metadata: authors: 0: author: Grover,Arti Goswami
1: author: Iacovone,Leonardo
2: author: Chakraborty,Pavel
count: Croatia
docna: 0: docna: Spatial Gaps in Management Quality :
            Evidence from a Lagging Region in Croatia
docty: Policy Research Working Paper
subtopic: Business Cycles and Stabilization Policies,Pulp & Paper Industry,Textiles, Apparel & Leather Industry,Food & Beverage Industry,Common Carriers Industry,Plastics & Rubber Industry,General Manufacturing,Construction Industry,Legal Reform,Judicial System Reform,Legislation,Real & Intellectual Property Law,Regulatory Regimes,Intellectual Property Rights,Legal Products,Common Property Resource Development,Social Policy,Educational Sciences,Labor Markets
teratopic: Macroeconomics and Economic Growth,Social Development,Law and Development,Governance,Industry,Social Protections and Labor,Rural Development,Public Sector Development,International Economics and Trade,Education
abstracts: cdata!: Embedding management and operational
            practices survey in a broader firm capabilities survey, this
            report finds that: (i) relative to the rest of Croatia, an
            average firm in the lagging region of the country (Eastern
            Croatia) is only slightly behind in the adoption of
            structured management practices. Nevertheless, overall,
            Croatia is farther from a frontier economy such as the
            United States. (ii) There is wide heterogeneity in adoption
            of management practices in the country, such that a large
            share of firms in the lagging region are badly managed
            relative to those in the rest of the country. (iii) Better
            managed firms in all regions, including Eastern Croatia,
            show superior firm performance. What drives better
            management? Global linkages matter for firms in other
            countries and in all regions of Croatia except the lagging
            region. Unlike other countries, firms in Croatia do not
            upgrade management quality as they age, perhaps due to lack
            of pro-competitive forces. This report recommends focusing
            on policies that improve allocative efficiency in the region
            and help firms establish global linkages, and more direct
            intervention for improving the management quality of firms.
geo_reg_key: 517208,517191
repnme: repnme: Spatial Gaps in Management Quality :
            Evidence from a Lagging Region in Croatia
display_title: Spatial Gaps in Management Quality :
            Evidence from a Lagging Region in Croatia
listing_relative_url: /research/2020/04/31948076/spatial-gaps-management-quality-evidence-lagging-region-croatia
topicv3: Education, Skills Development and Labor
            Market m1326135 1484,Manufacturing Sectors m1326521 1281,Patents m1326812 1041,Education m1327048 470,Labor Productivity m1504060 2756
publishtoextweb_dt: 2020-04-13T00:00:00Z
historic_topic: Macroeconomics and Economic Growth,Social Development,Law and Development,Governance,Industry,Social Protections and Labor,Rural Development,Public Sector Development,International Economics and Trade,Education
origu: EFI-FCI-TIC-Firms,Entrep,&Innov. (ETIFE)
no_of_pages: 35
author_keys: 0: author_key: 1066720
1: author_key: 900307
2: author_key: 1214958
model_extractions: Policy Research Working Paper 9213 Spatial Gaps in Management Quality Evidence from a Lagging Region in Croatia _Arti Grover Leonardo Iacovone Pavel Chakraborty_ Finance, Competitiveness and Innovation Global Practice April 2020
Policy Research Working Paper 9213

# **Abstract**

Embedding management and operational practices survey in a broader firm capabilities survey, this report finds that: (i) relative to the rest of Croatia, an average firm in the lagging region of the country (Eastern Croatia) is only slightly behind in the adoption of structured management practices. Nevertheless, overall, Croatia is farther from a frontier economy such as the United States. (ii) There is wide heterogeneity in adoption of management practices in the country, such that a large share of firms in the lagging region are badly managed relative to those in the rest of the country. (iii) Better managed firms in all regions, including Eastern Croatia, show superior firm performance. What drives better management? Global linkages matter for firms in other countries and in all regions of Croatia except the lagging region. Unlike other countries, firms in Croatia do not upgrade management quality as they age, perhaps due to lack of pro-competitive forces. This report recommends focusing on policies that improve allocative efficiency in the region and help firms establish global linkages, and more direct intervention for improving the management quality of firms.

This paper is a product of the Finance, Competitiveness and Innovation Global Practice. 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://www.worldbank.org/prwp. The authors may be contacted at agrover1@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
# **Spatial Gaps in Management Quality: Evidence from a Lagging Region in Croatia**

Arti Grover, Leonardo Iacovone and Pavel Chakraborty<sup>γ</sup>

**_JEL Classification_** : D22, D24, F14, L2, M2, O33,

**_Keywords_** : management, firm, productivity, competition, Croatia, Eastern Croatia

## **Acknowledgments**

<mark>The team is grateful to Todor Milchevski for leading the survey implementation and Šime Smolić for his careful work on data collection. The team thanks Kristen Himelein for her invaluable advice on sampling strategy and Andrea August for excellent research assistance. The report has benefited from overall guidance of Marialisa Motta as Practice Manager and Austin Kilroy as project Team Leader. Implementation of the survey was made with the gracious support of the Minister of Regional Development and EU Funds, including a letter of support sent by the Minister to survey recipients encouraging them to respond. The work on this paper is the result of the World Bank team activities for the Government of Croatia, under the ongoing Eastern Croatia Growth and Jobs Reimbursable Advisory Service, co-financed by the European Union from the European Regional Development Fund. This report does not necessarily represent the position of the European Commission and of the Croatian Government. An edited version of the working paper for a policy audience is available upon request.</mark>

> γ Finance competitiveness and innovation Global Practice, The World Bank, The authors can be reached at: <u>agrover1@worldbank.org, liacovone@worldbank.org; pavel.chakraborty@gmail.com. The findings, interpretations, and conclusions expressed in this paper are entirely</u> 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. The World Bank Group does not guarantee the accuracy of the data included in this work, which is drawn from multiple external sources.  Nothing herein shall constitute, or be considered to be, a limitation upon or waiver of the privileges and immunities of The World Bank Group, all of which are specifically reserved.
# **Section 1: Why Do Management Capabilities Matter?**

The persistence in productivity differences between firms, within the same industry, is striking and puzzling. For example, labor productivity for plants in the 90<sup>th</sup> percentile, within narrowly defined four-digit US manufacturing industries, is four times as high as plants in the 10<sup>th</sup> percentile. Likewise, the difference in Total Factor Productivity (TFP) is twice as high, when controlling for other factors (Syverson, 2011). These differences persist over time and are robust to controlling for plant-specific prices in homogeneous goods industries. Such TFP heterogeneity is not an artifact of the US data; it is also evident in several other countries. It is well-known that variations in productivity trump any other source of heterogeneity in firm performance: in the United States, firms in the 90th percentile of the productivity distribution produce twice as much with the same set of inputs as firms in the 10th percentile, whereas in China and India this gap is 5:1 (Hsieh and Klenow 2009). Often such within-industry productivity differentials are attributed to “hard” technological innovations, as embodied in patents or in adoption of advanced equipment. Bloom et al. (2016a) provide an alternative explanation, which is also the focus of this paper, that is, productivity differences reflect variations in management practices.

Bloom et al. (2016a) propose that some forms of management practices are like “technology”, in the sense that they raise firm productivity. Bloom and co-authors have significantly advanced the empirical foundations for measuring management practices across firms and countries, which has allowed core theories in many fields such as international trade, labor economics, industrial organization and macroeconomics to incorporate firm heterogeneity as a central component. While a frontier topic globally, there exists little evidence on managerial practices of firms in Croatia and the relationship between management and productivity. Nevertheless, there is some evidence on management in countries from the Europe and Central Asia region, where Bloom et al. (2011) find a strong association between managerial practices and firm performance.<sup>1</sup> To quantify the importance of management for the performance of firms in Croatia, and particularly in Eastern Croatia, we conducted a survey on firm capabilities in Croatia, which includes the following modules: (i) Working Time, Employed Personnel and Remunerations; (ii) Training; (iii) Business Capabilities and Entrepreneurship; (iv) Government Programs and Funding; (v) Global Production Chains; (vi) Science, Technology and Innovation and (vii) Access to Finance.

This study analyzes the outcomes for Eastern Croatia along several dimensions of firm performance, including not only labor productivity, total factor productivity (TFP) and profits, but also outcomes relating to average skill intensity, training, innovation and technology adoption. These outcomes are evaluated with management capabilities being the centerpiece, that is, we associate all the measures of firm performance with the adoption of structured management practices.

How are structured management practices measured? The survey module on Business Capabilities and Entrepreneurship includes 15 core questions of the US Census Management and Organizational Practices Survey <u>(MOPS) main module. The survey was deliberately designed to replicate the US Census MOPS to maximize</u> comparability with the United States as well as other countries where this survey has been conducted (e.g., the United Kingdom, Canada, the Russian Federation and Mexico). We exploit the survey data on 585 small and medium enterprises (SMEs) in the manufacturing and services sectors. Of these 585 firms, 145 firms are from Eastern Croatia. The survey was conducted from January 2019 to June 2019. The FINA database provides the sample frame for this survey, where the sample was stratified by region and sector.<sup>2</sup> Firms were randomly sampled and interviewed face to face. Firm responses to questions on managerial practices are aggregated into a single management score,

> 1 In 2008 and 2009, the European Bank for Reconstruction and Development (EBRD) in cooperation with the World Bank (WB) conducted a new survey, the EBRD-WB Management, Organization and Innovation (MOI) survey.

> 2 The Financial Agency (Fina) is the leading Croatian provider of financial data services. The database comprises of all tax registered firms in Croatia.

2
following Bloom et al. (2019a). Survey data on managerial practices, mark-ups, technology adoption and innovation are merged with other firm performance data such as profits, sales per employee and TFP from the FINA database.

One objective of this survey is to provide robust evidence on the link between management and firm performance in Croatia and in Eastern Croatia (or Slavonia).<sup>3</sup> The overall analysis may not allow to causally relate management capabilities to performance of firms but provides support for specific interventions aimed at improving firm productivity and for piloting policies and programs. For example, our analysis helps benchmark management capabilities in Eastern Croatia and in Croatia overall compared to other countries, the types of management practices that seem more relevant for firms, and the characteristics of enterprises whose management capabilities help explain further differences in performance.

We present some stylized facts for firms in Eastern Croatia and compare them with other regions in Croatia. We find that, _first,_ when benchmarking management scores in Slavonia and in Croatia against the United States, it is noteworthy that the average management score, just like TFP, is higher in the United States than it is in Croatia, and even higher than in Slavonia (Tables 1a and 1b). The average manufacturing firm in Eastern Croatia scores 0.532 in adopting advanced management practices, a value very similar to that in the rest of Croatia (0.542) but behind the one in the United States (0.615, Bloom et al., 2019a). Comparing Croatia’s management practices with those in Russia (Grover and Torre, 2019) and Mexico (Bloom et al., 2019b), other countries for which comparable data are available, we find that an average manufacturing firm in Croatia is better managed than its counterparts in Russia (average score, 0.43) and Mexico (average score, 0.39).<sup>4,5</sup> _Second,_ weaknesses in management practices particularly relating to data-driven performance monitoring cripples the overall management score in Croatia as well as Eastern Croatia. Data-driven performance monitoring includes specific practices that help managers define their key performance indicators (e.g. inventory, sales, absenteeism) and appropriately track them periodically over time, while incentives management practices relate to how managers and non-managers are awarded bonuses and promotion. The result for Croatia regarding the weaknesses of these subindices is similar to that in Russian manufacturing, that is, the monitoring aspect of structured management is weaker. By comparison, this finding is different from that in the United States and Mexico, where manufacturing firms are stronger in monitoring vis-à-vis structured management practices relating to workers’ incentives and target setting.

_Third,_ an interesting finding of this survey data is that services firms are farther from the frontier when it comes to adoption of structured management practices. Services firms were included in a MOPS framework survey for the first time in Mexico, where, as in the case of Slavonia and Croatia, it was also found that adoption of structured management practices is weaker relative to that in manufacturing (Bloom et al., 2019b). They attribute the lower management score in services to a lack of pro-competitive environment, which lowers the pay-off from adopting better management practices. In Eastern Croatia, an average services firm scores 0.519 on the adoption of the most advanced management practices, compared to 0.535 in manufacturing. As in Bloom et al. (2019b), we also conjecture

> 3 We use the terms Eastern Croatia and Slavonia interchangeably. ‘Slavonia’ is used as a shorthand for the region of Slavonija, Baranja & Srijem, consisting of five counties in Eastern Croatia. These five counties are: Brod-Posavina county, Osijek-Baranja county, Pozega-Slavonia county, Virovitica-Podravina county, and Vukovar-Srijem county.

> 4 Apart from data availability, it makes sense to compare Slavonia with the federal districts covered in Russia because, in both cases, the regions are part of a transition economy in Europe, although arguably Russian districts are much larger in size as well as in per capita GDP terms than any region in Croatia. Comparison with Mexico is also revealing in the sense that Mexico’s per capita GDP is closer to Slavonia (but lower than Croatia), but has a strong manufacturing base, and thus offers another perspective for comparison, apart from the United States, which is the benchmark frontier economy (upper bound). In fact, to minimize error margin, we took advantage of access to Mexican survey data on management capabilities at the sample stratification stage and the count of firms to be interviewed by sector within each region is based on an analogous comparator state in Mexico. For example, the sample distribution across sectors in Dalmatia is based on Quintana Roo, a state in Mexico with similar economic structure and relative income ranking as Dalmatia. Likewise, the target sample distribution of firms in Zagreb is based on Mexico City.

> 5 We are concerned that the higher score in Croatia may be a result of a low response rate and a likely selection bias. However, it should be noted that we did not find a significant selection bias based on observable characteristics of firms such as size, age, sector and export status.

3
||MANUF|ACTURI|NG|Croatia||||
|---|---|---|---|---|---|---|---|
||Mean|SD<br>|—p(l0)—s|p@5)—|p50)|pS)|pO)|
|Management score|0.542|0.15|<br>0.333|0431|0.558|0.637|0.724|
|Data drivenperformance monitoring|0.501|0.163|0.300|0367|0483|0.617|0.75|
|Incentives andtargets|0.362|0.191|0.298|O44|0.595|0.698|0.788|
|||||Slavonia||||
||Mean|SD|—p(l0)|=p@5)_—|p50)|TS)|pO)|
|Management score|0.535|<br>0.165|<br>0.306|<br>0417|0.565|0.667|0.706|
|Data drivenperformance monitoring|0.49|0.168|0.283|035|0467|0.6|0.767|
|Incentivesandtargets|0.55|0.217|0.286|042<br>Russia|0.605|0.708|08|
||Mean|SD<br>|— p(l0)—s|p@5)—|p50)|pS)|pO)|
|Management score|0.432|0.192|0.152|0.306|045|0.567|0.673|
|Data drivenperformance monitoring|0.323|0.227|0|0.133|03|035|0.633|
|Incentivesandtargets|0.496|0.221|0.167|0.361|0.523|0.663|0.762|
||||Mexico|(Bloom etal,|2019b)|||
||Mean|sD|p(i0)|p(23)|p(s0)|pt)|p(?0)|
|Management score|042|0.201|0.125|0.275|O44|0.576|0.673|
|Data drivenperformance monitoring|0.465|0.232|0.133|0.278|05|0.639|0.75|
|Incentivesandtargets|0.386|0.235|it]|02|0.398|0.568|O7|
||||United Sta|tes (Bloom e|t al, 2013)|||
||Mean|sD|p(i0)|p(23)|p(s0)|pt)|p(?0)|
|Management score|0.615|0.172|0.379|0.521|0.648|0.742|0.806|
|Data drivenperformance monitoring|0.643|0.199|0.365|0.521|0.677|0.792|0.865|
|Incentivesandtargets|0.383|0.215|03|o474|0.623|0.739|0.819|

||SE|RVICES||||||
|---|---|---|---|---|---|---|---|
|||||Croatia||||
|Management score|Mean<br>0.529|sD<br>0.148|p(id)<br>0.326|p23)<br>0441|pGd)<br>0.536|p>)<br>0.642|pid)<br>0.702|
|Data drivenperformance monitoring|O47|0.139|0.283|0.367|0.467|0.583|0.667|
|Incentives andtargets|0.537|0.195|0.286|0456<br>Slavonia|0.383|0.694|0.781|
||Mean|sD|p(l0)|p(23)|p(30)|p(75)|p(a0)|
|Management score|0.519|0.147|0.292|0.438|0.533|0.643|0.685|
|Data drivenperformance monitoring|0.463|0.147|0.267|0.383|0467|0.567|0.65|
|Incentivesandtargets|0.552|0.191|0.262<br>Mexico|0.456<br>(Bloom etal,|0.581<br> 2019b)|0.704|0.781|
||Mean|SD|p(l0)|ps)|p30)|p75)|p90)|
|Management score|0.395|0.204|O1|O244|0404|0.554|0.661|
|Data drivenperformance monitoring|0.409|0.226|0.067|0.222|o444|0.583|0.694|
|Incentivesandtargets|0.382|0.243|0|0.188|0.396|0.573|0.717|
A _fourth_ striking feature of this newly collected data in Croatia is that management shows a wide dispersion across firms in Eastern Croatia as well as in other regions in Croatia (see Figure 1), a finding comparable to other countries. Interestingly, the distribution of management score across firms suggests that management in Slavonia, relative to Croatia, has a thicker left tail and a thinner right tail, that is, relative to Croatia, a larger share of firms in Eastern Croatia are badly managed and a much smaller share is better managed. In particular, 42 percent of firms in Slavonia score below 0.5, as compared to 38 percent in other regions in Croatia, while only 3.5 percent of these firms have a score over 0.75 relative to 6 percent in other regions of Croatia. The heterogeneity in the distribution of management scores in Croatia is even more remarkable compared to countries at the frontier, for example, in the United States, 18 percent of firms have a management score over 0.75. Nonetheless, the finding on the distribution of the management score in Croatia is similar to that noted in Russia (Grover and Torre, 2019) and Mexico (Bloom et al., 2019b).

_Figure 1: Relative to other regions in Croatia, larger share of firms in Slavonia are poorly managed_ <!-- Start of picture text --> Management Scores<br>Croatian Firms (Manufacturing and Services), 2017<br>0 .2 .4 .6 .8 1<br>All Regions, Except Slavonia Slavonia<br>3<br>2<br>Density<br>1<br>0<br><!-- End of picture text --> Why does management matter? Across countries, Hall and Jones (1999) show how the stark differences in productivity account for a substantial fraction of the differences in average income. Differences in managerial quality are critical in explaining such cross-country differences in income levels, productivity, innovation and firm dynamism. For example, Bloom and Van Reenen (2010) attribute differences in productivity across firms in Asia, Europe, and North and South America to the heterogeneity in management practices across firms in these regions. Other performance measures, such as profitability and survival rates, are also positively correlated with good management practices. A novel finding of their work is that the cross-country variation in management practices was, in fact, smaller than differences between firms in the same country, suggesting that firm- and sector-specific factors were at least as important as the general business environment in shaping managerial performance. Differences in management are also correlated with competition, labor market flexibility, education and ownership structure.

_Fifth_ , consistent with the findings in other countries and data sets, a critical finding of this report is that structured management, that is, more intensive monitoring and more aggressive performance incentives (e.g., hiring, firing, pay and promotions), is associated with superior firm performance (figure 2). Figure 2 shows a clear pattern of higher sales per employee, wage per employee (quality of jobs), the share of firms adopting more sophisticated technology for quality controls, registering for patents, or training staff for their employees. More specifically, if management capabilities improve by magnitudes similar to that experienced in a field experiment on firms in India (that is, about 38 percent, see Bloom et al., 2013), then, conditional on observable factors such as industry, capital intensity, firm age, size and so on, such a change is associated with an increase in profit margin and sales per employee (labor 5
productivity) for an average firm in Eastern Croatia by 7 percent. Likewise, similar changes in management scores are associated with a 14 percent higher probability for an average firm in Eastern Croatia to introduce new products or processes, register for patents and 17 percent greater likelihood for an average firm to adopt more sophisticated technology, (e.g. for quality control). The analogous associated increase in all other regions is 13 percent in profits, 5 percent in sales per employee, while the probability of innovating and adopting more sophisticated technology increases by 24 and 9 percent respectively.<sup>6</sup> _Figure 2: Management matters for firm performance outcomes_ <!-- Start of picture text --> Sales Per Employee Sales Per Employee<br>Croatian Manufacturing Firms, 2017 Croatian Services Firms, 2017<br>1 2 3 4 1 2 3 4<br>Quartiles Quartiles<br>All Regions, Except Slavonia Slavonia All Regions, Except Slavonia Slavonia<br>Wage Per Employee<br>Croatian Manufactuing Firms, 2017 Wage per Employee (Real)<br>Croatian Services Firms, 2017<br>1 2 3 4<br>Quartiles 1 2 3 4<br>All regions, Except Slavonia Slavonia All other regions except Slavonia Slavonia<br>Use of Sophisticated Technology for Quality Control Use of Sophisticated Technology for Quality Control<br>Proportion of Croatian Manufacturing Firms, 2017 Proportion of Croatian Services Firms, 2017<br>1 2 3 4 1 2 3 4<br>All Regions, Except Slavonia Slavonia All Regions, Except Slavonia Slavonia<br>4,000<br>6,000<br>3,000<br>4,000<br>2,000<br>Sales/Employees Sales/Employees<br>2,000<br>1,000<br>0 0<br>1,000<br>1,000<br>800<br>600<br>Wage/Employees 400 500<br>200<br>0<br>0<br>.6 .4<br>.3<br>.4<br>.2<br>.2<br>.1<br>0 0<br><!-- End of picture text -->

> 6 As illustrated in figure 2, in the absence of controls, the relationship between management and firm performance appears to be weaker for Slavonia than in the rest of the regions. However, regression estimates that control for firm characteristics and fixed effects show that the correlation of firm performance and management is higher for firms in Slavonia for many economic outcomes, such as sales per employee and technology adoption.

6
<!-- Start of picture text --> Registration for Marks, Patents, Utility Models, and Industrial Designs Firms Participated in Training Programs<br>Proportion of Croatian Manufacturing Firms, 2017 Croatian Manufacturing Firms, 2017<br>1 2 3 4<br>1 2 3 4<br>Quartiles of Management Score<br>All Regions Except Slavonia Slavonia All Regions Except Slavonia Slavonia<br>.3 .8<br>.6<br>.2<br>.4<br>Proportion of Firms (%)<br>.1<br>.2<br>0<br>0<br><!-- End of picture text --> How do these results inform firm interventions designed for enhancing aggregate productivity? A simple answer to this question is that management can be improved with concerted effort. For example, an experiment with 17 textile firms in India provides a proof-of-concept that intensive individualized consulting can deliver lasting improvements in the practices of badly managed firms, resulting in productivity improvements by 17 percent (Bloom et al., 2013). Although this intervention improved management and firm performance, it came at a huge cost of approximately $75,000 per treated firm. This high cost is likely to be prohibitive for many small and medium enterprises (SMEs) to finance themselves, and for governments seeking to scale this up for assisting a large number of firms. To counter this, Iacovone et al. (2019) tested two alternative approaches to improving management among firms producing auto parts in Colombia. The first uses intensive and expensive one-on-one consulting, while the second draws on agricultural extension approaches to provide consulting to small groups of firms at approximately one-third of the cost of the individual consulting services. Their results show that both approaches lead to improvements in management practices of a similar magnitude (8-10 percentage points), so that the new group-based approach dominates on a cost-benefit basis.<sup>7</sup> This points to the potential of group-based approaches as a pathway to scaling up management improvements.

_Finally_ , given that management can be improved, our analysis of the survey data already points to some of the shortcomings in the incentive system for firms that inhibit adoption of structured management practices. For example, results suggest that management practices are negatively correlated with firm age, and especially so in lowtech manufacturing and non-knowledge intensive services. Moreover, the magnitude of this negative association is larger in Slavonia. This finding is surprising when compared with the United States or Mexico, where firms tend to improve their management practices as they age. The hypothesis is that, as firms grow, their production processes become more complex and, in order to stay in the market, they have to upgrade their management capabilities. However, in Croatia, firms continue to survive without the need to do so. This indicates the possibility that in Croatia learning and market selection are not operating perhaps due to the lack of pro-competitive forces.<sup>8</sup> Likewise, the finding that exporting firms are better managed confirms that the selection and learning mechanism actually works in Croatia, if firms compete in international markets. More precisely, the management score of a manufacturing exporter in Croatia is likely to be higher by 8 percent than for an average firm. The fact that this result is mainly driven by high-tech manufacturing exporters in the other regions of Croatia, where the management score is likely

> 7 Their results suggest that group-based intervention led to increases in firm size over the next 1.5 years, including a statistically significant increase in employment, while the impacts on firm outcomes are smaller and statistically insignificant for the individual consulting.

> 8 In the United States, it is well-known that “up-or-out” dynamics, in which unsuccessful firms exit or are bought out by more successful competitors who absorb the labor and capital released by exiting firms, drive productivity and business dynamism (Haltiwanger et al., 2013). In the case of Croatia, such selection dynamics do not seem to work in a similar way, and firms that are badly managed continue to survive.

7
to be 16 percent higher, points to the potential for improving management capabilities among other firms and sectors. By comparison, in Eastern Croatia, exporters are not significantly better managed than the rest of the firms.

The paper beyond this point is organized as follows: Section 2 compares firms in Eastern Croatia with Zagreb and other regions of Croatia on key parameters surveyed, including firm capabilities other than management (e.g. skills, innovation, technology adoption), outcomes on firm performance (e.g. labor productivity), and the constraints that firms face across different regions of Croatia. Section 3 introduces the methodology for computing management scores and compares management capabilities in Eastern Croatia with other regions of the country, and across countries. Section 4 presents some descriptive results on firm characteristics that are associated with management capabilities in Eastern Croatia relative to other regions in Croatia. Section 5 presents a simple regression framework for assessing the association between management practices and firm performance. Section 6 explores the drivers of good management practices. Section 7 concludes with policy recommendations.

# **Section 2: Firm Capabilities Survey**

In this section, we utilize the firm level survey to understand the differences between firms across regions in Croatia.

# **_2.1 Firm Performance, Technology Adoption and Obstacles – Comparing firms across regions_**

We compare firms based on three broad categories across Zagreb, Eastern Croatia and other regions in Croatia, excluding Zagreb and Eastern Croatia. The three categories are classified as follows: (1) firm performance – we use sales/employee (labor productivity) and gross value added (GVA) per employee as the two indicators; (2) innovation and technology adoption. For innovation, we assess whether a firm has registered itself for a new trademark, patent, utility model or industrial design and for the latter, we review the use of technology for quality and control management and introduction of new products and processes; and (3) the different types of obstacles the firms face during their operations.

_Figure 3: Firm performance in Slavonia is lower than that in Zagreb and other regions_ <!-- Start of picture text --> Productivity<br>Croatian Firms, 2017<br>Labour Productivity GVA per Employee<br>Other Regions Slavonia Zagreb Other Regions Slavonia Zagreb<br>5,000<br>150<br>4,000<br>3,000 100<br>2,000 Real GVA per Employee<br>50<br>Real Labour Productivity (Sales/Employee)<br>1,000<br>0 0<br><!-- End of picture text --> Comparing real labor productivity (sales per employee) and real GVA per employee of firms across Zagreb, Eastern Croatia and other regions of Croatia, we note that both the indicators of performance are highest in Zagreb, and lowest in Slavonia, especially in terms of GVA per employee (Figure 3). Labor productivity in Eastern Croatia is half that of Zagreb and other regions of Croatia; while, in the case of gross value-added it is one-third of that observed in Zagreb and one-half relative to other regions of Croatia.

8
# **_2.2 Technology adoption and innovation_**

Why is firm performance in Eastern Croatia lower relative to other parts of the country? One reason for the observed poor performance could be lower firm capabilities. This may manifest itself in the form of efforts to undertake innovation (process or products) and the adoption of sophisticated technology, for example for improving business processes, such as procurement or for tracking quality. The survey suggests that, while the share of firms that introduced new products and processes are similar in Slavonia relative to the rest of the regions, a much smaller share uses advanced technology for procurement and quality management (Figure 4).

When splitting the share of firms that introduced new processes versus products, firms in Eastern Croatia are more active in introducing new processes rather than innovative products. To this end the we consider the count of firms that have registered for trademarks, patents, utility models and industrial designs. Firms in Eastern Croatia are doing worse than their counterparts in Zagreb in introducing trademarks and patents. Impressively, firms in Slavonia are registering more for industrial designs than any other place in Croatia (Figure 5).

<!-- Start of picture text --> Figure 4: Firms in Slavonia lag behind in adoption Figure 5: Firms in Slavonia lag behind product<br>of advanced technology innovation but not with respect to industrial designs<br>Use of Technology and Introduction of New Products/Processes Registration for a New Innovation: Marks, Patents, Utility Models, and Industrial Designs<br>Croatian Firms, 2017 Croatian Firms, 2017<br>Other Regions Slavonia Zagreb<br>Other Regions Slavonia Zagreb<br>Marks Patents<br>Use of Technology: Control & Quality Managemen t New Goods or Processes Utility Models Industrial Designs<br>.8<br>.08<br>.6 .06<br>.4 .04<br>Proportion of Firms (%)<br>Proportion of Firms (%)<br>.02<br>.2<br>0<br>0<br><!-- End of picture text -->

# **_2.3 Skills_**

Another reason why firm performance in Eastern Croatia could be lower than the rest of the regions is perhaps found in the availability and quality of skills. One of the main problems, which has been identified by the firms across regions is the issue of skill shortage. We consider the top three shortage challenges with respect to skills among firms in Eastern Croatia, Zagreb and other regions. Ability to solve problems and initiative to participate in the job market are the two major problems cited by the firms for skill shortage across regions. The proportion of firms that perceive that the ability to solve problems is one of the core reasons for the skill shortage is highest in Eastern Croatia. Firms in Eastern Croatia additionally cite educational quality as the third most important problem, whereas firms in Zagreb and other regions do not perceive this as a big challenge; rather, problems relating to employees’ attitudes (e.g., discipline) could be a bigger constraint.

9
_Figure 6: Firms in Slavonia perceive education quality to be a top challenge for worker’s skills_ <!-- Start of picture text --> Main 3 Problems for Shortage of Skills: Across Regions<br>Croatian Firms, 2017<br>Other Regions Slavonia<br>Ability to Solve Problems Initiative Educational Quality<br>Discipline Initiative Ability to Solve Problems<br>Zagreb<br>Ability to Solve Problems Inititative<br>Discipline<br>25 40<br>20 30<br>15<br>20<br>10<br>5 10<br>Proportion of Firms (%)<br>0 0<br>25<br>20<br>15<br>10<br>5<br>Proportion of Firms (%)<br>0<br><!-- End of picture text -->

# **_2.4 Business Environment_**

External factors such as enabling conditions for businesses to flourish can also significantly influence firm performance. We investigate the obstacles for firms’ motivation to upgrade to better production or management processes. Figure 7 lists seven different problems in order of their importance reported by the firms. Most firms in Eastern Croatia (and in other regions, including Zagreb) perceive lack of skilled workers and political instability and corruption as the two main obstacles affecting their operations.

_Figure 7: Lack of skilled workers, political instability are among the top obstacles for firms in Croatia_ <!-- Start of picture text --> Obstacles for Production or Management Processes<br>Croatian Firms, 2017<br>Other Regions Slavonia Zagreb<br>Lack of Skilled Workers Cost of Capital<br>Small Market Size Internet<br>Flexibility of Regulations Technical Support from Govt/Private Sector<br>Corruption/Political Instability<br>40<br>30<br>20<br>Proportion of Firms (%) 10<br>0<br><!-- End of picture text --> Among the major economic problems that a firm perceives as binding constraints to their growth, Figure 8 suggests that Slavonian firms find taxes and qualification of the workforce to be a major roadblock. This is similar to the problems faced by firms in Zagreb and other regions.<sup>9</sup>

> 9 The survey asks firms to rank the top problems in their growth and operations. This does not necessarily imply that taxes, for example, vary sub-nationally but that firms in a given region perceive the noted problem as a bigger constraint.

10
_Figure 8: Slavonian firms find high taxes and qualification of the workforce to be a major hurdle_ <!-- Start of picture text --> Major 5 Problems for Growth of a Firm<br>Croatian Firms, 2017<br>Other Regions Slavonia Zagreb<br>Lack of Credit Qualification of Workforce<br>Cost of Labour Excess of Govt. Procedures<br>High Taxes<br>60<br>40<br>20<br>Proportion of Firms (%)<br>0<br><!-- End of picture text --> With firms facing multiple constraints, there are several government programs that are available to help firms. In fact, of the 585 surveyed firms, nearly 59 percent of these firms have applied for some government program in the last three years, with the largest share being in Eastern Croatia (62 percent), relative to Zagreb (58 percent) and other regions (59 percent).<sup>10</sup> Nonetheless, nearly 40 percent of the firms do not participate in government programs. Why? Among the programs that are available, a large share of firms in Eastern Croatia do not find it appropriate to their needs, while others find it administratively burdensome to fulfill the application requirements (Figure 9).

_Figure 9: Customizing programs to firm’s needs and reducing administrative burden may encourage participation in government programs_ <!-- Start of picture text --> Reasons for Not Requesting Govt. Programs<br>Croatian Firms, 2017<br>Other Regions Slavonia Zagreb<br>No programs for the firm Lot of administrative work<br>40<br>30<br>20<br>Proportion of Firms (%)<br>10<br>0<br><!-- End of picture text -->

**Section 3: Critical Firm Capabilities: Management in Focus**

# _3.1 Why do we need a management survey?_

Although managerial and organizational practices have been conceived to be critical in affecting firm outcomes since the time of Adam Smith’s pin factory and Walker’s 1887 paper on business performance, these practices are not well measured in administrative data on firms or the commercial data on companies’ accounts. Some studies have used

> 10 The lowest participation rate was observed in Dalmatia (47 percent).

11
Aspect Open (e.g. WMS) Closed (e.g. MOPs) Accuracy of responses = High: Interview format gives opportunity to Medium: Harder to elicit truthful answers if probe and ask for examples. Possible to respondents have preconceptions. Greater risk implement “double blind” method to reduce that respondents might misinterpret questions or preconception bias. rush through the survey. Cost per survey High: High quality trained interviewers needed Low: Initial design and execution costs, but this to run survey. Training includes one week initial fixed cost can be spread over a very large number training and ongoing debriefing and calibration. of respondents, so cost per survey is low. Costs Interviewers’ time primarily spent recruiting can be higher im poorer countries where managers to take part in the survey (rather than enumerators administer surveys onsite because of just running interviews). unreliable mail and e-mail networks. Response rates Medium: Interview is interactive and managers High: Co-operation with a National Statistics more engaged. We obtained an average response Agency can enable the survey to be mandatory. rate of 40%. Given this response rates ofaround 80%. Without such co-operation, response rates will be low. Replicability Medium: Training needed to ensure the surveyis High: Questionnaire essentially the same across delivered in same way. Useful to have some countries and already available pre-tested fromby individuals who have worked in previous survey US Census Bureau. waves as trainers for other surveys foster comparability. Traiming and survey material is available on-line. International High: Multiple countries can be interviewed Medium/High: Easier to implement but there is a comparability from same location. Using bilingual interviewers risk of differential interpretation if this is not means makes it is easier to cross-check carefully translated across languages. responses. Speed of delivery High: Can complete a full survey wave in about Medium: Involves cooperation with national 10 weeks. So including recruitment and set-up statistical agencies, so more planning work in time possible to complete a survey wave from advance. The survey period typically is around3 scratch in about 4 months. months plus 1 to 3 months of data cleaning.
Zagreb Slavonia Dalmatia Zagreb Virovitica-Podravina Zadar City of Zagreb Pozega-Slavonia Sibenik-Knin Northern Croatia Slavonski Brod-Posavina Split-Dalmatia Krapina-Zagorje Osijek-Baranja Dubrovnik-Neretva Varazdin Vukovar-Sirmium Koprivnica-Krizevei Croatian coastline and Istria Bjelovar-Bilogora Lika-Senj Medimurje Primorje-Gorski kotar Sisak-Moslavina Istria Karlovac
<!-- Start of picture text --> Services (by knowledge intensity) Manufacturing (by technology intensity)<br>Region knowledge Non-knowledge High Low Total<br>Croatian coastline and Istria 34 26 12 30 102<br>Dalmatia 25 20 4 26 15<br>Northern Croatia 51 34 29 36 150<br>Slavonia 4] 38 17 49 145<br>Zagreb 34 23 26 30 113<br>Total 185 141 88 171 585<br><!-- End of picture text -->

||Services (by|knowledge intensity)|Manufacturing|(by technology intensity)|
|---|---|---|---|---|
|Region|knowledge|Non-knowledge|High|Low<br>Total|
|Croatian coastline and Istria|34|26|12|30<br>102|
|Dalmatia|25|20|4|26<br>15|
|Northern Croatia|51|34|29|36<br>150|
|Slavonia<br>|4]<br>|38<br>|17<br>|49<br>145<br><br>|
|Zagreb|34|23|26|30<br>113|
|Total|185|141|88|171<br>585|
<!-- Start of picture text --> 0 2 4 6 8 1<br><!-- End of picture text --> <!-- Start of picture text --> Sweden United Kingdom United States<br>1 2 3 4 5 1 2 3 4 5 1 2 3 4 5<br><!-- End of picture text -->
<!-- Start of picture text --> All Regions, Except Slavonia Slavonia<br>oo<br>coso|<br>0 2 4 & 8 1 2 A & 8 1<br>———_ Kernel DensityofManagementScores ————___ Kernel Densityof ManagementScores<br><!-- End of picture text -->
<!-- Start of picture text --> AllRegions, Except Slavonia Slavonia<br>Pe<br>”<br>TM a<br>ry<br>22<br>a<br>3 4 5 F) 1 i 2 4 5 8<br><!-- End of picture text --> <!-- Start of picture text --> All Regions, Except Slavonia Slavonia<br>a<br>aD<br>=<br>co<br>a 2 r 8 a 1 a 2 A 6 a 1<br><!-- End of picture text -->
|||||||||s (N)|
|---|---|---|---|---|---|---|---|---|
|||All Regi|ons, Exce|pt Slav|onia||||
|Manufacturing||0.545|0.145|0.289|0.351|0.555|0.724|0.758|193|
|<br>Services|<br>0.532|0.149|0.278|0.3826|0.538|0.712|0.750|247|
||||Slavon|ia|||||
|Manufacturing||0.535|0.165|0.217|0.306|0.565|0.706|0.774|66|
|<br>Services|<br>0.519|0.147|0.229|0.292|0.533|0.685|0.726|79|

Notes: ‘Management Score’ is calculated following MOPS (See Bloom et al., 2018).

<!-- Start of picture text -->
- “<br>High-tech Lowetech KIS NKIS<br>Ka<br><!-- End of picture text -->

<!-- Start of picture text --> “<br>KIS NKIS<br>Ka<br><!-- End of picture text -->
<!-- Start of picture text --> Who takes the critical decision of a firm?<br>Croatian Firms, 2017<br>a<br>#<br>@<br>ES<br>ae.<br>5<br>t<br>a<br>Es<br>=<br>Other Regions Slavonia Zagreb<br>HE Founder «=ER Family member of the founder<br>HEE Manager<br><!-- End of picture text -->
<!-- Start of picture text -->
- mi Management level i Management spread<br>(sample normalized to 0) o<br>a<br>£<br>oOo<br>—ae2asOo©&o>£0s5<br>oo wf<br>~co> coo ®<br>ot cf E<br>fr Do<br>oSDo Seoo<br>Sec oc N<br>a2 s2<br>se Zo<br>©' gsY3<br>Efe)<br>£<br>+<br>12 3 4 5 6 7 8 9 10+<br>Firm Age<br><!-- End of picture text -->

<!-- Start of picture text --> Notes: Plots In(management) scores weighted by age. Results from simulating 5,000 firms per year in the<br>steady state taking the last 10 years of data and defining age based on the number of observed years.<br>Management normalized to zero on the sample. Replication file on http://web.stanford.edu/~nbloom/MAT.zip<br><!-- End of picture text -->
_Figure 17: In Croatia and in Slavonia, firms’ management score falls with age_ <!-- Start of picture text --> Median Management Scores (by Age Categories)<br>Croatian Firms (Manufacturing and Services), 2017<br>0-10 11-19 >= 20<br>All Regions, Except Slavonia Slavonia<br>.6<br>.4<br>.2<br>0<br><!-- End of picture text -->

# _f. Size_

In the United States, Bloom et al. (2014) show that better managed firms are significantly larger than poorly managed firms: In the United States, their work shows that a one standard deviation of management is associated with a 40 log point increase in employment size. We find similar results in Croatia and in Slavonia, where firm size is significant and positively correlated with management score.

_Figure 18: In Croatia and in Slavonia, firms’ management score rises with size_ <!-- Start of picture text --> Median Management Scores (by Size Categories)<br>Croatian Firms (Manufacturing and Services), 2017<br>06-10 11-20 21-34 >= 35<br>All Regions, Except Slavonia Slavonia<br>.6<br>.4<br>.2<br>0<br><!-- End of picture text -->

# _g. Exporters_

In manufacturing, the exporters have adopted significantly higher management practices, especially in Slavonia. On average, an exporter in Slavonia has adopted 60% of the management practices, whereas a non-exporter has only 51%. However, in the case of services, the difference is not very clear whether exporters are better managed, especially in Slavonia (Figure 19).<sup>22</sup>

> 22 See Annex Table A.4 for detailed results.

21
<!-- Start of picture text --> 2<br>t<br>~<br>2 M-Exporter M-NonExporter S-Exporter S-NonExporter<br><!-- End of picture text -->
<!-- Start of picture text --> Sales per employee Profits<br>1 3<br>25<br>08<br>2<br>15<br>0.6<br>1<br>04 05<br>0.2<br>05<br>-1<br>“15<br>02 -2<br>Over al Manufacturing Services Over al Manufacturing Services Overal Manufacturing Services Overal Manufacturing Services<br>Croatia,all regions except Slavonia Slavonia Croatia,allall regions except Slavonia Sevonia<br>Innovation: likelihood of introducing a new product/process Technology adoption: adoption: Likelohood of using sophisticaed technology in sophisticaed technology in technology in in<br>3 procuments/quality management management<br>15<br>15<br>1<br>1<br>05<br>-05 Overal Manufacturing Sevices Overal Manufacturing Services 05nene vera wanufacturing seviees oven Manufacturing seviees<br>Croatia, all regions except Slavonia Slavonia Croatia, all regions except except Slavonia Stavonia<br><!-- End of picture text --> <!-- Start of picture text --> Profits<br>3<br>25<br>2<br>15<br>1<br>05<br>05<br>-1<br>“15<br>-2<br>Overal Manufacturing Services Overal Manufacturing Services<br>Croatia,allall regions except Slavonia Sevonia<br><!-- End of picture text --> <!-- Start of picture text --> Technology adoption: adoption: Likelohood of using sophisticaed technology in sophisticaed technology in technology in in<br>procuments/quality management management<br>15<br>1<br>05<br>05nene vera wanufacturing seviees oven Manufacturing seviees<br>Croatia, all regions except except Slavonia Stavonia<br><!-- End of picture text -->
<!-- Start of picture text --> ©<br>©<br>aT2S<br>“<br>°<br>All Regions Except Slavonia Slavonia<br>f Estimated Management Score | Self Evaluated Management Score<br><!-- End of picture text -->
The realization that firms in Croatia and particularly those in services sector (non-knowledge intensive services, specifically for Eastern Croatia) are far from the frontier in adoption of structured management practices, what can we really do about this? Next, we analyze the factors that matter for management capabilities, with the objective of building on these capabilities to bridge the gap in firm upgrading.

Firm characteristics play a key role in explaining variations in management score. Annex Tables A.6 presents the detailed regression results for all regions, excluding Slavonia, and Slavonia. In Figure 23 we present rope ladder plots from the specification including all controls and fixed effects, for all sectors, top panel, and for manufacturing (bottom, left panel) and services (bottom, right panel). _First_ , both unconditional and conditional correlations suggest that, in line with prior studies, firm size plays a key role in adoption of management practices. This is true for both regions excluding Slavonia and Slavonia, especially for manufacturing industries. Doubling the firm size is associated with an increase in the management score of about 0.1. The significance of the relationship between firm size and management score in Slavonia is mainly driven by mainly the manufacturing sector, while this relationship is insignificant in services. This implies that management capabilities are weaker for services sector across all the range of the size of distribution. Although it is true that management practices are crucial for the performance of medium and large firms, the link of management with performance usually extends throughout the size distribution in the United States and Mexico (Bloom et al., 2019a; 2019b).<sup>23</sup> _Second_ , in Croatia age is negatively correlated with management score. Adoption of structured management practices are lower among older firms. Following similar analysis in Bloom et al. (2019b) on Mexico and the work of Hsieh and Klenow (2014) regarding the life cycle of firms, this finding appears to be indicative of poor allocative efficiency among firms in Croatia where clearly, market selection is not operating perhaps due to the lack of pro-competitive conditions, especially in services. Nevertheless, the finding in Croatia is somewhat similar to that in Russia, where firms also do not improve with age (Grover and Torre), although in Croatia it is very clear that this negative association is driven by the services sector.

_Third_ , exporters have higher scores in adopting structured management practices, and significantly so in manufacturing. More precisely, the management score of a manufacturing exporter in Croatia is likely to be higher by 8 percent than an average firm. The fact that this result is mainly driven by high-tech manufacturing exporters in regions other than Croatia, where management score is likely to be 16 percent higher, points to the potential for improving management capabilities among other firms and sectors. In Eastern Croatia, this relationship between exporting and higher managerial capabilities is not significant even for manufacturing. To design interventions for improving management capabilities in Eastern Croatia, it may be crucial to examine the export composition and destination markets for firms in Slavonia and more specifically in understanding why exporters do not find it worthwhile to improve management capabilities.

_Fourth_ , firms with more than 20% of their employees having a college degree are more likely to adopt structured management practices. Education of employees matters for managerial score in all regions except in Slavonia. This is a surprising finding and may need to be explored further. It may perhaps be related to the quality of education among workers in Slavonian firms.<sup>24</sup>

> 23 In Bloom et al. (2019b), only four questions from the U.S. MOPS were selected for microenterprises. The correlation between the management score calculated with this subsample of questions and the overall management score for SMEs and large firms is 0.86, indicating that this short score is a good measure of management practices. This result is similar to McKenzie and Woodruff (2017) who find an important role for management in micro-firms in developing countries.

> 24 As annex table A.6 shows, the overall explanatory power of firm characteristics in explaining the management score is still quite limited: the most complete specification (column 8) explains only 21% of the overall variation in the management score, implying that nearly 80% of the variation in management practices is explained by idiosyncratic, firm-specific factors.

25
<!-- Start of picture text --> At Regices Except Siaventa Siaweia<br>Sime —_— _—_—_<br>Age] —— —>—<br>Exporter<br>Eaucatcns ee<br>08 0 08 1 308 0 8 1<br><!-- End of picture text --> <!-- Start of picture text --> Se + —_—<br>Age<br>Expeter<br>Eauation =<br>Ineonatons ——<br>a i 4 Zz:Bo 0 . 1 : 2<br><!-- End of picture text --> <!-- Start of picture text --> ‘Size: —1—<br>Age —<br>coe,<br>fawcanes ——<br>lnnattion ~=—<br>iM a 1 1 6 1<br><!-- End of picture text -->
and the education level of non-managers are the most relevant. Surprisingly firm age is negatively associated with better management practices, especially in services. This implies that, unlike in the United States and Mexico, firms do not learn to be better managed as they age. Thus, it is possible that a lack of pro-competitive forces in Croatia and more so in the services sectors does not promote learning and possibly hinders market selection. Equally important in explaining the lack of upgrading among firms is the finding that firms do not realize that there is a problem with respect to their management practices. Firms in Eastern Croatia and in the rest of the regions perceive their management quality to be much higher than it actually is and hence do not feel the need to improve it.

Following the ABC framework for firm growth proposed in Grover, Medvedev and Olafsen (2019),<sup>25</sup> we make the following recommendations for enhancing productivity and business dynamics in Eastern Croatia and other regions in the country:

1. **A** llocative efficiency: The fact that management capabilities are negatively associated with firm age is an indication of a lack of a learning and selection mechanism operating in Croatia, especially in the services sector. Policies to support healthy business dynamics need to establish the basic enabling conditions: facilitate reallocation of resources (e.g., labor, capital, land) across firms, and ease the business environment for entry and exit of firms. Such policies will increase competition and the market will ensure that firms are motivated to upgrade and invest in their capabilities.

2. **B** usiness-to-business linkages: Our paper finds that firms with foreign linkages, that is, exporters, are more likely to be better managed. In this context, policies to connect firms to export markets can encourage learning and hence better management practices. Such firms are more likely to engage in quality upgrading, leading to higher productivity and firm growth. The finding that such a link does not exist for Slavonia is surprising and is at odds with the existing literature. Thus, a more detailed analysis of the product composition and destination markets of exporters in Slavonia may be warranted.

**3. C** apabilities of firms: More critically, our work confirms the tight association of managerial capabilities with firm performance for firms in Croatia as well as Slavonia. Management matters not only for productivity, but also for profits and innovation. Thus, firms in Croatia and also more so in Slavonia are more likely to benefit from training on structured management relating to these practices.

# **References**

Bender, S., N. Bloom, D. Card, J. Van Reenen, and S. Wolter. (2015). “Management Practices, Workforce Selection and Productivity”, mimeo.

Bertrand, M. and A. Schoar. (2003) “Managing with Style: The Effect of Managers on Firm Policies”, _Quarterly Journal of Economics_ , 118(4): 1169-1208 Bloom, N. and J. Van Reenen. (2007) “Measuring and Explaining Management Practices Across Firms and Countries”, _Quarterly Journal of Economics_ , 122(4): 1351-1408 Bloom, N. and J. Van Reenen. (2010) “Why Do Management Practices Differ across Firms and Countries?”, _Journal of Economic Perspectives_ , 24(1): 203-24 N. Bloom, H. Schweiger and J. Van Reenen. (2011), “Quality of management practices in transition countries”, NBER Working Paper No. 17231.

> 25 This framework proposes that policies for improving firm dynamism and supporting job creation should steer away from picking potential winners and focus on improving **A** llocative efficiency, strengthening **B** usiness-to-business spillovers, and building firm **C** apabilities. These policies rely on encouraging innovation, network and agglomeration economies, global linkages, worker skills and managerial capabilities, and financial development to rebalance growth/productivity policies.

27
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