Workshop productivity
Bern, Swit.
16-10-2006
Does competition stimulate innovation
and productivity in Dutch retail trade?
Henry van der Wiel
CPB Netherlands Bureau for Economic Policy Analysis
& CentER
OECD Workshop on Productivity Analysis and Measurement,
Bern, 16-18 October 2006
Outline
Workshop productivity
 Introduction/background
 Relation competition and innovation
 2 research questions
 Model for innovation and productivity
 Data and empirical results
Bern, Swit.
16-10-2006
 Concluding remarks
Background (I)
 Dutch retail trade on its return?
Workshop productivity
► Missed strong productivity growth of US since mid 1990s
► Gradually losing its strong position in EU since end of 1980s
Labour productivity (per hours worked) relative to EU-average (EU=100), 1979-2002
Bern, Swit.
16-10-2006
Source: GGDC,2005
Workshop productivity
Background (II):
lack of competition and innovation?
Bern, Swit.
16-10-2006
 General belief that competition may stimulate
productivity => static efficiency
► lower price margins
► efficient production (less X-inefficiencies)
 Likewise, innovation enhances productivity
(growth) => dynamic efficiency
 Dutch policy measures in 1990s focussed on
more competition
► New Competition Act in 1998
► Regulatory reforms in retail trade => longer opening
hours (1996)
Competition and innovation:
negative or positive?
Workshop productivity
 Negative relationship:
► Standard IO literature and most (early) endogenous
growth models
► Schumpeter model: competition reduces monopoly
rents and thus the expected pay off from innovation
 Positive relationship: mostly based on empirics
► Paper of Nickell (1996): competition is good for
innovation
 New development => inverted U-shaped curve
► Combining both theoretical ideas
Bern, Swit.
16-10-2006
► Empirically supported by Aghion et al. (2005, QJE)
for UK
Competition and innovation:
inverted U-curve?
 Inverted U: composition effect
Workshop productivity
► Weak competition:
Bern, Swit.
16-10-2006
– industry is relatively often in a level state =>
– increase in competition stimulates innovation by the
"escape" effect
► Intense competition:
– industry is often unlevelled=>
– increase in competition reduces innovation because
there is little incentive for laggards to catch up
Two questions
Workshop productivity
I.
Bern, Swit.
16-10-2006
II.

Did competition affect innovation in Dutch
retail trade?
Did competition and innovation contribute to
productivity growth in this industry?
Conclusion:
more competition in Dutch retail trade
stimulates both innovation and productivity
growth
Outline
Workshop productivity
 Introduction/background
 Relation competition and innovation
 2 research questions
 Model for innovation and productivity
 Data and empirical results
Bern, Swit.
16-10-2006
 Concluding remarks
Basic idea of CIP-model
Workshop productivity
 Assume no feedback from P to C or from I to C
Competition (C)
Static efficiency
Inverted U-curve?
Productivity (P)
Innovation(I)
Dynamic efficiency
Bern, Swit.
16-10-2006
Workshop productivity
CIP-model
Bern, Swit.
16-10-2006
 Presentation only focuses on results for
innovation and productivity
 Skip model for explaining competition (in
paper!), but not how to measure competition
 See also Creusen, Minne and Van der Wiel,
2006, in De Economist, September
How to measure competition
Workshop productivity
 We introduce a new measure, relative profits
measure (RPM):
Bern, Swit.
16-10-2006
► based on intuition that in a more competitive market,
firms are punished more harshly for being inefficient
 Firms differ in efficiency in terms of marginal
costs (or productivity level).
► Cost advantages lead up to higher profits
 We estimate for an industry the following
elasticity: percentage increase in profits due to
a 1 percent increase in efficiency
Workshop productivity
Cons traditional measures
competition
Bern, Swit.
16-10-2006
 Conventional ways of measuring competition
(concentration (H) and price cost margin (PCM)) are not
robust from a theoretical point of view
 Problem with H is that more aggressive conduct forces
inefficient firms out of the market thereby increasing
concentration
► It incorrectly suggests that competition is reduced
 As conduct becomes more aggressive, market share is
reallocated from inefficient firms (with low PCM) to
efficient firms (with high PCM) which tends to raise
industry wide PCM
► It incorrectly suggests that competition is reduced
Innovation: model
Workshop productivity
 Explanation of innovation:
inn = α0 + α1 RPM + α2 RPM 2 + βms
with
inn
log innovation rate (firm level)
RPM
ms
competition indicator (5-digit industry level)
log market share (firm level)
 Expectations
► If inverted U: α1 > 0 and α2< 0
► Scale effect: β > 0
Bern, Swit.
16-10-2006
Productivity growth: model
Workshop productivity
 Simple Cobb Douglas function:
Bern, Swit.
16-10-2006
► Split TFP-growth in contribution of competition and
innovation
 Explanation of labour productivity growth:
Δp = γ0 + γ1 ΔRPM + γ2 INN-1 + γ3 (Δk - Δl) + γ4 Δl
───────┬────────
TFP-growth
with Δp
labour productivity growth (firm level)
(Δk - Δl) capital intensity (firm level)
Δl
labour (economies of scale, firm level)
Outline
Workshop productivity
 Introduction/background
 Relation competition and innovation
 2 research questions
 Model for innovation and productivity
 Data and empirical results
Bern, Swit.
16-10-2006
 Concluding remarks
Data and method
Workshop productivity
 Firm-level data
► Two sources of Statistics Netherlands
– CIS-innovation surveys: 1996,1998 and 2000
– Annual surveys ‘Production Census’:1993-2002
► Matched both sources
– Number of observations ≈1150
 Regression methods:
► Innovation based on TOBIT I-method
Bern, Swit.
16-10-2006
– Innovation outlays left censored: no innovation in
75% of firms
► Productivity based on OLS
Innovation results (I)
Estimation results of quadratic model (Tobit-I model)
Workshop productivity
Determinant
Estimate
T-value
Intercept
−0.07
−1.76
Competition
−0.05
−1.50
Competition 2
0.02
2.22
Market share
0.24
4.59
Scale parameter a
Number of observations
Left-censored observations
21.65
No inverted
U-relation !!
Log-likelihood
Source: own calculations based on PS- and CIS-data
a Scale parameter in the distribution used to normalize the underlying variable
Bern, Swit.
16-10-2006
1147
864
 70.46
Innovation results (II):
simplified model
Workshop productivity
Estimation results of linear model innovation (Tobit-I model)
Determinant
Estimate
t-value
 0.14
-9.08
Competition
0.02
4.31
Market share
0.24
5.14
Intercept
Scale parameter
a
Number of observations
Left-censored observations
Log-likelihood
Bern, Swit.
16-10-2006
Source: own calculations based on PS- and CIS-data
a Scale parameter in the distribution used to normalize the underlying variable
0.10
1147
864
 72.9
Productivity growth results
Workshop productivity
Estimation results productivity, 1997-2001 a
Bern, Swit.
16-10-2006
Determinant
Estimate
T-value
Competition
0.07
1.91
Lagged innovation
0.01
2.19
Capital intensity
0.22
12.95
Labour (economies of scale)
 0.00
 0.45
Intercept
 0.02
 0.61
R-squared
0.17
Number of observations
883
Source: own calculations based on PS- and CIS-data
a Incorporated years: 1997, 1999, and 2001, due to limited availability of innovation data
Concluding remarks
Workshop productivity
 No inverted U-relationship in Dutch retail trade!
► positive relation between competition and innovation
 Both competition and innovation have a
positive impact on productivity growth
 So more competition in Dutch retail trade may
stimulate productivity growth
► in the short term by reductions in X-inefficiency
Bern, Swit.
16-10-2006
► in the longer term by innovation