and no longer keep separate accounting and financial<sup>statements.The pattern in our</sup> resulting sample in terms of both, region, year of privatization,<sup>and sector fits closely with</sup> the compiled list of privatizations of Privatisation<sup>Internationalandthe WorldBank,</sup> particularly, when excluding voucher privatizations.<sup>This leads us to reasonably conclude</sup> that our sample is unbiased.

Figure 1 shows the distribution of our sample by<sup>regionof the world with respect</sup> to the pattern found in the original privatization lists.<sup>Whereas33 percentof the</sup> privatizations in our sample are from Latin America,<sup>8 percent from Asia,21percent from</sup> Africa and the Middle East, 25 percent from developed<sup>countries,and13percentfrom</sup> Transition Economies, the corresponding percentages<sup>for the originallist are 30,10, 20,</sup> 23, and 18 percent, respectively. Similarly, Figure<sup>2comparesthedistribution of</sup> privatizations in our sample and the original list of<sup>privatizations. In both cases,the bulk</sup> of privatizations are between the mid-1990s<sup>and late 1990s,where more than half of</sup> operations in our sample were carried out. Finally,<sup>Figure 3 comparesthe distributionof</sup> privatizations by broad sector category and, as<sup>before,the resulting patternis remarkably</sup> similar in both cases. In fact, in our sample and<sup>inthe originalcompiledlist, privatizations</sup> occur mostly in services, industry and mining, in<sup>that order. I I</sup> Table 3 presents summary statistics for the variables<sup>usedin this paper.The set of</sup> variables is organized according to firm attributes,<sup>privatizationcharacteristics, labor</sup> characteristics, labor-restructuring policies, and some<sup>basic post-privatization hiring</sup> measures. Along the lines of L6pez-de-Silanes (1997)<sup>the net privatization priceis defined</sup> as the amount that accrues to the government after<sup>all privatizationandrestructuring costs</sup> are taken into account, such as government commitments<sup>at the timeof sale,and other</sup> adjustments are made to the sale contract. This number<sup>is adjusted by the percentageof</sup> company shares sold and divided by the average<sup>net salesduring the three years prior to</sup> privatization. The present value of the resulting number<sup>as of December2000 is the</sup> dependent variable employed which is labeled<sup>Net Privatization Price /Sales.'2</sup> The labor-downsizing variable may be viewed<sup>as a basic summarymeasure of</sup> labor restructuring, as it is typically the most widely<sup>employed and most relevant froma</sup> policy perspective. This variable is defined as<sup>a dummy variablethat equals one if the</sup> firm undertook any reduction in the labor force up<sup>to threeyears prior to privatization,and</sup> zero otherwise. We follow Haltiwanger and Singh<sup>(1999) andclassify this variable by</sup> type, as voluntary and compulsory, and by targeting<sup>nature,asage-biased, skill-biased,</sup> 10. In fact, only 26.3 percent of respondents provided<sup>some numericalinfornation.</sup> 11. The World Bank privatization data, which<sup>arefor developingand transition economies,only also</sup> has information on number of shares sold and<sup>foreign participation. When we compareour developing</sup> country sub-sample (231 observations) to the<sup>onefrom theWorld Bankwe also find avery consistent</sup> pattem between both databases.

12. L6pez de Silanes (1997) also uses the firms'<sup>total assets and total liabilitiesto developa so-called</sup> Privatization Q. In our case, such variable was<sup>not possibleto construct.However,asa rough proxy in our</sup> regressions we include a dummy variable that equals<sup>onewhen totalliabilitiesare greaterthan total assets</sup> (see Table I for variable definition).

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