برآورد اثر جبران خسارت بیمه بیکاری در تاریخ بازار نیروی کار کارگران آواره

In this paper US data on labor market histories of displaced workers are used to quantify the effect of unemployment insurance compensation (UIC) on both unemployment and employment durations. This results in the first available assessment of the effect that UIC has on the fraction of time spent employed. The estimation procedure simultaneously allows for unobserved heterogeneity, defective risks and sample selection into future spells, and uses alternative assumptions about agents’ knowledge of the UIC eligibility rules. Being entitled to UIC shortens workers’ employment durations. This negative effect on the fraction of time spent employed could be offset by suspending an extended benefits program in order to shorten unemployment durations.

While there have been numerous studies estimating the effect of unemployment insurance compensation (UIC) on duration of unemployment, there has been no empirical work analyzing the effect of UIC on employment durations in the United States. 2 This gap in the literature is somewhat surprising since there are at least two theoretical arguments for why we would expect UIC to affect employment durations. First, the implicit contract literature suggests that unemployment insurance makes layoffs more likely (e.g., Feldstein, 1976; Baily, 1977). Second, job search models suggest that workers with generous UI coverage will search less intensively while unemployed. As we discuss in Section 3, one can show that the optimal firm response to this behavior, in the presence of demand fluctuations and firm specific human capital, is for the firm to lay off workers with high levels of UI entitlement and recall workers as they approach exhaustion of their benefits.In this paper we therefore quantify the effect of UIC on both unemployment inflow and outflow using a micro data set on labor market histories of US workers. As a result, we obtain the first available assessment of the effect UIC has on the fraction of time spent employed. Relaxing the steady state assumption used above, we quantify the overall effect of UIC by simulating the process of finding and losing jobs for all individuals in our data under different levels of UIC. The lack of research on the UIC employment duration effect is likely caused by the fact that large micro data sets on employment durations and UI compensation are scarce. We use a data set which consists of a dislocated workers’ survey, augmented with information on the amount of UI compensation individuals can expect to receive if they are laid off or quit. Unemployment compensation provisions, including the trigger dates of various extended benefit programs, are coded for over 5 years for seven states. The resulting multiple-spell, event-history data set is unusually rich in terms of the variation of entitlement and benefit levels. The use of hazard models in analyzing duration data has become widespread, and accounting for unobserved heterogeneity is now a standard part of hazard estimation sensitivity analysis. The estimation procedure used here allows for the effects of unobserved heterogeneity in a number of ways and controls for sample selection into multiple spells, a potentially important issue in the estimation of duration models: Using multiple-spell data on employment and unemployment durations provides greater variation and improves identification of the unobserved heterogeneity distribution (Heckman and Singer, 1984). The use of this type of data, however, also raises the possibility of selection bias: i.e., the workers who have multiple employment spells may be a non-random sample. To control for this problem, we estimate employment and unemployment durations jointly while allowing the unobserved heterogeneity to be correlated across these spells.3 The estimation of employment duration effects of UIC also requires a separate focus on different ways of exiting an employment spell. A worker who quits will generally not be entitled to UI compensation. In the presence of a positive layoff probability, delaying a quit to non-employment will provide the worker with a chance of getting laid off and obtaining UI coverage. Thus, one may expect the opposite entitlement effects when comparing layoff and quit decisions, which motivates a separate analysis of quits and layoffs in a competing risk duration model. The richest estimated model is therefore a multiple-spell, multiple-state competing risk duration model with unobserved heterogeneity. Finally, the estimated unobserved heterogeneity models naturally extend to account for the possibility of defective risks (zero probability of a quit for a fraction of the sample). The theory modeling worker (firm) response to UIC is forward-looking: it evaluates future streams of income (profit). The nature of the UIC system, however, makes it hard to predict future level and availability of UIC, which depend on individual labor market histories as well as on the evolution of the labor market. Any attempt to evaluate the effects of UIC on economic outcomes therefore has to rely on arbitrary assumptions about how agents form expectations of the available UI compensation.4 In this paper, we examine the robustness of the empirical results with respect to different assumptions about how firms and workers account for UIC rules when determining eligibility for future UI claims. This issue has not been addressed previously. The type of assumption one makes in the estimation significantly affects the levels of the explanatory variable of interest-UI entitlement. In the empirical analysis we therefore compare results based on the assumption that future UI eligibility is ignored to results based on the assumption that future UI eligibility is taken into account. The empirical results suggest that being entitled to UI compensation significantly increases the layoff hazard (defined as the probability of getting laid off in a given week conditional on being employed up to that week). In contrast to theoretical prediction, however, neither the length of potential UI entitlement nor the dollar amount of UI benefits, conditional on being positive, affect the layoff hazard. The quit hazard is not affected by any of the UI system parameters. Findings on the UI effect on unemployment outflow are in accord with the existing literature. To measure the magnitude of the estimated UIC effects, we study the fraction of time (sampling frame) spent in employment under various policy experiments. This exercise suggests that the positive UIC layoff effect, which shortens employment durations and lowers the fraction of time spent employed, could (roughly) be offset by shortening of unemployment durations corresponding to suspending an extended benefits program. (See Section 4 for definitions of extended benefits programs.) The paper proceeds as follows. Section 2 discusses previous work and Section 3 models firm employment decisions. The data set is described in Section 4. Section 5 presents the econometric approach together with the empirical results. Section 6 concludes.

Empirical evidence on the effect of UI coverage on employment durations is scarce. This gap in the literature is a potential source of underestimation of the total impact of UIC on labor market histories. We employ methods similar to those used in the unemployment duration literature to examine how the UI system affects duration of employment. Unemployment and employment spells are analyzed jointly in order to control for selection into multiple spells. This also allows for assessing the UIC effect on the fraction of time spent in employment. The empirical results suggest that eligibility for UI compensation significantly raises the probability of a layoff. Conditional on eligibility, however, neither the length nor the dollar amount of the UI compensation to which workers are entitled appear to affect the risks of layoff. No aspect of UI affects the probability of a quit in any of the estimated specifications. Further, we find a relatively small effect of sample selection. This finding is reassuring for empirical applications which use multiple spell unemployment data to estimate the effect of the UI system on outflow from unemployment (e.g., Ham and Rea, 1987). Our most general heterogeneity specification also allows for the possibility of defective risks, an important consideration when the probability of a particular type of exit is very low for a fraction of the sample, as is the case with quits in the current study. Finally, the sensitivity analysis focuses on how different assumptions about the ability of firms and workers to impute available UI compensation affect the estimation. Our theoretical model predicts that the layoff probability should increase with the length of available UI entitlement. While the empirical results confirm that entitlement eligibility is positively related to the layoff risks, we do not find important effects of the length of UI entitlement on layoffs conditional upon being eligible. This inconsistency with the theoretical model might be due to (i) agents’ inability to correctly impute the level of available UI entitlement, in which case they could base their decisions on the simpler criterion of eligibility; and (ii) an imprecise modeling of the structure of the layoff costs. Moreover, our results conflict with those of Anderson and Meyer (1994), who use quarterly data to estimate the probability of a layoff as a function of the firm's experience rating and the available UI compensation. They find a significantly positive effect of UI benefits, but a negative or insignificant entitlement effect. Their results are, however, very sensitive to dealing with the person-specific unobservables. This study differs from Anderson and Meyer (1994) in that it uses event-history models on weekly data, and thus controls for duration dependence, monthly changes in demand, and sample selection in a coherent statistical framework.45 Both the conflicting theoretical and empirical results call for further analysis of the layoff impact of UI. Such research should focus on the agents’ forecasting abilities as well as on the structure of the layoff costs, and ideally use large and more representative data sets.46 The simulation evidence presented in this paper points to the importance of capturing the UIC effect on both duration and occurrence of spells. If we consider the fraction of time spent employed as the proper measure of the UIC effects, the simulations suggest that the UIC eligibility effect of shortening employment durations is roughly comparable in size (but opposite in sign) to the effect of suspending (triggering off ) an extended benefits program for all workers in the sample on shortening unemployment durations.