(Review of Law and Economics, 2018)
This paper estimates the effect that wealth and power have on criminal justice outcomes by exploiting the random matching of drivers to pedestrians in traffic accidents. If justice is impartial, we should observe the same share of rich offenders across victims of any wealth, conditional on location and time. Rich victims act as a control group to estimate the amount of missing rich offenders for poorer victims. I use this approach on the data from Russia, and find that its justice system is not impartial. The paper contributes methodologically to the literature by causally estimating the effect of wealth on justice.
Presented at CELS (Duke), SIOE (Montréal), Tilburg Economics Seminar, EUI Applied Micro Seminar
(TILEC Discussion Paper No. DP2020-016; with Anastasia Antsygina)
Settlements among parties are usually regarded as an efficient solution to a judicial dispute. However, frequent settlements between the rich and the poor can also mean unequal access to justice. We develop a model of settlements that takes wealth disparity of the parties into account, as the defendant and the victim must expend resources in court. Richer litigants can drive a harder bargain, and achieve more favorable settlement price. There has been surprisingly little evidence of this price effect in the empirical literature, likely due to the non-random selection of cases into court or private nature of settlements. We empirically show that this price effect exists by exploiting (1) the blurred line between civil and criminal litigation in Russia; (2) traffic collisions, where parties of different wealth are matched at random; and (3) the status of policemen, whose insider knowledge make them more powerful litigants, while lacking wealth for large settlements. We find that policemen settle more (less) often as defendants (victims) than their comparable wealth group, in line with the model’s prediction. The existence of the price effect highlights institutional failures, and is especially worrying for intentional offenses.
Presented at the Micro and Macro Foundations of Conflict workshop (Bath), IOEA 2019, EconomiX Seminar (Paris Nanterre), HSE Economics Seminar (Moscow), NES Economics Brown Bag Seminar (Moscow), St Petersburg Economic Seminar (EUSP), TILEC workshop, EUI Applied Micro Seminar
(TILEC Discussion Paper No. DP2020-019; with Matteo Sostero)
Is there a racial gap in the treatment of crime victims, and when does it first occur? We provide a causal test for racial gaps in victimization and clearance rates, using the unintentional nature of vehicle-pedestrian crashes: the victim’s race should not depend on the driver’s characteristics, conditional on location and time. We find that drivers in the U.S. flee more often if they hit a black pedestrian, and the clearance rates of hit-and-run cases are lower for black victims. The evidence points to out-group bias as a mechanism, but does not exclude different expectations of punishment as another cause.
Presented at SMYE (Brussels), TxECW 2020, SEG Lunch Meeting (Tilburg), EUI Applied Micro Seminar, and Tilburg Economics Workshop
"A Simple Test for Data-Drivenness of Markets" with Tobias Klein, Jens Prüfer, and Patricia Prüfer
"Search Engines, User Information, and Quality" with Tobias Klein, Jens Prüfer, and Patricia Prüfer
Newspaper column in Vedomosti (a leading independent business newspaper in Russia): on inequality in criminal justice (2017): https://www.vedomosti.ru/opinion/articles/2017/04/06/684386-zhiguli-protiv
Newspaper column in Vedomosti, on optimal deterrence of traffic offenses (2019): https://www.vedomosti.ru/opinion/articles/2019/03/28/797581-kak-zastavit