competition policy and productivity growth: an empirical analysis paolo buccirossi (lear) lorenzo...

Competition Policy and Productivity Growth: An Empirical AnalysisPaolo Buccirossi (LEAR)

Lorenzo Ciari (European University Institute & LEAR)Tomaso Duso (Humboldt University & WZB)Giancarlo Spagnolo (University of Rome Tor Vergata, SSE, & CEPR)Cristiana Vitale (LEAR)

ACLE conference “To Enforce and Comply“March 5-6, 2009

Tomaso Duso Competition Policy and Productivity Growth

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The Main Objective of this Study

We aim at analyzing the effectivenesseffectiveness of competition policy This is a difficult empirical task because:

1. One has to define and measure the objectivesobjectives of competition policy

2. One has to be able to measuremeasure the policy

Moreover, competition policy is just one dimension of a more general system of institutionssystem of institutions

Hence, to cleanly identify the effectiveness of competition policy we have to look at interactionsinteractions among different institutions/polices


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Competition Policy: Definition and Objective The term competition policycompetition policy refers to:

Competition legislation: Competition legislation: Set of prohibitions and obligations including merger control provisions that firms have to comply with

Its enforcementenforcement: An array of tools for policingtools for policing their behavior and and punishingpunishing any violation

The main objective of a competition policy regime is to achieve an efficient allocationefficient allocation of resources

It does this by deterring firms by deterring firms from undertaking any behavior that reduces social welfare by distorting competition, while not frightening any behavior that improves social welfare (no over-no over-deterrencedeterrence)

To directly measure deterrence is particularly difficult since it is impossible to directly observe intentionsimpossible to directly observe intentions if these do not materialize into actions


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Deterrence: Competition Policy Variables The optimal level of deterrenceoptimal level of deterrence is determined by 1) the size

of the sanctionssanctions 2) the (perceived) probability of detectiondetection and convictionconviction, and 3) the (perceived) probability of errorserrors

The following policy variables affect these three factors the formal independenceformal independence of the CA with respect to political or

economic interests the degree of separationdegree of separation between the adjudicator and the

prosecutor the quality of the lawquality of the law on the books the level of losslevel of loss that firms (and their employees) can expect to

suffer as a consequence of a conviction the type of investigative powerstype of investigative powers held by the CA the amount and quality of the financial and human resources financial and human resources

of the CA (budget and the skills of CA’s staff)


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The Competition Policy Indexes (CPIs) We submitted a set of tailored questionnairestailored questionnaires to the CAs in

13 jurisdictions13 jurisdictions and integrated them with information from the OECD country studiescountry studies and from the CAs’ own websitesCAs’ own websites

We obtained information on each of the six policy variableseach of the six policy variables identified as determinants of deterrence, separately separately for each type of possible competition law infringement (hard-core hard-core cartelscartels, abusesabuses, other infringementsother infringements) and for mergersmergers

Each piece of information at each step of the aggregation process was assigned a score/weightscore/weight on a scale of 0-1 against a benchmark of generally agreed best practiceagreed best practice

We have tested the sensitivity of the LCPIs to alternative weighting schemes using 1) a random weightsrandom weights technique and 2) factor analysisfactor analysis


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The Empirical Approach: The TFP Model As a measure of efficiency efficiency we propose to use TFP growth

The proposed specification builds on two recent papers by Nicoletti and Scarpetta (EP, 2003) and Griffith, Redding, and van Reenen (REStat 2004). The equation we estimate with a three-three-dimensional (country, industry, time) panel datadimensional (country, industry, time) panel data approach is:

where TFPLjt is the TFP level in the country on the productivity productivity

frontierfrontier, (TFPijt/TFPLjt) represents the productivity gapproductivity gap with this country, X and Z are sets of control variables (R&D, PMR, human capital, trade openness, and the quality of institutions) and are country-industry and time fixed effects

ijttijitijtLjt

ijtijtLjtitijt uZXTFP

TFPTFPLCPITFP

111

tij and


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The Empirical Approach: Measuring TFP

The dependent variable, TFP, is calculated using a growthgrowth accounting technique accounting technique based on the Solow residual Solow residual

Following Griffith et al. (2004) we correct this measure for differences across countries in hours worked and markups

The price cost margins price cost margins (PCM) are calculated as the ratio of value added in industry j of country i at time t over the sum of the relative variable labor and capital costs (Griffith et al. 2006):


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Endogeneity Issue The major empirical problem is the possible endogeneityendogeneity of the

CPIs. There are two potential sources of endogeneity: omitted variablesomitted variables two-way causalitytwo-way causality

To mitigate the first, we included all possible controlscontrols based on the existing literature on the determinants of TFP. Moreover, panel data allows us to control for time invariant unobserved individual time invariant unobserved individual heterogeneityheterogeneity

Three steps can be taken to tackle the problem of two-way two-way causalitycausality:

Lagging Lagging the potentially endogenous explanatory variables Aggregating Aggregating the features of the competition policy regime Using an Instrumental Variables Instrumental Variables (IV) approach. We propose

country specific political and institutional variables political and institutional variables as instruments


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The Data We selected 13 jurisdictions13 jurisdictions (Canada, Czech Republic, France,

Germany, Hungary, Italy, Japan, Netherlands, Spain, Sweden, UK, EUEU, and US) over the years from 1995 to 20051995 to 2005

For the countries that are part of the EUpart of the EU, we built a set of indexes that incorporate information on both national as well as EU competition policy regimes

For each jurisdiction, our sample includes 22 industries22 industries based on the definitions of the International Standard Industrial Classification (ISIC)

Data on TFP growth has been drawn from the KLEMS consortiumKLEMS consortium and from the Groningen Growth and Development CenterGroningen Growth and Development Center

Other data come from the OECD Structural Analysis (STANSTAN) database, the OECD Main Economic Indicators (MEIMEI) database, the OECD PMR databasePMR database, the OECD Analytical Business Enterprise Research and Development (ANBERDANBERD) database, and the World Bank Worldwide Governance Indicators (WGIWGI) database


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The Time Evolution of TFP and the Aggregate CPI

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1995 2000 2005 1995 2000 2005 1995 2000 2005 1995 2000 2005

Can Cze Fra Ger

Hun Ita Jap Net

Spa Swe UK USA

Mean TFP growth - corrected CPI

Mea

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FP

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cted

year

Graphs by country


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Main Results TFP: Aggregate CPI

Competition policy has a positive impact positive impact on TFP growth, and this is statistically significantstatistically significant at the 1% level

Once we include the EU dimension of the policy, the overall estimated effect appears much larger and still larger and still significantsignificant at the 1% level

We can reject the hypothesis of the policy being endogenous by using political variablespolitical variables (governments' type and their ideological position) as instruments

Controlling for institutionsinstitutions (contract enforcement and quality of the judiciary/law) does not alter our results. Yet, good institutions have a positive impact on TFP growth


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Main Results TFP: An Example

The coefficient estimates for the aggregate CPI imply an average elasticityaverage elasticity that ranges from 2.5% to 3.4%2.5% to 3.4%

To quantify the estimated effects we looked at a given country, for example the UKUK, in a specific industry, let’s say in “food food productsproducts”. Over the period 2001-2004, the average productivity growth rate was 2.23%.productivity growth rate was 2.23%. Our model implies that part of this growth rate is due to the effect of the improvement of competition policy

In the same period, the average growth rate of aggregate average growth rate of aggregate CPI was 4%CPI was 4%

Our estimates imply that, had competition policy not improved, the average TFP growth rate would have been TFP growth rate would have been between 2.05 and 2.1%between 2.05 and 2.1%


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Main Results: Sub-indexes

Both the Institutional CPI Institutional CPI and the Enforcement CPIEnforcement CPI coefficient are positive and significant positive and significant and have a similar quantitative impact

The Antitrust CPIAntitrust CPI coefficient is positive and strongly positive and strongly significantsignificant, while the Merger CPIMerger CPI coefficient is positive but less significantless significant

A positivepositive impact on the intensity of competition is suggested for the quality of the lawquality of the law and for the powers held by the CAspowers held by the CAs during the investigation

Also the resourcesresources held by the CAs have a positive impact on TFP growth


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Main Results: Robustness Checks The results are robust to the use of 1000 sets random random

weightsweights

The results are robust to the use of factor analysisfactor analysis to aggregate the information into several alternative indexes

The results are robust to the use of different TFP different TFP measuresmeasures (non-corrected for PCM) an aggregate aggregate measuremeasure of TFP at the country level

05

1015

2025

3035

4045

50F

requ

ency

.07 .08 .09 .1 CPI .12 .13 .14 .15Coefficient estimate for the CPI

Weights derived from 1000 draws form a uniform distribution (0,1)

Distribution of the estimated Coefficient


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Looking at country specific coefficients estimates we observe that CP has a significantly positive impact in SwedenSweden, UK UK, NetherlandNetherland, and Hungary Hungary, while it has a significantly negative impact in SpainSpain

We look at the interactionsinteractions between institutionsinstitutions and competition policy. CP has a significant impact only in countries with high enforcement of contractsenforcement of contracts high rule of lawrule of law highly impartial courtsimpartial courts highly independent judiciaryindependent judiciary

Moreover, only countries with EnglishEnglish legal origin do not present a significant coefficient for the CP while the effect is significantly higher in those with NordicNordic legal origin (Sweden)

Main Results: Heterogeneity


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Conclusions Competition policy appears to exert a significant and positive significant and positive

impact impact on efficiency. These results are robustrobust to several specification tests and estimation methods

In particular, alternative methodologies (e.g. random weightingrandom weighting, several kinds of factor analysisfactor analysis) to build the CPIs have been employed leading to similar qualitative and quantitative results

The powers held by the CAspowers held by the CAs during the investigations and the quality of the lawquality of the law seem to play the most important role in fostering TFP growth

To better identify competition policy effectiveness we look at how the quality of institutionsquality of institutions affects it. We find complementaritiescomplementarities between good judiciary institutions and good competition policy: the latter works better in countries with good institutions


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LSDV IV LSDV

TFP leader 0.102** 0.101*** 0.102**(0.0430) (0.0257) (0.0431)

L.Techno GAP 0.00124 0.00125 0.00124(0.00169) (0.00180) (0.00169)

L.R&D 0.00397** 0.00386*** 0.00407**(0.00155) (0.00123) (0.00158)

L.Human Capital 0.577** 0.556*** 0.628**(0.241) (0.204) (0.245)

L.PMR -0.0547*** -0.0578*** -0.0530***(0.0109) (0.0220) (0.0126)

L.CPI 0.110*** 0.151*(0.0131) (0.0836)

L.CPI EU 0.129***(0.0319)

Constant -0.224** -0.277*** 0.0378(0.0707) (0.0867) (0.0266)

Observations 1218 1218 1218


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L.CPI_CZE 0.017 0.036-0.0978 -0.156

L.CPI_FRA 0.347 1.076-0.367 -0.928

L.CPI_GER -0.411 -0.267-0.759 -0.489

L.CPI_HUN 0.619*** 0.766***-0.119 -0.103

L.CPI_ITA -0.88 -0.243-0.512 -0.285

L.CPI_NET 0.105** 0.0748*-0.0374 -0.0396

L.CPI_SPA -2.715*** -10.12***-0.712 -2.664

L.CPI_SWE 0.433** 0.295**-0.14 -0.109

L.CPI_UK 0.0735** 0.112-0.0255 -0.0633

L.CPI_USA 0.0814 0.177-0.265 -0.211

competition policy and productivity growth: an empirical analysis paolo buccirossi (lear) lorenzo...

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