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Competition Policy and Productivity Growth: An Empirical Analysis

This study examines the effectiveness of competition policy in achieving efficient resource allocation and its impact on productivity growth. It analyzes the deterrence factors and measures the Competition Policy Indexes (CPIs) in various jurisdictions. The empirical approach uses Total Factor Productivity (TFP) growth as a measure of efficiency and addresses endogeneity issues.

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Competition Policy and Productivity Growth: An Empirical Analysis

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  1. Competition Policy and Productivity Growth: An Empirical Analysis Paolo 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

  2. The Main Objective of this Study • We aim at analyzing the effectiveness of competition policy • This is a difficult empirical task because: • One has to define and measure the objectives of competition policy • One has to be able to measure the policy • Moreover, competition policy is just one dimension of a more general system of institutions • Hence, to cleanly identify the effectiveness of competition policy we have to look at interactions among different institutions/polices Competition Policy and Productivity Growth

  3. Competition Policy: Definition and Objective • The term competition policy refers to: • Competition legislation: Set of prohibitions and obligations including merger control provisions that firms have to comply with • Its enforcement: Anarray of tools for policing their behavior and punishing any violation • The main objective of a competition policy regime is to achieve an efficient allocation of resources • It does this 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-deterrence) • To directly measure deterrence is particularly difficult since it is impossible to directly observe intentions if these do not materialize into actions Competition Policy and Productivity Growth

  4. Deterrence: Competition Policy Variables • The optimal level of deterrence is determined by 1) the size of the sanctions 2) the (perceived) probability of detection and conviction, and 3) the (perceived) probability of errors • The following policy variables affect these three factors • the formal independence of the CA with respect to political or economic interests • the degree of separation between the adjudicator and the prosecutor • the quality of the law on the books • the level of loss that firms (and their employees) can expect to suffer as a consequence of a conviction • the type of investigative powers held by the CA • the amount and quality of the financial and human resources of the CA (budget and the skills of CA’s staff) Competition Policy and Productivity Growth

  5. The Competition Policy Indexes (CPIs) • We submitted a set of tailored questionnaires to the CAs in 13 jurisdictions and integrated them with information from the OECD country studies and from the CAs’ own websites • We obtained information on each of the six policy variables identified as determinants of deterrence, separately for each type of possible competition law infringement (hard-core cartels, abuses, other infringements) and for mergers • Each piece of information at each step of the aggregation process was assigned a score/weight on a scale of 0-1 against a benchmark of generally agreed best practice • We have tested the sensitivity of the LCPIs to alternative weighting schemes using 1) a random weights technique and 2) factor analysis Competition Policy and Productivity Growth

  6. Competition Policy and Productivity Growth

  7. The Empirical Approach: The TFP Model • As a measure of 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-dimensional (country, industry, time) panel data approach is: where TFPLjt is the TFP level in the country on the productivity frontier, (TFPijt/TFPLjt) represents the productivity 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 Competition Policy and Productivity Growth

  8. The Empirical Approach: Measuring TFP • The dependent variable, TFP, is calculated using a growthaccounting technique based on the Solow residual • Following Griffith et al. (2004) we correct this measure for differences across countries in hours worked and markups • The 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): Competition Policy and Productivity Growth

  9. Endogeneity Issue • The major empirical problem is the possible endogeneity of the CPIs. There are two potential sources of endogeneity: • omitted variables • two-way causality • To mitigate the first, we included all possible controls based on the existing literature on the determinants of TFP. Moreover, panel data allows us to control for time invariant unobserved individual heterogeneity • Three steps can be taken to tackle the problem of two-way causality: • Lagging the potentially endogenous explanatory variables • Aggregating the features of the competition policy regime • Using an Instrumental Variables (IV) approach. We propose country specific political and institutional variables as instruments Competition Policy and Productivity Growth

  10. The Data • We selected 13 jurisdictions (Canada, Czech Republic, France, Germany, Hungary, Italy, Japan, Netherlands, Spain, Sweden, UK, EU, and US) over the years from 1995 to 2005 • For the countries that are part 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 industries based on the definitions of the International Standard Industrial Classification (ISIC) • Data on TFP growth has been drawn from the KLEMS consortium and from the Groningen Growth and Development Center • Other data come from the OECD Structural Analysis (STAN) database, the OECD Main Economic Indicators (MEI) database, the OECD PMR database, the OECD Analytical Business Enterprise Research and Development (ANBERD) database, and the World Bank Worldwide Governance Indicators (WGI) database Competition Policy and Productivity Growth

  11. The Time Evolution of TFP and the Aggregate CPI Competition Policy and Productivity Growth

  12. Main Results TFP: Aggregate CPI • Competition policy has a positive impact on TFP growth, and this is statistically significant at the 1% level • Once we include the EU dimension of the policy, the overall estimated effect appears much larger and still significant at the 1% level • We can reject the hypothesis of the policy being endogenous by using political variables (governments' type and their ideological position) as instruments • Controlling for institutions (contract enforcement and quality of the judiciary/law) does not alter our results. Yet, good institutions have a positive impact on TFP growth Competition Policy and Productivity Growth

  13. Main Results TFP: An Example • The coefficient estimates for the aggregate CPI imply an average elasticity that ranges from 2.5% to 3.4% • To quantify the estimated effects we looked at a given country, for example the UK, in a specific industry, let’s say in “food products”. Over the period 2001-2004, the average 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 CPI was 4% • Our estimates imply that, had competition policy not improved, the average TFP growth rate would have been between 2.05 and 2.1% Competition Policy and Productivity Growth

  14. Main Results: Sub-indexes • Both the Institutional CPI and the Enforcement CPI coefficient are positive and significant and have a similar quantitative impact • The Antitrust CPI coefficient is positive and strongly significant, while the Merger CPI coefficient is positive but less significant • A positive impact on the intensity of competition is suggested for the quality of the law and for the powers held by the CAs during the investigation • Also the resources held by the CAs have a positive impact on TFP growth Competition Policy and Productivity Growth

  15. Main Results: Robustness Checks • The results are robust to the use of 1000 sets random weights • The results are robust to the use of factor analysis to aggregate the information into several alternative indexes • The results are robust to the use of different TFP measures (non-corrected for PCM) an aggregate measure of TFP at the country level Competition Policy and Productivity Growth

  16. Main Results: Heterogeneity • Looking at country specific coefficients estimates we observe that CP has a significantly positive impact in Sweden, UK, Netherland, and Hungary, while it has a significantly negative impact in Spain • We look at the interactions between institutions and competition policy. CP has a significant impact only in countries with • high enforcement of contracts • high rule of law • highly impartial courts • highly independent judiciary • Moreover, only countries with English legal origin do not present a significant coefficient for the CP while the effect is significantly higher in those with Nordic legal origin (Sweden) Competition Policy and Productivity Growth

  17. Conclusions • Competition policy appears to exert a significant and positive impact on efficiency. These results are robust to several specification tests and estimation methods • In particular, alternative methodologies (e.g. random weighting, several kinds of factor analysis) to build the CPIs have been employed leading to similar qualitative and quantitative results • The powers held by the CAs during the investigations and the quality 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 institutions affects it. We find complementarities between good judiciary institutions and good competition policy: the latter works better in countries with good institutions Competition Policy and Productivity Growth

  18. Competition Policy and Productivity Growth

  19. Competition Policy and Productivity Growth

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