metadata: authors: 0: author: De Rosa,Donato
1: author: Iootty De Paiva Dias,Mariana
2: author: Pirlea,Ana Florina
count: Romania
docna: 0: docna: Regulation, trade and productivity in
            Romania : an empirical assessment
docty: Policy Research Working Paper
subtopic: Construction Industry,Mining & Extractive Industry (Non-Energy),Common Carriers Industry,Food & Beverage Industry,General Manufacturing,Pulp & Paper Industry,Plastics & Rubber Industry,Labor Markets,International Trade and Trade Rules,Business Cycles and Stabilization Policies,Transport Services
teratopic: Environment,Transport,Private Sector Development,Macroeconomics and Economic Growth,Social Protections and Labor
abstracts: cdata!: Inappropriate regulation can influence
            productivity performance by affecting incentives to invest
            and adopt new technologies, as well as by directly curbing
            competitive pressures. Results of a labor productivity
            growth model for European  countries suggest that improving
            the regulatory environment -- proxied by the Worldwide
            Governance Indicators regulatory quality indicator -- and
            boosting effective exposure to competition through
            increasing trade integration -- expressed as the ratio of
            exports plus imports to gross domestic product -- have
            positive effects on productivity growth. In Romania a 10
            percent increase in openness to global trade over 1995-2010
            would have boosted productivity growth by 9.7 percent per
            year. A 10 percent increase in openness to European Union
            trade, in particular, would have led to an annual increase
            in productivity of 7 percent. Realizing the benefits from
            trade integration depends to some extent on regulation. In
            this regard, the effects of regulation on productivity
            growth are found to be positive, regardless of the indicator
            used to measure regulation, and both through direct and
            indirect channels (by increasing the speed at which a
            country catches up with productivity leaders). Simulation
            results also show how countries with different levels of
            regulatory quality would benefit from a regulatory
            improvement: had Romania improved its regulatory environment
            to the same level as Denmark in 2010, its annual
            productivity growth would have been 14 percent higher over 1995-2010.
geo_reg_key: 517208,517190,517191
repnme: repnme: Regulation, trade and productivity in
            Romania : an empirical assessment
display_title: Regulation, trade and productivity
            in Romania : an empirical assessment
listing_relative_url: /research/2013/06/17895959/regulation-trade-productivity-romania-empirical-assessment
topicv3: Mining Services m1326410 1701,Manufacturing Sectors m1326521 1281,Transport m1326661 135,Trade m1326924 698,Labor Productivity m1504060 2756
publishtoextweb_dt: 2013-06-01T00:00:00Z
historic_topic: Environment,Transport,Private Sector Development,Macroeconomics and Economic Growth,Social Protections and Labor
no_of_pages: 30
author_keys: 0: author_key: 901956
1: author_key: 1051061
2: author_key: 1184946
model_extractions: WPS6493 Policy Research Working Paper 6493 Regulation, Trade and Productivity in Romania

# An Empirical Assessment

_Donato De Rosa Mariana Iootty Ana Florina Pirlea_ The World Bank Europe and Central Asia Region Finance and Private Sector Development June 2013
Policy Research Working Paper 6493

# **Abstract**

Inappropriate regulation can influence productivity performance by affecting incentives to invest and adopt new technologies, as well as by directly curbing competitive pressures. Results of a labor productivity growth model for European countries suggest that improving the regulatory environment—proxied by the Worldwide Governance Indicators regulatory quality indicator—and boosting effective exposure to competition through increasing trade integration— expressed as the ratio of exports plus imports to gross domestic product—have positive effects on productivity growth. In Romania a 10 percent increase in openness to global trade over 1995–2010 would have boosted productivity growth by 9.7 percent per year. A 10 percent increase in openness to European Union trade, in particular, would have led to an annual increase in productivity of 7 percent. Realizing the benefits from trade integration depends to some extent on regulation. In this regard, the effects of regulation on productivity growth are found to be positive, regardless of the indicator used to measure regulation, and both through direct and indirect channels (by increasing the speed at which a country catches up with productivity leaders). Simulation results also show how countries with different levels of regulatory quality would benefit from a regulatory improvement: had Romania improved its regulatory environment to the same level as Denmark in 2010, its annual productivity growth would have been 14 percent higher over 1995–2010.

This paper is a product of the Finance and Private Sector Development, Europe and Central Asia Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at dderosa@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Regulation, Trade and Productivity in Romania: An Empirical Assessment**<sup>**1**</sup>

Donato De Rosa<sup>2</sup> (World Bank, <u>dderosa@worldbank.org)</u> Mariana Iootty<sup>3</sup> (World Bank, <u>miootty@worldbank.org)</u> Ana Florina Pirlea<sup>4</sup> (World Bank, <u>apirlea@worldbank.org)</u> Key words: cross country output convergence, aggregate productivity and regulation. JEL: O12, O47 Sector Board: Finance and Private Sector

> 1 The authors would like to thank Mamta Murthi, Peter Harrold, Francois Rantrua, Ismail Radwan, Pedro L. Rodriguez, Arabela Aprahamian  and Catalin Pauna  for useful comments. Views expressed in this paper are those of the authors and should not be held to represent those of the World Bank Group or its Executive Directors.

> 2 Senior Economist (FPDOK), corresponding author.

> 3 Economist (ECSSF2)

> 4 ETC (ECSF2)

1
# **1. INTRODUCTION**

Several theoretical and empirical studies are devoted to examining the question of whether less productive economies are catching up with their more productive counterparts. A particular strand of the empirical literature has tried to highlight the channels through which institutional settings can affect productivity differences across countries. The regulatory dimension is identified as one such channel, based on the premise that inappropriate regulation can shape the incentives to invest and adopt new technologies, as well as effectively curb competitive pressures, thus limiting the effects that the spur of competition can have on productivity enhancements.

Based on a set of OECD countries and using industry-level data, Nicoletti and Scarpetta (2003)<sup>5</sup> measure the extent to which multi-factor 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)<sup>6</sup> and Arnold, Nicoletti and Scarpetta (2008)<sup>7</sup> find evidence that anti-competitive regulation is harmful particularly for technology-driven productivity improvements in ICT-intensive sectors.<sup>8</sup> Using a different approach, Anos Casero and Udomsaph (2009)<sup>9</sup> analyze microlevel data from countries in Europe and Central Asia 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.

Openness to trade can also expected to positively affect productivity growth. Traditional models of the innovation-focused growth literature (see Grossman and Helpman (1991)<sup>10</sup> and Romer (1990)<sup>11</sup> for seminal interpretations) highlight three main channels through which trade could raise productivity: through diffusion of intermediate goods (or, implicitly, technologies); through an expansion of the market for the output of innovation; and through diffusion of general knowledge. The effective impact of increasing openness to trade on income and productivity growth is likely to depend on the country’s

> 5 Nicoletti, G. and S. Scarpetta (2003) “Regulation, productivity and growth: OECD evidence”, _Economic Policy_ 18 (36), 9–72

> 6 Conway, P., D. De Rosa, G. Nicoletti and F. Steiner (2006), "Product Market Regulation and Productivity Convergence", _OECD Economic Studies_ No. 43: 39-76

> 7 Arnold, J., G. Nicoletti and S. Scarpetta (2008),"Regulation, Allocative Efficiency and Productivity in OECD Countries: Industry and Firm-Level Evidence", _OECD Economics Department Working Papers_ , No. 616

> 8 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.

> 9 Anos Casero, P. and C. Udomsaph, (2009) “What Drives Firm Productivity Growth?” _World Bank Policy Research Working Paper Series_ N.4841,.

> 10  Grossman, G.M., and E. Helpman. (1991). _Innovation and growth in the global economy_ . Cambridge, MA: MIT Press.

> 11 Romer, P (1990) “Endogenous Technological Change” _The Journal of Political Economy_ , Vol. 98, No. 5, Part 2

2
institutional framework.<sup>12</sup> As highlighted by Aghion, Howitt and Mayor-Foulkes (2005)<sup>13</sup> and Acemoglu, Johnson and Robinson (2005)<sup>14</sup> , the positive long-run effects of trade on growth would only arise when combined with an institutional framework of a certain quality, which would include different types of laws, regulations, enforcement of property rights, social arrangements, etc.

This study attempts to shed light on the effect of trade and regulation on productivity convergence while focusing on the specific case of Romania.

The main results of the analysis can be summarized as follows:

- Openness to trade (measured both in relation to global trade as well as to trade with EU partners) is shown to have a positive impact on productivity convergence when controlling for the level of regulatory quality. The potential gains from increasing trade intensity are particularly high in Romania: a ten percentage point increase in openness to global trade over the 1995-2010 period would have boosted productivity growth by 9.7 percent per year. A 10% increase in openness to EU trade, in particular, would have led to an annual increase in productivity of 7%.

- As the realization of the benefits from trade integration depends to some extent on regulation, the effects of regulation on productivity growth are shown to be positive, regardless of the indicator used to measure regulation, and both through direct and indirect channels. Simulation results also show how countries with different levels of regulatory quality would benefit from a regulatory improvement: had Romania improved its regulatory environment to the same level as Denmark in 2010, its annual productivity growth would have been 14 percent higher over the 1995-2010 period.

- Productivity growth in the leader country has a positive and significant impact on productivity growth in the follower countries.

- The more distant a country is from the technological frontier, the greater is the scope for productivity improvements arising from the catching-up process.

- The coefficient of human capital (measured as education achievement but not necessarily representing the skills of the labor force) does not appear to be statistically significant, suggesting that the effect of quality of human capital -- at least in the measure used here -- is fully captured by the productivity gap term.

# **2. COUNTRY-LEVEL ANALYSIS**

To test the effect of regulation on catch-up to best practice, a model of labor productivity based on Conway et al. (2006) is adapted and estimated at the **country level** . In this framework, the productivity growth of a country depends on its ability to keep pace with the leader by either innovating or taking advantage of technology transfers. This potential is influenced by the policy environment in follower

> 12 In fact, there might be also negative consequences of openness to trade, particularly when a greater international trade leads a country to specialize in sectors with relatively growth potential (Grossman and Helpman (1991)) 13 Aghion, P., P. Howitt, and D. Mayor-Foulkes. (2005) “The effect of financial development on convergence: Theory and evidence” _Quarterly Journal of Economics_ 120: 173–222

> 14 Acemoglu, D., Johnson, S. and J. A. Robinson (2005) “Institutions as the Fundamental Cause of Long-Run Growth.” In Philippe Aghion and Steve Durlauf, eds., _Handbook of Economic Growth_ .

3
countries that can affect, positively or negatively, the incentives to increase productivity. The following specification is used: ∆lnLPit = δ�∆lnLPitleader�+ σ(prodgapit−1) + γRegit + α(Reg∗prodgap)it−1 + βhumanKit−1 + τOpen_tradeit−1 + ∑γi _Country_ i _+_ ∑θt _time_ t +∈it Eq.(1) where i and t denote countries and years, respectively. LP is labor productivity, defined as value added per employee, where both value added and number of employees are based on Eurostat data.

∆lnLPitleader reflects the productivity shocks in the leader country; productivity growth in the frontier country widens the production possibility set leading to faster productivity growth in follower countries.<sup>15</sup> prodgapit−1 is the productivity gap and is defined as the log ratio of the level of productivity in each country relative to that of the productivity leader. Assuming that a country's distance from the technological leader measures the scope for technology transfer, the σ coefficient captures the effect of differences in productivity levels between each country and the productivity leader on productivity growth. As prodgapit varies in the interval [− _∞_ , 0], a negative coefficient would suggest that the higher the productivity gap the greater is the scope for productivity improvements that might arise from the technological catch-up process.

Regit is the indicator of economy-wide regulation and proxies the policy environment of each country. In this particular exercise, it is measured by the regulatory quality indicator from the Worldwide Governance Indicators (WGI) database and is available from 1995 to 2010. The indicator captures the ability of a government to formulate and implement sound policies and regulations that permit and ‐ promote private sector development. The indicator is standardized between 2.5 and 2.5 with high scores corresponding to better outcomes.<sup>16</sup> The γ coefficient measures the _direct_ influence of regulation on productivity growth.

In order to reflect the possible effect of regulation on the speed with which each country catches up to the productivity leader, the model includes an interaction between regulatory quality and the productivity gap. Thus, the α coefficient measures the indirect effect of regulation on productivity growth. As prodgapit is always negative, a favorable regulatory environment (captured by higher – and positive – values of Regit ) would imply a negative value for the interaction term. As such, a _negative_ and significant value of the α coefficient would suggest that a _better_ regulatory environment accelerates the catch up process. Figure 1 presents the evolution of the regulatory quality indicator for Romania and some selected EU countries (while Table II, Annex, presents the indicator values for all countries).

> 15 The productivity leader is allowed to change over time.

> 16 Details of how this indicator is constructed are presented in Kaufman, K., A. Kraay, and M. Mastruzzi. (2009). “Governance Matters VIII: Aggregate and Individual Governance Indicators, 1996-2008”, World Bank Policy Research Working Paper No. 4978.

4
**Figure 1: Regulatory Quality indicator:1996-2010**

<!-- Start of picture text --> 2.5<br>Bulgaria<br>Czech Republic<br>2 Denmark<br>Estonia<br>France<br>1.5 Germany<br>Hungary<br>Italy<br>Latvia<br>1<br>Lithuania<br>Netherlands<br>Poland<br>0.5 Romania<br>Slovakia<br>Slovenia<br>0 Spain<br>Sweden<br>United Kingdom<br>‐0.5<br><!-- End of picture text --> _Source: WGI dataset available on_ _<u>http://info.worldbank.org/governance/wgi/index.asp</u>_ humanKit−1 is included to control for a possible (direct) influence (not reflected in the productivity gap term) of the quality of human capital on the ability of the economy to respond to shocks in the productivity frontier. It is defined as the proportion of the workforce with secondary education, with data drawn from the World Development Indicators (WDI) dataset.

Open_tradeit−1 measures trade openness accounting for the effect of competition from global trade on the country’s ability to converge to the productivity frontier. Two different measures are tested: i) the country’s openness to _global_ trade, defined as the sum of country i’s global exports and imports divided by country i’s GDP; and ii) the openness to trade _within the EU region_ , defined as the sum of country i’s exports to and imports from the EU region divided by country i’s GDP. Both trade and GDP data are from UNCTAD.

_Country_ i is a vector of country dummies included to account for unobserved time-invariant factors that might affect productivity growth in a particular country, while _time_ t is a vector of time dummies included to control for possible productivity shocks that might occur in a given year.

**The model is estimated over the 1995-2010 period for a set of 30 countries** : EU countries, including Romania, plus Iceland , Norway and Switzerland)<sup>**17**</sup> . Tables 1 and 2 below provide summary statistics for the variables listed in Eq(1) while the estimation results are presented in Table 3.

> 17 See Table I, annex, for the set of countries covered by the current analysis.

5
**Table 1: Summary Statistics of Variables (all countries, 1995-2010 period)**

|**Variables**|**N**|**Mean **|**Std.**<br>**Dev**|**25**<sup>**th**</sup><br>**pctile**|**75**<sup>**th**</sup><br>**pctile**|
|---|---|---|---|---|---|
|∆lnLP|450|0.05|0.07|0.02|0.08|
|∆lnLP<sup>leader</sup>|450|0.03|0.04|0.01|0.06|
|prodgap|480|-0.96|0.80|-1.59|-0.38|
|Reg|480|1.23|0.43|0.95|1.60|
|humanK|480|47.74|16.85|38.60|60.25|
|Open_trade|480|101.95|48.16|66.00|133.00|
|Open_trade_EU|480|52.96|26.09|33.00|70.00|

**Table 2: Summary Statistics of Variables (Romania, 1995-2010 period)**

|**Variables**|**N**|**Mean**|**Std.**<br>**Dev**|**25**<sup>**th**</sup><br>**pctile**|**75**<sup>**th**</sup><br>**pctile**|
|---|---|---|---|---|---|
|∆lnLP|15|0.08|0.16|0.01|0.17|
|∆lnLP<sup>leader</sup>|15|0.03|0.04|0.01|0.06|
|prodgap|16|-2.38|0.35|-2.65|-2.12|
|Reg|16|0.23|0.27|0.03|0.50|
|humanK|16|57.26|4.72|52.20|61.13|
|Open_trade|16|69.75|8.27|62.50|76.00|
|Open_trade_EU|16|42.63|7.41|35.00|48.00|

Productivity growth in the leader country is found to have a positive and significant impact on productivity growth in the follower countries. The coefficient of the productivity gap term is negative and significant, suggesting that the more distant a country is from the technological frontier the greater is the scope for productivity improvements arising from the catching-up process. The coefficient of human capital (measured as education achievement but not necessarily representing the skills of the labor force) does not appear to be statistically significant, suggesting that the effect of quality of human capital -- at least in the measure used here -- is fully captured by the productivity gap term.<sup>18</sup>

> 18 In principle any effect of quality of human capital (or of any other input) on productivity growth by country should be captured by the productivity gap term. Human capital is included as a distinct variable in the model to check whether it has a _direct_ effect on the ability of the country to catch up with the productivity frontier.

6
[exp(PAX) — 1]x100 ° = 6(AlnLP ) + o(prodgap + y 0 + y y »; 0 {exp ~~|_——)~~ * AOpen_trade| — 1} * 100
points in Romania’s openness to global trade over the 1995-2010 period would boost the country’s productivity growth by 9.7 percent per year, the highest value among the countries for which the average marginal effect is statistically significant, where the effect in the country with the second highest predicted effect -- Latvia – is only 4.9 percent, 50% less than for Romania. The same exercise for trade intensity within the EU region shows similar results. Romania, again, is the country that could potentially benefit most from increasing trade intensity: ten extra percentage points of openness to trade within the EU region would increase productivity growth by almost 7% per year.

**Figure 2: Increase in average annual productivity growth over the 1995-2010 period given an increase of ten percentage points of openness to trade**

<!-- Start of picture text --> Openness to Global Trade Openness to EU Trade<br>12.00 8.00<br>6.99<br>9.72 7.00<br>10.00<br>6.00<br>8.00 5.00 4.49 4.61<br>4.00<br>6.00<br>4.89<br>3.00 2.43 2.54<br>4.00<br>2.00<br>2.39 2.57<br>2.00 1.00<br>0.00<br>0.00 Slovakia Czech Bulgaria Latvia Romania<br>Slovakia Czech Republic Latvia Romania Republic<br>percent<br>percent<br><!-- End of picture text --> _Note: this figure shows the results of those countries for which the average marginal effect of openness to trade was statistically significant. Table III, Annex, presents the estimated marginal effect of openness to trade for all countries._ Reaping the benefits from trade integration depends to some extent on regulation. In this regard, the direct effect of regulation on productivity growth is found to be positive (and significant), indicating that a less burdensome regulatory environment is conducive to productivity growth. Based on the model, regulatory improvement would also have indirect consequences for productivity growth by impacting the speed of the catch up process. As argued by Conway et al (2006), this could be due to the fact that less burdensome regulation would increase the incentives and reduce the costs of incorporating new technologies into the production process. The coefficient of (Reg ∗prodgap)it−1 is negative and statistically significant at 10% level suggesting that well-functioning regulation is positively associated to a faster catch-up process.

The _total_ effect of the regulatory environment on productivity growth (combining the direct and indirect channels) can be assessed by estimating the average marginal effect of the Regit variable in Eq(1). Results show that, all else equal, improving the regulatory indicator by one standard deviation (0.43) over the 1995-2010 period is associated with an increase of 2.86 percent in average annual productivity growth.<sup>21</sup>

> 21 The average marginal effect of regulatory quality was 0.0648; the 2.86 percent results from the following computation [exp(0.0648*0.43)-1]*100.

8
To show how countries with different levels of regulatory quality would benefit from an improved regulatory improvement, we estimate the average marginal effect of the Regit variable by country and then simulate the gains in productivity growth across countries if they all engage in a sustained reform effort aimed at achieving the best practice of the countries in the sample. Following a reasonable conjecture, this hypothetical improvement would not have the same magnitude in all countries, as it would be conditioned on the last observed value for regulatory conditions in 2010. Specifically, the reform would imply, for each country, augmenting the Regit variable from its observed value in 2010 to the value of the country with the highest observed value in the same year, which is Denmark (with a value of 1.9). In other words, the benchmark for regulatory reform used in this exercise is the implementation of the regulatory settings related with the country with the best environment in 2010. The closer a country is to this 2010 benchmark the less ambitious would be the reform it would implement.

It is worth acknowledging that the simulated values produced by this kind of exercise should be only considered as indicative parameters. Regulatory reform is not assumed to change the estimated average parameters of the model, and for this reason, it would not change the estimated average relationship between the outcome variable and the other covariates. Nevertheless, this kind of exercise can be a useful instrument to have a sense of the magnitude of the impact on the economy of a possible policy change.

Figure 3 presents the results of a simulation that considers the impact on productivity growth due to a regulatory reform initiative that improves the country’s regulatory environment to the level of Denmark in 2010. The average increase in annual productivity growth ranges from 0.5 percent for Finland to 15.5 percent for Bulgaria. Romania stands out with the second highest productivity dividend (14.1 percent).

**Figure 3: Increase in average annual productivity growth (over 1995-2010) given a move to a regulatory environment equivalent to Denmark in 2010**

<!-- Start of picture text --> 18.00<br>16.00<br>14.00<br>12.00<br>10.00<br>8.00<br>6.00<br>4.00<br>2.00<br>0.00<br>percent<br>Finland Netherlands Ireland Sweden United Kingdom Austria Germany Norway Belgium Malta France Estonia Cyprus Spain Iceland Italy Czech Republic Portugal Greece Hungary Slovenia Slovakia Poland Lithuania Latvia Romania Bulgaria<br><!-- End of picture text --> _Note: The regulatory environment is measured by the regulatory quality indicator (WGI data). Results for Switzerland and Luxembourg are not presented as the corresponding marginal effects of regulatory quality were not statistically significant. Table IV, Annex, presents the average marginal effect of regulatory quality for all countries. The figure is based on the estimation of Eq(1) with_ Open_trade _variable. Results are robust to the use of_ Open_tradeEU _variable._ 9
# **3. SECTOR-LEVEL ANALYSIS**

In order to shed light on the sectoral dimension of productivity growth, the following equation is estimated: where: i, j and t denote countries, sectors (Nace 1.1)<sup>22</sup> and years, respectively. LP stands for labor productivity and is defined as sectoral value added per employee, based on Eurostat data. Reflecting data availability, the model is estimated **at sector level over the period of 2003-08** for the same countries of Eq(1), except for Switzerland and Malta, given the lack of data on sectoral productivity for these countries.

All the variables are defined as in Eq(1), except Reg for which an additional proxy for the quality of the regulatory environment is used.<sup>23</sup> In addition to the regulatory quality indicator - from the WGI database - a set of alternative indicators constructed through a principal component analysis (PCA) based on Doing Business (DB) data is used. The first (All DB) is a comprehensive index including all DB indicators in all topics. The second (Business Start-up_DB) measures the complexity of a number of procedural aspects related to the entry and exit process; it encompasses the indicators for _starting a business, registering property_ and _closing a business_ . The third (Business Operations_DB) captures the burden of regulations faced by an enterprise in managing regular operations; it covers the topics of _dealing with construction permits, paying taxes, trading across borders_ and _employing workers_ . The fourth and last index (Institutional Environment_DB) measures the quality of the legal and institutional framework and aggregates the indicators for _protecting investors, getting credit_ and _enforcing contracts_ . All PCA indices based on DB data are coded such that higher values indicate simpler regulation.<sup>24</sup> It is worth mentioning that none of the regulatory proxies are available at the sector level, only at the country level. The same happens with Open_trade and humanK. Table VI (Annex) provides summary statistics for all proxies of regulatory environment used for the estimation at sector level while Figure 4 shows the evolution of the comprehensive PCA indicator on DB data (Table VII, Annex, shows the values for all PCA indicators for all comparator countries).

> 22 See Table IV in the annex.

> 23 The productivity leader is allowed to change over time and across sectors.

> 24 In this sense, the PCA indices – based on DB data - are consistent with the regulatory quality indicator (based on WGI data); even though the PCA indices are scaled differently, they are also defined in such a way that higher values mean better regulatory environment.

10
# **Box 1 – Constructing alternative proxies of regulatory environment: Principal Component Analysis using Doing Business data**

The PCA indices are linear combinations of Doing Business sub-indicators, where each sub-indicator is multiplied by an optimal weight that best accounts for the variance of the indicators. For example, the principal components analysis index for business entry is calculated through the following equation: _Business Entry index = w0*(Starting a Business) + w1*(Registering Property)+ w2*(Closing a Business),_ where the weights w0, w1, and w2 are the weights that lead to the greatest variance. All principal components analysis indices are coded so higher numbers indicate less complex regulation.

**Figure 4: PCA indicator (All_DB):2003-2008**

<!-- Start of picture text --> 100<br>Bulgaria<br>Czech Republic<br>90 Denmark<br>Estonia<br>France<br>80<br>Germany<br>Hungary<br>70 Italy<br>Latvia<br>Lithuania<br>60<br>Netherlands<br>Poland<br>Romania<br>50<br>Slovakia<br>Slovenia<br>40 Spain<br>2003 2004 2005 2006 2007 2008<br><!-- End of picture text --> _Note: Authors’ elaboration based on DB data_ The results of estimating Eq(2) are given in Table 4. Consistent with the previous set of results at the country level, labor productivity growth in less productive sectors is positively influenced by the speed at which productivity grows in the same sectors in the best performing countries. In addition, the coefficient of productivity gap is, again, always negative.

11
**Table 4: Productivity Convergence and Regulation: sector level analysis for 2003-08 period** (robust standard errors in parenthesis)

||1|2|3|4|5|6|7|8|9|10|
|---|---|---|---|---|---|---|---|---|---|---|
|∆lnLPit<br>leader|0.0257***|0.0334***|0.0276***|0.0309***|0.0302***|0.0246***|0.0326***|0.0278***|0.0300***|0.0298***|
||(0.007)|(0.007)|(0.007)|(0.007)|(0.007)|(0.007)|(0.007)|(0.007)|(0.007)|(0.007)|
|prodgapijt−1|-0.0548***|-0.0568***|-0.0946***|-0.0483***|-0.0217|-0.0556***|-0.0576***|-0.0947***|-0.0489***|-0.0217|
||(0.007)|(0.014)|(0.022)|(0.013)|(0.017)|(0.007)|(0.014)|(0.022)|(0.013)|(0.017)|
|humanKit−1|0.0017|0.001|0.0004|0.0011|0.0015|0.0015|0.001|0.0003|0.0011|0.0013|
||(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|
|Open_tradeit−1|0.0005|0.0004|-0.0003|0.0005|0.000||||||
||(0.001)|(0.001)|(0.001)|(0.001)|(0.000)||||||
|Open_tradeEUit−1||||||0.0003|0.0005|-0.0007|0.0005|-0.0003|
|||||||(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|
|Regit|0.0515*|||||0.0439*|||||
||(0.0340)|||||(0.025)|||||
|(Reg∗prodgap)it−1|-0.0110**|||||-0.0104**|||||
||(0.004)|||||(0.004)|||||
|All_DBit||0.0047***|||||0.0047***||||
|||(0.002)|||||(0.002)||||
|(All_DB∗prodgap)ijt−1||-0.0002**|||||-0.0001**||||
|||(0.000)|||||(0.000)||||
|Start−up_DBit|||0.0081***|||||0.0081***|||
||||(0.002)|||||(0.002)|||
|(Start−up_DB∗prodgap)ijt−1|||0.0003|||||0.0003|||
||||(0.000)|||||(0.000)|||
|Bus. Operations_DBit||||0.0025**|||||0.0024*||
|||||(0.001)|||||(0.001)||
|(BusOperations_DB∗prodgap)ijt−1||||-0.0003|||||-0.0002||
|||||(0.000)|||||(0.000)||
|Inst−Env_DBit|||||0.002*|||||0.0019*|
||||||(0.001)|||||(0.001)|
|(Inst−Env_DB∗prodgap)ijt−1|||||-0.0007***|||||-0.0007***|
||||||(0.000)|||||(0.000)|
|_cons|-0.5913***|-0.7969***|-0.9979***|-0.6575***|<br>-0.5876**|-0.5314***|-0.7765***|0.000|-0.6335***|<br>-0.5541**|
||(0.157)|(0.179)|(0.221)|(0.171)|(0.229)|(0.154)|(0.184)|(0.000)|(0.175)|(0.234)|
|R-squared (within)|0.1348|0.1312|0.1247|0.1334|0.1379|0.136|0.1322|0.1239|0.1347|0.1379|
|N. obs|5129|5129|5129|5129|5129|5129|5129|5129|5129|5129|

_Note:_ Country, sector and time dummies were included but not reported. _* significant at 10%; ** significant at 5%; *** significant at 1%_ 12
The _direct_ effect of regulation on productivity convergence is found to be positive regardless of the proxy used to measure the quality of the regulatory environment. Regarding the _indirect_ effect of regulation, the coefficient of the (Reg∗prodgap)ijt−1 variable is shown to be negative and statistically significant for three out of the five proxies of regulatory environment, suggesting that, at least for these cases, the effect of regulation on the speed of the catch-up process is positive.

The total effect of regulation on productivity growth – when assuming both direct and indirect effects – is also shown to be positive: estimations of the marginal effect of the quality of the regulatory environment on productivity growth points to a positive (and statistically significant) effect for all proxies used (see Table VI in the Annex for the results). Figure 5 below displays the estimated effect on productivity growth due to a one standard variation in each regulatory proxy over the 2003-08 period. Results suggest that productivity dividends are higher when the regulatory framework is measured by the indicator Institutional Environment_DB, which captures the quality of the legal and institutional framework for _protecting investors, getting credit_ and _enforcing contracts._

**Figure 5: Increase in average annual productivity growth (over 2003-08 period) given a one standard deviation**

**increase in each regulatory proxy**

<!-- Start of picture text --> 8.0<br>6.9<br>7.0<br>6.1<br>6.0<br>4.8 4.9<br>5.0<br>3.8<br>4.0<br>3.0<br>2.0<br>1.0<br>0.0<br>percent<br><!-- End of picture text --> _Note: Reg is the regulatory quality indicator, according to WGI data. One standard deviation of each regulatory proxy is computed over the whole sample of countries for the 2003-08 period. See Table VI, Annex, for the respective values considered._ To identify the sectors in which the impact of regulation on productivity growth is higher, the average marginal effect of the regulatory variable was computed.<sup>25</sup> Results show that the marginal impact of the regulatory environment on productivity growth is positive and statistically significant for all sectors, regardless of the proxy used. Table 5 displays the effects on productivity growth associated with a one standard deviation (0.38) increasing of regulatory quality indicator (Reg) over the 2003-08 period.<sup>26</sup> Sectoral

> 25 See Table VIII in the Annex for the estimated marginal effects of all regulatory proxies used.

> 26 The effects on productivity growth due to variation of other proxies of regulatory environment were also computed. Results are available upon request.

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productivity dividends resulting from regulatory improvement range from 3.9 to 5.2 percent annually. The low variance of these estimations suggests that potential gains of regulatory upgrading seem to be equally distributed across sectors. However, among the sectors listed, the non-manufacturing ones – like Electricity, gas and water supply; Water transport; Air transport, Post and telecommunications, Retail trade and Other business activities – are particularly relevant, as these are normally the most regulated in the economy and inappropriate regulation of these activities tends to have “trickle down” effects on the rest of the economy, as all industries tend to be heavy users of non-manufacturing inputs.

**Table 5: Increase in average annual productivity growth** **_by sector_ given a one standard deviation augment of regulatory environment over 2003-08 period**

|**Sector **|**Estimated**<br>**effect (%)**|
|---|---|
|Mining of coal and lignite; extraction of peat|5.2|
|Manufacture of wearing apparel; dressing; dyeing of fur|5.2|
|Manufacture of leather and leather products|5.2|
|Manufacture of textiles|5.1|
|Hotels and restaurants|5.1|
|Manufacture of furniture; manufacturing n.e.c.|5.1|
|Retail trade, except of motor vehicles and motorcycles; repair of personal and household goods|5.1|
|Manufacture of wood and wood products|5.0|
|Manufacture of other transport equipment|5.0|
|Manufacture of food products and beverages|5.0|
|Manufacture of fabricated metal products, except machinery and equipment|5.0|
|Other business activities|5.0|
|Manufacture of machinery and equipment n.e.c.|5.0|
|Manufacture of rubber and plastic products|5.0|
|Manufacture of electrical machinery and apparatus n.e.c.|5.0|
|Forestry, logging and related service activities|5.0|
|Sale, maintenance and repair of motor vehicles and motorcycles; retail sale of automotive fuel|4.9|
|Fishing|4.9|
|Land transport; transport via pipelines|4.9|
|Construction|4.9|
|Manufacture of radio, television and communication equipment and apparatus|4.9|
|Manufacture of other non-metallic mineral products|4.9|
|Manufacture of medical, precision and optical instruments, watches and clocks|4.9|
|Manufacture of motor vehicles, trailers and semi-trailers|4.9|
|Publishing, printing and reproduction of recorded media|4.9|
|Manufacture of pulp, paper and paper products|4.9|
|Recycling|4.9|
|Agriculture, hunting and related services|4.9|
|Manufacture of basic metals|4.8|
|Wholesale trade and commission trade, except of motor vehicles and motorcycles|4.8|
|Manufacture of office machinery and computers|4.8|
|Other mining and quarrying|4.8|

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|Computer and related activities|4.8|
|---|---|
|Supporting and auxiliary transport activities; activities of travel agencies|4.8|
|Air transport|4.7|
|Manufacture of chemicals, chemical products and man-made fibres|4.7|
|Post and telecommunications|4.7|
|Water transport|4.6|
|Research and development|4.6|
|Manufacture of tobacco products|4.5|
|Electricity, gas and water supply|4.5|
|Renting of machinery and equipment without operator and of personal and household goods|4.4|
|Extraction of crude petroleum and natural gas; service activities incidental to oil and gas extraction,<br>excluding surveying|4.3|
|Manufacture of coke, refined petroleum products and nuclear fuel|4.3|
|Real estate activities|3.9|

_Note: one standard deviation of regulatory quality indicator (0.38) is computed over the whole sample of countries for the 2003-08 period (see Table VI, Annex)._ Results from Table 4 show that openness to trade – measured at the country level – does not present a statistically significant effect on productivity convergence at sector level. When testing alternative measures for openness to (overall) trade at sector level - covering agriculture, fishing, mining and manufacturing sectors at 2 digit level of Nace 1.1 - estimation results in Table 6 suggest that trade openness has in fact a positive (and statistically significant) effect on productivity growth.<sup>27</sup>

> 27 Openness to (global) trade at sector level is defined as the sum of sector j’s global exports and imports divided by sector j’s production value. Data for global imports and exports by sector is from Comtrade, while production value information is from Eurostat.

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**Table 6: Productivity Convergence and Regulation: sector level analysis for 2003-08 period with openness to trade data at sectoral level (robust standard errors in parenthesis)**

||1|2|3|4|5|
|---|---|---|---|---|---|
|∆lnLPit<br>leader|0.0278***<br>(0.009)|0.0336***<br>(0.009)|0.0296***<br>(0.009)|0.0315***<br>(0.009)|0.0311***<br>(0.009)|
|prodgapijt−1|-0.0735***|-0.0762***|-0.1073***|-0.0693***|-0.034|
||(0.009)|(0.018)|(0.028)|(0.016)|(0.024)|
|humanKit−1|0.0005|-0.0002|-0.0001|-0.0001|0.0006|
||(0.002)|(0.002)|(0.002)|(0.002)|(0.002)|
|Open_tradeijt−1|0.0001**|0.0001**|0.0001**|0.0001**|0.0001**|
||(0.000)|(0.000)|(0.000)|(0.000)|(0.000)|
|Regit|0.1184**<br>(0.048)|||||
|(Reg∗prodgap)it−1|-0.0044**<br>(0.002)|||||
|All_DBit||0.0049**||||
|||(0.002)||||
|(All_DB∗prodgap)ijt−1||-0.002**<br>(0.000)||||
|Start−up_DBit|||0.0069**<br>(0.003)|||
|(Start−up_DB∗prodgap)ijt−1|||0.0003<br>(0.000)|||
|Bus. Operations_DBit||||0.0030**<br>(0.001)||
|(BusOperations_DB∗prodgap)ijt−1||||-0.0001<br>(0.000)||
|Inst−Env_DBit|||||0.0019*<br>(0.001)|
|(Inst−Env_DB∗prodgap)ijt−1|||||-0.0006*<br>(0.000)|
|_cons|-0.6108***|-0.7523***|-0.9707***|-0.6276***|-0.5760**|
||(0.146)|(0.186)|(0.273)|(0.168)|(0.263)|
|R-squared (within)|0.1259|0.1262|0.1249|0.1257|0.1252|
|N. obs|3155|3155|3155|3155|3155|

_Note: Country, sector and time dummies were included but not reported .* significant at 10%; ** significant at 5%; *** significant at 1%_ The computation of the marginal effect of trade openness on productivity convergence by sector allows identifying the industries for which productivity growth is most responsive to a variation in trade intensity. Figure 6 displays the effects on productivity growth due to a one standard deviation increasing of trade openness by sector over the 2003-08 period.<sup>28</sup> Only the sectors for which the estimated effect was statistically significant are presented. Manufacture of basic metals is the activity with the highest productivity dividend: a one standard deviation increase in the sector’s openness to trade over the 2003-08 period would lead to a productivity growth almost 34 percent higher (yearly). The average value of trade openness for this sector in Romania is largely inferior to the sector average of all countries considered in the analysis; this

> 28 The presented effects of trade openness on productivity growth refer to the model that includes _Reg_ as the regulatory proxy used. The trade effects considering alternative regulatory proxies were also computed. Results are available upon request.

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suggests that there is space for Romania to increase its trade integration which can largely benefit productivity convergence. The same seems to happen to the other selected sectors.

**Figure 6 - Increase in average annual productivity Figure 7- Average openness to trade by sector: 2003-08 growth** **_by sector_ given a one standard deviation period augment of sectoral openness to trade over 2003-08**

<!-- Start of picture text --> period<br>40.0 18.0 17.1<br>15.9<br>33.7 16.0<br>35.0<br>14.0<br>30.0<br>12.0<br>25.0 9.9<br>10.0<br>20.0<br>8.0<br>15.0<br>6.0<br>10.0 7.7 6.2 4.0<br>5.0 2.0<br>0.0 0.0<br>Manufacture of basic Manufacture of motor Mining of coal and Manufacture of basic Manufacture of motor Mining of coal and<br>metals vehicles, trailers and lignite; extraction of metals vehicles, trailers and lignite; extraction of peat<br>semi‐trailers peat semi‐trailers<br>All countries Romania<br>percent<br>percent per year<br><!-- End of picture text --> Note: _one standard deviation of trade openness for the manufacture of basic metals, manufacture of motor vehicles, trailers and semi-trailers, and mining of coal and lignite (63.7, 15.5 and 42.8, respectively) are computed over the whole sample of countries for the 2003-08 period._

# **4. CONCLUDING REMARKS**

This paper attempts to shed light on the effect of trade and regulation on productivity convergence while focusing on the specific case of Romania. A model of labor productivity based on Conway et al. (2006) was adapted and estimated, first, at country the level over the 1995-2010 period for a set of 30 countries: EU countries, including Romania, plus Iceland, Norway and Switzerland. Proxying the regulatory environment by the regulatory quality indicator from the WGI dataset, the **country level** model has provided results which can be summarized as follows:

- Openness to global trade (measured both in relation to global trade as well as to trade with EU partners) is shown to have a positive impact on productivity convergence when controlling for the level of regulatory quality. The potential gains for increasing trade intensity in Romania are particularly high: a 10% increase in openness to global trade over the 1995-2010 period would have boosted productivity growth by 9.7 percent per year. A 10% increase in openness to EU trade, in particular, would have led to an annual increase in productivity of 7%.

- As the realization of the benefits from trade integration depends to some extent on regulation, the effects of regulation on productivity growth are shown to be positive, regardless of the indicator used to measure regulation, and both through direct and indirect channels. Simulation results also show how countries with different levels of regulatory quality would benefit from a regulatory improvement: had Romania improved its regulatory environment to the same level as Denmark in 2010, its annual productivity growth would have been 14 percent higher over the 1995-2010 period.

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- Productivity growth in the leader country has a positive and significant impact of productivity growth in the follower countries.

- The more distant a country is from the technological frontier, the greater is the scope for productivity improvements arising from the catching-up process.

- The coefficient of human capital (measured as education achievement but not necessarily representing the skills of the labor force) does not appear to be statistically significant, suggesting that the effect of quality of human capital -- at least in the measure used here --  is fully captured by the productivity gap term.

In order to shed light on the sectoral dimension of productivity growth, the same model was estimated at sector level over the period of 2003-08 for the same countries, except for Switzerland and Malta. In this sector level model, besides the regulatory quality indicator - from WGI database - a set of alternative indicators constructed through a principal component analysis (PCA) based on Doing Business (DB) data was used. The **sector level** results can be summarized as follows.

- Trade openness at sector level has a positive (and statistically significant) effect on productivity growth. The computation of the marginal effect of trade openness on productivity convergence by sector has pointed manufacture of basic metals as the activity to show the highest productivity dividend. As the average value of trade openness for this sector in Romania is largely inferior to the sector average of all countries considered in the analysis, this suggests that there is space for Romania to increase its trade integration to the benefit of productivity convergence.

- The total effect of regulation on productivity growth – when assuming both direct and indirect effects – was also shown to be positive: estimations of the marginal effect of the quality of the regulatory environment on productivity growth points to a positive (and statistically significant) effect for all proxies used. In particular, results suggest that productivity dividends are higher when the regulatory framework is measured by the indicator Institutional Environment_DB, which captures the quality of the legal and institutional framework regarding protecting investors, getting credit and enforcing contracts.  In order to identify the sectors in which the impact of regulation on productivity growth is higher, the average marginal effect of the regulatory environment variable was computed and results have shown that the marginal impact of the regulatory environment on productivity growth is positive and statistically significant for all sectors, regardless of the proxy used. Sectoral productivity dividends resulting from regulatory improvement range from 3.9 to 5.2 percent yearly.

- Consistent with the previous set of results at country level, labor productivity growth in less productive sectors is positively influenced by the speed at which productivity grows in the same sectors in the best performing countries. In addition, the coefficient for the productivity gap was, again, negative.

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