Service regulation and growth: evidence from OECD countries

Federico CinganoBank of Italy

Guglielmo BaroneBank of Italy

Structural Reforms, Crisis, Exit Strategies and Growth

Paris, December 2010

• Worldwide trend toward more market-friendly regulatory frameworks and policies

– Regulatory barriers have fallen in many countries over time

• The economic crisis strengthened consensus about need for further deregulation:

– OECD Going for growth, Structural Policy Priorities

– EC proposal to monitor “growth enhancing” structural reforms within the new framework for strengthening EU economic governance

• But, do countries with lower anti-competitive regulation perform better economically?

Introduction

Introduction

• Large empirical support regarding the direct effects of regulation (static and dynamic efficiency arguments)

– Economy-wide restrictions as Red Tape restrict firms entry favouring concentration, reduces responsiveness to demand or technology shocks, ultimately lowering productivity growth (Fisman and Sarria Allende, 2004; Nicoletti and Scarpetta, 2005; Klapper et al 2006; Ciccone and Papaioannou, 2006).

– Industry-specific restrictions decrease investment and employment, and tend to increase price dynamics in regulated industries (Alesina et. al, 2004; Bertrand and Kramarz, 2002; Schivardi and Viviano; 2010)

• Less is known as to indirect effects, mediated by input-output linkages, i.e. from regulation in upstream markets to economic performance of downstream industries.

This paper: approach

• We examine whether countries with less regulation of a given service (s) see faster growth in manufacturing industries (j)using the service more intensively.

– Idea: Regulation-induced distortions in service markets (e.g. higher prices, lower quality) affect the patterns of resource allocation (e.g. investment decisions) across downstream manufacturing industries

– Identification: Intensity of consequences depends on each industry intensity in regulated services (“comparative (dis-)advantages”)

Service regulation (s)

Industrygrowth (j)

Industry service intensity (j,s)

This paper: approach

• Follow the approach pioneered for the case of financial development (Rajan and Zingales, 1998)

– Main dependent variable (SERVREGjc) is the interaction between an industry characteristic (service dependence, wjs) and a country characteristic (service regulation, Xsc). Hence, SERVREG measures the exposure of industry j to service regulation in country c.

– Look at cross-country, cross-industry (value added, productivity and export) growth, accounting for time invariant country and industry characteristics

• Est. eq.: gjc = β*SERVREGjc + µj + µc + εjc

• SERVREGj,c =Σs wjsXsc

Industry j dependence on service s

Service s regulation in country c

This paper: related literature

• Relates to the recent literature on the role of institutions and policies for resource allocation and comparative advantages.

– Claessens and Laeven (2003): intangible-assets intensive industries grow relatively faster in countries with better property rights protection.

– Nunn (2007) and Levchenko (2007): countries with better contract enforcement specialize in relationship-specific-investment intensive (and more “complex”) industries.

• Relates to recent OECD works on service regulation and technology absorption

– Conway et al, 2006; Arnold et al. 2008; Cette et al 2010.

• Country-industry-level (gjc): OECD-STAN dataset – Data on VA, exports and employment for 21 OECD countries and 15

industries. Years 1996-2002

• Country-level (Xc): OECD PMR database.

– Containing indicators on the degree of anti-competitive regulation: barriers to entry, restrictions to market conduct and degree of vertical integration

– Services: Energy, Professional services, Communications, Transports (0 to 6 from least to most restrictive). Year 1996.

• Industry-level: Downstream industries dependence on services (wj,s):

– Technical (/Leontief) coefficients from a benchmark-country (US) input-output matrix (i.e. wj,s = wUS

j,s)

Data and measures

Main findings – VA growth

( ) cjjcs

scsjcj XwAV ,,,, **ˆ εμμβ +++= ∑

Service-intensive industries grew more slowly in highly regulated countries

Main findings – VA growth

( ) cjjcs

scsjcj XwAV ,,,, **ˆ εμμβ +++= ∑

Service-intensive industries grew more slowly in highly regulated countries

Main findings – VA growth

( ) cjjcs

scsjcj XwAV ,,,, **ˆ εμμβ +++= ∑

Service-intensive industries grew more slowly in highly regulated countries

Main findings – VA growth

( ) cjjcs

scsjcj XwAV ,,,, **ˆ εμμβ +++= ∑

Service-intensive industries grew more slowly in highly regulated countries

Implied effects on growth: ∂g/∂w∂X

• Consider the annual VA Growth differential between a high service intensity industry (Pulp, paper and printing, 75th

percentile) and a low service intensity industry (Fabricated metal products, 25th percentile)

→ Estimates imply this differential is 0.75 percentage points higher when they operate in a low regulation than in a high regulation country (Canada vs. France) → For comparison, median VA growth in sample is 1.8%.

Main findings – Productivity growth

( ) cjjcs

scsjcj XwPL ,,,, **ˆ εμμβ +++= ∑

75°-25° percentile exercise = 0.9 pct points

Main findings – Export growth

( ) cjjcs

scsjcj XwPXE ,,,, **ˆ εμμβ +++= ∑

75°-25° percentile exercise = 1 pct point

Robustness: other forms of regulation

Robust to accounting for Labour mkt regulation, Red tape, FDI restrictions, public ownership

( ) cjjccjs

scsjcj gReOthervXwAV ,,,, )*(***ˆ εμμγβ ++++= ∑ (1) (2) (3) (4) (5) Employment

Protection Red tape FDI

regulationPublic Own.

All

Service regulation -0.191** -0.203** -0.182** -0.232** -0.272**[SERVREGj,c] (0.071) (0.067) (0.068) (0.074) (0.073)

Fin. dev. × external dep. 0.011** 0.010* 0.011** 0.010** 0.012** [FDc × EDj] (0.004) (0.004) (0.004) (0.004) (0.004)

Lab. market reg. × lab. int. -0.400 -0.578+ [LMRc × LABINTj] (0.323) (0.304)

Red tape costs × gr. opp. -1.449+ -1.599+ [COSTc × GROPj] (0.871) (0.871)

FDI restrictions 0.879 0.807 [FDIREGj,c] (0.794) (0.806) Public ownership 0.084+ 0.059 [POWNj,c] (0.047) (0.047) Observations 220 220 220 220 220 R-squared 0.68 0.68 0.68 0.68 0.70

Robustness: other sources of specialization

( ) cjjccjs

scsjcj WvXwAV ,,,, )*(***ˆ εμμγβ ++++= ∑ (1) (2) (3) (4) Human

Capital Physical Capital

Both Property Rights

Service regulation -0.154* -0.174* -0.154* -0.176* [SERVREGj,c] (0.066) (0.068) (0.067) (0.068) Financial dev. × external dep. 0.007+ 0.010* 0.007+ 0.010* [FDc × EDj] (0.004) (0.004) (0.004) (0.004) Human capital × 0.101* 0.101* skill intensity (0.048) (0.048) Physical capital × -0.468 0.082 physical capital intensity (2.885) (2.790) Property rights × -0.001 Intangible assets intensity (0.003) Observations 220 220 220 220 R-squared 0.69 0.67 0.69 0.67

Determinants of industry-specialization: human capital, physical capital and property right protection

Robustness: other checks

• Industry dependence:

– Experiment with US-1987 (as opposed to 1997), UK-1998 I-O weights,

– with fitted I-O weights following Ciccone and Papaioannou (2006) procedure

• Remove influential (country- industry-specific) observations

• Use OECD indicator of “regulation impact” as alternative measure

Main findings: service-specific effects

Previous results driven by regulation in professional services(entry barriers, mkt conduct) and energy (entry barriers, vertical integration)

( ) cjjcs

scsjscj XwAV ,,,, **ˆ εμμβ +++= ∑ (1) (2) (3) (4) (5) Energy

services Prof.

services Commun. services

Transp. services

All services

Energy Regulation × Energy dependence -0.482** -0.540* [Xc,ENERGY × wj, ENERGY] (0.147) (0.232)

Prof. Serv. Reg.n × Prof. Serv. dependence -0.286* -0.254* [Xc,PROSERV × wj, PROSERV] (0.124) (0.118)

Communications Regulation × Comm. dep. -0.417 0.115 [Xc,TLCPOST × wj,TLCPOST] (1.193) (1.147)

Transports Regulation × Transports dependence -0.231 0.101 [Xc,TRANSP × wj, TRANSP] (0.160) (0.247)

Financial dev. × external dep. 0.010* 0.011** 0.010* 0.011* 0.011** [FDc × EDj] (0.004) (0.004) (0.005) (0.005) (0.004)

Observations 220 220 220 220 220 R-squared 0.69 0.68 0.67 0.67 0.70

Implied effects on growth: ∂g/∂w∂X

• Professional services: Consider the annual VA Growth differential between a high service intensity industry (Chemicals) and a low service intensity industry (Fabricated metal product)

• Estimates imply this differential is 0.8 pct points higher in a low regulation than in a high regulation country (UK vs. Spain)

• Energy: even larger implied effects (1.4 pct points)

→ Empirical support to policy recommendations – “unbundling of network operation from supply and generation in

energy” (EC’s “Third Legislative Package on Energy Markets”, July 2009)

– “reform of unjustified restrictions in the professional services sector” (EC’s report on “Competition in Professional Services”, February 2004)

• We study the effects of anti-competitive service regulation by examining whether OECD countries with less anti-competitive regulation see better economic performance in manufacturing industries that use less-regulated services more intensively.

• Find that lower service regulation increases value added, productivity, and export growth in downstream, service intensive industries.

• Policy: results emphasize the beneficial growth effects from lowering regulation of professional services and energy provision.

• Future research: inside the transmission black box (micro data?)

Conclusions

Data – Oecd regulation indicators (Xc,s) in 1996

Data – Regulation indicators and market outcomeEnergy – price TLC – price

PS – price-cost margin Transport – price-cost margin

Data – countries & industries

UsaUsa

• Country-sector specific measures of service regulation (0 to 6; 0=full deregulation).

• Years: electricity, …, road = 1980-2003; Professional services = 1996 and 2003

Data – OECD regulation indicators (Xcs)

SECTOR Entry Barriers

Vertical Integration

Conduct regulation

Public Ownership

ENERGY

ELEC X X X GAS X X X

COMMUNICATION

TLC X X POST X X

TRANSPORTATION

AIR X X RAIL X X X

ROAD X

PROF. SERVICES LEGAL X X

ACCOUNT X X ARCH-ENG X X

Robs on VA growth: appropriateness of US weights

• Accounting for measurement error in wj,s if wj,s ≠ “true” weights. Following Ciccone and Papaioannu (2006):

For each service sector s:(1) regress cjcjcjcj Xw ,, νθλλ +++=

(2) compute *ˆˆˆ cjjj Xw θλ +=

where c* = most deregulated country for service s. It will not reflect input intensities that are regulation or country-specific

=> SERVREG = -0.193* (0.087) with c* = US (baseline -0.176**)=> SERVREG = -0.218* (0.105) with varying c* (baseline -0.176**)

Effects on country-industry deflators and nominal value added

APPENDIX Presentation