Understanding whether, and in what situations, time spent in prison is criminogenic or preventive has proven challenging due to data availability and correlated unobservables. This paper overcomes these challenges in the context of Norway's criminal justice system, offering new insights into how incarceration affects subsequent crime and employment. We construct a panel dataset containing the criminal behavior and labor market outcomes of the entire population, and exploit the random assignment of criminal cases to judges who differ systematically in their stringency in sentencing defendants to prison. Using judge stringency as an instrumental variable, we find that imprisonment discourages further criminal behavior, and that the reduction extends beyond incapacitation. Incarceration decreases the probability an individual will reoffend within 5 years by 27 percentage points, and reduces the number of offenses over this same period by 10 criminal charges. In comparison, OLS shows positive associations between incarceration and subsequent criminal behavior. This sharp contrast suggests the high rates of recidivism among ex-convicts is due to selection, and not a consequence of the experience of being in prison. Exploring factors that may explain the preventive effect of incarceration, we find the decline in crime is driven by individuals who were not working prior to incarceration. Among these individuals, imprisonment increases participation in programs directed at improving employability and reducing recidivism, and ultimately, raises employment and earnings while discouraging further criminal behavior. Contrary to the widely embraced 'nothing works' doctrine, these findings demonstrate that time spent in prison with a focus on rehabilitation can indeed be preventive.

Despite a broad consensus on the need to take into account the value of public services in distributional analysis, there is little reliable evidence on how the inclusion of such non-cash income actually affects poverty and inequality estimates. In particular, the equivalence scales applied to cash income are not necessarily appropriate when including noncash income, because the receipt of public services is likely to be associated with particular needs. In this paper, we propose a theory-based framework designed to provide a coherent evaluation of the distributional impact of local public services. The valuation of public services, identification of target groups, allocation of expenditures to target groups, and adjustment for differences in needs are derived from a model of local government spending behaviour. Using Norwegian data from municipal accounts and administrative registers we find that the inclusion of non-cash income reduces income inequality by about 15 percent and poverty rates by almost one-third. However, adjusting for differences in needs for public services across population subgroups offsets about half the inequality reduction and some of the poverty decrease.

What do the education premiums look like over the life cycle? What is the impact of schooling on lifetime earnings? How does the internal rate of return compare with opportunity cost of funds? To what extent do progressive taxes attenuate the incentives to invest in education? This paper exploits Norwegian population panel data with nearly career long earnings histories to answer these important questions. We provide a detailed picture of the causal relationship between schooling and earnings over the life cycle, following individuals over their working lifespan. To account for endogeneity of schooling, we apply three commonly used identification strategies. Our estimates show that additional schooling gives higher lifetime earnings and steeper age-earnings profile, in line with predictions from human capital theory. These estimates imply an internal rate of return of around 10 percent, after taking into account income taxes and earnings-related pension entitlements. Under standard conditions, this finding suggests it was financially profitable to take additional schooling because the rates of return were substantially higher than the market interest rates. By comparison, Mincer regressions understate substantially the rates of return. We explore the reasons for this downward bias, finding that it is driven by Mincer's assumptions of no earnings while in school and exogenous post-schooling employment. JEL classification: J24, J31