10 by the firm's replacement value (net fixed assets plus inventory).<sup>8</sup> Table 1, Panel C reports summary statistics. The mean Q across all five years is 0.81 which is very close to the 0.85 reported by MSV for their sample of US firms. There is a decline in mean Q over the years as the aggregate stock market went down after the initial surge in 1992. Agriculture is the only sector where mean Q increased over the period (Table A2). Typically, firms in high-skill intensive sectors and with valuable intangible assets will have high Qs, while firms in physical capital intensive industries and/or industries where the output prices are regulated will have low Qs. The sectoral dispersion of Czech firms' Qs is consistent with this: 7 of the top 10 firms (highest Qs) are in services, while 8 of the bottom 10 (lowest Qs) firms are in utilities.<sup>9</sup> Profitability is defined as gross (operating) profit over net fixed assets plus inventory. Table 1, Panel C reports summary statistics. It increases monotonically over time in all sectors (Table A2), varying between 12 % in 1992 and 17% in 1995 on average. 7 of the top 10 firms (highest profitability) operate in the engineering and architectural design, management, accounting sectors; six of the bottom 10 operate in the basic metals and the fabricated metal products (including armaments) sectors. The correlation between Tobin's Q and profitability goes up over time, which suggests that the market valuation becomes a better indicator of relative profitability as accounting data start to reflect the changes in the firms' performance.

# IV. **Regression Results**

We run the regressions using all years and all firms in each year, i.e., as an unbalanced panel. F-tests reject the hypothesis of a common constant term across firms. The Hausmanspecification tests indicate that either the fixed or random effects model can be used. Following Mundlak (1978) we choose the random effects model.'<sup>0</sup> The pooled OLS estimates are also reported (Table A3). We also ran cross-section OLS regressions for every year separately to investigate the behavior of the parameters over time (not reported). As control variables, we use the firm's leverage (the ratio of assets to equity) and year and sector dummies (regional dumrnmies 8. We have to use the face value of debt as market values of debt are not available. We do not think this introduces a bias in the regressions for three reasons. First, since all debt is floating interest rate-all fixed interest-rate debt was transferred from firms to a special agency in 1990-par and market values are close. Second, while (the risk of) non-payment could lower market values below par values, this would bias Tobin's Q downward for low Q-firms as these are more likely to risk repayment problems. This would mean that the slopecoefficients would be underestimated. Third, we also tested the relationships between the ratio of market value of equity to the book value of equity only-thus not including the value of debt-and ownership and control variables, and found similar results.

9. The Qs of most firms are stable over time: nine firms are in the top ten over the whole period. Those include 3 trading firms-Transacta (Q=2.54), KOVO (Q=2.33), Strojimport (Q=2.82); two engineering and design firmsMetrostov (Q=2.43), Plynostav Pardubice (Q=3 .37); two beer producers-Prazske Pyvovary Staroprame (Q=3. 13), Plzensky Prazdroj (Q=2.71); one construction firm-Vitkovicke Stavby (Q=2.49); one transport firmCechofracht (Q=2.68). Six of the bottom ten firms are water utilities-Vodovody a Kanalizaci Nachod (Q=0. 10), Zlin (Q=0.12), Prostejov (Q=0.14), Kraslice (Q=0.13), Slovacke (Q=0.13), and Nymburk (Q=0.12).

10. From a practical standpoint, the fixed effects model is costly in terms of degrees of freedom, and in a longitudinal dataset as ours, random effects have some intuitive appeal.