way to control for institutional differences across countries and over time is to use enterprise data from several countries, i.e., enterprises under different institutional environments, and apply a random-effects model. This way one controls for differences in the legal and other aspects of the overall external environment, as well as enterprise-specific heterogeneity.

Third, the SV model indicates that the degree of stabilization can greatly affect enterprise performance. Improvements in enterprise performance may then wrongly be attributed to privatization when they are mainly due to hardening of the budget constraint. A cross-country comparison through a panel approach would correct for differences in overall monetary tightness. But, the hardening of the budget constraint may differ across enterprises, as the political costs and benefits of soft budgets may depend on the size of the enterprise, the labor intensity of production, type of products, etc. It is thus necessary to use firm-specific proxies for hardening of the budget constraint. One candidate is the (change in the) amount of new bank lending to the enterprise in question since, ex-post, much of it often ended up being subsidies in disguise. Direct subsidies from the state can also be included.

Fourth, and this a more general point, the SV model indicates that it is necessary to control for initial conditions at the enterprise level. Enterprises are differently endowed in terms of quality of machinery, labor, management, links with foreign markets, etc. This is especially the case in transition economies where the decisions on new investment, worker training, etc., were taken at the central level and were seldom driven by previous track record. It may have given some firms a competitive advantage or disadvantage once liberalization took place, leading to higher or lower profitability. Some of this can be captured by controlling for sectors, but not all. Provided there is no clear relationship of initial conditions with privatization, this still need not bias any results. There has been a presumption, however, that better firms are more likely to be privatized. As a result, measures of productivity would be biased when comparing the performance of privatized and state-owned enterprises. One should thus control for the initial level of productivity. Furthermore, it can be expected, as confirmed for market economies, that firms' productivity tends to converge over time, i.e., increased competition will make higher profitable firms less profitable (Waring, 1996). When combined with a selection bias of better firms more likely to be privatized, this may mean that in terms of changes in profitability, privatization is associated with an actual worsening of performance over time.

The SV model also suggests a number of clear predictions of the effects of privatization on profitability, labor and efficiency. These are summarized in Table 1. Under full corruption excess labor is not reduced and efficiency does not change with privatization. The only affected variable is soft financing which decreases as politicians incur higher cost in handing out subsidies. The effect of privatization in the absence of deregulation and without stabilization leads to perverse results. While in a public firm the politician needs to pay for excess employmen **t** hrough politically costly subsidies, in a regulated privatized firm he can force the managers to pay for the increase in excess labor and decreased efficiency. This suggests that, in the absence of full corruption, regulation might be an even greater problem than public ownership. Privatization with deregulation, but without stabilization increases soft financing, as the managers are in a 7