.  
- Milanovic, Branko, 2002, “Can We Discern the Effect of Globalization on Income Distribution? Evidence from Household Budget Surveys,” World Bank Research Paper 2876.  
- Papageorgiou, Demetris, Michael Michaely, and Armeane Choksi, 1991, Liberalizing foreign trade, Cambridge, Mass. and Oxford: Blackwell.  
- Porto, Guido, 2006, “Using Survey Data to Assess the Distributional Effect of Trade Policy,” Journal of International Economics, 70(1): 140–60.  
- Roberts, Mark, and James Tybout, 1996, Industrial evolution in developing countries: Micro patterns of turnover, productivity, and market structure. Oxford and New York: Oxford University Press.  
- Sachs, Jeffrey, Ashutosh Varshney, and Nirupam Bajpai, 1999, India in the Era of Economic Reforms. Oxford University Press, 1999.  
- Stiglitz, Joseph, 1970, “Factor Price Equalization in a Dynamic Economy.” Journal of Political Economy, 78(3): 456–88.  
- Wacziarg, Romain, and Jessica Wallack, 2004, “Trade Liberalization and Intersectoral Labor Movements.” Journal of International Economics, 64(2): 411–39.  

*References list as presented in the source PDF.*

---


_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2010/_wp10218.pdf_