Services Reform and Manufacturing Performance: Evidence from India

Transcription

1 Services Reform and Manufacturing Performance: Evidence from India Jens M. Arnold, OECD Economics Dept. Molly Lipscomb, Notre Dame Beata S. Javorcik, Oxford Aaditya Mattoo, World Bank

2 India: Strong performance after 1991 reforms After a BOP crisis and IMF intervention in 1991, India embarked on a series of economic reforms, including: Goods trade liberalisation Industrial delicensing ( license raj ) Product market reforms in non-manufacturing services like telecommunications, transport services, banking and insurance. Manufacturing sector boomed after these reforms: 5.7% average annual growth rate over A link between policies and outcomes? While the former two are often mentioned as explanations for the subsequent economic boom, the latter is generally neglected in the literature.

3 Why services matter for manufacturing performance Services are an input into almost any manufacturing activity. Anti-competitive regulation implied: inefficient public monopolies no competitive pressure to deploy new services, cut prices or improve quality no foreign engagement, limited access to foreign know-how Liberalisation may affect: prices quality Variety of available producer services. Unlike in goods, the scope for importing is limited.

4 India s services policies changed profoundly Telecoms: 1992: first license to private telecoms provider 1994: new law improves environment for private investment, cellular licenses 2002: long-distance sector fully open, no limits on the number of providers FDI equity limits went from 0% to 74 or 100% Banking: 1994: first new private banking licenses issued 2001: interest rate deregulated 2002: FDI equity limits lifted to 49% But many restrictions remain in these sectors. (OECD Economic Survey of India, 2011)

5 Turnaround time at ports Phone faults Airline passengers Concentration in banking

6 Measuring policy reform Gathered detailed (qualitative) information on timing of policy reforms through local WB consultants. Consultants took stock of legal changes, conducted interviews with former government officials and business associations. Condensed this information into a quantitative policy index, following the template of the EBRD Transition Report 2004 (Scale 0-5).

7 The pace of services reform Policy index constructed for: -Telecoms -Banking -Transport -Insurance

8 Measuring manufacturing performance 3771 manufacturing firms over Data source: Capitaline data base Sample covers 62% of India s manufacturing output Estimate firm-level TFP using Ackerberg et al. (2006) method for 11 manufacturing industries Regress value added (net of real material, services and energy inputs) on real capital and labour inputs. Use material and services inputs as proxy for unobserved TFP shocks.

9 Linking services reform and manufacturing performance Use information from the Input-Output matrix on intersectoral linkages: Services _ Index reform jt jk where α jk is the share of inputs sourced by manufacturing sector j from services sector k. k kt Also create indices for individual services sectors, e.g. for banking: Banking _ Index reform jt j, banking bankingt, For banking, use Rajan-Zingales measure of financial dependence as robustness check.

10 Baseline estimation equation Regress TFP on I-O-weighted services index. Control for additional factors: Tariff protection in own sector Upstream tariff protection (using I-O-weights) Foreign ownership dummy Firm and time fixed effects lntfp ijt Services 1 _ index Tariff Input tariff jt 1 2 jt 1 3 jt 1 4 Foreign it i t it

11 Baseline results Table 4: Productivity Effects of Services Liberalization. Ackerberg et al. TFP Measure Services Index (t-1) Banking Index (t-1) Banking Index Rajan-Zingales weights (t-1) Telecom Index (t-1) Insurance Index (t-1) Transport Index (t-1) Tariffs (t-1) Input Tariffs (t-1) Foreign 1.171*** (0.227) 1.046*** 0.911*** (0.249) (0.245) 0.194*** 0.190*** (0.032) (0.040) 4.765*** 4.037*** (1.281) (1.213) (1.608) 1.649* (0.952) (0.994) (1.090) 3.675** 4.300** 3.000* (1.702) (1.660) (1.717) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.009) (0.009) (0.009) (0.009) (0.009) (0.008) (0.007) (0.007) * 0.030* 0.033** 0.035** 0.041** 0.032** 0.035** (0.017) (0.017) (0.017) (0.017) (0.017) (0.016) (0.016) (0.016) Observations 22,558 22,558 22,558 22,558 22,558 22,558 22,558 22,558 R-squared Number of firms Notes: The dependent variable is the log TFP estimated using the Ackerberg et al. method for each of the 11 industries listed in Table 2. All specifications include firm and year fixed effects. Robust standard errors, clustered at the industry-year level, are reported in parentheses. *** denotes significant at the 1 percent level, ** at the 5 percent level, * at the 10 percent level

12 Baseline results A one-standard-deviation improvement in overall services reform improves manufacturing productivity by 9.1%. Most robust results for telecoms, banking and transport Cannot identify a significant effect of tariff reductions. Foreign-owned firms are more productive. AND: Regulatory reform in services industries emerges as one of the key drivers of manufacturing performance.

13 Table 5: Differential Effect of Services Liberalization on Foreign Firms. Ackerberg et al. TFP Measure Services Index (t-1) Services Index (t-1)* Foreign Banking Index (t-1) Banking Index (t-1) * Foreign Banking Index Rajan-Zingales weights (t-1) Banking Index Rajan-Zingales weights (t-1) * Foreign Telecom Index (t-1) Telecom Index (t-1) * Foreign Insurance Index (t-1) Insurance Index (t-1) * Foreign Transport Index (t-1) Transport Index (t-1) * Foreign 1.106*** (0.236) 0.135** (0.063) 0.932*** 0.896*** (0.264) (0.263) 0.239** (0.115) (0.124) 0.182*** 0.186*** (0.034) (0.042) 0.026** (0.012) (0.022) 4.000*** 3.454** (1.391) (1.337) (1.706) 1.442*** 1.198** (0.454) (0.554) (0.595) (0.955) (0.955) (1.100) 2.061*** 1.630*** 1.626** (0.449) (0.508) (0.642) 3.659** 4.347*** 3.067* (1.700) (1.656) (1.715) 0.258* (0.135) (0.160) (0.178) Tariffs (t-1) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) Input Tariffs (t-1) (0.009) (0.009) (0.009) (0.009) (0.009) (0.008) (0.007) (0.007) Foreign Are foreign-owned firms particularly affected? ** (0.017) (0.017) (0.017) (0.017) (0.017) (0.016) (0.016) (0.016) Observations 22,558 22,558 22,558 22,558 22,558 22,558 22,558 22,558 R-squared Number of firms Notes: The dependent variable is the log TFP estimated using the Ackerberg et al. method for each of the 11 industries listed in Table 2. All specifications include firm and year fixed effects. Robust standard errors, clustered at the industry-year level, are reported in parentheses. *** denotes significant at the 1 percent level, ** at the 5 percent level, * at the 10 percent level

14 Addressing the possible endogeneity of policy reforms Instrument the pace of progress in policy reforms in India using proxies of services liberalisation in competitor economies. Idea: India will react to progress in competitor economies. Instrument: number of WTO commitments by China and Indonesia in each sector, weighted by I-O matrix Instruments vary across manufacturing sector and time and are specific to each services sector. Alternative: use all WTO members commitments.

15 Table 6: Productivity Effects of Services Liberalization. Instrumental variables approach using Ackerberg et al. TFP Second stage regressions Services Index (t-1) 1.277*** (0.260) Banking Index (t-1) 1.061*** 0.864*** (0.247) (0.280) Banking Index Rajan-Zingales weights 0.224*** (t-1) (0.056) (0.092) Telecom Index (t-1) 5.459*** 4.199*** 4.364** (1.469) (1.507) (2.153) Insurance Index (t-1) 2.527** 2.646* (1.139) (1.500) (2.671) ** 9.906* Transport Index (t-1) (4.206) (4.288) (5.759) Other covariates as before First stage regressions WTO commitments China 2.970*** 3.746*** *** 1.471*** 2.645*** 0.675*** (0.229) (0.288) (2.282) (0.199) (0.598) (0.196) WTO commitments Indonesia 0.564*** 0.210** *** 0.398** 4.972*** (0.141) (0.120) (1.665) (0.146) (0.198) (0.941) Tariffs (t-1) *** (0.0003) (0.0001) (0.0018) (0.0000) (0.0000) (0.0001) Input Tariffs (t-1) (0.0005) (0.0001) (0.0074) (0.0001) (0.0001) (0.0003) Foreign 0.003*** 0.001** * (0.001) (0.000) (0.009) (0.000) (0.000) (0.000) Test statistics Shea Partial R-squared F-stat p-value Underindentification test p-value Sargan test p-value

16 A simpler measure of services reform: Structural breaks Weighting the importance of different reforms is the most difficult part of constructing an index. Identifying the main reform is easier. Hence code a dummy for structural break, and apply I-O weights: Break jt = a jk I kt Can only be done for individual services sectors because timing is different for each of them.

17 Table 7: Productivity Effect of Services Liberalization, Structural Break Approach. Ackerberg et al. TFP measure Banking Break 2001 Rajan-Zingales Break 2001 Telecom Break 2002 Insurance Break 2002 A simpler measure of services reform: Structural breaks 2.626*** 2.269*** (0.641) (0.549) 0.484*** 0.408*** (0.081) (0.086) 8.126*** 6.226*** (2.347) (2.223) (2.632) 5.218** (2.227) (1.937) (2.180) Transport Break *** 8.528*** 7.511*** (2.628) (2.633) (2.681) Tariffs (t-1) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) Input Tariffs (t-1) (0.009) (0.009) (0.009) (0.009) (0.007) (0.006) (0.006) Foreign Dummy 0.029* 0.030* 0.034** 0.035** 0.043*** 0.034** 0.036** (0.017) (0.017) (0.017) (0.017) (0.016) (0.016) (0.016) Observations 22,558 22,558 22,558 22,558 22,558 22,558 22,558 Number of firms R-squared

18 Additional robustness checks Common upward trends: Try to falsify the structural break tests by including also dummies for the two years prior to the main reform. Common upward trends: Replace time dummies by sector-specific trends for manufacturing sectors. Alternative TFP measures: OLS regressions in one stage. Regress value added on labour, capital, services index, tariffs, foreign ownership and fixed effects. Autocorrelation: Follow procedure proposed by Bertrand et al. (2004).

19 Conclusions Previous explanations of India s post-1991 manufacturing success have ignored an essential factor: Product market reforms in services sectors. This paper demonstrates a strong and significant link between regulatory reforms in services and performance in downstream manufacturing sectors. Banking and telecommunications seem to have the most robust effects. Transport results are somewhat weaker, possibly because state-level variation is not well captured. Results are promising, given that there is still much scope for improving service sector policies in India (OECD, 2011).

20 Thank you for your attention.