Do market pressures induce economic efficiency? The case of Slovenian manufacturing, 1994-2001.
Orazem, Peter F. ; Vodopivec, Milan
1. Introduction
A long-held but infrequently tested proposition in economics is
that competitive pressure will force firms to be efficient. (1) The
transition to market in formerly planned economies offers a natural
laboratory to test the competitive hypothesis. As reviewed by Boeri
(2000), the consensus expectation at the outset of transition is that
competitive pressures from the emerging market system would force
greater productive efficiency on enterprises that remained from the old
system. Furthermore, converting state-owned enterprises into
profit-maximizing firms was expected to create incentives to improve the
efficiency of these often-under-performing sectors, either through
profit motives or through the rigors of investor scrutiny (Brada 1996).
This study examines whether market competition had the expected effect
on productive efficiency in Slovenia.
The early evidence from transition economies does not demonstrate
immediate evidence of efficiency gains. From an initial reduction in
gross domestic product (GDP) averaging 25% in Central and Eastern Europe
and 50% in the former Soviet states, production recovered unexpectedly
slowly. Only 2 of 25 transition countries had matched their 1989
production levels 10 years later (Campos and Coricelli 2002). Some of
the slow recovery may be that competitive pressures grew slowly. For
example, most countries only gradually abandoned tax and transfer
policies that effectively taxed the expanding sectors to subsidize those
in decline, and it took time to establish legal institutions that
supported property rights and limited corruption (Boeri 2000; Svejnar
2002). However, some have argued that increased competition itself may
have contributed to reduced production because it disrupted the formerly
well-organized trading systems linking Warsaw Pact countries (Blanchard
and Kremer 1997).
As the transition to market has progressed, a consensus is emerging
that efficiency gains are forthcoming from competitive market pressures;
although, the magnitude of the effect is uncertain. The review by
Djankov and Murrell (2002), summarizing 23 studies of the impact of
increased competition on firm performance, suggests that competition
raised efficiency in Central and Eastern Europe but not in the former
Soviet Union. Similarly, their examination of 37 studies on the impacts
of privatization finds that competition raised efficiency in Central and
Eastern Europe but not in countries of the former Soviet Union. Even
within regions, however, there is substantial variation in the
magnitude, and even the sign of the productivity effects, so the average
masks considerable variation across studies. (2)
Past studies of the impact of transition on firm efficiency have
concentrated on potentially unrepresentative subsets of the firms in
transition economies. As we demonstrate in this study, these subsamples
can yield misleading inferences regarding efficiency gains in these
economies. One common strategy is to concentrate on large, formerly
state-owned enterprises that survived into the transition. The focus is
natural because these are the types of firms that existed under
socialism, but this approach misses the contributions to efficiency from
the entry of new, more efficient firms and from the closing or exit of
the least efficient firms. McMillan and Woodruff (2002, p. 154) argue
that the "success or failure of a transition economy can be traced
in large part to the performance of its entrepreneurs." They
conclude that the most successful transition economies were those that
fostered the entry and success of new firms and not necessarily those
that most aggressively privatized former state enterprises. In addition,
most studies use a single cross section of data or else a short time
frame, but most countries adopted competitive policies only gradually
over several years. If efficiency gains were only realized over time,
short panels may understate the impact of market competition on
efficiency.
This study contributes to the existing knowledge regarding the
impact of market forces on production efficiency by utilizing a unique
data set encompassing every manufacturing firm in Slovenia over a long
time span. Our data include not only continuously existing firms but
also newly formed firms and firms that cease production during the
period of study. In contrast to many existing studies, we can therefore
identify the impacts of firm entry and exit on productive efficiency in
the transition to market. Second, we examine the progress of efficiency
over a long period of time: from 1994 through 2001. The eight-year
period is sufficiently long to determine whether measured efficiency
gains or losses are permanent or a consequence of short-term economic
shocks. And, third, the article deals with Slovenia, a country often
considered a special case among transition countries, and thus it can
provide interesting case findings from the comparative perspective.
Our results strongly confirm the importance of competitive
pressures in raising firm total factor productivity (TFP). The
efficiency gains were progressive, rising each year, and they are broad
based, occurring in almost all industries examined. Although the largest
gains were in private firms, consistent with findings in other
transition economies, competitive pressures at the industry level
appeared to increase TFP in firms under state and other (3) ownership
types as well. Firm ownership type did matter in the aggregate. In
industries with higher market shares attributable to private firms,
foreign-owned firms, and imported goods, all firms were more productive,
whether privately owned, state owned, or foreign owned. An important
factor driving this increased productivity was competitive pressure,
which drove out the least efficient firms, including inefficient
state-owned enterprises. At the same time, newly entering firms were at
least as efficient as surviving firms. This sorting effect is at least
as large as the effect of competition on continuing firms in our
preferred specification. These conclusions are not sensitive to
alternate specifications or controls or firm-specific factors. As a
result, the role of market forces in generating economic efficiency is
strongly confirmed.
2. Policies That Affect the Market Competition in Slovenia
As part of former Yugoslavia, Slovenia's economy was
characterized by government rather than private ownership of assets.
Although nominally under a worker-managed system, there was extensive
political interference in firm decisions regarding investment,
employment, and wages. To meet mandated payrolls, a massive system of
discretionary taxes and transfers taxed away net revenue from profitable
enterprises to subsidize failing firms that could not meet their
payrolls. Inefficient firms could lose money indefinitely; whereas,
efficient firms could not build up reserves that could allow expansion.
(4) Restrictions on capital mobility also restricted efficient resource
allocations. Socially owned firms were not allowed to sell their assets,
nor could workers obtain a return on capital if they invested in the
firm by accepting wage concessions. Consequently, there was little
incentive to invest in capital. Private firms were limited to no more
than 10 workers and so also faced limits to growth.
[FIGURE 1 OMITTED]
Slovenia's transition to market began toward the end of 1988,
but most reforms came into effect much later. Based on European Bank for
Reconstruction and Development (EBRD) transition reports, summarized in
Figure 1, Slovenia's structural reforms progressed steadily but
unevenly across sectors. Liberalization of foreign trade and of prices
was already well underway by 1991, as was privatization of small firms.
Other reforms began later and made slower progress. The legal process
for privatization of large state enterprises began in 1993 and started
in earnest in 1994. About the same time, reforms of the banking system
and of other financial institutions began, as did relaxation of rules
governing the formation of new firms. (5)
Slovenia was slow to attract foreign direct investment, and foreign
investors purchased less than 1% of the initially offered shares of
Slovenian privatized firms. Consequently, the most important source of
competition from foreign firms is through imports. Slovenia already had
liberalized trade restrictions before the transition began, and the
Custom and Tariff Acts of 1996 reduced average tariffs to 5.7%.
By the end of 1993, government subsidies to failing firms were
discontinued. Roughly 27% of manufacturing firms in existence in 1994
had failed by 2001. (6) Even state-owned firms were allowed to fail. In
contrast, many transition economies maintained formal and informal
transfers that retarded both state and private sector firm failures
(Estrin 2002). (7) In western economies, a large share of productivity
growth in industrialized economies has been attributed to resource
reallocation through new firm start-ups and closings (Olley and Pakes
1996; Bartelsman and Doms 2000).
Compared to other transition economies, Slovenia's pace of
structural reforms was slower than average (Svejnar 2002). Nevertheless,
by the end of the period, Slovenia's slow but steady growth in the
overall EBRD transition index, shown in Figure 1, reached the average of
other countries. (8) Our interest is in assessing whether there are
coincident changes in measures of firm efficiency that correspond to
cross-sectional or time series variation in measures of the degree of
competition facing firms. Our analysis begins in 1994 when newly
installed firm reporting procedures created a consistent set of
accounting rules for all incorporated firms operating in Slovenia. By
that point, the government transfer system was completely disabled, and
so measures of firm revenues are not clouded by remaining direct
political and economic interference in firm decisions regarding entry,
exit, or resource allocation. Instead, efficiency should reflect the
ongoing process of institutional reforms.
3. Methodology
Our strategy is to trace changes in individual firm efficiency over
time, using a measure of TFP. (9) To derive our TFP measure empirically,
we assume that the technology faced by the ith firm in the jth industry
in year t is assumed to be approximated by the translog production
function
ln [q.sub.ijt] = [[alpha].sub.0] + [n.summation over (k = 1)]
[[alpha].sub.k] ln [x.sub.ijkt] + 1/2 [n.summation over (k = 1)]
[n.summation over (l = 1)] [[beta].sub.kl] ln [x.sub.ijkt] ln
[x.sub.ijlt] + [[epsilon].sub.ijt], (1)
where output is denoted by [q.sub.ijt]; the n inputs [x.sub.ijkt]
include measures of labor, capital, and material inputs; [[alpha].sub.k]
and [[beta].sub.kl] are, respectively, first- and second-order translog
production parameters; and [[epsilon].sub.ijt] is an error term. The
error term, a variant of the Solow residual, is our measure of TFP. (10)
The TFP has three components that we will explore: time-varying
industry-specific factors, [[eta].sub.jt]; time-varying firm-specific
factors, [[psi].sub.it], and time-invariant firm-specific factors,
[[theta].sub.i]. In addition, we allow a purely random technology shock,
[[xi].sub.ijt]. (11) The formulation for the error term in Equation 1 is
written
[[epsilon].sub.ijt] = [[eta].sub.jt] + [[psi].sub.it] +
[[theta].sub.i] + [[xi].sub.ijt]. (2)
Our strategy is to specify the elements of the error components in
a manner that will allow us to identify factors that are tied to changes
in TFP across firms and across time. The industry-specific component is
specified as
[[eta].sub.jt] = [I.sub.jt][gamma] + [[iota].sub.jt], (3)
where [I.sub.jt], is a 1 x J vector of industry attributes, such as
industry concentration or import penetration, [gamma] is a J x 1
parameter vector that translates industry attributes into measured TFP
for firms in the industry, and [[iota].sub.jt] is a random error.
Similarly, we can specify the time-varying firm-specific component as
[[psi].sub.it] = [f.sub.it][delta] + [[phi].sub.it], (4)
where [f.sub.it] is a 1 x M vector of firm attributes that change
over time, such as ownership structure, [delta] is an M x 1 vector of
parameters describing how these firm attributes affect TFP, and
[[phi].sub.it] is a random error.
The time-invariant firm component is specified as
[[theta].sub.i] = [F.sub.i][mu] + [[upsilon].sub.i], (5)
where [F.sub.i] is an N x 1 vector of observable firm attributes
that do not change over time, [mu] is a 1 x N vector of parameters, and
[[upsilon].sub.i] is a vector of unobserved time-invariant firm
productivity. (12)
Equation 5 summarizes the selection issues that could bias our
estimates of [gamma] and [delta]. Suppose that [[theta].sub.i]
represents a firm-specific technology component that is observable by
potential investors. Then changes in firm ownership status to private
ownership or stock ownership from state ownership will be correlated
with [[theta].sub.i]. (13)
If [[upsilon].sub.i] = 0 for all firms, then selection into firm
types is based on the observables, [F.sub.i]. Attractive candidates for
inclusion in the vector [F.sub.i] are ultimate ownership status measures
for the firms. In other words, [F.sub.i] will contain dummy variables
indicating whether the firm ultimately became privately owned, foreign
owned, a company issuing common stock, or some other ownership type. The
coefficients on these measures, [mu], will reveal whether firms that
ultimately attained ownership status [F.sub.i] had atypically high or
low TFP before any changes in their ownership. The related estimate of
[delta] will reveal whether there was a change in TFP associated with
the change in ownership status.
When [[upsilon].sub.i] = 0 for all L we can estimate [gamma],
[delta] and mu] by inserting Equations 2-5 into Equation 1 and applying
ordinary least squares (OLS) to the resulting reduced form equation.
(14) If [[upsilon].sub.i] in Equation 5 is not zero but is distributed
N(0, [[sigma].sub.i]), then selection into ownership states on the basis
of expected efficiency will still be driven by the observables,
[F.sub.i]. All the parameters [gamma], [delta], and [mu] can be
estimated with the appropriate substitutions of Equations 2-5 into
Equation 1. However, additional efficiency can be obtained by applying a
random effects estimator to accommodate the firm-specific error
variance, [[sigma].sub.i].
If E([[upsilon].sub.i]) [not equal to] 0 for at least some i, then
selection into ownership types will be based in part on the unobservable
[[upsilon].sub.i]. The correlation between [F.sub.i] and
[[upsilon].sub.i] will yield biased coefficients on the [gamma] and
[delta]. With multiple years of data, we can use fixed-effects to
estimate a separate [[theta].sub.i] for each firm. We will no longer be
able to capture the [mu], but we can derive unbiased estimates of
[gamma] and [delta].
Although individual elements of [I.sub.jt], [f.sub.it], and
[F.sub.i] may be of interest, we are particularly interested in
exploring the relative importance of industry and firm factors in
affecting TFP growth. Competitive forces will have common effects across
firms in the industry; whereas, ownership structure will affect TFP
growth for specific firms in the industry. The aggregate impacts of
industry, time-varying and time-invariant firm attributes on TFP growth
over the sample period can be estimated respectively by ([[bar.I].sub.t]
- [[bar.I].sub.0])[gamma], and ([[bar.f].sub.t] - [[bar.f].sub.0].)
[delta], and ([[bar.F].sub.t] - [[bar.F].sub.o])[mu]. The terms of form
([[bar.X].sub.t] - [[vbar.X].sub.0]) are the change in the average
values of X from the base period to period t. Notice that although the
luted effects, [[bar.F].sub.t], do not change over time for an
individual firm, the average values of these firm fixed effects will
change as weak firms are sorted out of the market and strong firms are
retained.
4. Data
The data for this study are based on the universe of manufacturing
firms existing in Slovenia between 1994 and 2001. The primary
information on firms comes from four data sources. The official
financial records of the firm, submitted annually under uniform
accounting procedures to the government of Slovenia, provide information
on the firm's capital stock, material inputs, and revenues from
domestic and foreign sales. The Slovenian Business Registry includes
information on the four-digit industries that describe each firm's
product line(s), the year the firm initiated production, and the
firm's type and ownership structure. (15) We supplement these
categorizations of ownership type with additional information from the
Bank of Slovenia on firms that are at least 10% owned by foreign
individuals or entities. The work history data set tells us how many
employees of each education level work for each firm. These three data
sets can be integrated using a common firm identification number used in
all three series. (16) The variable definitions and sample means are
reported in Table 1. (17)
The employment information includes the number of two- or four-year
college graduates, the number of high school graduates, and the number
of primary educated workers in the firm. This employment information is
in real terms by construction. However, the accounting data on firm
output and capital and material inputs are reported in nominal terms. We
convert the nominal data into real data, using industry input and output
price deflators reported for all years 1994-2001. The material input
price deflator is a weighted sum of sectoral prices where the weights
are sectoral input shares generated from an input-output matrix of the
Slovenian economy. Output price deflators are reported for each
industry. There is a single capital price series that was applied to all
firms. Using these input and output price series, we generate series for
real output, capital, and material inputs for each firm and for each
year. (18)
Numerous changes suggest an increase in the competitive pressure on
Slovenian manufacturing firms from imports, foreign owners, more firms,
more new firms, and more private firms that presumably will be trying to
produce efficiently. There is also considerable evidence that firms fail
over the period. The sample means show a dramatic increase in the number
and the market share of private firms. Within individual four-digit
industries, the Herfindahl index falls over time, indicating greater
competition. The proportion of firms under foreign ownership changes
only modestly over time, but their market share doubles. Import
penetration, measured by the proportion of industry sales attributable
to imports, rises by 79%. The market share of industry output
attributable to new entrants (firms that initiated sales after 1993)
rises from 4% to 21%. In 1994, firms that will cease operations by 2001
were responsible for 17% of industry sales. (19) All of these trends
suggest rising competitive pressure on firms.
5. Total Factor Productivity Growth over Time and across Firms
Our first task is to document the extent of TFP growth in the
Slovene economy. This section demonstrates that efficiency gains in
Slovenia following the policy reforms were experienced in virtually all
sectors of the economy. We also demonstrate that measured TFP growth is
sensitive to the inclusion or exclusion of entrants, exiters, and small
firms, and that their exclusion greatly understates the efficiency gains
during the transition.
TFP Growth Is Not Sensitive to Measurement
As shown in Table 2, trend growth of productive efficiency in
Slovenia manufacturing is robust to alternative assumptions about the
error process. Three specifications of the translog formulation of
Equation 1 were estimated: OLS, a fixed-effects variant that allows for
a separate constant term for each firm, and a random effects variant
that assumes a different variance for each firm. The three series are
highly correlated and yield the same general inference: There has been a
consistent increase in TFP in the 1994-2001 period. The increase in TFP
per firm is substantial, varying from 0.222 to 0.244 log points, which
implies a 24.9% to 27.6% increase in TFP. (20) In other words, the
average manufacturing firm in Slovenia was producing about 25% more from
the same level of inputs in 2001 as in 1994.
We also report measures of skewness and kurtosis for the least
squares variant of the TFP. (21) TFP is skewed left in every year, and
so there are more outliers at the bottom tail of the productivity
distribution. However, the skewness and kurtosis measures are similar at
the beginning and the ending of the period. Mean TFP is rising because
the entire distribution of firm TFP is shifting to the right over time
and not just because an atypical upper tail is driving up the mean.
Lower tail firms in 2001 are more productive than lower tail firms in
1994. In 1994, three-quarters of firms had TFP measures in the negative
range, but by 2001, only one-third had below average productivity.
TFP growth in Slovenia was faster than rates reported for 13
Organisation for Economic Co-operation and Development (OECD)
manufacturing sectors over the 1980-1988 period (Benjamin and Ferrantino
2001). It is also faster than the annual TFP growth rates reported for
the overall business sectors of those 13 OECD countries over the
1981-1995 period, and faster than 12 of the 13 over the 1996-2000 period
(Gust and Marquez 2004). (22)
TFP Grew across All Firm Ownership Types
In Table 3 we report TFP growth for different firm ownership
structures. Because there was little substantive difference in the time
paths of TFP growth using the various estimation methods, we used the
TFP levels based on OLS. The first column repeats the estimates from
Table 2 of the average TFP level across all firms to provide a frame of
reference. The second column lists average TFP for privately owned
firms, and the third column lists TFP for all other firms. Firm
efficiency was initially significantly lower in private firms, but TFP
grew faster in private firms. Some of the growth was due to relatively
efficient firms moving from the state sector to the private group, but
sorting cannot explain much of the rise in TFP among private firms.
First, the initial gap in efficiency is less than 0.03 log points, so
the rise in efficiency is much larger than can be explained by sorting
alone. Second, TFP is rising in both groups, not just the private group.
If migration across firm types were the only factor, we would see
decreases in TFP among the firms remaining in the nonprivate group as
the more efficient state firms switched to the private group. One
conclusion from Table 3 is that privately owned firms have more rapid
TFP growth. However, a second conclusion is that TFP grows in
state-owned enterprises as well, albeit more slowly. Over the full
period, efficiency in privately owned firms rose 28%; whereas, it rose
18% in nonprivate firms.
Foreign-owned firms were slightly more efficient (0.036 log points)
than average in 1994. They retained that TFP advantage through the end
of the period. Over the eight-year period, TFP grew almost the same in
foreign-owned firms as in the average manufacturing firm at about 25%
growth.
Firms that entered limited liability arrangements may be under
private, state, or a mixture of private and state ownership. They began
the period with below average efficiency, but gained efficiency somewhat
more rapidly than average. By 2001, limited liability firms were
significantly more efficient than other firms, having experienced a
27.5% gain in TFP versus 24.9% for firms on average.
The firms with other ownership modalities began the period with a
small TFP advantage, but experienced slower efficiency gains. By 2001,
their TFP advantage had disappeared. Stock-owned companies also started
the period with a TFP advantage, but experienced slower TFP growth. By
2001, stock-owned companies had significantly lower TFP levels than did
the average manufacturing firm.
Birth and Death of Firms and Small Firm Growth Are Important
Elements of TFP Growth
Table 4 reports TFP levels by firm size and by entry or exit
status. Initially, large firms had a significant TFP advantage, but the
faster TFP growth in small firms erased the gap by 1998. The implied
efficiency growth was 25.6% in small firms versus 21.3% in large firms,
so ignoring small firms understates efficiency growth.
Firms that opened for business after 1993 maintained a 0.01 log
point TFP advantage over the average firm throughout the period. The
average TFP advantage of 0.03 log points for new entrants over the full
period is even larger than the annual advantage of 0.01 log points. The
reason is that even though TFP levels for new entrants were similar to
TFP levels for older firms, there were many more new entrants by the end
of the period when prevailing efficiency levels were higher. Hence the
weight of the effect of new entrants is to raise efficiency.
Firms that exited business by 2001 were significantly less
efficient than the average firm. The disadvantage for firms destined to
close was quite large, with an average TFP gap of 17% over the eight
years. Eliminating these inefficient firms and growth of their more
efficient rivals had a substantial effect on overall Slovene TFP growth.
We can illustrate the impact of firm entry and exit by replicating
our TFP measurement and including only firms that were continually in
business for the entire period. As shown in column 7, focusing on a
balanced panel results in markedly smaller estimated TFP growth. The
implied productivity gain of 0.177 log points, or 19.4%, is
three-fourths of the true growth of 24.9% reported in column 1. If we
further exclude firms with fewer than 100 employees, the productivity
gains are even smaller at 0.154 log points, or 16.6%. Clearly, ignoring
the productivity contributions of entrants, exiters, and small firms
significantly biases downward the estimated growth in firm efficiency
during the transition.
TFP Growth Occurs in Almost Every Manufacturing Sector
Table 5 carries the investigation of the distribution of TFP growth
to the three-digit industry level. The included industries represent
about two-thirds of all manufacturing firms. Industries were chosen so
that they would have a sufficient number of firms to allow us to
estimate the production function with some degree of precision. We
estimated the Cobb-Douglas variant of Equation 1 to conserve on degrees
of freedom. (23) The results support the view that TFP growth was
widespread in the Slovenian economy. Only in the bakery industry did TFP
levels fall, and in only three others did TFP rise by less than 10%
(footwear, books and periodicals, and printing). In all other sectors
TFP grew rapidly.
The evidence in Tables 2-5 tells a convincing story that virtually
all manufacturing firms in Slovenia became more efficient as the
transition progressed, regardless of sector, firm size, ownership
modality, or date of entry. Firms that did not become more efficient
went out of business. Furthermore, ignoring the role of small firms,
entering firms and exiting firms can understate TFP growth by as much as
one-third of the true productivity growth.
6. Regression Analysis of the Factors Affecting Total Factor
Productivity
This section reviews the extent to which measures of market
competition can be tied to the heterogeneity in TFP growth across firms.
By embedding Equation 2 into the translog specification of Equation 1,
we can identify factors that are tied to atypically rapid or slow
increases in TFP. Our results are reported in Table 6.
Least Squares Analysis
To set a basis of comparison, the first specification includes only
current firm attributes, including whether the firm was a new entrant.
The results suggest that private firms and firms with other ownership
are more efficient. Firms that entered after the passage of the Amended
Law on Enterprises in 1993 are also more efficient; although, the impact
is small. Stock-owned companies have marginally lower efficiency, and
foreign-owned firms have comparable efficiency to domestically owned
firms. At the bottom of the table, we have aggregated the impacts of the
various changes in current firm attributes from 1994 to 2001 into a
single metric. The implied TFP growth due to changes in current firms
attributes is just 0.046, or 21% of the total growth over the period.
These first column results do not control for selection into the
various ownership modalities. If, for example, only the most efficient
firms are privatized, then private firms may be more productive because
of efficiencies that predate the private ownership. To control for this
selection bias, we add the remaining constant firm attributes that
include the ultimate ownership status for the firm. The coefficients on
the future status variables will capture the average effect of all firms
that eventually become private firms. The coefficient on the current
firms attributes will then capture the change in efficiency associated
with the move to the new ownership status.
The coefficients on future attributes suggest that firms that were
targeted for foreign or stock ownership had average productivity. Firms
that came under other ownership or limited liability arrangements were
more productive than average. The impacts are small, suggesting that
there is not a strong selection process driving the results. However,
there is strong evidence that firms that will ultimately go out of
business have significantly lower TFP. The coefficient on EXIT implies
that firms that are destined to close have TFP that is 18% below firms
destined to survive. (24)
The combined effect of fixed firm attributes is 0.054 log points.
(25) Adding these fixed firm attributes lowers the impact of current
firm characteristics to 0.034 log points. Together, these current and
fixed firm effects account for only 40% of TFP growth.
In column 3, we add the measures associated with the extent of
competitive pressure in the industry. In contrast to the firm
attributes, industry attributes are extremely important in explaining
variation in firm efficiency. The Herfindahl index is based on domestic
market shares, with 0 indicating perfect competition and 1 indicating
the firm is a monopolist. The coefficient on the Herfindahl index
implies that a monopolist would be 23% less efficient than an otherwise
equivalent perfectly competitive firm. Firms in industries with a higher
share of foreign-owned firms were significantly more efficient. Note
that the foreign-owned firms themselves were not more efficient, but
their presence made all firms in the industry more efficient. Private
firms were more efficient, but their presence in the industry made all
other firms more efficient as well. Firms destined to exit are
presumably weak competitors. Firms in industries in which exiting firms
have a higher output share are less efficient, even those that do not
ultimately exit. Firms in industries in which entrants have a greater
market share are also more efficient. There is no apparent impact of
greater import penetration on incumbent firm efficiency. Overall,
increases in these competitive pressures at the industry level increased
firm productivity by 0.172 log points, or over three-quarters of the
total TFP growth over the period. Meanwhile, current firm attributes
drop still further in importance, as do firm fixed effects.
The specification in column 3 presumes that selection into
ownership types is based solely on observable attributes, so that
[[upsilon].sub.i] = 0 in Equation 5. If [[upsilon].sub.i] # 0, but
E([u.sub.i]) = 0 for all i, selection will still depend only on
observables, but a random effects estimator will provide added
efficiency. Results from that specification are reported in column 4.
The test for nonzero variance of the [[upsilon].sub.i] favored the
random effects estimator over the least squares estimate of column 3.
Individual results are similar to those in column 3 with the exception
that current firm attributes lose magnitude and significance, while firm
constant attributes gain strength. On the other hand, all measures of
competitive pressure are now significant and pushing incumbent firms to
be more efficient. Overall, industry competitive pressures account for
0.12 log points of TFP growth, which is half of the total TFP growth.
Changes in firm fixed attributes due to the sorting out of weak firms
and sorting in of strong firms can account for an additional 0.061 log
points of TFP growth, or one-quarter of the overall gain. Firm current
attributes become irrelevant.
The Hausman test suggests that unobservable (to the econometrician)
productive attributes were also important, so we turn to the
fixed-effect estimates. When fixed effects are imposed, only one
firm-level current measure retains significance and the joint test that
the coefficients on current firm attributes were equal to zero could not
be rejected at standard significance levels. The aggregated impact of
the [delta] suggests that current firm attributes explain none of the
growth in TFP over the sample period.
On the other hand, all industry-level measures still retain signs
that are consistent with the implied impact of market competition on
productive efficiency. The only imprecisely estimated effect is that of
the Herfindahl index, which implies a monopolist is only 2% less
efficient than a perfectly competitive firm. Recall that the Herfindahl
index was defined only on domestic production, so even a monopolist
could face competition from foreign producers. (26) All the other
estimated industry effects support the role of competition in
significantly enhancing firm efficiency. Firms in industries that have
higher market shares (net of own firm production) controlled by private
firms, foreign-owned firms, and new entrants all had rising TFP. We
emphasize that private firms and foreign-owned firms were not themselves
more efficient, but their presence in an industry made all the firms in
that industry more efficient. Firms in industries with higher import
penetration were also more efficient. Firms are less efficient in
industries with weak competitors, as indicated by a high net market
share going to eventual exiters. Aggregating these industry effects, we
find that rising industry competition can explain 0.091 log points, or
41% of the growth in TFP over the period. These represent external
benefits from market competition, independent of the impact of current
firm-specific factors.
The fixed-effects estimation eliminates the firm fixed factors from
the model. Nevertheless, we know that a portion of the remaining
efficiency gain must be due to the entry and exit of firms. If we take
only the implied impacts of these two factors from column 3, we have
that firm exits contributed 0.04 log points and new entrants contributed
0.005 log points to TFP growth. Together, firm entry and exit contribute
an additional 21% of the estimated TFP growth over the sample period.
The role of firm entry and exit in explaining efficiency growth in
Slovenian manufacturing corresponds closely to the proportion of
efficiency growth attributable to entry and exit in western economies,
as summarized by Bartelsman and Doms (2000).
In sum, we estimate that 62% of the growth in firm efficiency
between 1994 and 2001 can be attributable to the combined influence of
increased industry market competition, to the birth of relatively
efficient firms, and to the death of relatively inefficient firms. The
remaining 38% of TFP growth is due to common effects across all firms.
These could be due to business cycle effects or to reversion to mean
efficiency levels following the initial shock of the transition.
However, if the competitive policy changes, summarized in Figure 1, have
any impact, they would be responsible for at least some of the 38% of
TFP growth not explained by entry, exit, or our measures of
industry-level competition. Our estimate that competitive pressures and
sorting are responsible for 62% of TFP growth is therefore a lower-bound
estimate of their true effects.
The Konings, Van Cayseele, and Warzynski (2005) investigation of
price-cost margins in Romanian and Bulgarian firms finds similar roles
for competition in fostering efficiency. They report that firms in more
competitive sectors had significantly lower price cost margins. To the
extent that their results generalize to Slovenia, our finding that firms
in more competitive markets also had atypically large TFP gains, and
hence falling production costs, suggests a double benefit of competition
to a transition economy. Not only does competition foster more efficient
production, but the benefits to consumers in the form of lower prices
are even greater than the cost saving to the firm.
The relative unimportance of firm ownership structure in our study
contrasts with findings in earlier studies. For example, Konings, Van
Cayseele, and Warzynski (2005) find that privatized firms and
foreign-owned firms had higher price-cost margins, other things equal.
It is possible that our finding that ownership structure did not matter
for efficiency gains is a consequence of the fact that all Slovene
enterprises, state or private, faced the possibility of bankruptcy. As a
result, state firms behaved more like private firms in Slovenia. Second,
the scope for improvements of corporate governance in Slovenia may have
been smaller than in other transition countries to the extent that
managers in the worker self-managed Yugoslav system had considerable
autonomy, which may have led some firms to be relatively efficient even
before transition. Consequently, the privatized state firms did not
experience atypical growth in efficiency. However, the most interesting
finding in our context is that although privately owned firms or
foreign-owned firms were not atypically efficient, industries with
higher market shares attributable to private firms, foreign-owned firms,
newly entered firms, or foreign-sourced goods had faster efficiency
growth. When we ignore these industry-level aggregates of firm
attributes, it appears that private or foreign ownership behave more as
in previous studies. Consequently, earlier productivity effects
attributed to ownership structure may have masked the market competition
effects that dominate our article.
7. Robustness
In Table 7, we replicate the fixed-effect estimates under various
scenarios. In column 2, we report a variant of the Olley-Pakes (1996)
estimation strategy. Their concern was in deriving unbiased estimates of
[alpha] and [beta] in Equation 1, which is tangential to our concern
with evaluating factors affecting the time path of [[epsilon].sub.ijt].
Nevertheless, there may be a concern that unmeasured firm heterogeneity
in production is correlated with our industry-level measures of market
competition. Under the assumption that firm exit and investment
decisions are predicated on firm expectations of future market structure
and factor prices, and that firm profits are increasing in capital, the
firm's idiosyncratic productivity in Equation 4, [[phi].sub.it],
can be written as
[[phi].sub.it] = h([i.sub.t], [a.sub.t], [k.sub.t], [[member
of].sub.it]), (6)
where it is current investment, [a.sub.t] is the age of the firm,
[k.sub.t] is the firm's capital stock, and [[epsilon].sub.it] is an
approximation error assumed to be purely random. Inserting Equation 6
into Equation 4 gives us
[[psi].sub.it] = [f.sub.it][delta] + h([i.sub.t], [a.sub.t],
[k.sub.t], [[member of].sub.it]). (4')
Olley and Pakes used an explicit formulation for h(.) to derive
unbiased structural estimates of the [alpha] and [beta] in Equation 1.
We are not interested in those parameters, so instead we replace h(*)
with its second-order Taylor approximation and then estimate Equation 1
imposing Equations 2, 3, and 4'. The results are reported in the
second column of Table 7. The proportion of TFP growth that can be
jointly attributed to market competition falls somewhat from 41% to 38%.
Nevertheless, the coefficients are very consistent in both sign and
magnitude. The null hypothesis that all the coefficients in the
approximation of h(.) are jointly zero could not be rejected. Current
firm attributes continue to have no effect.
In column 3, we repeat the fixed-effect estimation excluding
entrants and exiters from the sample. Current firm attributes continue
to have no effect. The market competition measures still retain sign and
significance. Their joint effect actually rises to 0.107, or 60% of the
TFP growth in those firms. Thus, although using a balanced sample biases
downward the overall estimate of TFP growth, it increases the proportion
attributable to market competition.
The last column repeats the exercise but excludes firms with fewer
than 100 employees. The conclusion that current firm attributes have no
effect still holds. However, several of the market competition variables
switch signs and significance from the full sample. The share of
foreign-owned firms and market entrants now lower efficiency. The impact
of import penetration is reduced by half, and the joint effect of market
competition on efficiency falls to 0.052, or just 34% of the total TFP
growth in those firms. It is apparent that excluding small firms from
the sample causes significant downward bias in the estimated impact of
market pressures on firm efficiency.
[FIGURE 2 OMITTED]
The results from Table 7 demonstrate that the general finding that
increased market competition leads to increased efficiency holds when
alternative definitions and assumptions about the error process are
imposed. They also show that excluding small firms, entrants, and
exiters can have large effects on the estimated magnitude of the market
competition effect.
8. Structural Reform and Efficiency
We cannot perform a rigorous test of the relationship between
structural policy reforms and our measures of productive efficiency
because the EBRD data presented in Figure 1 are common across all firms
and industries, and we can identify only relative efficiency effects
between firms. Nevertheless, the correlation between the two series is
of interest. In Figure 2 we present the simple bivariate relationship
between our aggregate TFP measure and the average of the structural
reform indexes shown in Figure 1. The average of the EBRD indexes
explains 93% of the variation in the TFP measure over time. The average
of the various EBRD indexes strongly outperformed any single index,
consistent with the presumption that it is the mixture of liberalization
policies supporting competition that is important, as opposed to any
single policy. Of course, with only seven degrees of freedom, this can
be viewed only as a suggestive result.
9. Conclusion
One of the oldest propositions in economics is that competition
spurs economic efficiency. The introduction of competition was expected
to improve the efficiency of formerly planned economies, moderating the
adverse consequences of transition for output. Our evaluation of the
data from Slovenian manufacturing is strongly supportive of the role of
market competition. TFP growth in Slovenia over the period averaged 2.8%
per year, a growth rate that compares favorably to most OECD countries.
The TFP growth is broad based across industries, across private and
state firms, across small and large firms, and at both the top and
bottom of the efficiency distribution.
Changes from one ownership type to another had virtually no impact
on firm TFP growth. Beyond a firm-specific, time-invariant productivity
level, firm-level variables do not alter TFP. However, changes in
industry attributes, such as the extent of foreign competition, foreign
ownership, private ownership, and the market share of new entrants and
eventual exiters, can explain 41% of TFP growth. An additional 21% can
be attributed to the entrance of relatively efficient firms, and, more
importantly, the exit of relatively inefficient establishments. These
changes coincide with the timing of policy liberalization in Slovenia,
suggesting that policies fostering market competition contributed to the
growth of market pressures.
Many studies have attempted to measure the impact of transition by
comparing the performance of state enterprises against that of private
firms. For example, Frydman et al. (1999) find that private firms
generate more sales than state enterprises, but have similar unit costs.
Anderson, Lee, and Murrell (2000) find that Mongolian state enterprises
had a TFP advantage over privately owned firms. Djankov and
Murrell's (2002)review finds that privatization had a wide range of
effects on productivity, most positive but some negative. In Slovenia,
state firms are not protected from competition or risk of bankruptcy.
Our results suggest that the distinction between firm ownership types is
not as important as whether those firms face competitive pressures.
However, firm ownership type did matter in that an increased industry
share of private firms, foreign-owned firms, and imported goods raises
competitive pressures on all firms in the industry, resulting in
increased TFP growth for all surviving firms regardless of ownership
structure.
Small firms, new market entrants, and exiting firms have a large
impact on measured TFP growth in transition. Efficiency gains appear to
occur over time and not at one instance. Our findings suggest that past
studies that concentrated only on large firms, balanced panels, and
short time frames may have understated the efficiency gains that
resulted from the transition to market.
Received July 2006; accepted September 2008.
References
Anderson, James H., George Korsun, and Peter Murrell. 2000. Which
enterprises (believe they) have soft budgets after mass privatization.
Journal of Comparative Economics 28:219-46.
Anderson, James H., Young Lee, and Peter Murrell. 2000. Competition
and privatization amidst weak institutions: Evidence from Mongolia.
Economic Inquiry 38:527-49.
Bartelsman, Eric J., and Mark Doms. 2000. Understanding
productivity: Lessons from longitudinal microdata. Journal of Economic
Literature 38:569-94.
Benjamin, Nancy, and Michael J. Ferrantino. 2001. Trade policy and
productivity growth in OECD manufacturing. International Economic
Journal 15:95-115.
Blanchard, Olivier, and Michael Kremer. 1997. Disorganization.
Quarterly Journal of Economics 112:1091-126.
Blanchflower, David, and Stephen Machin. 1996. Product market
competition wages and productivity: International evidence from
establishment-level data. Annales-d' Economie-et-de-Statistique
17:21933.
Boeri, Tito. 2000. Structural change, welfare systems and labour
reallocation. Oxford: Oxford University Press.
Boeri, Tito, and Catherine Terrell. 2002. Institutional
determinants of labor reallocation in transition. Journal of Economic
Perspectives 16:51-76.
Bojnec, Stefan, and Aria Xavier. 2004. Entry and exit in transition
economies: The Slovenian manufacturing sector. Post-Communist Economies
16:191-214.
Brada, Josef C. 1996. Privatization is transition--Or is it?
Journal of Economic Perspectives 10:67-86.
Campos, Nauro F., and Fabrizio Coricelli. 2002. Growth in
transition: What we know, what we don't, and what we should.
Journal of Economic Literature 40:793-836.
Djankov, Simeon, and Peter Murrell. 2002. Enterprise restructuring
in transition: A quantitative survey. Journal of Economic Literature
40:739-92.
Estrin, Saul. 2002. Competition and corporate governance in
transition. Journal of Economic Perspectives 16:101-24. European Bank
for Reconstruction and Development (ERBD). Transition Report. Various
Issues. London, UK. Frydman, Roman, Cheryl Gray, Marek Hessel, and
Andrzej Rapaczynski. 1999. When does pfivatization work? The impact of
private ownership on corporate performance in the transition economies.
Quarterly Journal of Economics 114:1153-91.
Gust, Christopher, and Jaime Marquez. 2004. International
comparisons of productivity growth: The role of information technology
and regulatory practices. Labour Economics 11(1): 33-58.
Haltiwanger, John, and Milan Vodopivec. 2003. Worker flows, job
flows and firm wage policies: An analysis of Slovenia. Economics of
Transition 11:253-90.
Institute of Macroeconomic Analysis and Development (IMAD). 2003.
Development report 2003. Ljubljana, Slovenia: IMAD.
Joskow, Paul L., and Nancy L. Rose. 1989. The effects of economic
regulation. In Handbook of industrial organization, vol. 2, edited by R.
Schmalensee and R. Willig. Amsterdam: Elsevier Science Publishers, pp.
1449-1506.
Konings, Jozef, Patrick Van Cayseele, and Frederic Warzynski. 2005.
The effects of privatization and competitive pressure on firms'
price-cost margins: Micro evidence from emerging economies. Review of
Economics and Statistics 87(1): 124-34.
Li, David D., and Minsong Liang. 1998. Causes of the soft budget
constraint: Evidence on three explanations. Journal of Comparative
Economics 26(1): 104-16.
McMillan, John, and Christopher Woodruff. 2002. The central role of
entrepreneurs in transition economies. Journal of Economic Perspectives
16:153-70.
Megginson, William L., and Jeffrey M. Netter. 2001. From state to
market: A survey of empirical studies on privatization. Journal of
Economic Literature 39:321-89.
Nickell, Stephen. 1996. Competition and competitive performance.
Journal of Political Economy 104:724-46.
Olley, G. Steven, and Ariel Pakes. 1996. The dynamics of
productivity in the telecommunications equipment industry. Econometrica
64:1263-97.
Orazem, Peter F., and Milan Vodopivec. 2000. Male-female
differences in labor market outcomes during the early transition to
market: The cases of Estonia and Slovenia. Journal of Population
Economics 13:289-303.
Riboud, Michelle, Carolina Sanchez-Paramo, and Carlos
Silva-Jauregui. 2001. Does eurosclerosis matter? Institutional reform
and labor market performance in central and Eastern European countries
in the 1990s. Mimeo, the World Bank.
Simoneti, Marko, Andreja Bohm, Marko Rems, Matija Rojec, Joze P.
Damijan, and Boris Majcen. 2001. Secondary privatization in Slovenia:
Evolution of ownership structure and company performance following mass
privatization. Warsaw: Center for Economic and Social Research (CASE)
Reports No. 46
Svejnar, Jan. 2002. Transition economies: Performance and
challenges. Journal of Economic Perspectives 16:3-28.
Vodopivec, Milan. 1993. Determination of earnings in Yugoslav
firms: Can it be squared with labor management? Economic Development and
Cultural Change 41:337-48.
Peter F. Orazem * and Milan Vodopivec ([dagger])
* Department of Economics, 267 Heady Hail, Iowa State University,
Ames, IA 50011-1070, USA; E-mail pfo@iastate.edu; corresponding author.
([dagger]) World Bank, 1818 H Street NW, Washington, DC 20433, USA;
E-mail mvodopivec@worldbank.org.
The authors are grateful for support from a grant provided by the
U.S. Department of State's Program for Study of Eastern Europe and
the Independent States of the Former Soviet Union (Title VIII) and
administered by the William Davidson Institute, and from World Bank
research project RF-P064129-RESE-BBRSB. The article would not have been
possible without tremendous help in obtaining the data from the
Statistical Office of Slovenia, the Agency of Slovenia for Public
Statistics and Services, and the Bank of Slovenia. We thank the Bank of
Slovenia for conducting analyses using restricted data on foreign
ownership. Helpful comments and advice were provided by Mico Mrkaic,
Matija Rojec, Marko Simoneti, Andreja Vodopivec, and the referees. Tomaz
Rejec and Jakob Tomse provided excellent assistance in setting up the
data sets, and Donna Otto prepared the manuscript. The opinions,
findings, and conclusions or recommendations expressed herein are those
of the authors and do not necessarily reflect those of the World Bank,
the U.S. Department of State, or the William Davidson Institute.
(1) The Joskow and Rose (1989) summary suggests that increased
market competition from deregulation in the United States and
privatization of public enterprise in Europe generally led to increases
in labor productivity. Megginson and Netter (2001) present a more recent
review including other areas of the world and derive similar
conclusions. The few studies that examine the role of competition in
fostering efficiency in unregulated environments yield mixed results.
For example, in two studies of British firms, Nickell (1996) finds that
competition enhances efficiency; whereas, Blanchflower and Machin (1996)
find no effect.
(2) Of course, much of the variation reflects differences in
methodology and measures of firm performance. However, even the most
careful studies that control for selection problems can generate
conflicting results. For example, Anderson, Lee, and Murrell (2000) find
that state enterprises were more efficient than private firms; whereas,
Frydman et al. (1999) find that privatization raises measures of firm
performance. The differences may be in the measure of firm performance
used. When Frydman et al. use a measure of efficiency, namely, unit
cost, the differences between private and state enterprise disappear.
Their other measures (revenue growth, employment growth, and revenue per
employee) do not have an obvious connection to efficiency.
(3) For the purpose of this study, we define other ownership to
include cooperative ownership and split state and private ownership, two
categories used by the Statistical Office of Slovenia for firms that do
not fit naturally into the other firm types.
(4) Vodopivec (1993) discusses this system in detail.
(5) A more detailed summary of the Slovenian reforms can be found
in Orazem and Vodopivec (2000).
(6) Bojnec and Xavier's (2004) analysis of the number of firms
by industry in Slovenia suggests exit rates from manufacturing of 5% per
year, roughly consistent with our longitudinal data on Slovenian
manufacturing firms.
(7) The likelihood that the government will prevent state firm
failure may vary even within countries. Anderson, Korsun, and Murrell
(2000) find that only 27% of Mongolian state enterprise thought the
government would bail them out at least partially if the firm failed,
with 73% stating the government would do nothing to help. In China, Li
and Liang (1998) find that state enterprises with negative cash flow did
not reduce their employment of redundant workers, apparently because all
expected the government to make up the losses.
(8) The EBRD index did not include labor market reforms, but
Slovenia also took a gradualist approach in adjusting labor market
policies. Early on, the government imposed many provisions to protect
jobs in traditional sectors. By 1991, restrictions on layoffs and
mandated severance were reduced. Despite the liberalization, Riboud,
Sanchez-Paramo, and Silva-Jauregui (2001) conclude that Slovenia's
labor policies were the most restrictive of the formerly planned
economies that were being targeted for accession to the European Union.
Boeri and Terrell (2002) provide a comparative review of labor market
policies in transition economies.
(9) Konings, Van Cayseele, and Warzynski (2005) derive a dual
formulation of the traditional Solow residual framework that we employ.
Their method assumes that firms are maximizing profits, an assumption
that is inconsistent within our framework in which some firms may become
more efficient over time due to competitive pressures, while other firms
that are more insulated from competition are able to remain inefficient.
The Konings, Van Cayseele, and Warzynski framework is aimed at
estimating price-cost margins and not firm efficiency per se, and they
ultimately difference away the Solow residual that is the focus of our
analysis. Nevertheless, our results correspond with theirs in
interesting ways, as will be discussed below.
(10) Note that by construction, [[epsilon].sub.ijt] is orthogonal
to the inputs, so it is productivity attached to the firm's overall
production but not to specific inputs.
(11) We could also specify a time varying error component that is
common across all firms and industries. The most likely source of such
common national shocks would be government tax and transfer policies and
regulatory policies. However, these policies were stable over the sample
period.
(12) Bartelsman and Doms (2000) conclude that there is considerable
persistence in firm productivity so that highly productive firms in one
year are likley to be highly productive in other years. This suggests
that the fixed effect component [[upsilon].sub.i] is likely to be
important.
(13) This is almost certainly true. Simoneti et al. (2001) find
that insider investment is heaviest in firms that had higher profits in
the years preceding privatization. It is not clear if the higher
profitability is a permanent or transitory state. Our own results
suggest the latter, in that firms that become stock-owned have slower
TFP growth than other firms.
(14) Note that it is more efficient to estimate the system of
equations in one step than to estimate Equation 1, derive estimates of
[[epsilon].sub.ijt], and then to estimate Equation 2 with appropriate
substitutions for q [[eta].sub.jt], [[psi].sub.it] and [[theta].sub.i].
(15) We distinguish private and state ownership, as well as
ownership by domestic and foreign owners. We also have information about
whether the firm is a publicly traded stock company or a limited
liability company.
(16) For more information about the data sets, see Haltiwanger and
Vodopivec (2003), who use the same sources.
(17) Note that to suit our empirical analysis, the variables ENTRY
and EXIT are defined in a specific way. Namely, ENTRY is set equal to
one in all years if the firm came into existence any year after 1993
(thus a firm that was founded in 1995 is considered an entrant also in
1996 and subsequent years of analysis). Similarly, EXIT is set equal to
one in all years if the firm had no employees in 2001. Thus, a firm that
began operations in 1996 and ceased operations in 2000 will have ENTRY =
1 and EXIT= 1 for all years of its existence.
(18) Most studies of market efficiency in western economies have
concentrated on manufacturing because data on inputs and outputs are
more readily available and comparable across firms. In our case, we did
not have sufficient detail on input and output prices to allow us to
perform the analysis on industries outside manufacturing. For example,
we would not be able to assess how much of the revenue changes in the
service sector was due to increases in service output versus increases
in unit prices. However, our results for manufacturing may not carry
over to all sectors. According to IMAD (2003), growth of market-oriented
services in Slovenia has been so slow that the gap in the share of these
services in GDP rose between Slovenia and the European Community from
1995 to 2001. The slow growth in these services has been attributed to
their being shielded from market pressures, causing the service sector
to lag behind other sectors in productivity growth.
(19) Employment shares are similar. New entrants were responsible
for 16% of all employment in manufacturing in 2001, while firms that
exit by 2001 employed 15% of all manufacturing employees in 1994.
(20) Computed, for example, as 100*(exp(0.222) - 1).
(21) These measures were similar across the various TFP measures,
and so these are reported as a representative example.
(22) Finland had faster TFP growth over the 1996-2000 period.
(23) This constrains all the [[beta].sub.kl] = 0 in Equation 1.
(24) Bojnec and Xavier (2004) report that firms are more likely to
exit in sectors with greater import penetration and lower (more
competitive) Herfindahl indexes, consistent with our presumption that
competition helps force exits of inefficient firms.
(25) Even though these are firm fixed effects, the composition of
firms is changing over time to favor more efficient factors. Firms whose
fixed factors are associated with lower efficiency are exiting, while
entering firms tend to avoid attributes that lower efficiency.
(26) The simple correlation between the Herfindahl index and import
share was 0.27, suggesting a modest increase in import penetration in
more concentrated sectors.
Table 1. Sample Means and Standard Deviations for the Full Sample
and Means for 1994 and 2001
1994-2001
Std.
Variable Mean Dev.
Endogenous
TFP Total factor productivity from OLS 0.000 0.363
TFPfe Total factor productivity assuming 0.000 0.406
fixed effects
TFPre Total factor productivity assuming 0.023 0.367
random effects
lnrq Log of real output 6.01 2.03
Inputs
lnrk Log of real capital stock 4.62 2.45
lnrm Log of real value of materials 5.46 2.08
lnuniv Log of two- or four-year university 0.60 1.11
educated employees
lnhigh Log of high school educated 1.70 1.64
employees
lnprim Log of employees with < high 1.02 1.59
school education
lnmonth Log of months of operation 2.481 0.073
Current firm attributes
state owned Firm is currently state owned 0.101 0.301
(reference)
private Firm is private in current year 0.837 0.369
stockco Firm currently issues publicly 0.075 0.264
traded stock
ltdliab Firm is currently a limited 0.858 0.349
liability firm
other Firm is currently under other 0.061 0.239
ownership type
forown Firm is currently at least 10% 0.098 0.297
foreign owned
Constant firm attributes
ENTRY Firm's birth year after 1993 0.254 0.435
EXIT Firm has no employees by 2001 0.111 0.314
PRIVATE Firm becomes private by 2001 0.884 0.321
STOCKCO Firm issues publicly traded 0.108 0.311
stock by 2001
LTDLIAB Firm becomes a limited liability 0.895 0.306
firm by 2001
OTHER Firm under other ownership type 0.089 0.285
by 2001
FOROWN Firm under at least 10% foreign 0.118 0.323
ownership by 2001
Four-digit industry attributes (a)
HERF Herfindahl concentration index 0.137 0.151
PRIVSHR Industry market share of private 0.589 0.305
firms
FORSHR Industry market share of firms 0.166 0.207
with forown = 1
ENTSHR Industry market share of 0.147 0.142
firms entering after 1993
EXITSHR Industry market share of firms 0.059 0.097
that will exit by 2001
IMPORTSHR Industry market share of imports 0.338 0.22
N 28047
1994 2001
Variable Mean Mean
Endogenous
TFP Total factor productivity from OLS -0.137 0.086
TFPfe Total factor productivity assuming -0.159 0.086
fixed effects
TFPre Total factor productivity assuming -0.116 0.108
random effects
lnrq Log of real output 6.188 6.088
Inputs
lnrk Log of real capital stock 4.797 4.667
lnrm Log of real value of materials 5.746 5.433
lnuniv Log of two- or four-year university 0.783 0.565
educated employees
lnhigh Log of high school educated 1.890 1.693
employees
lnprim Log of employees with < high 1.303 0.948
school education
lnmonth Log of months of operation 2.480 2.483
Current firm attributes
state owned Firm is currently state owned 0.284 0.039
(reference)
private Firm is private in current year 0.636 0.906
stockco Firm currently issues publicly 0.037 0.085
traded stock
ltdliab Firm is currently a limited 0.823 0.862
liability firm
other Firm is currently under other 0.08 0.054
ownership type
forown Firm is currently at least 10% 0.076 0.102
foreign owned
Constant firm attributes
ENTRY Firm's birth year after 1993 0.074 0.324
EXIT Firm has no employees by 2001 0.265 0.000
PRIVATE Firm becomes private by 2001 0.788 0.916
STOCKCO Firm issues publicly traded 0.154 0.094
stock by 2001
LTDLIAB Firm becomes a limited liability 0.868 0.893
firm by 2001
OTHER Firm under other ownership type 0.123 0.074
by 2001
FOROWN Firm under at least 10% foreign 0.106 0.111
ownership by 2001
Four-digit industry attributes (a)
HERF Herfindahl concentration index 0.14 0.041
PRIVSHR Industry market share of private 0.204 0.732
firms
FORSHR Industry market share of firms 0.100 0.230
with forown = 1
ENTSHR Industry market share of 0.036 0.205
firms entering after 1993
EXITSHR Industry market share of firms 0.168 0.000
that will exit by 2001
IMPORTSHR Industry market share of imports 0.196 0.350
N 2904 4244
(a) Except for IMPORTSHR, these measures are net of own firm's output
share.
Table 2. Time Path of Alternative Estimates of Firm Total Factor
Productivity in Slovenia Manufacturing, 1994-2001
All Firms, All Firms, All Firms,
Year TFP (a) TFPfe (b) TFPre (c)
1994 -0.136 -0.158 -0.115
1995 -0.115 -0.119 -0.090
1996 -0.048 -0.046 -0.023
1997 0.010 0.014 0.034
1998 0.015 0.021 0.039
1999 0.032 0.036 0.055
2000 0.081 0.085 0.104
2001 0.086 0.086 0.108
1994-2001 0.222 0.244 0.223
Average 0.000 0.000 0.023
Correlation matrix of the alternative TFP estimates
over 28,047 observations
TFP TFPfe TFPre
TFP 1.0
TFPfe 0.90 1.0
TFPre 0.99 0.941 1.0
Skewness and kurtosis of the TFP distribution
Year Skewness Kurtosis
1994-1996 -1.88 44.13
1998-2001 -1.89 40.00
(a) TFP is total factor productivity measured as the error from OLS
estimates of the translog production function (Eqn. 1).
(b) TFPfe is total factor productivity measured as the error derived
from a fixed-effects estimate of the translog production function.
(c) TFPre is total factor productivity measured as the error derived
from a random effects estimate of the translog production function.
Table 3. Time Path of Firm Total Factor Productivity by Slovenian
Manufacturing Firm Ownership Type, 1994-2001 (a)
All Firms, Not Foreign
Year TFP Private (b) Private (b) Owned (b)
1994 -0.136 -0.147 ** -0.119 ** -0.107
1995 -0.115 -0.116 * -0.143 * -0.113
1996 -0.048 -0.053 -0.079 -0.017
1997 0.010 0.015 ** -0.018 ** -0.005
1998 0.015 0.022 ** -0.032 ** 0.027
1999 0.032 0.036 ** 0.000 ** 0.054
2000 0.081 0.085 * 0.046 * 0.094
2001 0.086 0.090 0.050 0.120 *
1994-2001 0.222 0.247 0.169 0.227
Average 0.000 0.017 ** -0.053 ** 0.026 **
Limited
Liability Other Stock
Year Firm (b) Ownership (b) Company (b)
1994 -0.148 ** -0.107 -0.122
1995 -0.117 -0.105 -0.052 **
1996 -0.048 0.009 ** -0.001 **
1997 0.010 0.021 0.044 **
1998 0.015 0.011 0.015
1999 0.032 0.054 0.032
2000 0.084 * 0.083 0.061
2001 0.095 ** 0.087 0.039 **
1994-2001 0.243 0.194 0.161
Average 0.001 0.012 0.018 **
(a) Total factor productivity is measured as the error from OLS
estimates of the translog production function (Eqn. 1).
(b) t-tests of the null hypothesis that mean TFP are equal between
the stated ownership type versus all other firms were conducted,
allowing for different variances in the two groups.
* Significant differences at the 0.10 confidence level.
** Significance at the 0.05 level.
Table 4. Time Path of Firm Total Factor Productivity by Slovenian
Manufacturing, Firm Size, Entry Cohort, and Mortality (a)
All Firms, <100 100+
Year TFP Employees (b) Employees (b) Entry (b)
1994 -0.136 -0.142 ** -0.101 ** -0.129
1995 -0.115 -0.118 * -0.090 * -0.115
1996 -0.048 -0.050 ** -0.025 ** -0.058
1997 0.010 0.008 * 0.031 * 0.006
1998 0.015 0.014 0.024 0.022
1999 0.032 0.034 0.018 0.045
2000 0.081 0.081 0.084 0.092
2001 0.086 0.086 0.092 0.097
Difference
between
2001 and
1994 0.222 0.228 0.193 0.226
Average 0.000 -0.0001 0.001 0.031 **
Balanced Balanced Large
Panel, (c) Firm Panel, (d)
Year Exit (b) TFP (a) TFP (a)
1994 -0.229 ** -0.112 -0.087
1995 -0.223 ** -0.097 -0.073
1996 -0.164 ** -0.032 -0.012
1997 -0.114 ** 0.016 0.035
1998 -0.126 ** 0.012 0.024
1999 -0.182 ** 0.027 0.009
2000 -0.205 ** 0.067 0.066
2001 0 (e) 0.065 0.067
Difference
between
2001 and
1994 0.229 0.177 0.154
Average -0.181 ** 0.000 0.000
(a) TFP is measured as the error from OLS estimates of the translog
production function (Eqn. 1).
(b) t-tests of the null hypothesis that mean TFP are equal between
the stated ownership type versus all other firms were conducted,
allowing for different variances in the two groups.
(c) TFP estimate over the subsample of firms in continuous production
from 1994 through 2001.
(d) TFP estimate over the subsample of firms with more than 100
employees in continuous production from 1994 through 2001
(e) By definition, TFP = 0 for firms no longer in business.
* Significant differences at the 0.10 confidence level.
** Significance at the 0.05 level.
Table 5. Total Factor Productivity Estimates by Detailed
Manufacturing Sectors
Industry SIC (b) Share (c) 1994 1995
Bakery 15.8 2.9% 0.055 0.008
Woven textiles 17.4, 17.5 1.6% -0.105 -0.087
Clothing 18.2 8.0% -0.125 -0.042
Footwear 19.2, 19.3 1.9% 0.02 -0.14
Lumber 20.1 2.3% -0.07 -0.095
Plywood 20.2 2.0% -0.134 -0.075
Wooden crates 20.4 1.3% -0.15 -0.103
Paper products 21.21-21.23 0.9% -0.135 -0.167
Book, 22.11-22.13 1.4% -0.021 -0.146
periodicals
Printing 22.21, 22.22 2.6% -0.065 -0.118
Rubber 25.1 0.8% -0.097 -0.183
Plastics 25.2 5.3% -0.119 -0.179
Cement and 26.6, 26.7 1.2% -0.121 -0.149
stone products
Metal castings 27.5 0.7% -0.055 -0.075
for plumbing,
etc.
Metal finishing 28.5 9.8% -0.108 -0.089
Cutlery, hand 28.6 2.4% -0.044 -0.113
tools
Manufacturing 29.2 1.7% -0.13 -0.149
equipment
Power hand 29.5 2.0% -0.117 -0.166
tools
Electrical 31.6 3.5% -0.221 -0.107
machinery
Radio, TV, 32 1.9% -0.185 -0.092
communication
equip.
Precision testing 33.2, 33.3 1.2% -0.286 -0.15
and control
Furniture 36.1 8.3% -0.148 -0.053
Industry 1996 1997 1998 1999
Bakery -0.054 0.039 0.018 -0.008
Woven textiles -0.004 0.048 -0.001 -0.009
Clothing 0.014 0.032 0.037 -0.024
Footwear -0.03 0.007 0.02 0.023
Lumber -0.064 -0.017 0.025 0.041
Plywood -0.046 -0.015 -0.004 0.009
Wooden crates -0.084 0.053 0.029 0.024
Paper products -0.004 0.051 0.03 0.051
Book, 0.002 0.021 0.032 0.065
periodicals
Printing -0.031 0.06 0.053 0.093
Rubber -0.054 0.037 0.05 -0.149
Plastics -0.06 -0.02 0.026 0.038
Cement and -0.096 0 0.029 0.082
stone products
Metal castings 0 -0.074 0.028 0.053
for plumbing,
etc.
Metal finishing -0.026 -0.077 -0.035 0.033
Cutlery, hand -0.026 -0.052 0.006 0.072
tools
Manufacturing -0.079 -0.078 -0.04 -0.042
equipment
Power hand -0.045 0.014 -0.011 0.019
tools
Electrical -0.077 -0.037 0.036 0.078
machinery
Radio, TV, -0.093 0.045 0.067 0.131
communication
equip.
Precision testing -0.112 -0.019 0.019 0.018
and control
Furniture -0.019 0.028 0.011 0.016
Cumulative
Industry 2000 2001 1994-2001
Bakery 0.028 -0.067 -0.122
Woven textiles 0.04 0.042 0.147
Clothing 0.036 0.076 0.201
Footwear 0.02 0.03 0.01
Lumber 0.018 0.106 0.176
Plywood 0.117 0.049 0.183
Wooden crates 0.072 0.124 0.274
Paper products 0.022 0.063 0.198
Book, 0.022 0.003 0.024
periodicals
Printing 0.025 0.003 0.068
Rubber 0.113 0.117 0.214
Plastics 0.114 0.09 0.209
Cement and 0.064 0.059 0.18
stone products
Metal castings 0.068 0.051 0.106
for plumbing,
etc.
Metal finishing 0.069 0.029 0.137
Cutlery, hand 0.086 0.073 0.117
tools
Manufacturing 0.092 0.152 0.282
equipment
Power hand 0.192 0.221 0.338
tools
Electrical 0.121 0.226 0.447
machinery
Radio, TV, 0.287 0.288 0.473
communication
equip.
Precision testing 0.11 0.153 0.439
and control
Furniture 0.065 0.084 0.232
(a) Total Factor Productivity measured by residuals from OLS estimation
of the Cobb-Douglas form of Equation 1, restricting all second-order
coefficients to zero.
(b) Industrial classification numbers used for the Slovenian National
Income and Product Accounts.
(c) Industry's share of total manufacturing output in Slovenia. These
sectors represent approximately two-thirds of Slovenian manufacturing
output over the period.
Table 6. Estimation of Impacts of Firm and Industry Variables on Total
Factor Productivity in Slovenian Manufacturing Firms, 1994-2001
1: OLS: 2: OLS: 3: OLS:
Variable Variable and Firm and
Firm Fixed Firm Industry
Attributes Attributes Attributes
Current firm
attributes, [delta]
private 0.159 ** 0.117 ** 0.066 **
(16.70) (8.65) (4.73)
stockco -0.036 ** -0.025 -0.048 **
(2.71) (1.41) (2.68)
ltdliab -0.014 -0.038 ** -0.035 **
(1.47) (2.67) (2.46)
other 0.123 ** 0.069 ** 0.039 **
(10.20) (4.01) (2.23)
forown -0.008 0.003 -0.014
(1.04) (0.16) (0.80)
Constant firm
attributes, [mu]
ENTRY 0.035 ** 0.028 ** 0.020 **
(6.83) (5.50) (3.69)
EXIT -0.201 ** -0.154 **
(28.6) (21.2)
PRIVATE 0.008 0.018
(0.60) (1.35)
STOCKCO -0.001 0.02
(0.04) (1.31)
LTDLIAB 0.053 ** 0.058 **
(4.02) (4.37)
OTHER 0.032 ** 0.037 **
(2.30) (2.68)
FOROWN -0.001 0.021
(0.05) (1.34)
Industry attributes,
[gamma]
HERF -0.258 **
(17.1)
PRIVSHR 0.152 **
(17.9)
FORSHR 0.117 **
(10.4)
ENTSHR 0.043 **
(2.45)
EXITSHR -0.271 **
(11.10)
IMPORTSHR -0.014
(1.32)
N 27,958 27,949 25,735
[R.sup.2] 0.97 0.97 0.97
Estimated growth components from 1994 to 2001
([[bar.f].sub.01] - 0.046 0.034 0.018
[[bar.f].sub.94])
[delta]
([[bar.F].sub.01] - NA 0.054 0.042
[[bar.F].sub.94])
[gamma]
([[bar.I].sub.01] - NA NA 0.172
[[bar.I].sub.94])
[gamma]
Total TFP growth 0.222 0.222 0.222
4: Random 5: Fixed
Effects: Firm Effects: Firm
and Industry and Industry
Attributes Attributes
Current firm
attributes, [delta]
private 0.035 ** 0.019
(2.51) (1.23)
stockco -0.040 ** -0.021
(2.33) (1.10)
ltdliab -0.047 ** -0.038 **
(3.06) (2.16)
other 0.025 0.01
(1.47) (0.53)
forown -0.024 -0.027
(1.47) (1.57)
Constant firm
attributes, [mu]
ENTRY 0.030 ** (Dropped)
(3.08)
EXIT -0.173 ** (Dropped)
(15.0)
PRIVATE 0.100 ** (Dropped)
(5.08)
STOCKCO -0.050 ** (Dropped)
(2.11)
LTDLIAB 0.055 ** (Dropped)
(2.59)
OTHER 0.050 ** (Dropped)
(2.30)
FOROWN -0.01 (Dropped)
(0.52)
Industry attributes,
[gamma]
HERF -0.122 ** -0.021
(7.27) (1.08)
PRIVSHR 0.098 ** 0.050 **
(11.00) (4.91)
FORSHR 0.069 ** 0.062 **
(5.48) (4.25)
ENTSHR 0.073 ** 0.081 **
(3.58) (3.35)
EXITSHR -0.186 ** -0.149 **
-8.05 -5.86
IMPORTSHR 0.026 * 0.099 **
(1.74) (4.99)
N 25,735 25,735
[R.sup.2] 0.97 0.97
Estimated growth components from 1994 to 2001
([[bar.f].sub.01] - 0.012 0.002
[[bar.f].sub.94])
[delta]
([[bar.F].sub.01] - 0.061 NA
[[bar.F].sub.94])
[gamma]
([[bar.I].sub.01] - 0.120 0.091
[[bar.I].sub.94])
[gamma]
Total TFP growth 0.244 0.223
Coefficients are taken from translog production function estimation
of Equation 1 augmented with the variables that make up Equation 2.
The coefficients on the translog specification, including all first-
and second-order terms in the logs of real capital, materials, numbers
of university, high school, and primary school trained workers, are
withheld to conserve space. Coefficients on the log of months of firm
operation, dummy variables indicating no employees and education group,
and the constant are also suppressed.
t-statistics are reported in parentheses.
* Significance at the 0.10 level.
** Significance at the 0.05 level.
Table 7. Alternative Fixed-Effect Estimation of Impacts of
Firm and Industry Variables on Total Factor Productivity
in Slovenian Manufacturing Firms, 1994-2001
1 2
Current firm Column 5 of
attributes, [delta] Table 6 Olley-Pakes
private 0.018 0.006
(1.19) (0.37)
stockco -0.021 0.002
(1.13) (0.12)
ltdliab -0.038 ** -0.038 **
(2.15) (1.97)
other 0.010 -0.003
(0.54) (0.16)
forown -0.010 -0.007
(0.61) (0.40)
Industry attributes,
[gamma]
HERF -0.023 -0.019
(1.16) (0.93)
PRIVSHR 0.054 ** 0.048 **
(5.29) (4.27)
FORSHR 0.107 ** 0.094 **
(5.23) (4.66)
ENTSHR 0.070 ** 0.077 **
(2.88) (3.02)
EXITSHR -0.149 ** -0.117 **
(5.90) (4.20)
IMPORTSHR 0.097 ** 0.082 **
(4.90) (3.66)
N 25,726 22,447
[R.sup.2] 0.97 0.96
Estimated growth components from 1994 to 2001
([[bar.f].sub.01] - 0.002 0.0001
[[bar.f].sub.94])
[delta]
([[bar.I].sub.01] - 0.091 0.084
[[bar.I].sub.94])
[gamma]
Total TFP growth 0.223 0.223
3 4
Current firm Balanced Balanced Large
attributes, [delta] Panel Firm Panel
private 0.022 0.034
(1.36) (1.44)
stockco -0.030 -0.024
(1.58) (0.96)
ltdliab -0.043 ** -0.041
(2.44) (1.57)
other 0.020 0.026
(1.06) (1.06)
forown -0.015 -0.057
(0.78) (2.37)
Industry attributes,
[gamma]
HERF -0.013 -0.021
(0.56) (0.34)
PRIVSHR 0.061 ** 0.060 **
(5.44) (2.13)
FORSHR 0.066 ** -0.010
(4.13) (0.32)
ENTSHR 0.132 ** -0.149 **
(4.86) (2.21)
EXITSHR -0.156 ** -0.217 **
(5.66) (2.89)
IMPORTSHR 0.104 ** 0.051
(4.83) (0.99)
N 16,914 2,258
[R.sup.2] 0.97 0.93
Estimated growth components from 1994 to 2001
([[bar.f].sub.01] - 0.002 0.004
[[bar.f].sub.94])
[delta]
([[bar.I].sub.01] - 0.107 0.052
[[bar.I].sub.94])
[gamma]
Total TFP growth 0.177 0.154
Column I is taken from the last column in Table 6. Column 2 is a
variant of the Olley-Pakes (1996) specification. In this application,
we supplement the specification in column I with i, [i.sup.*]k,
[a.sup.*]k, [a.sup.*]i, and [i.sup.2] where i is the logarithm of real
investment, k is the logarithm of the capital stock, and a is the
logarithm of the firm's age. Linear and quadratic terms in firm age
are controlled by the faced effect. The null hypothesis that the five
terms can be excluded could not be rejected at standard significance
levels (F(5,16,893)) = 1.81. Column 3 replicates Column 1 but excludes
firms that enter or exit the sample. Column 4 replicates Column 3 but
excludes firms with fewer than 100 employees. Other notes are the
same as in Table 6.
