Skip to main content

Which Companies Benefit from Liberalization? a Study of the Influence of Initial Productivity


Theoretical research shows that competition has positive effects on productivity, for companies that are initially efficient, but not for unproductive firms. Our empirical analysis on a panel data of Czech companies, years 1995–2004, confirms this result. In addition, our analysis shows that when economic reforms affect both domestic and foreign competition, controlling for domestic competition is crucial when assessing the impact of trade liberalization. Otherwise, the effect of trade liberalization on firm productivity is upward biased.

This is a preview of subscription content, access via your institution.


  1. For instance, see Winters (2004) for the impact of openness on firm performance. Also see Djankov and Murell (2002) for a survey of literature for transition economies.

  2. We are aware of the paper by Topalova and Khandelwal (2011) but the original Topalova (2004) working paper is more directly showing results depending on the initial productivity levels of the firms.

  3. As we go directly for TFP effects in our study, this is an aspect where the Iacovone (2012) paper differs from ours. Papers that primarily base their results on labor productivity usually have to discuss quite thoroughly that their results also reflects overall TFP patterns, see also Lileeva and Trefler (2010).

  4. We have also included a measure of firm age and its square in our regressions. As these variables were not significant we decided to drop them from the equations.

  5. The log transformation does not really capture the non-linearity of a U shape. We favored this specification as the alternative specifications based on quadratic terms induced problems of multicollinearity. In addition, estimations based on quadratic form specifications have shown that in most cases our firms have a position on one leg of the parabola only.

  6. As pointed out in the literature by e.g. Klette and Griliches (1996), Katayama et al. (2003) and Katayama et al. (2009) then estimates of the coefficients of the production function may be biased when prices at the firm level are not available but prices at the industry level are used instead. This is a complicated issue and as we do not have access to prices at the firm level, we use the industry level prices referring to the results of Mairesse and Jaumandreu (2005) that indicates that deflating value added with PPI rather than a firm specific price index leads to very similar estimates of the coefficients in the production function.

  7. We have performed a Hausmann test for firm specific effects and the null of no effects was actually rejected. In this test, however, we did not take the hidden dynamics into account.

  8. It can be argued that our results are valid for the transition period and that this period must be considered more or less over with respect to Tariff changes at the end of our sample. Hence extending the sample to include even more recent periods may not be meaningful.


  • Aghion P, Bloom N, Blundell R, Griffith R, Howitt P (2005a) Competition and innovation: an inverted U relationship. Q J Econ 120(2):701–728

    Google Scholar 

  • Aghion P, Burgess R, Redding SJ, Zilibotti F (2005b) Entry liberalization and inequality in industrial performance. J Eur Econ Assoc 3(2–3):291–302

    Article  Google Scholar 

  • Aghion P, Blundell R, Griffith R, Howitt P, Prantl S (2009) The effect of entry on incumbent innovation and productivity. Rev Econ Stat 91(1):20–32

    Article  Google Scholar 

  • Arrow, K. (1962): Economic welfare and the allocation of resources for inventions, in The Rate and Direction of Inventive Activity, ed. R. Nelson, Princeton University Press, Princeton.

  • Bernard AB, Jensen JB, Schott PK (2006) Trade costs, firms and productivity. J Monet Econ 53(5):917–937

    Article  Google Scholar 

  • Bessonova, E., K. Kozlov and K. Yudaeva (2003): Trade liberalization, foreign direct investment, and productivity of russian firms, CEFIR Working Papers w0035.

  • Boone J (2000) Competitive pressure: the effects on investments in product and process innovation. RAND J Econ 31(3):549–569

    Article  Google Scholar 

  • Djankov S, Murell P (2002) Enterprise restructuring in transition: a quantitative survey. J Econ Lit 40:739–792

    Article  Google Scholar 

  • Green A, Mayes D (1991) Technical inefficiency in manufacturing industries. Econ J 101:523–538

    Article  Google Scholar 

  • Hart OD (1983) The market mechanism as an incentive scheme. Bell J Econ 14:366–382

    Article  Google Scholar 

  • Hermalin BE (1992) The effects of competition on executive behavior. RAND J Econ 23(3):350–365

    Article  Google Scholar 

  • Holmstrom, B. (1982): Managerial incentive problems – a dynamic perspective, in Essays in Economics and Management in Honor of Lars Wahlbeck, Helsinki: Swedish School of Economics.

  • Iacovone L (2012) The better you are the stronger it makes you: evidence on the asymmetric impact of liberalization. J Dev Econ 99:474–485

    Article  Google Scholar 

  • Javorcik BS (2004) Does foreign direct investment increase the productivity of domestic firms? In search of spillovers through backward linkages. Am Econ Rev 94(3):605–627

    Article  Google Scholar 

  • Katayama H., S. Lu and J. Tybout (2003): Why plant level productivity studies are often misleading, and an alternative approach to inference, NBER Working Paper 9617.

  • Katayama H, Lu S, Tybout J (2009) Firm level productivity studies: illusions and a solution. Int J Ind Organ 27:403–413

    Article  Google Scholar 

  • Klette J, Griliches Z (1996) The inconsistency of common scale estimators when output prices are unobserved and endogenous. J Appl Econ 11:343–361

    Article  Google Scholar 

  • Konings, J. and H. Vandenbussche (2007): Antidumping Protection and Productivity of Domestic Firms: A Firm Level Analysis, mimeo.

  • Lawrence, R.Z. (2000): Does a kick in the pants get you going or does it just hurt? The Impact of International Competition on Technological Change in US Manufacturing, in Feenstra, R.E. ed., The Impact of International Trade on Wages, University of Chicago Press for the National Bureau of Economic Research, Chicago, pp. 197–224.

  • Levinsohn J, Petrin A (2003) Estimating production functions using inputs to control for unobservables. Review of Economic Studies 70(2):317–341

    Article  Google Scholar 

  • Lileeva A, Trefler D (2010) Improved access to foreign markets raises plant-level productivity … for some plants. Q J Econ 125(3):1051–1099

    Article  Google Scholar 

  • MacDonald JM (1994) Does import competition force efficient production? Review of Economics and Statistics 76(4):721–727

    Article  Google Scholar 

  • Mairesse J, Jaumandreu J (2005) Panel-data estimates of the production function and the revenue function: what difference does it make? Scand J Econ 107(4):651–672

    Article  Google Scholar 

  • Martin S (1993) Endogenous firm efficiency in a cournot principal-agent model. J Econ Theory 59:445–450

    Article  Google Scholar 

  • Meyer MA, Vickers J (1997) Performance comparisons and dynamic incentives. J Polit Econ 105(3):547–581

    Article  Google Scholar 

  • Nalebuff BJ, Stiglitz JE (1983) Information, competition, and markets. Am Econ Rev 73:278–283

    Google Scholar 

  • Nickell, S.J. (1994): Competition and corporate performance, Discussion Paper 182, London school of economics, Centre for Economic Performance.

  • Nickell SJ (1996) Competition and corporate performance. J Polit Econ 104(4):724–746

    Article  Google Scholar 

  • Nickell SJ, Wadhwani SB, Wall M (1992) Productivity growth in U.K. Companies, 1975–1986. Eur Econ Rev 36:1055–1085

    Article  Google Scholar 

  • Olley GS, Pakes A (1996) The dynamics of productivity in the telecommunications equipment industry. Econometrica 64(6):1263–1297

    Article  Google Scholar 

  • Pavcnik N (2002) Trade liberalization, exit, and productivity improvements: evidence from Chilean plants. Review of Economic Studies 69(1):245–276

    Article  Google Scholar 

  • Romer P (1994) New goods, old theory and the welfare cost of trade restrictions. J Dev Econ 43(1):5–38

    Article  Google Scholar 

  • Sabirianova K, Svenjar J, Terrell K (2005) Distance to the efficiency frontier and FDI spillovers. J Eur Econ Assoc 3(2–3):576–586

    Article  Google Scholar 

  • Scharfstein (1988) Product-market competition and managerial slack. RAND J Econ 19(1):147–155

    Article  Google Scholar 

  • Scherer F (1967) Market structure and the employment of scientists and engineers. Am Econ Rev 57:524–531

    Google Scholar 

  • Schmidt KM (1997) Managerial incentives and product market competition. Review of Economic Studies 64:191–213

    Article  Google Scholar 

  • Schumpeter, J. (1934): The theory of economic development, Cambridge, MA: Harvard University Press.

  • Schumpeter, J. (1942): Capitalism, Socialism and Democracy, New York: Harper.

  • Topalova, P. (2004): Trade Liberalization and Firm Productivity: the Case of India, IMF Working Papers 04/28.

  • Topalova P, Khandelwal A (2011) Trade liberalization and firm productivity: the case of India. Rev Econ Stat 93(3):995–1009

    Article  Google Scholar 

  • Tybout J (2003) Plant- and firm-level evidence on ‘new’ trade theories. In: Choi EK, Harrigan J (eds) Handbook of international economics. Basil-Blackwell, Oxford

    Google Scholar 

  • Winters LA (2004) Trade liberalization and economic performance: an overview. Econ J 114(2):F4–F21

    Article  Google Scholar 

Download references


This paper has benefited from extensive discussions and feedback from Pascalis Raimondos-Møller. We gratefully acknowledge his help. Also we thank Steffen Andersen, Jan. Hanousek, Lubomir Lizal, Stephan Juraida, Anders Sørensen, Moira Daly and Jonathan Temple for valuable comments and insights. We also thank the Danish Social Science Research Council for financial support.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Lisbeth Funding la Cour.


Appendix 1 – Data Description

Firm level data are from Amadeus. Amadeus is a pan-European commercial database, provided by Bureau van Dijk, which contains financial information on public and private companies. We used data from all versions of the Amadeus database since 1996 with information on medium and large firms. Most of the Czech firms included in the database produce goods in several industries at 4 digit NACE level. We have classified firms according to their main activity.

We did the following modifications to the data:

i. we excluded all companies that had less than 10 employees:

ii. we excluded firms with non-positive investment levels when estimating firm productivity.

iii. Since we did not have enough observations in three industries at 2-digit NACE level (16 – manufacture of tobacco, 19 - Leather manufacturing, 22 – Publishing and printing, 23 – manufacture of coke, refined petroleum and nuclear fuel, 26 - Non-metallic mineral products, 30 – manufacture of office machinery and computers, 32 - Radio, television and communication equipment and apparatus 37 - Recycling) to estimate the production function we dropped companies from this sector.

iv. the data was trimmed at the 1 % and 99 % quantiles.

Tables 6, 7, 8, 9

Table 6 Variables
Table 7 Descriptive statistics – observations based on which firm productivity is estimated
Table 8 Descriptive statistics – observations based on which the impact of competition on firm productivity is estimated
Table 9 Number of firms and their average size by year

Appendix 2: Time line for important reforms in Czech Republic 1990–2005

Table 10

Table 10 Main economic reforms

Appendix 3: Results of the Estimation of the Production Function

Table 11, 12, Fig. 1

Table 11 OLS and Wooldridge estimates of production function
Table 12 Statistics of the distributions of the TFP estimates by 2 digit industry (based on the Wooldridge estimates of the production function)
Figure 1.
figure 1

Density of firm productivity (pooled sample)

Appendix 4 – Robustness Checks

Table 13, 14, 15

Table 13 The impact of competition on firm productivity using OLS Productivity
Table 14 The impact of competition on firm productivity using OP productivity
Table 15 The impact of competition on firm productivity if market concentration rather than the Herfindahl index is used to measure domestic competition

Appendix 5 Estimation Methods for Coefficients of the Production Function

Wooldridge (2009) estimation

This appendix section explains the approach, based on Wooldridge (2009), used to estimate the production function parameters and recover the productivity term used in our analysis. We assume a value-added Cobb-Douglas production function:

$$ {\mathrm{y}}_{\mathrm{it}}={\upbeta}_{\mathrm{l}}{\mathrm{l}}_{\mathrm{it}}+{\upbeta}_{\mathrm{k}}{\mathrm{k}}_{\mathrm{it}}+{\upomega}_{\mathrm{it}}+{\upeta}_{\mathrm{it}} $$

where y it is the log of value added, l it is the log of employment, k it is the log of real capital stock, ω it the transmitted component of the firm specific productivity shock, and η it represents firm specific iid productivity shock or measurement errors.

As in Olley and Pakes (1997), Levinsohn and Petrin (2003), or Wooldridge (2009) we express productivity as a function of the state variable (k it ) and a proxy variable. Following e.g. Petrin and Sivadasan (2013) we use the Wooldrige version of Levinsohn and Petrin and use intermediate inputs (materials) m it as the proxy variable:

$$ {\upomega}_{\mathrm{it}}=\mathrm{g}\left({\mathrm{k}}_{\mathrm{it}};{\mathrm{m}}_{\mathrm{it}}\right) $$

We restrict the dynamics of productivity shocks in the following way:

$$ \mathrm{E}\left[{\upomega}_{\mathrm{i}\mathrm{t}}|{\mathrm{k}}_{\mathrm{i}\mathrm{t}};{\mathrm{l}}_{\mathrm{i}\mathrm{t}-1};{\mathrm{k}}_{\mathrm{i}\mathrm{t}-1};{\mathrm{m}}_{\mathrm{i}\mathrm{t}-1};\dots; {\mathrm{k}}_{\mathrm{i}1};{\mathrm{l}}_{\mathrm{i}1};{\mathrm{m}}_{\mathrm{i}1}\right]=\mathrm{E}\left[{\upomega}_{\mathrm{i}\mathrm{t}}|{\upomega}_{\mathrm{i}\mathrm{t}-1}\right]=\mathrm{f}\left(\mathrm{g}\left({\mathrm{k}}_{\mathrm{i}\mathrm{t}-1};{\mathrm{m}}_{\mathrm{i}\mathrm{t}-1}\right)\right) $$

And assume that variable inputs (l it andm it ) are correlated with productivity innovations (a it ) but k it and all past values of l , k and m are uncorrelated with a it , i.e. E[a it | k it  ; l it - 1 ; k it - 1 ; m it - 1 ;  …  ; k 1 ; l 1 ; m 1] = 0.

Then we can rewrite the production function as:

$$ {\mathrm{y}}_{\mathrm{it}}={\upbeta}_{\mathrm{l}}{\mathrm{l}}_{\mathrm{it}}+{\upbeta}_{\mathrm{k}}{\mathrm{k}}_{\mathrm{it}}+\mathrm{f}\left(\mathrm{g}\left({\mathrm{k}}_{\mathrm{it}-1};{\mathrm{m}}_{\mathrm{it}-1}\right)\right)+{\mathrm{u}}_{\mathrm{it}} $$

Where u it  ≡ a it +η it

The moment conditions to identify the parameters are

$$ \mathrm{E}\left[{\mathrm{u}}_{\mathrm{i}\mathrm{t}}|{\mathrm{k}}_{\mathrm{i}\mathrm{t}};{\mathrm{l}}_{\mathrm{i}\mathrm{t}-1};{\mathrm{k}}_{\mathrm{i}\mathrm{t}-1};{\mathrm{m}}_{\mathrm{i}\mathrm{t}-1};\dots; {\mathrm{k}}_{\mathrm{i}1};{\mathrm{l}}_{\mathrm{i}1};{\mathrm{m}}_{\mathrm{i}1}\right]=0 $$

We follow the literature and approximate f(g(k it - 1; m it - 1)) using a third order polynomial. In addition to the exogenous state variable (k it ) we use first lags of materials and labor as instruments. The estimation is undertaken separately for each 2-digit industry. Table A3.1 summarizes the coefficient estimates and we compute productivity as \( {\omega}_{it}={y}_{it}-{\widehat{\beta}}_l{l}_{it}-{\widehat{\beta}}_k{k}_{it} \)

Olley and Pakes (1996) Estimation

The OP method is extensively used in the literature and therefore we do not describe it in detail here. This method could be also used to control for the exit bias (i.e. firms with more capital may sustain higher adverse shocks without exiting and therefore, if these shocks are not taken into account, the coefficient of capital are biased downwards). We do not control for it because in our sample there are too few firms that exit the market.

We first estimated a Cobb-Douglas production function, y i , t  = β l l i , t  + (β 0 + β k k i , t  + h(i i , t , k i , t )) + υ i , t , where y is value added, l is log of labor(employment), k is log of capital, h() accounts for firm productivity which according to the OP assumptions can be written as a function of capital and investment, i, (h() was approximated by a 3rd degree polynomial function), and υ is white noise. Subscripts i and t are firm and time indices, respectively. From this step we retained the coefficient of labor, β l . Further, to determine β k , we estimated \( {y}_{i,t}-{\beta}_l{l}_{i,t}={\beta}_k{k}_{i,t}+\theta \left({\widehat{y}}_{i,t-1}-{\widehat{\beta}}_l{l}_{i,t-1}-{\beta}_k{k}_{i,t-1}\right)+{\xi}_{i,t} \) where, given the OP assumption that productivity follows a first order Markov process, firm productivity is a function, θ(), of its t-1 value. ξ i , t is the error term. We used non-linear estimations where θ() was approximated by a 3rd degree polynomial function. Time varying firm total factor productivity is then calculated as \( p{r}_{i,t}={y}_{i,t}-{\widehat{\beta}}_l{l}_{i,t}-{\widehat{\beta}}_k{k}_{i,t} \).

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Baghdasaryan, D., la Cour, L.F. & Schneider, C. Which Companies Benefit from Liberalization? a Study of the Influence of Initial Productivity. J Ind Compet Trade 16, 101–125 (2016).

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:


  • Firm productivity
  • Trade liberalization
  • Competition
  • Initial productivity


  • D24
  • F10