Many studies use matched employer-employee data to estimate a statistical model of earnings determination with worker and firm fixed effects. Estimates based on this model have produced influential yet controversial conclusions. The objective of this paper is to assess the sensitivity of these conclusions to the biases that arise because of limited mobility of workers across firms. We use employer-employee data from the United States and several European countries while taking advantage of both fixed effects and random effects methods for bias correction. We find that limited mobility bias is severe and that bias correction is important.

We show how a discrete instrument can be used to identify the marginal treatment effects under a functional structure that allows for treatment heterogeneity among individuals with the same observed characteristics and self-selection based on the unobserved gain from treatment. Guided by this identification result, we perform a marginal treatment effect analysis of the interaction between the quantity and quality of children. Our estimates reveal that the family size effects vary in magnitude and even sign and that families act as if they possess some knowledge of the idiosyncratic effects in the fertility decision.

We develop, identify, and estimate a model of imperfect competition in both labor and product markets. Our context is the US construction industry, where firms compete for workers, private market projects, and government procurements. Our empirical approach leverages bidding data from procurement auctions linked to employer-employee tax records. We find imperfect competition in both markets generates a total wage markdown of more than 30 percent and a total price markup of around 45 percent. By contrast, if one erroneously assumed a perfectly competitive product (labor) market, then one would conclude wages (prices) are marked down (up) by only 20 percent (16 percent).

There is no evaluation of the consequences of Disability Insurance (DI) receipt that captures the effects on households’ net income and consumption expenditure, family labor supply, or benefits from other programs. Combining detailed register data from Norway with an instrumental variables approach based on random assignment to appellant judges, we comprehensively assess how DI receipt affects these understudied outcomes. To consider the welfare implications of the findings from this instrumental variables approach, we estimate a dynamic model of household behavior that translates employment, reapplication, and savings decisions into revealed preferences for leisure and consumption. The model-based results suggest that on average, the willingness to pay for DI receipt is positive and sizable. Because spousal labor supply strongly buffers the household income and consumption effects of DI allowances, the estimated willingness to pay for DI receipt is smaller for married than single applicants.

The influence of peers could play an important role in the take up of social programs. However, estimating peer effects has proven challenging given the problems of reflection, correlated unobservables, and endogenous group membership. We overcome these identification issues in the context of paid paternity leave in Norway using a regression discontinuity design. We find strong evidence for substantial peer effects of program participation in both workplace and family networks. Coworkers and brothers are 11 and 15 percentage points, respectively, more likely to take paternity leave if their peer was exogenously induced to take up leave. The most likely mechanism is information transmission about the costs and benefits of taking paternity leave, including increased knowledge of how an employer will react. The estimated peer effect snowballs over time, as the first peer interacts with a second peer, the second peer interacts with a third peer, and so on. This leads to long-run participation rates which are substantially higher than would otherwise be expected.

We investigate the existence and importance of family welfare cultures, where the receipt of a welfare program by one generation causes increased participation in the next generation. Our context is Norway’s disability insurance (DI) system. To overcome the challenge of correlated unobservables across generations, we take advantage of random assignment of judges to DI applicants whose cases are initially denied. Some appeal judges are systematically more lenient, which leads to random variation in the probability a parent will be allowed DI. Using this exogenous variation, we find strong evidence for a causal link across generations: when a parent is allowed DI at the appeal stage, their adult child’s participation over the next five years increases by 6 percentage points. This effect grows over time, rising to 12 percentage points after 10 years. Although these findings are specific to our setting, they highlight that welfare reforms can have long-lasting effects on program participation, since any original effect on the current generation could be reinforced by changing the participation behavior of their children as well. The detailed nature of our data allows us to compare the intergenerational transmission with spillover effects in other networks and to explore mechanisms.

Using a random judge design and panel data from Norway, we estimate that imprisonment discourages further criminal behavior, with reoffense probabilities falling by 29 percentage points and criminal charges dropping by 11 over a 5-year period. Ordinary least squares mistakenly reaches the opposite conclusion. The decline is driven by individuals not working prior to incarceration; these individuals increase participation in employment programs and raise their future employment and earnings. Previously employed individuals experience lasting negative employment effects. These findings demonstrate that time spent in prison with a focus on rehabilitation can be preventive for a large segment of the criminal population.

It is often desired to rank different populations according to the value of some feature of each population. For example, it may be desired to rank neighbourhoods according to some measure of intergenerational mobility or countries according to some measure of academic achievement. These rankings are invariably computed using estimates rather than the true values of these features. As a result, there may be considerable uncertainty concerning the rank of each population. In this paper, we consider the problem of accounting for such uncertainty by constructing confidence sets for the rank of each population. We consider both the problem of constructing marginal confidence sets for the rank of a particular population as well as simultaneous confidence sets for the ranks of all populations. We show how to construct such confidence sets under weak assumptions. An important feature of all of our constructions is that they remain computationally feasible even when the number of populations is very large. We apply our theoretical results to re-examine the rankings of both neighbourhoods in the U.S. in terms of intergenerational mobility and developed countries in terms of academic achievement. The conclusions about which countries do best and worst at reading, math, and science are fairly robust to accounting for uncertainty. The confidence sets for the ranking of the fifty most populous commuting zones by measures of mobility are also found to be small. These confidence sets, however, become much less informative if one includes all commuting zones, if one considers neighbourhoods at a more granular level (counties, census tracts), or if one uses movers across areas to address concerns about selection.

We study the effects of broadband internet use on the investment decisions of individual investors. A public program in Norway provides plausibly exogenous variation in internet use. Our instrumental variables estimates show that internet use causes a substantial increase in stock market participation, driven primarily by increased fund ownership. Existing investors tilt their portfolios toward funds, thereby obtaining more diversified portfolios and higher Sharpe ratios, and do not increase their trading activity in stocks. Overall, access to high‐speed internet spurs a “democratization of finance,” with individuals making investment decisions that are more in line with the advice from portfolio theory.