Priorities and Sequencing in Privatization: Theory and Evidence from the Czech Republic

While privatization of state-owned enterprises has been one of the most important aspects of economic transition from a centrally planned to a market system, no transition economy has privatized all its firms simultaneously. This raises the issue of whether governments strategically privatize firms. In this paper we examine theoretically and empirically the determinants of the sequencing of privatization. First, we develop new and adapt existing theoretical models in order to obtain testable predictions about factors that may affect the sequencing of privatization. In doing so, we characterize potentially competing government objectives as (i) maximizing sales revenue from privatization or public goodwill from transferring shares of firms to voters, (ii) increasing economic efficiency, and (iii) reducing political costs due to layoffs. Next, we use an enterprise-level data set from the Czech Republic to test the competing theoretical predictions about which firm characteristics affect the sequencing of privatization. We find strong evidence that more profitable firms were sold first. This suggests that the government sequenced the sale of firms in a way that is consistent with our theories of sale revenue maximization and/or maximizing public goodwill from subsidized share transfers to citizens. Our results are also consistent with Shleifer and Vishny's (1994) prescription for increasing efficiency when there are political costs to employment losses caused by privatization. We also find that the Glaeser-Scheinkman (1996) recommendations for increasing efficiency by privatizing first firms subject to large informational shocks are consistent with our results. Finally, our findings are inconsistent with the government pursuing a static Pareto efficiency objective. In addition to enhancing the general understanding of privatization, our evidence suggests that many empirical studies of the effects of privatization on firm performance may suffer from selection bias since privatized firms are likely to have observable and unobservable characteristics that make them more profitable than firms that remain under state ownership.http://deepblue.lib.umich.edu/bitstream/2027.42/39707/3/wp323.pd

Estimating the Effect of Training on Employment and Unemployment Durations: Evidence From Experimental Data

Using data from a social experiment, we estimate the impact of training on the duration of employment and unemployment spells for AFDC recipients. Although an experimental design eliminates the need to construct a comparison group for this analysis, simple comparisons between the average durations or the transition rates of treatments' and controls' employment and unemployment spells lead to biased estimates of the effects of training. We present and implement several econometric approaches that demonstrate the importance of and correct for these biases. For the training program studied in the paper, we find that it raised employment rates because employment durations increased. In contrast, training did not lead to shorter unemployment spells.

Randomization, Endogeneity and Laboratory Experiments

In conducting experiments with multiple trials, outcomes from previous trials can impact on current behavior. One of the most obvious cases in which this can happen, and the case considered in this paper, is in an auction market experiment, where earnings from previous auction trials alter cash balances which, in turn, can affect bidding behavior. (The most obvious mechanism for such a result, within standard theory, is if bidders are risk averse and do not have constant absolute risk aversion. One can imagine a number of non-standard reasons for such effects as well.) Use of OLS regressions with cash balances included as a right hand side variable are likely to lead to a biased estimate of the cash balance effect since the variation in cash balances is largely related to differences in bidding strategies across individuals. Fixed effect regressions can commonly control for these endogeniety problems at the potential cost of obtaining inefficient estimates, since this estimator does not exploit between-individual variation. This paper addresses this problem in two ways. First we consider an experimental design that reduces the potential bias of OLS estimates while increasing the precision of fixed effect estimates. Second, we consider instrumental variables estimation of the cash balance effect where the instruments are produced by the experimental design. To the best of our knowledge, neither of these approaches has been explored in the experimental literature.

Priorities and Sequencing in Privatization: Theory and Evidence from the Czech Republic

While privatization of state-owned enterprises has been one of the most important aspects of economic transition from a centrally planned to a market system, no transition economy has privatized all its firms simultaneously. This raises the issue of whether governments strategically privatize firms. In this paper we examine theoretically and empirically the determinants of the sequencing of privatization. First, we develop new and adapt existing theoretical models in order to obtain testable predictions about factors that may affect the sequencing of privatization. In doing so, we characterize potentially competing government objectives as (i) maximizing sales revenue from privatization or public goodwill from transferring shares of firms to voters, (ii) increasing economic efficiency, and (iii) reducing political costs due to layoffs. Next, we use an enterprise-level data set from the Czech Republic to test the competing theoretical predictions about which firm characteristics affect the sequencing of privatization. We find strong evidence that more profitable firms were sold first. This suggests that the government sequenced the sale of firms in a way that is consistent with our theories of sale revenue maximization and/or maximizing public goodwill from subsidized share transfers to citizens. Our results are also consistent with Shleifer and Vishny's (1994) prescription for increasing efficiency when there are political costs to employment losses caused by privatization. We also find that the Glaeser-Scheinkman (1996) recommendations for increasing efficiency by privatizing first firms subject to large informational shocks are consistent with our results. Finally, our findings are inconsistent with the government pursuing a static Pareto efficiency objective. In addition to enhancing the general understanding of privatization, our evidence suggests that many empirical studies of the effects of privatization on firm performance may suffer from selection bias since privatized firms are likely to have observable and unobservable characteristics that make them more profitable than firms that remain under state ownership.

The Effect of Medicaid Expansions for Low-Income Children on Medicaid Participation and Insurance Coverage: Evidence from the SIPP

Increased availability of public health insurance for children has led to two potentially contradictory concerns for public policy: that expanded availability of public insurance may lead families to decline private insurance and that additional public coverage may not reach many uninsured children. We examine these two concerns using data from the 1987-1993 Surveys of Income and Program Participation. Using static models we find that the expansions resulted in increased Medicaid coverage, although the estimates of take-up are smaller than estimates from previous research. We find little evidence of a negative relationship of any significant magnitude between eligibility for Medicaid and private coverage. We also find that children who have been eligible for Medicaid longer are more likely to be enrolled in Medicaid but no more likely to have lost private coverage. Including individual fixed effects reduces the magnitude of the estimated take-up effect, while the fixed effects estimates for the private insurance regression become negative and marginally statistically significant in some specifications. Simple dynamic models of insurance choice show that insurance choice is quite persistent. The estimated long run impact of eligibility in the dynamic models is larger than the estimate from the static models, while the immediate impact of expanded Medicaid eligibility from the dynamic models is smaller than the estimated effect from the static models.

Did Expanding Medicaid Affect Welfare Participation?

Using data from the 1988-1996 Current Population Surveys (CPS), we re-examine the evidence presented in Yelowitz (1995) showing that expansions in Medicaid eligibility for children were associated with increased labor force participation and reduced participation in Aid to Families with Dependent Children (AFDC) among single mothers. We find that Yelowitz's results were the result of two factors. First, he imposed a strong restriction on the parameter estimates that is not predicted by theory and is rejected in the CPS data. Second, he used only one of the two income tests that families must pass to be eligible for AFDC, resulting in higher imputed AFDC breakeven income levels for larger families. Once these problems are addressed, the Medicaid income limits have no significant effect on AFDC participation. The AFDC income limits, however, are significantly related to welfare and labor force participation in both his original sample and the entire 1988-1996 sample.

The Impact of Public Health Insurance on Labor Market Transitions

An often-cited difficulty with moving low-income families out of welfare and into the labor force is the lack of health insurance in many low-wage jobs. Consequently, many low-income household heads may be reluctant to leave welfare and thereby lose health insurance coverage for their children. The expansions in the Medicaid program to cover low-income children and pregnant women who are not eligible for cash benefits may help alleviate the problem by allowing disadvantaged household heads to accept jobs which do not provide health insurance. We use a discrete time (monthly) hazard rate model and data from several panels of the Survey of Income and Program Participation to assess whether expansion of public health insurance to cover children of working parents contributes to increase transitions out of welfare and into employment and reduce transitions into welfare and out of employment. We model spells in progress and spells that start during the sample separately, which allows us to assess the effect on long-term welfare recipients. We find some evidence that expanded Medicaid eligibility for children leads single mothers to exit welfare more quickly; however the effects are not robust to the inclusion of year effects. In addition, the effect appears to be strongest and most consistent among long-term recipients (as proxied by recipients who begin the sample on welfare). We find less evidence of an effect of expanded Medicaid eligibility on transitions into welfare. A somewhat surprising finding is that higher AFDC income limits also appear to have little effect on the probability of such transitions.

The Effect of Medicaid Expansions for Low-Income Children on Medicaid Participation and Private Insurance Coverage : Evidence from the SIPP

We examine Medicaid enrollment and private coverage loss following expansions of Medicaid eligibility. We attempt to replicate Cutler and GruberÂ’s (1996) results using the Survey of Income and Program Participation, and find smaller rates of take-up and little evidence of crowding out. We find that some of the difference in results can be attributed to different samples and recall periods in the data sets used. Extending the previous literature, we find that take-up is slightly increased if a childÂ’s siblings are eligible and with time spent eligible. Focusing on children whose eligibility status changes during the sample, we estimate smaller take-up effects. We find little evidence of crowding out in any of our extensions.

Estimating Heterogeneous Take-up and Crowd-Out Responses to Marginal and Non-Marginal Medicaid Expansions

We use a linear probability model with interactions and a switching probit model (SPM) to estimate heterogeneous effects of Medicaid expansions on Medicaid take-up, private insurance coverage and crowd-out. Specifically, we estimate: i) LATEs; ii) ATETs for the currently eligible; and iii) ATETs for those made eligible by a non-marginal (counterfactual) expansion in Medicaid eligibility. Both estimation methods can control for observable differences across individuals, while SPM can also control for unobservable differences. For Medicaid take-up and private insurance coverage, the effects are precisely estimated and differ dramatically across demographic groups, but this is less true for the crowd-out estimates.Medicaid expansions, take-up, crowd-out, treatment effects, switching probit model, linear probability model with interactions, counterfactual policy analysis

Caught in the Bulimic Trap? Persistence and State Dependence of Bulimia Among Young Women

Eating disorders are an important and growing health concern, and bulimia nervosa (BN) accounts for the largest fraction of eating disorders. Health consequences of BN are substantial and especially serious given the increasingly compulsive nature of the disorder. However, remarkably little is known about the mechanisms underlying the persistent nature of BN. Using a unique panel data set on young women and instrumental variable techniques, we document that unobserved heterogeneity plays a role in the persistence of BN, but strikingly up to two thirds is due to true state dependence. Our results, together with support from the medical literature, provide evidence that bulimia should be considered an addiction. Our findings have important implications for public policy since they suggest that the timing of the policy is crucial: preventive educational programs should be coupled with more intense (rehabilitation) treatment at the early stages of bingeing and purging behaviors. Our results are robust to different model specifications and identifying assumptions.bulimia nervosa, demographics, state dependence, instrumental variables, dynamic panel data estimation, addiction