We study from both a theoretical and an empirical perspective how a network of military alliances and enmities affects the intensity of a conflict. The model combines elements from network theory and from the politico-economic theory of conflict. We obtain a closed-form characterization of the Nash equilibrium. Using the equilibrium conditions, we perform an empirical analysis using data on the Second Congo War, a conflict that involves many groups in a complex network of informal alliances and rivalries. The estimates of the fighting externalities are then used to infer the extent to which the conflict intensity can be reduced through (i) dismantling specific fighting groups involved in the conflict; (ii) weapon embargoes; (iii) interventions aimed at pacifying animosity among groups. Finally, with the aid of a random utility model, we study how policy shocks can induce a reshaping of the network structure.

A growing number of school districts use centralized assignment mechanisms to allocate school seats in a manner that reflects student preferences and school priorities. Many of these assignment schemes use lotteries to ration seats when schools are oversubscribed. The resulting random assignment opens the door to credible quasi-experimental research designs for the evaluation of school effectiveness. Yet the question of how best to separate the lottery-generated randomization integral to such designs from non-random preferences and priorities remains open. This paper develops easily-implemented empirical strategies that fully exploit the random assignment embedded in a wide class of mechanisms, while also revealing why seats are randomized at one school but not another. We use these methods to evaluate charter schools in Denver, one of a growing number of districts that combine charter and traditional public schools in a unified assignment system. The resulting estimates show large achievement gains from charter school attendance. Our approach generates efficiency gains over ad hoc methods, such as those that focus on schools ranked first, while also identifying a more representative average causal effect. We also show how to use centralized assignment mechanisms to identify causal effects in models with multiple school sectors.

We investigate systematic changes in corporate effective tax rates over the past 25 years and find that effective tax rates have decreased significantly. Contrary to conventional wisdom, the decline in effective tax rates is not concentrated in multinational firms; effective tax rates have declined at approximately the same rate for both multinational and domestic firms. Moreover, within multinational firms, both foreign and domestic effective rates have decreased. Finally, changes in firm characteristics and declining foreign statutory tax rates explain little of the overall decrease in effective rates.

Accountants examine multiple indicators when assessing whether individual assets are impaired. Different indicators predict cash flows over varying time horizons, and their importance varies with how far into the future individual assets are expected to generate cash flows. We predict that earnings exhibits asymmetric timeliness with respect to multiple indicators, including stock return, sales change, and operating cash flow change, which differentially explain write-downs of current assets, long-lived tangible assets, and indefinite-lived goodwill. We predict an interaction effect between indicators, such that the total impact of several consistent indicators is greater than the sum of their individual impacts. Empirical estimates for U.S. firms are consistent with our predictions and yield new insights about the effects of multiple indicators for both conservatism and impairment research. Our multi-indicator asymmetric models also change inferences about the relative explanatory power of economic factors versus reporting incentives in asset impairments.

An extensive literature examines the causes and effects of financial misconduct based on samples drawn from four popular databases that identify restatements, securities class action lawsuits, and Accounting and Auditing Enforcement Releases (AAERs). We show that the results from empirical tests can depend on which database is accessed. To examine the causes of such discrepancies, we compare the information in each database to a detailed sample of 1,243 case histories in which regulators brought enforcement actions for financial misrepresentation. These comparisons allow us to identify, measure, and estimate the economic importance of four features of each database that affect inferences from empirical tests. We show the extent to which each database is subject to these concerns and offer suggestions for researchers using these databases.

Many school and college admission systems use centralized mechanisms to allocate seats based on applicant preferences and school priorities. When tie-breaking uses non-randomly assigned criteria like distance or a test score, applicants with the same preferences and priorities are not directly comparable. The non-lottery setting does generate a kind of local random assignment that opens the door to regression discontinuity designs. This paper introduces a hybrid RD/propensity score empirical strategy that exploits quasi-experiments embedded in serial dictatorship, a mechanism widely used for college and selective K-12 school admissions. We use our approach to estimate achievement effects of Chicago's exam schools.