Abstract
We develop a theoretical framework for defensive and strategic restructuring, and provide estimates of restructuring in privatized firms in an advanced transition economy: Slovenia. Our rich data point to both types of restructuring, as well credit rationing and bargaining with respect to investment. Privatized firms display profit-maximizing behavior, and a firm's export orientation and institutional features, such as insider vs outsider privatization, employee ownership, and employee control, do not affect the firm's employment and investment behavior. The results suggest that a major exposure to world competition induces similar economic behavior in firms with different structural and institutional characteristics.
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Notes
Earlier studies are reviewed for instance in Megginson and Netter (2001) and Djankov and Murrell (2002). A survey of both the earlier and more recent studies may be found in Estrin, Hanousek, Kocenda, and Svejnar (2007).
Early surveys of privatization in the transition economies vary from finding no systematic performance effect (Bevan, Estrin, & Schaffer, 1999) to noting that a positive effect probably dominates (Megginson & Netter, 2001), to concluding that the overall effect is positive (Carlin, Fries, Schaffer, & Seabright, 2001; Djankov & Murrell, 2002; Shirley & Walsh, 2000). The recent survey by Estrin et al. (2007) finds a strong positive performance effect of privatization for foreign owners, but a much weaker or insignificant effect for domestic owners. Given that better-performing firms tend to be privatized first (Gupta, Ham, & Svejnar, 2007), it is likely that the positive effect of privatization is often overestimated. Stiglitz (1999) argues that the main reason for relatively poor performance in early transition is that successful privatization requires effective institutional infrastructure. Svejnar (2002) points out that virtually all the transition economies in Central and East Europe (CEE) and the Commonwealth of Independent States (CIS) rapidly carried out Type I reforms (macroeconomic stabilization, price liberalization, break-ups of SOEs and monobank system, small-scale privatization, and reduction of direct state subsidies). However, the CIS countries, Bulgaria, Czech Republic, and Romania were slower in carrying out Type II reforms (effective large-scale privatization, establishment of a market-oriented legal system and accompanying institutions, and further development of the commercial banking and financial system), and also performed worse than the CEE countries that carried out both types of reform. Finally, Estrin (2002) notes that reform policies have been applied more consistently and effectively in the Visegrad countries, the Baltic States, and Slovenia than elsewhere, especially in the rest of the former Soviet Union.
Firms in our sample also differ markedly in the extent to which they carried out restructuring. Our data hence contain sizeable variation in the values of the key variables, and lend themselves to detecting systematic effects.
For earlier studies see Cable and FitzRoy (1980), Clegg (1983), Crouch (1983) and Svejnar (1982).
Most Latin American countries, India and many other Asian economies, and most African countries followed the infant industry prescription in maintaining sizeable tariff and non-tariff protection for decades.
The 1992 Privatization Law allocated 20% of a firm's shares to insiders (workers), 20% to the Development Fund that auctioned the shares to investment funds, 10% to the National Pension Fund, and 10% to the Restitution Fund. In addition, in each enterprise the workers' council or board of directors (if one existed) was empowered to allocate the remaining 40% of company shares for sales to insiders (workers) or outsiders (through a public tender). Based on the decision on the allocation of this remaining 40% of shares, firms can be classified as being privatized to insiders (the internal method) or outsiders (the external method).
Grosfeld and Roland (1997) and Aghion et al. (1997) introduce the theoretical concepts, while Frydman et al. (1999) estimate the effects of ownership on changes in revenues and costs using balance sheet data. We present theoretical models that develop and apply the concepts of restructuring, and we test the predictions using a wide variety of performance indicators.
The formulation nests the fixed proportions (σ=0) and Cobb–Douglas (σ=1) production functions.
In the literature there are usually two general approaches, assuming that agents' expectations are either perfect or rational. (See Hamermesh (1993) for further discussion.)
A conceptually important point is that the flexible difference equation (1′) may be viewed as an arbitrary flexible approximation to dynamic adjustment, or it may be derived formally from an underlying cost minimization behavior of the firm (e.g., Nickell, 1984; Bresson, Kramarz, & Sevestre, 1992). In particular, suppose firms face exogenous output constraints and quadratic costs d and e in adjusting their labor L and capital K inputs, respectively, and minimize input costs C t :
subject to a production constraint
where E is the expectation operator, c t is the user cost of capital, ΔL t =L t −L t −1, and ΔK t =K t −K t −1, respectively. Assuming further that the production function is of the Cobb–Douglas form, that changes in employment from period to period are relatively small, and that the exogenous variables follow an autoregressive process of the second degree, one obtains a log-linear equation such as (1′).
Error correction models were introduced into the investment literature by Bean (1981) and have been considered in the context of firm data estimating demand for capital by Bond, Elston, Mairesse, and Mulkay (1997), while Nickell (1984, 1985) and Bresson et al. (1992) have applied them to employment demand. The models represent a suitable alternative to more structural models (e.g., Q or Euler equations) that are often found to have unexpected signs on key explanatory variables.
Many Slovenian firms introduced transactional management in the period of early transition, which led to lower R&D expenses and the closing down of R&D departments. After firms were privatized, R&D expenditures increased, especially to exchange “old-fashioned” products for new ones and to improve technology.
Slovenian firms are good laboratories because they were “forced” to reorient their business activities in the transition period from the “low demand” ex-Yugoslav market to the “high demand” European market, where they compete for a market share with competitors from all over the world. Moreover, with the liberalization of foreign trade, competition on the domestic markets increased as well.
With testing the null hypothesis of whether the coefficient on the second lagged level of output is equal to zero, we implicitly test the hypothesis that the long-run elasticity of capital with respect to output equals unity.
An alternative interpretation of the case in which the firm's level of investment varies positively with internal funds – one that is consistent with perfectly functioning capital markets – is that the firms can borrow investment funds at a constant market rate, but that this rate exceeds the rate at which the firms can lend because of transaction costs (e.g., Almeida & Campello, 2002; Fazzari et al., 1988; Kaplan & Zingales, 1997).
In the context of the transition to a market economy, the investment–wage issue is especially important. The lifting of central controls and insider privatization gave workers significant powers in enterprises in a number of countries, including Russia and Ukraine. Moreover, with the inability of many firms in these economies to pay wages, the trade-off between using the firm's value-added for financing investment vs paying wages and fringe benefits has become particularly acute.
The reservation wage is defined as the wage below which employees would be unwilling to work in the firm.
That is, we capture the fact that employees may try to appropriate as income some funds that could otherwise be used for expenditures on R&D, marketing, and training. We also implicitly assume that the reservation level of these expenditures is zero, which is not unrealistic in the context of the transition economies.
In the case of factor demand estimation, as in investment or labor demand equations, the endogeneity of RHS variables (apart from lagged dependent variable) is quite common, introducing a new source of bias when using OLS or within-firms estimators. Any variable included as an explanatory variable and affected by firm-specific shocks to investments will be endogenous and correlated to the firm fixed effects and error term. Examples of such variables are cash flow or estimates of the shadow values of capital. This means that not only dynamic but also static models of investment might suffer from inconsistencies of parameter estimates described above.
This arises from the magnification of the “noise to signal” ratio (ratio of the variance of the serially uncorrelated measurement error in a variable and the net variance of this variable) by the differencing transformation. This magnification is larger for first differences than for the within differences (or for longer differences) (e.g., Griliches & Hausman, 1986; Mairesse, 1990.)
Arellano (1989) reports that for the simple dynamic error components models, the estimator that uses differences rather than levels for instruments has very large variances over a significant range of parameter values. In contrast, the estimator that uses instruments in levels has much smaller variances and is therefore recommended.
The actual number of firms used is somewhat lower, and varies across regressions (from 109 in the employment equation to 126 in the training equation), depending on the availability of data for particular variables.
Marketing expenses are usually divided into expenses for research, market communication, sales, and distribution (Preisner, 1996). In order to be able to compare firms across industries, we have excluded expenses related to salespersons employed in retailing positions.
The reservation wage is calculated on the basis of the average wage within each industry in a given region, region-specific unemployment rate, and average annual unemployment compensation:
where AIW is the average annual wage per employee in a given industry and region, UR is the average annual unemployment rate in a given region, and UC is the average annual unemployment compensation.
We calculate the stock of intangible (knowledge) capital by using the permanent inventory method, originally proposed by Griliches (1979) for R&D capital. This method assumes that the current state of knowledge is the result of present and past expenditures in knowledge capital. In particular,
where R it is the current level of soft capital spending, δ i k is the firm-specific rate at which the “knowledge” stock depreciates, k denotes different forms of soft capital investment, and INT it is the stock of knowledge capital. Substituting INT it −1 by past expenditures on soft capital investment, we obtain
or
Since our focus is on the sample of firms that underwent ownership transformation in the middle of the 1990s, and were operating in a labor-management system before the process of transition that started in 1991, it makes sense to assume that the process of investing started in 1992, with the initial level of knowledge capital being zero. As our data start in 1996, we assume that the value of investment n knowledge capital in each year is 5% smaller than in the following year. Finally, we assume a depreciation rate of 15%.
The average share of employees fell from 23.5 to 16%, while the managers' share rose on average from 3 to 4%.
Within this category, the average share of state funds declined from 23.4 to 13.2%, while the share of private investment funds increased from 13.6 to 18%.
Within this category, the average share of small shareholders fell from 3.8 to 3%, whereas the average ownership shares of banks and state remained the same at 1.3 and 2%, respectively.
Expenses for training include only payments for the services of external educational institutions. Many firms run internal training programs, the cost of which is not included in our data. Similarly, Milkovich and Boudreau (1997) report that in the United States firms with more than 100 employees paid $10.3 billion on training to external providers, while the total training cost was $52.2 billion in 1995.
We also checked whether ownership structure captures size variations. Exploring correlation coefficients between ownership variables and typical size variables (number of employees, amount of fixed assets, and capital), we found that none of them is higher than 0.3.
The chi-squared result χ 2=3.69 (p-value 0.59) does not permit us to reject the null hypothesis.
The average firm in our sample financed more than 60% of its investment in fixed capital by depreciation, 10% by retained profit, 10% by long-term loans, 5% by short-term loans, 5% by state funds and loans from other firms, 5% by disinvestments, and less than 1% by issues of shares. As to investment in R&D, the sampled firms on average financed 90% of this investment from internal funds, 3% by loans, less than 2% by funds firms received from the National Fund for Technology and Development, and 2% by funds from partners.
Wald tests of the joint significance ownership variables are 1.20 (p-value 0.87), 34.9 (0.00), 2.24 (0.69), 0.40 (0.98), and 1.59 (0.81) for fixed investment R&D investment, marketing investment on domestic market, marketing investment on foreign markets, and employee training, respectively.
Although it is usually perceived that workers are less risk averse and therefore less likely to support R&D investment, evidence from Slovene firms suggests that in the early post-privatization period other types of domestic owners behaved as short-term rent-seekers who tried to maximize dividends and other transfers of funds from firms. Moreover, foreign owners tended to reduce R&D in the acquired firms and concentrate it in a few Western locations: see Prašnikar and Gregorič (2002). We would like to thank Bernard Yeung for encouraging us to pursue the analysis in this direction.
In the early phases of restructuring, many of these firms broke up into several units or spun off parts of the original firm (Lizal, Singer, & Svejnar, 2001).
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Acknowledgements
Prašnikar's and Domadenik's research in this paper was in part supported by the Slovenian Research Agency's grant no. P5-0128, Behavior of Slovene Firms in Global Competition. Svejnar's research was in part supported by NSF grant no. SES 0111783. The authors are indebted to two referees and Bernard Yeung for useful comments, and to numerous Slovenian enterprises for providing them with the data used in this paper. The usual caveat applies.
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Accepted by Bernard Yin Yeung, Departmental Editor, 20 June 2007. This paper has been with the authors for two revisions.
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Domadenik, P., Prašnikar, J. & Svejnar, J. Restructuring of firms in transition: ownership, institutions and openness to trade. J Int Bus Stud 39, 725–746 (2008). https://doi.org/10.1057/palgrave.jibs.8400379
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DOI: https://doi.org/10.1057/palgrave.jibs.8400379