Wo

rksh

op

pro

du

ctiv

ity

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

Wo

rksh

op

pro

du

ctiv

ity

Bern, Swit.16-10-2006

Outline

Introduction/background

Relation competition and innovation

2 research questions

Model for innovation and productivity

Data and empirical results

Concluding remarks

Wo

rksh

op

pro

du

ctiv

ity

Bern, Swit.16-10-2006

Background (I)

Dutch retail trade on its return?► 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

Source: GGDC,2005

Wo

rksh

op

pro

du

ctiv

ity

Bern, Swit.16-10-2006

Background (II):lack of competition and innovation?

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)

Wo

rksh

op

pro

du

ctiv

ity

Bern, Swit.16-10-2006

Competition and innovation:negative or positive?

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► Empirically supported by Aghion et al. (2005, QJE)

for UK

Wo

rksh

op

pro

du

ctiv

ity

Bern, Swit.16-10-2006

Competition and innovation: inverted U-curve?

Inverted U: composition effect► Weak competition:

– 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

Wo

rksh

op

pro

du

ctiv

ity

Bern, Swit.16-10-2006

Two questions

I. Did competition affect innovation in Dutch retail trade?

II. Did competition and innovation contribute to productivity growth in this industry?

Conclusion:

more competition in Dutch retail trade stimulates both innovation and productivity growth

Wo

rksh

op

pro

du

ctiv

ity

Bern, Swit.16-10-2006

Outline

Introduction/background

Relation competition and innovation

2 research questions

Model for innovation and productivity

Data and empirical results

Concluding remarks

Wo

rksh

op

pro

du

ctiv

ity

Bern, Swit.16-10-2006

Basic idea of CIP-model

Assume no feedback from P to C or from I to C

Competition (C)

Innovation(I)

Productivity (P)

Static efficiency

Dynamic efficiency

Inverted U-curve?

Wo

rksh

op

pro

du

ctiv

ity

Bern, Swit.16-10-2006

CIP-model

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

Wo

rksh

op

pro

du

ctiv

ity

Bern, Swit.16-10-2006

How to measure competition

We introduce a new measure, relative profits measure (RPM): ► 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

Wo

rksh

op

pro

du

ctiv

ity

Bern, Swit.16-10-2006

Cons traditional measures competition

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

Wo

rksh

op

pro

du

ctiv

ity

Bern, Swit.16-10-2006

Innovation: model

Explanation of innovation:

inn = α0 + α1 RPM + α2 RPM 2 + βms

with inn log innovation rate (firm level)

RPM competition indicator (5-digit industry level)

ms log market share (firm level)

Expectations► If inverted U: α1 > 0 and α2< 0

► Scale effect: β > 0

Wo

rksh

op

pro

du

ctiv

ity

Bern, Swit.16-10-2006

Productivity growth: model

Simple Cobb Douglas function:► 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)

Wo

rksh

op

pro

du

ctiv

ity

Bern, Swit.16-10-2006

Outline

Introduction/background

Relation competition and innovation

2 research questions

Model for innovation and productivity

Data and empirical results

Concluding remarks

Wo

rksh

op

pro

du

ctiv

ity

Bern, Swit.16-10-2006

Data and method

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

– Innovation outlays left censored: no innovation in 75% of firms

► Productivity based on OLS

Wo

rksh

op

pro

du

ctiv

ity

Bern, Swit.16-10-2006

Innovation results (I)

Estimation results of quadratic model (Tobit-I model)

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 21.65

Number of observations 1147

Left-censored observations 864

Log-likelihood 70.46

Source: own calculations based on PS- and CIS-dataa Scale parameter in the distribution used to normalize the underlying variable

No inverted U-relation !!

Wo

rksh

op

pro

du

ctiv

ity

Bern, Swit.16-10-2006

Innovation results (II):simplified model

Estimation results of linear model innovation (Tobit-I model)

Determinant Estimate t-value

Intercept 0.14 -9.08

Competition 0.02 4.31

Market share 0.24 5.14

Scale parameter a 0.10

Number of observations 1147

Left-censored observations 864

Log-likelihood 72.9

Source: own calculations based on PS- and CIS-dataa Scale parameter in the distribution used to normalize the underlying variable

Wo

rksh

op

pro

du

ctiv

ity

Bern, Swit.16-10-2006

Productivity growth results

Estimation results productivity, 1997-2001 a

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-dataa Incorporated years: 1997, 1999, and 2001, due to limited availability of innovation data

Wo

rksh

op

pro

du

ctiv

ity

Bern, Swit.16-10-2006

Concluding remarks

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► in the longer term by innovation