Product Market Reform and Growth:
New Country-Sector-Level Evidence
Romain Duval (IMF)
with Romain Bouis and Johannes Eugster (IMF)
2017 Annual Meetings of the ASSA
Chicago, January 7th, 2017
1
Introduction: literature
• Voluminous theoretical and empirical (macro, sector and firm-level) literature
on impact of product market deregulation on output through higher
productivity and/or employment:
– Theory: Blanchard and Giavazzi, 2003; Ebell and Haefke, 2009; Fang and
Rogerson, 2011; Felbermayr and Prat, 2011
– Country/sector-level empirical studies: Aghion et al., 2009; Alesina et al.,
2005; Bassanini and Duval, 2009; Barone and Cingano, 2011; Bourlès et
al., 2013; Cette et al., 2016; Conway et al., 2006; Egert, 2016; Fiori et al.,
2012; Inklaar et al., 2008; Nicoletti and Scarpetta, 2003
– Firm-level empirical studies: Aghion et al., 2004, 2009; Gal and Hijzen,
2016
2
Introduction: short-term effects of
deregulation
• Short-term/dynamic effects of product market deregulation largely unknown:
– Literature has focused on long-term effect (theory, country/sector-level
studies), or short-term firm-level effect without addressing GE effect (firmlevel studies)
• Theory unsettled—product and labor market frictions could imply ST costs
(Cacciatore and Fiori, 2015; Cacciatore, Duval, Ghironi and Fiori, 2016a,b):
– Standard DSGE models fail to capture the relevant frictions.
– Disappearance of incumbents and associated sunk costs (e.g. loss of firmspecific human capital); sunk entry costs need to be financed.
– Non-profit maximization and X-inefficiency, firm strategic behavior (strategic
capital accumulation vs. scrapping).
3
Introduction: this paper
• Empirical analysis of dynamic effects of product market deregulation in
network industries at country-sector level
• New, unique dataset of major reform shocks in electricity and gas, rail and
road transport, air transport, telecoms, postal services for 26 countries
over 1970-2013.
• Dynamic impact at country-sector level estimated through local projection
method (Jorda AER 2005) used e.g. by Romer & Romer AER 2015 for
impact of financial crises.
• Novel instrumentation of reform shocks using instruments derived from
legislative and political economy considerations.
4
Data
• Duval, Furceri, Jalles and Nguyen (forthcoming): “narrative” approach to
identify major legislative and regulatory actions based on OECD Economic
Surveys and additional country-specific sources. See e.g. Romer and Romer’s
papers on fiscal, monetary and—closest to our paper—financial crisis shocks.
• Alternative criteria to identify reforms: (i) normative language; (ii) actions
mentioned several times across different surveys and/or in retrospective
assessments; (iii) large corresponding changes in OECD ETCR indicators.
• Advantages compared to existing databases: (i) identification of major events;
(ii) exact timing; (iii) exact actions underpinning indicator changes; (iv) larger
country and time coverage.
• Shortcomings: (i) reforms may be endogenous -> issue addressed in the
empirical analysis; (ii) heterogeneity of reform shocks -> average historical
impact estimated.
• Mapped with OECD STAN ISIC Rev-4 data on outcomes (Y, L, Y/L, I, P,
5
extrapolated backward using ISIC Rev-3 data in some cases).
Histogram of reform shocks
25
D35 - Electricty & Gas
D49 - Rail & Road
20
D51 - Air Transport
D53 - Postal Services
15
D61 - Telecommunication
10
5
2013
2011
2009
2007
2005
2003
2001
1999
1997
1995
1993
1991
1989
1987
1985
1983
1981
1979
1977
1975
0
6
Descriptive statistics: differences in
differences
Reform vs. No-Reform Observations
Pre-post reform differences from non-reforming observations
pct pts
20
15
10
5
0
-5
-10
-15
-20
Real VA
Relative Price
Employment
Investment
Productivity
Difference of average differences (in percentage points) of cumulative 5-year growth of “Reform” versus “No
Reform” observations, over [T-5; T] and [T; T+5] respectively for the Pre-Reform and for the Post-Reform periods,
where T is the year a major reform is observed in a particular country/sector (using joint reforms in case of “rail and
road” and “electricity and gas”). The “Reform” observations are country/sector observations which experienced a
major reform in year T. The “No Reform” observations are observations of the same sector as the “Reform”
observations in a different country but which did not experience any major reform over a 10-year window
surrounding year T.
7
Empirical methodology
• Local projection method:
yc,s,t+j – yc,s,t =0 + ct + cs + trends
+ 𝛽𝑗 ∗ 𝑟𝑒𝑓𝑜𝑟𝑚𝑐,𝑠,𝑡 +
𝑗
𝑘=1 𝛾𝑘
∗ 𝑐𝑜𝑛𝑡𝑟𝑜𝑙𝑠𝑐,𝑠,𝑡+𝑘 + cst
• Instrumentation: 3 instruments:
– External pressure: presence of competition-related EU Directive (D = 1 if
Directive adopted over the past 5 years but not yet implemented in the
country considered)
– Peer pressure: number of other countries having carried out reform in
the same sector over the past 3 years.
– Scope for reform: initial stance of regulation in sector considered,
measured as OECD regulatory indicator value lagged three years
8
OLS results
Relative Prices
20
5
15
0
Percentage Points
Percentage Points
Real Value Added
10
-5
-10
5
-15
0
0
1
2
3
4
-20
-5
0
Number of Years after the Shock
2
3
4
3
4
Number of Years after the Shock
Labor Productivity
Employment
20
15
15
Percentage Points
10
Percentage Points
1
5
0
-5
10
5
0
-5
0
1
2
Number of Years after the Shock
3
4
0
1
2
Number of Years after the Shock
Baseline Results with Country-Industry and Country-Year FE and Industry-specific trend. Cluster robust
standard errors at country-industry level. Dotted lines indicate 90%- and 95% confidence intervals.
9
IV results
Relative Prices
10
20
0
Percentage Points
Percentage Points
Real Value Added
30
10
-10
0
-20
-10
-30
0
1
2
3
4
0
1
2
3
4
3
4
Number of Years after the Shock
Number of Years after the Shock
Employment
Labor productivity
15
20
Percentage Points
Percentage Points
10
5
0
-5
-10
10
0
0
1
2
-10
0
1
2
Number of Years after the Shock
3
4
Number of Years after the Shock
IV Results with Country-Industry and Country-Year FE and Industry-specific trend. Cluster robust standard errors
at country-industry level. Dotted lines indicate 90%- and 95% confidence intervals.
10
Conclusion
• New analysis of dynamic growth impact of product market deregulation in
network industries, applying local projection method with novel IV strategy
to new “narrative” dataset of major reform shocks
• Large medium-term gains from major reform in deregulated industries: 1014% increase in real VA after 5 years, on average
• Mostly a productivity effect, concomitant with relative (VA) price decline
• Gains materialize only gradually (no significant effect before about 3 years)
but no evidence of short-term costs.
• No significant effect at sector level on employment and investment:
downsizing of incumbents vs. entry of new firms?
• Significant employment gains where job protection is more stringent,
however, in line with economic theory (see paper)
11
Supplementary Slides
12
IV estimation: rationale
Reform vs. No-Reform Observations
pre- and post reform differences from non-reforming countries
pct pts
15
10
5
0
-5
-10
-15
-20
Real VA
Relative Price
Employment
Pre-Reform
Investment
Productivity
Post-Reform
Average differences (in percentage points) of cumulative 5-year growth of “Reform” versus “No Reform”
observations, over [T-5; T] and [T; T+5] respectively for the Pre-Reform and for the Post-Reform periods, where T is
the year a major reform is observed in a particular country/sector (using joint reforms in case of “rail and road” and
“electricity and gas”). The “Reform” observations are country/sector observations which experienced a major reform
in year T. The “No Reform” observations are observations of the same sector as the “Reform” observations in a
different country but which did not experience any major reform over a 10-year window surrounding year T.
13
OLS results: real value added
Effect of Reform Shock on Value-Added
(1)
(2)
t
t+1
Reform Shock
0.62
2.98
(1.36)
(2.21)
Country-Year FE
Yes
Yes
Country-Ind. FE
Yes
Yes
Ind.-specific Trend
Yes
Yes
N
2269
2181
(3)
t+2
4.54
(3.20)
Yes
Yes
Yes
2093
(4)
t+3
7.31*
(3.69)
Yes
Yes
Yes
2005
(5)
t+4
10.09**
(4.66)
Yes
Yes
Yes
1917
The dependent va ri a bl e i s the l og di fference of rea l va l ue a dded between yea r t-1,
the yea r precedi ng the s hock, a nd yea r t+j. Cl us ter robus t s tanda rd errors a re
reported i n pa renthes es . *,**, a nd *** denote s tatis tica l s i gni fi ca nce a t the 10, 5,
a nd 1% l evel s , res pectivel y.
(6)
t+5
12.76**
(5.14)
Yes
Yes
Yes
1829
14
IV results: real value added
Effect of Reform Shock on Value-Added
(1)
(2)
t
t+1
Reform Shock
-1.13
2.09
(1.86)
(2.98)
N
2264
2181
1st Stage F
243.54
228.05
(3)
t+2
3.46
(3.84)
2093
205.49
(4)
t+3
9.26**
(4.00)
2005
177.80
(5)
(6)
t+4
t+5
13.66*** 17.55***
(5.08)
(5.53)
1917
1829
206.74
207.30
The dependent variable is the log difference of real value added between year t-1,
the year preceding the s hock, and year t+j. Clus ter robus t s tandard errors are
reported in parenthes es . *,**, and *** denote s tatis tical s ignificance at the 10, 5,
and 1% levels , res pectively.
15