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The identification of average causal effects of a treatment in observational studies is typically based either on the unconfoundedness assumption or on the availability of an instrument. When available, instruments may also be used to test for the unconfoundedness assumption (exogeneity of the treatment). In this paper, we define variables which we call quasi-instruments because they allow us to test for the unconfoundedness assumption although they do not necessarily yield nonparametric identification of the average causal effect. A quasi-instrument is defined as an instrument except for that its relation to the treatment is allowed to be confounded by unobservables, thereby resulting in a wider range of potential applications. We propose a test for the unconfoundedness assumption based on a quasi-instrument, and give conditions under which the test has power. We perform a simulation study and apply the results to a case study where the interest lies in evaluating the effect of job practice on employment.

Sweden has obligatory sickness and disability insurance which is both financed (from payroll taxes) and administrated by the government. In order to receive sickness benefits, insured individuals must have certificates issued by a medical doctor. Since health care is administrated at the county level, this means that monitoring is, to some extent, decentralized at a lower jurisdictional level than the funding and governance of the insurance. This paper studies one consequence of such decentralization: the effet on individual sickness absence when such certificates are not approved be the Sickness Insurance Agency (SIA) and are instead re-remitted to the doctor completion and, potential, reapproval by the SIA. We find that this re-remission increases the length of sickness absence spells by an average of 30 percent. A suggestive test of the reason for the observed effect indicates that it is due to a decrease in health caused by increased stress related to the uncertainty about entitlement and future sickness benefits. Given that added resorces improve the quality of the patients' medical certificates, directed intergovernmental grants from the state to the counties would be cost saving.

Objective:In this article, we estimate the effect of a multidisciplinary collaborationprogram on the length of sickness absence. The intention with the programwas to avoid long-term sickness absence by providing an early and holistic evaluation of the sick-listed individuals' conditions. The target group was individuals who were at risk of becoming long-term sick. The eligibility criteria were mainly based on register information that we have access to.Methods:Using this register information, we estimate different Cox regression models and apply a nonparametric matching estimator. We have also conducted a small randomized experiment.Results:The result from the randomized experiment is not statistically significant, but the point estimate provides the same result as was found in the observational study: The program prolongs rather than shortens the sickness absence spell. That is, the average sickness absence spell is prolonged by about 3 months.Conclusions:Our main explanation for this discouraging result is that the team focuses too much on rehabilitation rather than encouraging the sick-listed individual to return to work.

The labor market integration of immigrants is a top political priority throughout the Organization for Economic Cooperation and Development (OECD) countries. Social and fiscal gains, as well as sustained future labor supply make governments search for effective policies to increase employment among the mostly disadvantaged. The author studies SIN, a Swedish pilot workplace introduction program targeting these groups, using very detailed individual data and allowing for effects through several channels. The results show increased transitions from unemployment to work experience schemes and improved future employment probabilities for those who entered these schemes. A rough calculation suggests that each job year created cost about Euro 30,000.

We evaluate an immigrant workplace introduction program aimed at helping individuals considered employable but at the same time expected to experience substantial difficulties in finding work. Using supported employment methods, the SIN program may influence outcomes through several channels. We use in-dividual data and a difference-in-differences approach to estimate the effects of the program. The results suggest that the program increased transitions from unemployment to work experience schemes, and improved future employment probabilities for those who entered these schemes.

This paper discusses the evaluation problem using observational data when the timing of treatment is an outcome of a stochastic process. We show that the duration framework in discrete time provides a fertile ground for effect evaluations. We suggest easy-to-use nonparametric survival function matching estimators. These estimators can be used to estimate the time profile of the treatment. We apply one of the estimators to evaluate the effects of an employment subsidies program. The longer run program effects are positive. The estimated time profile suggests locking-in effects while participating in the program and a big upward jump in the employment hazard upon program completion.

Using a unique micro panel data set we investigate whether active labor market programs improve employment prospects and increase mobility in the longer run. We consider two prototype programs: job creation programs and training programs. We find that both programs reduce the chances of finding a job substantially. Moreover, both programs are associated with a locking-in e.ect: the probability of finding a job outside the home region decreases after program participation. However, this e.ect appears to stem exclusively from the decrease in the overall job finding rate.