When interpreting the PMR indicators, two caveats need to be considered. The first is that the PMR approach measures officially adopted policies. It does not capture implementation and enforcement. In this regard, interviews with business associations suggest a significant gap between some of the businessfriendly, officially adopted policies, on the one hand, and implementation and enforcement, on the other. Romania has achieved a number of good results in terms of having laws that are more conducive to private sector development. However, the lack of a greater effort in terms of implementation and enforcement can substantially reduce the impact of the policies adopted in recent years which would hurt the competitiveness of the Romanian economy in the longer run. The second caveat is that the current analysis compares Romania in 2011 with OECD and EU countries in 2008 (the most recent year in which a PMR survey was conducted). As most OECD and EU members have actively continued to improve their product markets over the last three or four years, the analysis over-estimates how Romania ranks relative to comparators today.

In the following sections we present a short methodological summary of the PMR indicator, a detailed analysis covering the component indicators of the three main policy areas surveyed: state control, barriers to entrepreneurship, and barriers to trade and investment. The last section concludes and puts forth a number of policy recommendations.

# **2. THE PMR METHODOLOGY**

A regulatory environment propitious to competition in product markets is widely believed to spur GDP growth through two main channels: productivity and employment. Competition in product markets impacts productivity as firms that are faced with vigorous competition have strong incentives to reduce costs, innovate and become more efficient and productive than their rivals. Based on a set of OECD countries and using industry-level data, Nicoletti and Scarpetta (2003) measure the extent to which multifactor productivity (MFP) growth is affected by measures of product market regulation (reflecting the intensity of competition). They find that restrictive regulation in manufacturing tends to reduce MFP growth mainly via the process of technological catch-up. Using a similar approach, Conway et al. (2006) and Arnold, Nicoletti and Scarpetta (2008) find evidence that anti-competitive regulation is harmful particularly for technology-driven productivity improvements in ICT-intensive sectors.<sup>4</sup> Using a different approach, Anos Casero and Udomsaph (2009) analyze micro-level data from ECA countries to estimate total-factor productivity (TFP) and examine how changes in business environment and productivity growth are correlated in the 2001-2004 period. Successful efforts to improve the business environment are found to have a strong impact on firm productivity. By the same token, pro-competitive regulation influences employment growth as reduced barriers to entry curb the market power of incumbents while

> 4 All these studies use the framework proposed by Aghion and Griffith (2005) in which productivity growth in a country/sector depends on the pace with which the country/sector grows in relation to the country/sector leader. In this sense, productivity growth of a lagging country depends on how fast the leader grows and the speed at which the productivity gap is being closed. This, in turn, depends on the policy environment in the follower country/sector, especially with reference to policies that promote firm rivalry and market entry. Apart from this common framework, these three studies have some differences. Arnold, Nicoletti and Scarpetta (2008) use micro-level data and focus on MFP growth. Nicoletti and Scarpetta (2003) also measure MFP but using industry level information, while Conway et al (2006) also rely on industry level data but measuring labor productivity growth. Finally, all these studies rely on the OECD sample of countries.

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