1 Introduction
Over the past decade, a growing body of evidence has accumulated suggesting that the
reallocation of factors of production – including labour – plays a major role in driving
productivity growth (see, for example, Olley and Pakes (1996), Griliches and Regev (1995),
Foster et al. (2001), Foster et al. (2002) and Bartelsman et al. (2004)). New firms enter the
market and create new jobs, while other unprofitable firms exit the market contributing to job
destruction (see, for example, Sutton (1997), Pakes and Ericson (1998), Geroski (1995)).
Incumbent firms are in a continuous process of adaptation in response to the development of
new products and processes, the growth and decline in markets and changes in competitive
forces (Davis and Haltiwanger (1999)). Market structure and size composition of firms play a
major role in shaping the magnitude of job flows and their characteristics (Davis et al. (1996)).
For example, smaller businesses are inherently more dynamic, in part because they tend to be
young ventures and adjust through a learning-by-doing process (Dunne et al. (1988), Dunne
et al. (1989)). In addition, some industries have inherently higher job flows than others in all
countries, given the smaller size of their typical business and lower inherent entry costs (for
example, Foster et al. (2002) report that job flows in the US retail sector are 1.5 times higher
than in the manufacturing sector).
Standard models (see, for example, Hopenhayn and Rogerson (1993)) predict that, in addition to
technology and market-driven factors, the institutional and regulatory environment in which
firms operate will have an impact on the pace of job flows. Moreover, consistent with the
discussion above, such models imply that restrictions that dampen reallocation will in turn lower
productivity as the dampening of job reallocation reduces the extent to which an economy is
allocating activity to the most productive producers. However, the empirical evidence on labour
regulations and job flows is inconclusive – countries with different types of labour regulations
are observed to have fairly similar gross job flows (see, for example, Bartelsman et al. (2009),
Bertola and Rogerson (1997), Boeri (1999)).
The lack of a strong empirical relationship between labour flexibility regulations and gross job
flows at the aggregate level may be due to various elements. Stringent labour regulations may be
associated with other regulatory and institutional factors that also affect job flows. For example,
Bertola and Rogerson (1997) argue that the greater compression of wages in Europe than in the
US can compensate the differences in labour regulations and so explain the similarity of the job
turnover rates. A more fundamental problem is that cross-country analyses of job flows may be
flawed by severe omitted variable problems and measurement error, including differences in the
distribution of activity across industries and size of firms, as well as different business size cut-off points in the enterprise surveys from which job flows data are obtained. In this paper, we
overcome these obstacles by using detailed indicators of job flows drawn from harmonised and
integrated firm-level databases covering 16 developed, emerging and transition economies of
central and eastern Europe. With these data, we explore in detail the industry and size
dimensions of job flows, and relate them to institutional differences across countries.
To preview results, we find that countries share a number of features of job flows along the
industry and size dimensions. All countries are characterised by large job flows compared with
net employment changes. These vary significantly and systematically across industries, pointing
to technological and market-driven factors, but they vary especially across firms of different
size. To provide a perspective on the importance of firm size, we find that industry effects alone
account for about 5 per cent of the variation in job reallocation rates across country, industry and
size classes, while firm size effects alone account for about 47 per cent of the same variation.
However, even after controlling for industry and size effects, there remain notable cross-country
differences in job flows. In this paper, we develop a formal test of the role that hiring and firing
regulations have in explaining these differences, and also test for the robustness of our results to
the inclusion of other regulations affecting business operations. We use a
difference-in-difference approach in which we identify an industry and size class’s baseline job
reallocation from the US data. The advantage, compared with standard cross-country (or even
cross-country/cross-industry) empirical studies, is that we exploit within-country differences
across industrysize groups based on the interaction between country and industrysize
characteristics. Thus, we can also control for country and industrysize effects, thereby
minimising the problems of omitted variable bias and other misspecifications. We find support
for the general hypothesis that hiring and firing costs reduce turnover, especially in those
industries and size classes that require more frequent labour adjustment. Moreover, stringent
labour regulations have a stronger effect on the labour reallocation that is originated by the entry
and exit of firms than that due to reallocation among incumbents.
Before proceeding, it is useful to discuss two recent papers that exploit job flows across
industries within countries to investigate the role of employment protection: Micco and Pages
(2007) and Messina and Vallanti (2007). Messina and Vallanti (2007) focus on cyclical and
secular variation in job turnover.2 The paper that is closest to ours in terms of questions and
approach is Micco and Pages (2007). The latter paper exploits industry level gross job flows
data for manufacturing for 18 countries and uses a difference-in-difference specification close to
the specification we consider in this paper. Our analysis differs from this study along a number of related key dimensions. First, our indicators are drawn from a harmonised firm-level database
that covers all firms with at least one employee for both manufacturing and non-manufacturing
sectors. Second, our indicators allow exploiting country, industry and firm size variation in the
data, while previous studies tend to concentrate on country and industry variation. Interestingly,
we find that firm size is by far the most important factor accounting for variation in the job flows
across country, industry and firm size classes. This suggests that exploiting data by firm size is
important to provide greater within-country variation in job flows for our empirical identification
strategy but also that distortions to job flows across countries may very well interact with the
flow and firm size relationship. Indeed, evidence from enterprise surveys suggests that
policy-induced distortions tend to affect firms of different size very differently.3 Lastly, our data
allow distinguishing between job flows generated by the entry and exit of firms and those
generated by the reallocation of labour by incumbent firms. As shown in the paper, this sheds
additional light on labour reallocation and the role of regulations in labour and product markets.
The remainder of the paper is organised as follows. Section 2 presents our harmonised
firm-level dataset and discusses the different concepts we have used to characterise labour
reallocation. Section 3 analyses the main features of job flows, highlighting the role of firm
dynamics, industry and size compositions. Section 4 introduces the difference-in-difference
approach used in the econometric analysis and discusses the empirical results for the baseline
and policy-augmented specifications of the job flow equations. It also describes a battery of
robustness tests. Lastly, section 5 presents concluding remarks.
2 Data
Our analysis of job flows is based on detailed indicators drawn from a harmonised firm-level
database that includes 16 industrial, emerging and transition economies (Argentina, Brazil,
Chile, Colombia, Estonia, Finland, France, Germany, Hungary, Italy, Latvia, Mexico, Portugal,
Slovenia, the United Kingdom and the US) and covers the 1990s (the time period covered varies
by country - see Table A.1). Beyond the country dimension, the job flow indicators vary across
detailed industry and size classes and over time. They have been extracted from country
firm-level datasets with an active participation of local experts in each of the countries, and
involved the harmonisation of key concepts to the extent possible (such as entry and exit of
firms, job creation and destruction, and the unit of measurement), as well as the definition of
common methods to compute the indicators (see Bartelsman et al. (2009) for details).
The key features of the micro data underlying the analysis are as follows:
Unit of observation: Data used tend to conform to the following definition: “an
organisational unit producing goods or services which benefits from a certain
degree of autonomy in decision-making, especially for the allocation of its current
resources” (EUROSTAT (1998)). Generally, this will be above the establishment
level.
Size threshold: While some registers include even single-person businesses (firms
without employees), others omit firms smaller than a certain size, usually in terms
of the number of employees (businesses without employees), but sometimes in
terms of other measures such as sales (as is the case in the data for France). Data
used in this study exclude single-person businesses. However, because smaller firms
tend to have more volatile firm dynamics, remaining differences in the threshold
across different country datasets should be taken into account in the international
comparison.
Industry coverage: Special efforts have been made to organise the data along a
common industry classification (ISIC Rev.3) that matches the OECD-Structural
database (STAN). In the panel datasets constructed to generate the tabulations, firms
were allocated to the single STAN industry that most closely fit their operations
over the complete time-span.
The firm-level and job flows data come from business registers (Estonia, Finland, Latvia,
Slovenia, the United Kingdom and the US), social security databases (Germany, Italy, Mexico)
or corporate tax rolls (Argentina, France, Hungary). Annual industry surveys are generally not
the best source for firm demographics, due to sampling and reporting issues, but have been used nonetheless for Brazil, Chile, and Colombia. Data for Portugal are drawn from an
employment-based register containing information on both establishments and firms. All these
databases allow firms and jobs to be tracked over time because addition or removal of firms
from the registers reflects the actual entry and exit of firms.
We define four size classes based on the number of firm employees: 1- 19 workers, 20-49
workers, 50-99 workers, and 100 or more workers. The job reallocation rate (sum) is defined as
the sum of job creation (pos) and job destruction (neg) rates, and we allow those to vary by the
type of firm: entering, exiting or continuing firms. Job creation rate is defined as
and job destruction rate as
where i represents industry, s represents size class, c represents country, t represents time (year) and E denotes employment. Capital letters S and C refer to a set of size classes or countries, respectively, SC+ denotes positive changes in employment and SC-� negative changes in employment. The symbol D denotes the first-difference operator,
The job flows are calculated on a yearly basis. In all our empirical analysis, we use time averages to reduce the possible impact of business cycle fluctuations in the years for which we have the data and the possibility that such fluctuations were not synchronised across countries and thus not captured by the use of common time fixed effects.
3 Basic facts about job turnover in industrial and emerging economies of Latin America and central and eastern Europe
In this section, we highlight the key stylised facts emerging from our analysis of job flows
across countries, industries and firm size. These stylised facts are used in the following sections
to guide our multivariate analysis.
1. Large job turnover in all countries
The first stylised fact emerging from the data is the large magnitude of gross job flows (the sum
of job creation and job destruction) in all countries compared with net employment changes,
both at the level of total economy and in manufacturing (see Table B.1 in the appendix and
Haltiwanger et al. (2006)). Gross job flows range from about 25 per cent of total employment on
average in the OECD countries, to about 30 per cent in Latin America and the transition
economies. By contrast, net employment changes tend to be very modest if not nil in the OECD
and Latin America over the sample period, while the transition economies recorded a significant
net job growth in the period covered by the data, after the substantial job losses of the early
phases of the transition.
Taken at face value, the observed high pace of job reallocation in all countries may suggest a
high degree of dynamism in virtually all economies. However, even at the aggregate level there
are significant cross-country differences and, in addition, many different country-specific factors
tend to influence the pace of job reallocation, within each country, across industries and size
classes. Accordingly, the identification of the impact of regulations requires exploiting more
than simply cross-country variation.
2. Firm turnover plays a major role in total job flows
The second stylised fact is the strong contribution of firm creation and destruction to job flows.
Entering and exiting firms account for about 30-40 per cent of total job flows (see Table B.1 in
the appendix). In the transition countries, entry was even more important in the early years of
transition to a market economy, while the exit of obsolete firms became more predominant in
the second half of the 1990s, both for the total economy and in manufacturing, when market
contestability strengthened.
3. Small firms contribute disproportionately to job flows
Small firms account disproportionately for job flows and firm turnover in all countries of our
sample. Figure 1 presents job reallocation rates by firm size classes and countries. In general,
job reallocation is highest in firms with less than 20 employees, and the lowest in firms with
100+ employees. In the US, job turnover declines monotonically with firm size, and the decline is particularly marked among large units (100+). Latin American countries follow similar
patterns to those of the US, while the European countries, with the exception of France, have a
less marked drop of job reallocation among larger units. The transition countries, on the other
hand, show a steeper slope in smaller size classes, especially in the early years of transition. It
is this variation of job flows by size class as well as the variation across industries and countries
that we exploit in our empirical analysis.
The analysis of size-specific job reallocation rates should be complemented with a
decomposition of the overall job reallocation into that due to firms of different sizes. We find
small firms account for the largest share of firm turnover and also for a significant, albeit less
dominant, share of total job flows. In terms of shares of job reallocation by size class, we find a
U-shaped relationship that reflects two offsetting effects – first, job flows are higher for small
firms as evidenced in Figure 1 and second, employment is concentrated in larger firms.
4. Analysis of variance
The next step is to assess the relative importance of the different dimensions – country, industry
and size – in explaining the overall variance in job flows. Table 1 presents the analysis of
variance of job flows, for the unbalanced total economy and manufacturing samples.12 We
consider different indicators of job flows - gross job reallocation, job reallocation from entry and
exit and job reallocation for continuers. We also assess the contribution to the total variance of
industry, size, country and industrysize effects separately and, in addition, differentiate the
analysis of variance by region (OECD, transition economies and Latin America).
It is noticeable that technological and market structure characteristics that are reflected in the
industry-specific effects explain only 5.1 per cent of the overall variation in gross job
reallocation across industry, size and country classes, although they account for a higher share in
Latin America (18.4 percent). They explain much less of the overall variation in the
manufacturing sample. By contrast, differences in the size structure of firms explain as much as
47.0 per cent of the total variation in cross-country gross job reallocation overall, and even more
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