Working papers results
We study mean-variance approximations for a large class of preferences. Compared to the standard mean-variance approximation that only features a risk variability term, a novel index of variability appears. Its neglect in an empirical estimation may result in puzzling in ated risk terms of standard mean-variance approximations.
We consider a model of a limit order book and determine the optimal tick size set by a social planner who maximizes the welfare of market participants. In a 2-period model where only two agents arrive sequentially, the tick size is a friction that constrains investors to use discrete price grids, and as a consequence the optimal tick size is equal to zero. However, in a model with sequential arrival of more than two investors who can endogenously either take liquidity or supply liquidity by undercutting or queuing behind existing orders, the tick size is positive: it is a strategic tool a social planner uses to optimally affect the choice made by investors between liquidity demand and supply. In addition, the optimal tick size is a function both of the value of the asset and of trading volume. The policy implication of such findings is that the European tick size regime and the “Intelligent Ticks” Nasdaq proposal dominate Reg. NMS Rule 612 that formalizes the tick size regime for the U.S. markets. Using data from the U.S. and the European markets we test our model’s empirical predictions.
Why, in the face of scandals and misbehaviors, do partisan supporters hardly change their minds about their favored candidates? We study individuals’ online engagement with negative news on candidates in the 2016 US Presidential Election. Compared to independents, partisan users avoid commenting bad news on their favorite candidate, but seek them on its opponent, a political “ostrich effect”. When they do comment on bad news about their candidate, they try to rationalize them, display a more negative sentiment, and are more likely to cite scandals of the opponent. This behavior is consistent with the predictions of a model of online interactions where paying attention to non-consonant news is emotionally or psychologically costly, while paying attention to consonant ones is pleasing. Because users enjoy receiving positive feedback on their views, intrinsic biases that drive ideological segregation are amplified on social media.
We explore how business groups use internal labor markets (ILMs) in response to changing economic conditions. We show that following the exit of a large industry competitor, groupaffiliated firms expand and gain market share by increasing their reliance on the ILM to ensure swift hiring, especially of technical managers and skilled blue collar workers. The ability to take advantage of this shock to growth opportunities is greater in firms with closer access to their affiliates’ human capital, as geographical proximity facilitates employee relocations across units. Overall, our findings point to the ILM as a prominent mechanism making affiliation with a business group valuable at times of change. For the ILM to perform its role in the face of industry shocks, group sectoral diversification must be combined with geographical proximity between affiliates.
We study the implications of employment targets on firm dynamics during the privatization of the East German economy. Exploiting novel contract-level data, we document three stylized facts. First, the policy distorted firm size choices and generated bunching of firms around their committed employment target. Second, exploiting heterogeneous labor preferences of privatizers, we show that assigning tight commitments to firms causes an increase in employment growth and leads to higher productivity growth. Finally, tighter commitments also result in significant costs by leading to increased firm exit. We interpret these results through the lens of a dynamic model with endogenous productivity growth at the firm level. The model highlights that while tight commitments distort the employment decision statically and lead to a higher exit probability, they also induce a “catch-up” increase in productivity growth. This is because although firm profits are lower under tight commitments, marginal profits with respect to productivity are higher. We calibrate the model to our data and find that the policy lead to a 3 percentage points higher aggregate TFP growth thanks to the productivity improvements of firms with tight contracts.
We investigate the impact of prices on ratings using Airbnb data. We theoretically illustrate two opposing channels: higher prices reduce the value for money, worsening ratings, but they increase the taste-based valuation of the average traveler, improving ratings. Results from panel regressions and a regression discontinuity design suggest a dominant value-for-money effect. In line with our model, hosts strategically complement lower prices with higher effort more when ratings are relatively low. Finally, we provide evidence that, upon entry, strategic hosts exploit the dominant value-for-money effect. The median entry discount of seven percent improves medium-run monthly revenues by three percent.