## 1. India: External Tariffs

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---

### Introduction
- Context: Trade liberalization became central to many countries’ development strategies over the past two decades.
- Competing views:
  - Pro-liberalization: opening markets and FDI improves domestic productivity and resource allocation.
  - Skeptical view: domestic firms may fail to adopt foreign technologies or face binding credit constraints, limiting gains from liberalization.
- Empirical background: Evidence on firm-level productivity effects of liberalization is mixed (examples cited: Tybout et al. (1991); Harrison (1994); Tybout and Westbrook (1995); Pavcnik (2002); Fernandes (2003)).
- Research questions:
  - Did India’s early-1990s trade reforms raise economy-wide and firm-level productivity?
  - How did firm and environment characteristics interact with the policy shock?
  - Were effects influenced by firm ownership or initial productivity?
  - Did state-level institutional features (financial development, investment climate, labor laws) matter?

### The case of India: the 1991 reforms
- Policy shock and context:
  - 1991: India requested a Stand-By Arrangement from the IMF; structural reforms included major trade liberalization.
  - Reforms included massive reductions in tariffs and non-tariff barriers and a reduction in the standard deviation of protection.
  - Government export-import policy (1992–97) sharply reduced role of import/export controls.
- Key numerical changes:
  - Share of products subject to quantitative restrictions fell from 87 percent in 1987/88 to 45 percent in 1994/95.
  - Average tariffs fell from more than 80 percent in 1990 to 37 percent in 1996.
  - The standard deviation of tariffs dropped by 50 percent during the same period.
  - Indian rupee devalued by 20 percent against the U.S. dollar in July 1991, with a further devaluation in February 1992; subsequently fully convertible for current account transactions.
  - Ratio of total trade to GDP rose from an average of 13 percent in the 1980s to nearly 19 percent of GDP in 1999/00.
  - Export and import volumes increased sharply from the early 1990s, outpacing growth in real output.
- Industry heterogeneity:
  - Most industries experienced a sharp tariff drop from 1991 to 1992, but the magnitude varied widely across industries.
- Political economy and timing:
  - Reforms in 1991–96 characterized as rapid and relatively comprehensive; authors treat tariff changes across industries in this window as plausibly exogenous.
  - Post-1996 (1997–2001) period shows evidence of more selective tariff-setting, heightening concerns about policy endogeneity in later years.

### Empirical strategy and data
- Productivity measurement:
  - Firm-level Hicks-neutral Total Factor Productivity (TFP) computed using Levinsohn and Petrin (2003) methodology (raw material inputs used as proxy to address simultaneity).
  - Assumed Cobb-Douglas production function; parameters estimated at 2–digit NIC level due to sample sizes.
  - Productivity index created as logarithmic deviation from a reference firm’s productivity in the industry in base year (1989/90).
- Baseline econometric specification:
  - prjit = α + β Tradej,t-1 + X•γ + Yt + Ij + υjit
    - prjit: productivity index for firm i in industry j at time t.
    - Tradej,t-1: lagged trade protection at the 4–digit NIC level (industry-level lagged nominal tariffs).
    - X: firm characteristics (age, age squared, ownership categories: private stand alone, private group, government-owned, foreign firms; size categories: large [top 1 percent by average sales], medium [> median excluding top 1 percentile], small [< median]).
    - Yt: year dummies; Ij: industry fixed effects.
  - Interest: coefficient β captures percentage change in firm-level productivity associated with industry-level differences in trade protection.
- Data:
  - Firm-level dataset from Prowess covering 1989–2001.
  - Approximately 4,100 individual manufacturing companies; 116 industries (4–digit NIC classification).
  - More than 5,000 HS product lines matched to 116 NIC codes to calculate average industry-level tariffs.
  - Variables deflated using price deflators from India’s national accounts statistics.
  - Primary measure of trade protection: lagged nominal tariffs (NTBs acknowledged as important but not fully included).
  - Authors prefer tariff measures over endogenous volume measures (e.g., import penetration).

### Endogeneity checks
- Tariff movement patterns:
  - 1989–96: majority of tariff changes across products moved uniformly (increased, decreased, or constant); policymakers less selective.
  - 1997–2001: tariff movements less uniform; evidence of selective changes.
- Test of tariff endogeneity:
  - Regressed industry-level tariffs in period t+1 on current industry-level productivity (average firm TFP weighted by sales), controlling for industry and year fixed effects and weighting by number of companies.
  - Results:
    - 1989–96: correlation between future tariffs and current productivity indistinguishable from zero.
    - 1997–2001: coefficient on current productivity negative and significant at the 1 percent level, suggesting tariffs may have been adjusted to reflect industries’ relative performance in this later period.
- Identification decision:
  - To avoid endogeneity bias, analysis is restricted to 1989–96 and uses lagged tariffs (Tradej,t-1). Industry fixed effects absorb time-invariant political-economy factors.

### Results and robustness — main quantitative findings
- Main empirical finding:
  - A decrease in tariffs by 10 percent leads to about 0.5 percent increase in TFP.
  - Trade liberalization (tariff reductions) raises productivity at the firm level and leads to faster productivity growth.
  - Evidence indicates productivity improvements occurred within surviving firms rather than being driven primarily by exit; exit rates in the sample are low and reestimating for firms in operation in 1996 leaves the positive impact of tariff reductions on productivity levels virtually unchanged.
- Magnitude and statistical significance (selected estimates):
  - Firm-level regressions (Table 3, Panel A) report negative and statistically significant coefficients on lagged tariffs; examples include:
    - Lagged Tariffs = -0.070 *** (column 1, Panel A)
    - Lagged Tariffs = -0.056 *** (column 5, Panel A)
    - Lagged Tariffs = -0.050 *** (column 7, Panel A)
  - Productivity growth (Table 3, Panel B) also shows negative coefficients on lagged tariffs, e.g.:
    - Lagged Tariffs = -0.021 ** (column 1, Panel B)
    - Lagged Tariffs = -0.044 ** (column 4, Panel B)
    - Lagged Tariffs = -0.086 *** (column 7, Panel B)
  - Industry-level aggregation (Table 4) retains negative and statistically significant effects:
    - Lagged tariffs = -0.066 * (Panel A, column 1)
    - Lagged tariffs = -0.043 ** (Panel A, column 2)
    - Lagged tariffs = -0.054 ** (Panel A, column 3)

### Heterogeneity by firm characteristics
- Ownership
  - Government owned companies are on average 10 percent less productive than private companies not associated with a business group; their TFP growth is also significantly smaller.
  - Productivity of public sector firms does not respond to trade liberalization; point estimates for public enterprises are much smaller in magnitude than for private enterprises (Table 5).
  - Foreign companies experienced no change in their productivity as a result of tariff reductions (column (5), Table 5).
- Business group membership and firm size
  - No significant difference in response between private stand-alone companies and companies belonging to a business group (columns (3) and (4), Table 5).
  - Firm size does not seem to affect the ability to respond to the trade liberalization shock (columns (14), (15) and (16), Table 5).
- Ownership concentration
  - Dispersed companies (promoters hold less than 50 percent of total equity) show a larger magnitude effect of trade liberalization than companies with concentrated ownership (columns (6) and (7), Table 5). Results are not always statistically different, but point estimates for concentrated ownership are much lower and often insignificant.
  - Bottom third (dispersed) vs top third (concentrated) in promoter share: effect larger for dispersed (columns (8) and (9), Table 5).
- Initial productivity
  - No compelling evidence that trade liberalization favored firms closer to the technological frontier. Splitting by average TFP in 1989–1991 above/below industry median yields no consistent differential impact (columns (10) and (11), Table 5).
  - Arellano Bond estimates suggest a possible higher rise for firms with higher initial productivity in some specifications, but results are not robust across specifications. Table 6 shows no consistent pattern for the interaction of lagged tariffs and pre-reform productivity; some specifications have a positive interaction term suggesting potential convergence.

### Environmental and regional heterogeneity
- Geography and market access
  - No significant difference in estimated impact across firms in coastal and non-coastal states; the point estimate is slightly higher for companies in non-coastal states (Table 7, columns (1) and (2)).
- Investment climate, financial development, and growth
  - Investment climate (Goswami et al. (2002) classification) shows little difference; if anything, firms in states with poor investment climate seem to benefit more from trade reforms (Table 7, columns (3) and (4)).
  - Level of financial development (credit per capita in 1992, above/below median) makes no meaningful difference to the estimated effect (columns (8) and (9), Table 7).
  - No evidence that firms in states with rapid pre-reform growth (1980s) or states with above median per capita income in 1991 reaped more benefit from trade liberalization (Table 7, columns (10)-(13)).
- Labor market institutions
  - No systematic difference in firms’ response to trade liberalization by the quality of state labor laws (pro-worker, neutral, pro-employer) (Table 7, columns (5)-(7)).

### Robustness, methodology, and data construction
- Identification and specification
  - Industry-specific tariff reduction exploited using inter-temporal and inter-industry variation from over 5,000 tariff line items during 1989–96.
  - Empirical specifications include year fixed effects and industry fixed effects (NIC 4-digit and NIC 2-digit in some regressions) to control for common secular trends and unobserved time-invariant political economy factors.
  - Regressions use lagged tariffs, which are more appropriate if productivity adjustments do not occur instantaneously.
- Estimators and checks
  - Results are robust across specifications: pooled industry regressions, firm fixed effects, inclusion of lagged total factor productivity, balanced panels, and Arellano Bond dynamic panel estimator.
  - Aggregating productivity to the 4-digit industry level and weighting by number of companies still yields a negative and statistically significant effect of lagged tariffs on productivity at the 1 percent level (Table 4, Panel A).
  - The effect of tariff reductions on productivity growth is similar in magnitude at industry level but statistically significant only under the Arellano Bond estimator.
- Data and production function estimation
  - Productivity estimation uses value of total output, gross fixed assets, salaries and wages, raw materials expenses, power and fuel expenses, and depreciation from CMIE company balance sheets and income statements.
  - Capital stock constructed following Balakrishnan et al. (2000) using a Perpetual Inventory Model, revaluation factor for replacement cost with a 20-year lifetime assumption, and deflation using gross capital formation series.

### Policy implications and conclusions
- Summary policy-relevant conclusions:
  - Trade liberalization in India caused increased firm-level efficiency; a 10 percent tariff decrease yields about 0.5 percent higher TFP.
  - Productivity gains are mainly due to efficiency improvements within firms, not large-scale exit of less productive firms.
  - Public sector firms do not appear to benefit from trade liberalization in terms of higher productivity; in an environment of weaker hard budget constraints, privatization could enhance the productivity gains from liberalization.
  - Other firm characteristics (size, initial productivity) and state-level environment factors (geography, institutions, financial development, investment climate) generally do not condition the transmission of the trade liberalization shock in a systematic way.
- Two lessons highlighted by the authors:
  - Trade policy may be strongly related to firm productivity when set absent of external pressure.
  - Liberalization can increase productivity but may deliver larger gains if combined with privatization of public firms.

*Source: _wp0428 - References (content excerpt).*

### 1. India: External Tariffs..............................................................................................

### 1. India: External Tariffs

### Major Sections
- 2. Evolution of Tariffs by Industry, 1987–2001 ................................................................7
- 3. Foreign Trade, 1980/81–2001/02...................................................................................9
- 4. Tariff Changes, 1988–2001 .........................................................................................14

### Tables (listed)
- 1. India: Non-Tariff Barriers on Imports .........................................................................21
- 2. Trade Policy Endogeneity: Effect of Current Productivity on Future Tariffs .............22
- 3. Effect of Trade Protection on Total Factor Productivity .............................................23
- 4. Effect of Trade Protection on Total Factor Productivity at the Industry Level ...........24
- 5. Firm Characteristics and the Effect of Trade Protection on Productivity....................25
- 6.         Relative         Initial         Productivity and the Effect of Trade Protection on Productivity........27
- 7. Geography, Institutions, Financial Development, and Growth and the Effect 
   of Trade Protection on Productivity...........................................................................28

### Appendices
- I. Estimating the Production Function.............................................................................30
- II.        Dataset Tables ..............................................................................................................31

*Source: _wp0428 - 1. India: External Tariffs..............................................................................................*

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

### _wp0428 - References

### Introduction
- Context: Trade liberalization became central to many countries’ development strategies over the past two decades.
- Competing views:
  - Pro-liberalization: opening markets and FDI improves domestic productivity and resource allocation.
  - Skeptical view: domestic firms may fail to adopt foreign technologies or face binding credit constraints, limiting gains from liberalization.
- Empirical background: Evidence on firm-level productivity effects of liberalization is mixed (examples cited: Tybout et al. (1991); Harrison (1994); Tybout and Westbrook (1995); Pavcnik (2002); Fernandes (2003)).
- Research questions addressed:
  - Did India’s early-1990s trade reforms raise economy-wide and firm-level productivity?
  - How did firm and environment characteristics interact with the policy shock?
  - Were effects influenced by firm ownership or initial productivity?
  - Did state-level institutional features (financial development, investment climate, labor laws) matter?

### The case of India: the 1991 reforms
- Policy shock and context:
  - 1991: India requested a Stand-By Arrangement from the IMF; structural reforms included major trade liberalization.
  - Reforms included massive reductions in tariffs and non-tariff barriers and a reduction in the standard deviation of protection.
  - Government export-import policy (1992–97) sharply reduced role of import/export controls.
- Key numerical changes:
  - Share of products subject to quantitative restrictions fell from 87 percent in 1987/88 to 45 percent in 1994/95.
  - Average tariffs fell from more than 80 percent in 1990 to 37 percent in 1996.
  - The standard deviation of tariffs dropped by 50 percent during the same period.
  - Indian rupee devalued by 20 percent against the U.S. dollar in July 1991, with a further devaluation in February 1992; subsequently fully convertible for current account transactions.
  - Ratio of total trade to GDP rose from an average of 13 percent in the 1980s to nearly 19 percent of GDP in 1999/00.
  - Export and import volumes increased sharply from the early 1990s, outpacing growth in real output.
- Industry heterogeneity:
  - Most industries experienced a sharp tariff drop from 1991 to 1992, but the magnitude varied widely across industries.
- Political economy and timing:
  - Reforms in 1991–96 characterized as rapid and relatively comprehensive; authors treat tariff changes across industries in this window as plausibly exogenous.
  - Post-1996 (1997–2001) period shows evidence of more selective tariff-setting, heightening concerns about policy endogeneity in later years.

### Empirical strategy and data
- Productivity measurement:
  - Firm-level Hicks-neutral Total Factor Productivity (TFP) computed using Levinsohn and Petrin (2003) methodology (raw material inputs used as proxy to address simultaneity).
  - Assumed Cobb-Douglas production function; parameters estimated at 2–digit NIC level due to sample sizes.
  - Productivity index created as logarithmic deviation from a reference firm’s productivity in the industry in base year (1989/90).
- Baseline econometric specification:
  - prjit = α + β Tradej,t-1 + X•γ + Yt + Ij + υjit
    - prjit: productivity index for firm i in industry j at time t.
    - Tradej,t-1: lagged trade protection at the 4–digit NIC level (industry-level lagged nominal tariffs).
    - X: firm characteristics (age, age squared, ownership categories: private stand alone, private group, government-owned, foreign firms; size categories: large [top 1 percent by average sales], medium [> median excluding top 1 percentile], small [< median]).
    - Yt: year dummies; Ij: industry fixed effects.
  - Interest: coefficient β captures percentage change in firm-level productivity associated with industry-level differences in trade protection.
- Data:
  - Firm-level dataset from Prowess covering 1989–2001.
  - Approximately 4,100 individual manufacturing companies; 116 industries (4–digit NIC classification).
  - More than 5,000 HS product lines matched to 116 NIC codes to calculate average industry-level tariffs.
  - Variables deflated using price deflators from India’s national accounts statistics.
  - Primary measure of trade protection: lagged nominal tariffs (NTBs acknowledged as important but not fully included).
  - Authors prefer tariff measures over endogenous volume measures (e.g., import penetration).

### Endogeneity checks
- Tariff movement patterns:
  - 1989–96: majority of tariff changes across products moved uniformly (increased, decreased, or constant); policymakers less selective.
  - 1997–2001: tariff movements less uniform; evidence of selective changes.
- Test of tariff endogeneity:
  - Regressed industry-level tariffs in period t+1 on current industry-level productivity (average firm TFP weighted by sales), controlling for industry and year fixed effects and weighting by number of companies.
  - Results:
    - 1989–96: correlation between future tariffs and current productivity indistinguishable from zero.
    - 1997–2001: coefficient on current productivity negative and significant at the 1 percent level, suggesting tariffs may have been adjusted to reflect industries’ relative performance in this later period.
- Identification decision:
  - To avoid endogeneity bias, analysis is restricted to 1989–96 and uses lagged tariffs (Tradej,t-1). Industry fixed effects absorb time-invariant political-economy factors.

### Results and robustness
- Main findings:
  - Reductions in trade protection lead to higher levels of productivity.
  - The negative coefficient on lagged trade protection (β) is negative and statistically significant at the 1 percent level across multiple specifications.
  - Effect heterogeneity by ownership:
    - Robust and highly statistically significant productivity gains for private companies.
    - No evidence of productivity improvements for government-owned or foreign companies following liberalization.
  - State-level characteristics (labor regulations, investment climate, financial development) do not appear to influence the effect of trade liberalization on productivity.
- Robustness checks and specifications:
  - Standard errors corrected for heteroskedasticity and clustered at industry–year level.
  - Specifications include: 4-digit industry fixed effects; 2-digit industry dummies; balanced panel; firm fixed effects; inclusion of lagged TFP to account for Markov process; Arellano-Bond panel estimator to address bias from lagged dependent variables.
- Note on magnitude:
  - The regression results report a statistically significant negative β implying that tariff reductions raise productivity; the text indicates "Since the productivity measure is in log terms, the estimated coefficient implies that a 10 percent reduction in tariffs (at the 4-digit industry level) will lead to about" (statement in source text is truncated at this point).

*Source: _wp0428 - References (content excerpt)._*

### 0.5 percent increase in TFP. The results are highly statistically significant, robust across

### _wp0428 - 0.5 percent increase in TFP. The results are highly statistically significant, robust across

### Main empirical finding
- A decrease in tariffs by 10 percent leads to about 0.5 percent increase in TFP.  
- Trade liberalization (tariff reductions) raises productivity at the firm level and leads to faster productivity growth.  
- Evidence indicates productivity improvements occurred within surviving firms rather than being driven primarily by exit; exit rates in the sample are low and reestimating for firms in operation in 1996 leaves the positive impact of tariff reductions on productivity levels virtually unchanged.

### Magnitude and statistical significance (selected estimates)
- Firm-level regressions (Table 3, Panel A) report negative and statistically significant coefficients on lagged tariffs; examples include:
  - Lagged Tariffs = -0.070 *** (column 1, Panel A)
  - Lagged Tariffs = -0.056 *** (column 5, Panel A)
  - Lagged Tariffs = -0.050 *** (column 7, Panel A)
- Productivity growth (Table 3, Panel B) also shows negative coefficients on lagged tariffs, e.g.:
  - Lagged Tariffs = -0.021 ** (column 1, Panel B)
  - Lagged Tariffs = -0.044 ** (column 4, Panel B)
  - Lagged Tariffs = -0.086 *** (column 7, Panel B)
- Industry-level aggregation (Table 4) retains negative and statistically significant effects:
  - Lagged tariffs = -0.066 * (Panel A, column 1)
  - Lagged tariffs = -0.043 ** (Panel A, column 2)
  - Lagged tariffs = -0.054 ** (Panel A, column 3)

### Heterogeneity by firm characteristics
- Ownership
  - Government owned companies are on average 10 percent less productive than private companies not associated with a business group; their TFP growth is also significantly smaller.
  - Productivity of public sector firms does not respond to trade liberalization; point estimates for public enterprises are much smaller in magnitude than for private enterprises (Table 5).
  - Foreign companies experienced no change in their productivity as a result of tariff reductions (column (5), Table 5).
- Business group membership and firm size
  - No significant difference in response between private stand-alone companies and companies belonging to a business group (columns (3) and (4), Table 5).
  - Firm size does not seem to affect the ability to respond to the trade liberalization shock (columns (14), (15) and (16), Table 5).
- Ownership concentration
  - Dispersed companies (promoters hold less than 50 percent of total equity) show a larger magnitude effect of trade liberalization than companies with concentrated ownership (columns (6) and (7), Table 5). Results are not always statistically different, but point estimates for concentrated ownership are much lower and often insignificant.
  - Bottom third (dispersed) vs top third (concentrated) in promoter share: effect larger for dispersed (columns (8) and (9), Table 5).
- Initial productivity
  - No compelling evidence that trade liberalization favored firms closer to the technological frontier. Splitting by average TFP in 1989–1991 above/below industry median yields no consistent differential impact (columns (10) and (11), Table 5).
  - Arellano Bond estimates suggest a possible higher rise for firms with higher initial productivity in some specifications, but results are not robust across specifications. Table 6 shows no consistent pattern for the interaction of lagged tariffs and pre-reform productivity; some specifications have a positive interaction term suggesting potential convergence.

### Environmental and regional heterogeneity
- Geography and market access
  - No significant difference in estimated impact across firms in coastal and non-coastal states; the point estimate is slightly higher for companies in non-coastal states (Table 7, columns (1) and (2)).
- Investment climate, financial development, and growth
  - Investment climate (Goswami et al. (2002) classification) shows little difference; if anything, firms in states with poor investment climate seem to benefit more from trade reforms (Table 7, columns (3) and (4)).
  - Level of financial development (credit per capita in 1992, above/below median) makes no meaningful difference to the estimated effect (columns (8) and (9), Table 7).
  - No evidence that firms in states with rapid pre-reform growth (1980s) or states with above median per capita income in 1991 reaped more benefit from trade liberalization (Table 7, columns (10)-(13)).
- Labor market institutions
  - No systematic difference in firms’ response to trade liberalization by the quality of state labor laws (pro-worker, neutral, pro-employer) (Table 7, columns (5)-(7)).

### Robustness and methodology
- Identification and specification
  - Industry-specific tariff reduction exploited using inter-temporal and inter-industry variation from over 5,000 tariff line items during 1989–96.
  - Empirical specifications include year fixed effects and industry fixed effects (NIC 4-digit and NIC 2-digit in some regressions) to control for common secular trends and unobserved time-invariant political economy factors.
  - Regressions use lagged tariffs, which are more appropriate if productivity adjustments do not occur instantaneously.
- Estimators and checks
  - Results are robust across specifications: pooled industry regressions, firm fixed effects, inclusion of lagged total factor productivity, balanced panels, and Arellano Bond dynamic panel estimator.
  - Aggregating productivity to the 4-digit industry level and weighting by number of companies still yields a negative and statistically significant effect of lagged tariffs on productivity at the 1 percent level (Table 4, Panel A).
  - The effect of tariff reductions on productivity growth is similar in magnitude at industry level but statistically significant only under the Arellano Bond estimator.

### Data and production function estimation
- Productivity estimation uses value of total output, gross fixed assets, salaries and wages, raw materials expenses, power and fuel expenses, and depreciation from CMIE company balance sheets and income statements.
- Capital stock constructed following Balakrishnan et al. (2000) using a Perpetual Inventory Model, revaluation factor for replacement cost with a 20-year lifetime assumption, and deflation using gross capital formation series.

### Policy implications and conclusions
- Trade liberalization in India caused increased firm-level efficiency; a 10 percent tariff decrease yields about 0.5 percent higher TFP.  
- Productivity gains are mainly due to efficiency improvements within firms, not large-scale exit of less productive firms.  
- Public sector firms do not appear to benefit from trade liberalization in terms of higher productivity; in an environment of weaker hard budget constraints, privatization could enhance the productivity gains from liberalization.  
- Other firm characteristics (size, initial productivity) and state-level environment factors (geography, institutions, financial development, investment climate) generally do not condition the transmission of the trade liberalization shock in a systematic way.  
- Two lessons: (1) trade policy may be strongly related to firm productivity when set absent of external pressure; (2) liberalization can increase productivity but may deliver larger gains if combined with privatization of public firms.

*Source: Author's estimates as presented in the provided text.*

### References

### References

### Cited works

- Aghion, P., R. Burgess, S. Redding and F. Zilibotti, 2003, “The Unequal Effects of Liberalization: Theory and Evidence from India,” unpublished.
- Aw, B., X. Chen, and M. Roberts, 2001, “Firm-Level Evidence on Productivity Differentials and Turnover in Taiwanese Manufacturing,” Journal of Development Economics, Vol. 66(1).
- Balakrishnan, P., K. Pushpangadan and M.S. Babu, 2000, “Trade Liberalization and Productivity Growth in Manufacturing: Evidence from Firm-Level Panel Data,” Economic and Political Weekly (October).
- Besley, T. and R. Burgess, 2003, “Can Labor Regulations Hinder Economic Performance? Evidence From India,” unpublished.
- Cerra, Valerie and Sweta Saxena, 2000, “What Caused the 1991 Currency Crisis in India?,” IMF WP/00/157 (October).
- Chopra, Ajai, Charles Collyns, Richard Hemming and Karen Parker, 1995, “India: Economic Reform and Growth,” IMF Occasional Paper No. 134 (December).
- Debroy B. and A. T. Santhanam, 1993, “Matching Trade Codes with Industrial Codes,” Foreign Trade Bulleting, Vol. 24(1).
- Epifani, P., 2003, “Trade Liberalization, Firm Performance and Labor Market Outcomes in the Developing World. What Can We Learn from Micro-Level Data?,” unpublished.
- Fernandes, Ana, 2003, “Trade Policy, Trade Volumes and Plant Level Productivity in Colombian Manufacturing Industries,” World Bank Policy Research Working Paper 3064.
- Goldar, B., 2002, “Trade Liberalization and Manufacturing Employment,” Employment Paper 2002/34, International Labor Organization.
- Goldberg, P. and N. Pavcnik, 2001, “Trade Protection and Wages: Evidence from the Colombian Trade Reforms,” NBER Working Paper 8575 (November).
- 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 (January).
- Grossman, G. and E. Helpman, 2002, Interest Groups and Trade Policy, Princeton University Press.
- Harrison, A., 1994, “Productivity, Imperfect Competition and Trade Reform,” Journal of International Economics, Vol. 36.
- Hasan, R., 2002, “The Impact of Imported and Domestic Technologies on the Productivity of Firms: Panel Data Evidence from Indian Manufacturing Firms,” Journal of Development Economics, Vol. 69.
- Hasan, R., D. Mitra and K. V. Ramaswamy, 2003, “Trade Reforms, Labor Regulations and Labor-Demand Elasticities: Evidence from India,” NBER Working Paper 9879, (July).
- Krishna, P. and D. Mitra, 1998, “Trade Liberalization, Market Discipline and Productivity Growth: New Evidence from India,” Journal of Development Economics, Vol. 56.
- Krueger, A., 2003, Heinz Arndt Memorial Lecture, (August).
- Levinsohn, J. and A. Petrin, 2003, “Estimating Production Functions Using Inputs to Control for Unobservables,” Review of Economic Studies, Vol. 70(243) (April).
- Melitz, Mark J., 2003, “The Impact of Trade on Intra-Industry Reallocations and Aggregate Industry Productivity, unpublished.
- Nouroz, H., 2001, Protection in Indian Manufacturing: An Empirical Study, MacMillan India Ltd., Delhi.
- Olley, G. S. and A. Pakes, 1996, “The Dynamics of Productivity in the Telecommunications Equipment Industry,” Econometrica, Vol. 64(6).
- Pavcnik, N., 2002, “Trade Liberalization, Exit and Productivity Improvements: Evidence from Chilean Plans,” Review of Economic Studies, Vol. 69(238).
- Shleifer, A., 1992, “State Versus Private Ownership,” Journal of Economic Perspectives, Vol. 12(4).
- Stiglitz, J., 2002, Globalization and Its Discontents, WW Norton and Co.
- Tybout, J., 2001, “Plant and Firm-Level Evidence on “New” Trade Theories,” NBER Working Paper 8418, August 2001.
- Tybout, J., J. De Melo, and V. Corbo, 1991, “The Effects of Trade Reforms on Scale and Technical Efficiency: New Evidence from Chile,” Journal of International Economics, Vol. 31.
- Tybout, J. and M. Westbrook, 1995, “Trade Liberalization and the Dimensions of Efficiency Change in the Mexican Manufacturing Industries,” Journal of International Economics, Vol. 39.
- Unel, Bulent, 2003, “Productivity Trends in India’s Manufacturing Sectors in the Last Two Decades,” IMF Working Paper, WP/03/22.
- World Bank, 1995, Bureaucrats in Business, London: Oxford University Press.
- Young, Alwyn, 1991, “Learning by Doing and the Dynamics Effects of International Trade,” Quarterly Journal of Economics, Vol. 10.

*Source: _wp0428 - References*

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