Kosuke Uetake

A Note on Estimation of Two-Sided Matching Models

We propose an estimation strategy for two-sided matching models with non-transferable utility based on the characterization using pre-matching that exploits a fixed-point characterization of the set of stable matchings.

Signaling in Online Credit Markets

This paper studies how signaling can facilitate the functioning of a market with classical adverse selection problems. Using data from Prosper.com, an online credit market where loans are funded through auctions, we provide evidence that reserve interest rates that borrowers post can serve as a signaling device. We then develop and estimate a structural model of borrowers and lenders where low reserve interest rates can credibly signal low default risk. Announcing a high reserve interest rate increases the probability of receiving funding at the cost of higher expected interest payments conditional on obtaining a loan. Borrowers regard this trade-off differentially, which results in a separating equilibrium. Using the estimated parameters of the model, we compare the credit supply curve and welfare under three alternative market designs in our counterfactual policy experiment -- a market with signaling, a market without signaling, and a market with no asymmetric information. We find that the cost of adverse selection can be as much as 16% of the total surplus created under no asymmetric information, up to 95% of which can be restored with signaling. We also estimate the credit supply curves for each of the three market designs and find backward-bending supply curves for some of the markets, consistent with the prediction of Stiglitz and Weiss (1981).

Estimating Supermodular Games Using Rationalizable Strategies

We propose a set-estimation approach to supermodular games using the restrictons of rationalizable strategies, which is a weaker solution concept than Nash equilibrium. The set of rationalizable strategies of a supermodular game forms a complete lattice, and are bounded above and below by two extremal Nash equilibria. We use a well-known alogrithm to compute the two extremal equilibria, and then construct moment inequalities for set estimation of the supermodular game. Finally, we conduct Monte Carlo experiments to illustrate how the estimated confidence sets vary in response to changes in the data generating process.

Strategic Network Formation and Performance in the Venture Capital Industry

I investigate the network structure of venture capitalists based on co-investments, and the effects of network structure on investment performance. As venture capitalists select their partners, network structure is endogenously determined in equilibrium. Using comprehensive data on venture capital firms in the U.S., I jointly estimate a model of strategic network formation and a performance equation, taking endogeneity of network structure into account. In the estimation of the strategic network formation model, instead of imposing an equilibrium selection rule, I exploit the partial identification approach. My estimation strategy relies only on the necessary conditions of pairwise stability and is computationally feasible. I find that the network of venture capitalists tends to be homophilous in terms of asset size, but anti-homophilous in terms of investment experience and industry expertise. Moreover, I fi nd that not taking the endogeneity into account results in signi ficant overestimates of the effects of the network structure on investment performance. Lastly, I conduct a counterfactual policy experiment in which the government makes direct investment into the market by establishing a venture capital firm. I examine the effects of the additional venture capital fi rm on equilibrium network structure and investment performance.

Harnessing the Small Victories: Empirical Evidence from a Calorie and Weight Loss Tracking Application

We investigate the role of short-term goal achievement on long-term goal achievement under the context of weight loss. Using unique and large-scale data from a freemium mobile weight management application (Lose It!), we track the daily dynamics of weight loss across a large number of users. The application sets a salient daily budget for calories, and by comparing cases in which the user is slightly under or over-budget, we provide a causal link between short-term goal achievement and long-term outcomes such as future weight loss, achievement of goal weight, and setting of more ambitious weight loss targets. Short-term goal achievement also have implications on future customer development as staying within the daily budget leads to an increase in premium account upgrades. Furthermore, we show that the impact of short-term goal achievement varies across user segments. We later demonstrate using a dynamic regression discontinuity design that the short-term goal achievement effects persist over time, and in fact, induce users to accomplish even more ambitious short-term goals in the future. Finally, estimates from a dynamic structural model of calories management reveal that users receive positive utility from past short-term goal accomplishments, and counterfactual analysis with the estimated model quantify the long-run user benefits of various hypothetical policies that adjust the daily budget of calories.

Taxation and Market Power in the Legal Marijuana Industry

In 2012 the state of Washington created a legal framework for production and retail sales of marijuana. Nine other U.S. states and Canada have followed. These states hope to generate tax revenue for their state budgets while limiting harms associated with marijuana consumption. We use a unique administrative dataset containing all transactions in the history of the industry in Washington to evaluate the effectiveness of different tax and regulatory policies under consideration by policymakers and study the role of imperfect competition in determining these results. We examine 3 main research questions. First, how effective is Washington’s excise tax at raising revenue? With the nation’s highest tax rate on marijuana, is Washington maximizing revenue or potentially overtaxing, leading to reduced legal sales and lower tax revenue. Second, what is the incidence of taxes in this industry? Finally, most states have restricted entry, resulting in firms with substantial market power. What is the role of imperfect competition in studying these basic questions on tax policy? We combine structural methods and a reduced form sufficient statistic approach to show a number of results. First, Washington’s 37% excise tax is still on the upward sloping portion of the Laffer curve and state revenue could be substantially higher with a higher tax rate. The amount of revenue generated by a tax increase is significantly larger due to retailer market power than it would be under perfect competition. In addition, these taxes are primarily borne by consumers and not by firms, and there is a large social cost associated with each dollar raised.

Multidimensional Sales Incentives in CRM Settings: Customer Adverse Selection and Moral Hazard

In many firms, incentivized salespeople with private information about their customers are responsible for customer relationship management (CRM). Private information can help the firm by increasing sales efficiency, but it can also hurt the firm if salespeople use it to maximize own compensation at the expense of the firm. Specifically, we consider two negative outcomes due to private information — ex-ante customer adverse selection at the time of acquisition and ex-post customer moral hazard after acquisition. This paper investigates potential positive and negative responses of a salesforce to managerial levers — multidimensional incentives for acquisition and retention performance and job transfers that affect the level of private information. Salespeople are responsible for managing customer relationships and compensated through multidimensional performance incentives for customer acquisition and maintenance at many firms. This paper investigates how a salesperson’s private information on customers affect their response to multiple dimensions of incentives. Using unique matched panel data that links individual salesperson performance metrics with customer level loans and repayments from a microfinance bank, we find that sales people indeed possess private information that is not available to the firm. Salespeople use the private information to engage in adverse selection of customers in response to acquisition incentives. Customer maintenance incentives serve a dual purpose; they not only reduce loan defaults, but also moderate adverse selection in customer acquisition. Transfers that eliminate private information reduces the adverse selection effects of acquisition incentives, but increase loan defaults — customer moral hazard. Despite the potential negative adverse selection effects due to private information, the effort increasing effect of each of the three dimensions of sales management we investigate — acquisition incentive, maintenance incentive and transfers all have a net positive effect on firm value. Methodologically, the paper introduces an identification strategy to separate customer adverse selection and customer moral hazard (loan repayment), by leveraging the multidimensional incentives of an intermediary (salesperson) responsible for both customer selection and repayment with private information about customers.