Browsing by Author "Tang, Xun"

Now showing 1 - 12 of 12
  • Thumbnail Image
    Item
    Delegation, Agency and Competitive Representation
    (2015-08-12) Atanasov, Iliya; Stevenson, Randolph T.; Hamm, Keith E.; Dobelman, John; Martin, Lanny; Tang, Xun
    Traditional agency models focus on the conceptual line of delegation running from principal to agent. The more information about agents’ preferences and actions, the better able the principals to use selection and sanctioning to achieve desirable outcomes. Following this conventional wisdom, institutional transparency is viewed as an unequivocal good and representative democracy as built on delegation and control. However, this is an incomplete picture at best. Game-theoretic and case analysis shows that the elevation of the elected European Parliament as a legislative chamber coequal to the intergovernmental Council of the European Union may be a ruse to undermine lobbyist influence by diluting formal responsibility. Less transparency in decision-making may help align EU policy closer to broader societal objectives. The Commission, perhaps most heavily influenced by special interests, and not Council has lost clout in the legislative process as a result of the changes. In several generalized noncooperative formal settings with information asymmetries, delegation can work for principals only if the set of potential agents is diverse. Not only does selection dominate sanctioning as a control mechanism, but the very existence of compliance equilibria is contingent upon the a priori arrangement of candidate agents’ policy preferences relative to one another and to the principals’. The principal–agent relationship is dependent on and may be only secondary to between-agent competition. This insight has far-reaching implications for a number of research programs within political science. Schumpeter viewed modern democracy as a system where elites compete for the support of the masses. This conceptualization suggests a new path towards sustainable democratization. Building elite capacity in undemocratic conditions through institutionalized, if unfair, competition may be a more effective approach than parachuting fully democratic institutions in an unreceptive environment. Empirical analysis of over two hundred years of data shows that states with competitive political institutions, regardless of whether those are democratic, are most likely to develop and sustain full-fledged democracy.
  • Thumbnail Image
    ItemEmbargo
    Essays in Education Economics and Family Economics
    (2024-04-18) Hu, Qinyou; Cunha, Flavio; Calvi, Rossella; Tang, Xun; Perrigne, Isabelle; Thirkettle, Matthew; Fiel, Jeremy
    This dissertation contains three chapters in the fields of development economics and labor economics. In the first chapter, I highlight the social impact of empathy on school bullying reduction. I collect unique data by conducting a randomized control trial---a parent-directed empathy education intervention in middle schoolers in China. Program evaluation shows it reduces bullying by indirectly changing the network structure, making bullies less popular in the classrooms. I estimate a unified framework incorporating an empathy production function, a network formation model, and a social interaction model of the final bullying outcomes. I find that the social channel of empathy accounts for almost half of its human capital effect. Policy counterfactuals suggest that targeting bullies’ friends is more effective than targeting bullies directly. The second chapter (co-authored with Flavio Cunha, Yiming Xia, and Naibao Zhao) provides the context and a comprehensive introduction to the empathy intervention program. The program leads to more parental investment and higher empathy levels. Using a state-of-the-art generalized random forest method, we find more reductions in bullying for those with lower parental investment and academic stress. Cost analysis shows that reducing one bullying incident costs $16.30 for the intervention, suggesting a scalable and low-cost strategy to inform public policy on bullying prevention in other similar settings. In the third chapter, I develop a new approach to identify intrahousehold resource allocation and the extent of joint consumption for extended families using a collective household model. It allows for endogenous living arrangement decisions with fewer data requirements. Application to nationally representative household survey data in China reveals that the elderly are allocated the least resource shares, and women tend to be more altruistic in consumption sharing than men. I also confirm that co-residence households enjoy economic efficiency gains compared to nuclear households, but there is still room for explanations on why multi-generations choose to live together.
  • Thumbnail Image
    Item
    Essays in Empirical Industrial Organization and Financial Economics
    (2021-12-02) Amani Hamedani, Mahya; Tang, Xun
    This dissertation is composed of three essays in Empirical Industrial Organization and Financial Economics. The first essay, titled “Non-Compete Agreements in the Investment Advisory Industry,” studies how labor mobility constraints affect competition in the US investment advisory industry. In this industry, advisors play a critical role in the attraction and retention of clients. Non-Compete Agreements constrain advisors’ movement among firms except for the Broker Protocol members. I develop and estimate a dynamic industry equilibrium model that features firms’ strategic decisions on entry, exit, investment, and adoption of the Broker Protocol. Estimation results based on the data from 2011 to 2018 establish the role of the Broker Protocol in changing the market structure and industry markups. Given the structural estimates, I examine the consequences of policies that change the cost of entry and labor mobility for firms. The second essay employs a novel approach to estimate applicant preferences with partially observed data from centralized matching mechanisms such as the Gale-Shapley Deferred Acceptance algorithm. In a Monte Carlo analysis, I illustrate the performance of the estimation method in recovering demand parameters. I apply this method to the university admission data from Iran. The dataset contains information on grades, rank-order lists, and admission results of more than 8,000 applicants matched to programs after being ranked in a centralized exam. Estimates of the demand parameters shed light on how disparities in locational preferences of female and male applicants form their choices. Moreover, the results suggest that gender-neutral policies aiming to enhance educational opportunities for applicants from underdeveloped areas can worsen gender disparities in higher education. The third essay investigates the role of investment advisors’ misconduct in a Berk and Green-type rational model of investment management. The model generates two interesting implications. First, misconduct weakens the belief updating. In other words, the model implies that misconduct reduces the speed of updating investors’ beliefs about the advisor’s ability. However, when an advisor engages in more misconduct, she will experience faster investors’ belief updating in the future. Second, engaging in misconduct in addition to a mild negative correlation between advisors’ ability and misconduct decreases the correlation between survival rate and misconduct. I analyze and compare the model implications under three different assumptions about the relationship between advisors’ ability and misconduct. I further present empirical evidence consistent with the model findings that associate the probability of investment advisory firm closure to misconduct.
  • Thumbnail Image
    Item
    Essays in Financial Economics and Asset Pricing
    (2024-08-06) Zhao, Binyu; Back, Kerry; Tang, Xun
    The dissertation consists of three essays that investigate the information contents and the implications of the formulation process of financial asset prices. Chapter 1, The Information Content of Municipal Bond Auctions, explores the information contents of municipal bond auctions. Based on the auction data of municipalities in the U.S. from the year 2018 to 2019, this paper tests whether the dispersion of bidders’ values leads to overpricing of municipal bonds, and whether the price informativeness of municipal bonds decreases with the dispersion. An affiliated private value auction model is applied to estimate the variances of bidders’ values, and then regression analysis is performed. The main finding is that bonds issued by municipalities with larger dispersion tend to be overpriced. One standard deviation increase in the dispersion causes around a 0.0531 standard deviation decrease in spreads. Another finding is that the correlation between bond prices and local economy is significant only for counties with value variances in the second quartile, which suggests that the dispersion decreases the price informativeness of municipal bonds. Chapter 2, Information Precision, Liquidity, and Risk Premiums: Evidence from Stock Call Auctions in the U.S., investigates the effects of information precision on financial market outcomes. Using the data from NYSE Arca call auctions, this paper tests the empirical implications of the demand schedule submission model in Kyle (1989). After showing the solid predictive power of order books and estimating the predictive precision, this paper demonstrates that higher precision increases market liquidity and that the precision levels of different types of traders do not interact with each other to affect liquidity measures such as daily turnover. Another finding is that precision is priced in excess returns, but the relation between precision and risk premiums is not linear. The main channel for precision to take effects is marginal utility. The sensitivity of a trader's marginal utility to her trading quantity is determined by her risk aversion and her own information precision. Therefore, precision affects the elasticity of demand curves and thus affects the final market outcomes. Chapter 3, A Discussion on Call Auction Data: Explore the Predictive Power of Order Books, explores the predictive power of order book data during NYSE Arca closing call auctions by applying various machine learning algorithms, including Gradient Boosting, Random Forests, Lasso, and Ridge. For each algorithm, predictions are evaluated over different tuning parameter choices. Then grid search is applied to determine the optimal parameters for each algorithms, and the performances of different algorithms are compared. The findings include that the overall prediction performances could not increase monotonically with the model complexity, because the increase in the model complexity also leads to over-fitting and finally impairs prediction accuracy. For the order book data analyzed, Random Forests achieves the best prediction performance. In general, tree-based models perform better than linear models. It suggests that the relation between order book statistics and future equity returns could have a complex non-linear form.
  • Thumbnail Image
    Item
    Essays on Causal Inference and Treatment Effects in Productivity and Finance: Double Robust Machine Learning with Deep Neural Networks and Random Forests
    (2021-04-28) Varaku, Kerda; Sickles, Robin C.; Tang, Xun
    In this dissertation, I use novel methodologies that incorporate machine learning into causal policy evaluation such as double robust machine learning to study some key issues in Productivity and Finance. In the first chapter, I evaluate the impacts of European public subsidies on innovation. I use double machine learning with deep neural networks to explore the effects of public subsidies on firms’ R&D input and output. I find that public subsidies increase both R&D intensity and R&D output and these results remain economically and statistically significant even after accounting for treatment endogeneity. In the second chapter, I evaluate the effects of public subsidies and collaboration agreements on innovation output. Many public schemes related to R&D have pushed towards collaborative agreements between firms/organizations and this chapter studies whether subsidies not promoting collaboration perform as well in terms of stimulating R&D output. Results show that subsidized noncollaborative firms would have gained in terms of R&D output had they collaborated. I also find that collaboration alone seems to generate significantly higher (double) R&D output compared to subsidies alone. In the third chapter, I analyze the impacts of offering non-core and non-financial ("plus") services in addition to core financial services on Microfinance Institutions' (MFIs) performance using a double machine learning model with random forests. The results indicate no differences in the performance of MFIs offering core financial and microfinance plus services, however, MFIs that offer non-core financial services together with non-financial services are serving less poor clients, suggesting a rather surprising "mission drift". In the fourth chapter, I analyze the impacts of regulation on MFIs' performance. I provide evidence of the impact of regulation on the double bottom line of the microfinance industry using double machine learning with neural networks. Results show that regulation does not affect financial results but affects the outreach of savings-and-loan MFIs. Regulation increases the depth of outreach of this group, indicating fewer poor clients, and suggesting a mission drift. In the fifth chapter, I investigate the link between the term structure of sovereign credit default swaps and the market efficiency of carry trades. I use Kneip et al. (2012) factor model to deal with large dimensions and unknown forms of unobservable heterogeneous effects. I document a divergent pattern of carry trade risk for developed and developing countries. In the sixth chapter, I use recurrent neural networks and feed forward deep networks, to predict NYSE, NASDAQ and AMEX stock prices from historical data. I experiment with different architectures and compare data normalization techniques. Then, I leverage those findings to question the efficient-market hypothesis through a formal statistical test and I find evidence of an inefficient stock market. Each of these studies requires the implementation of new methods of estimation and inference that have not been utilized to examine these important economic policy issues. My research points to many advantages of the approaches that I introduce in my dissertation. Robustness of inferences is a crucial dimension to acceptable policy recommendations and my development of semi/nonparametric estimators and their applications to crucial evaluations of public policy and regulatory oversight provides evidence that they are well-motivated theoretically, that they can be feasibly implemented in empirical applications, and they are in many cases, a dominant strategy in regard to model specification and estimation.
  • Thumbnail Image
    Item
    Essays on Discrete Choice Demand Estimation and Spatial Analysis
    (2023-04-21) Yu, Fisher; Tang, Xun
    This dissertation thesis contains three chapters in the fields of empirical industrial organization and applied econometrics. In my first chapter, I combine complementarity in bundle choice and consideration set of products into a demand model for differentiated products. I explore the identification when the market shares of products, not bundles are observed, and use a novel estimation approach via combining the loglikelihood of consumer choices and market shares with moment conditions. I apply the model to the yogurt market with consumer-level and store-level data. I find a considerable demand synergy in the bundle of different products and a significant proportion of consumer inertia, defined here as choosing from the last purchases, in consumer demand for yogurt. Compared to the standard discrete choice model, my estimation results suggest that accounting for complementarity between products and consumers’ limited consideration set can substantially affect price competition analysis. The second chapter is a collaborated work on the application of spatial econometrics in banking industry. We examine the direct and indirect impacts of natural disasters on deposit rates of bank branches during the 2008 – 2017 period. We find that spatial spillover effects substantially explain the total impact for deposit rate-setting branches. Our analysis and findings contribute to the existing literature by showing that the responses of branches to natural disasters are not confined only to those branches in counties directly affected but to branches in neighboring counties through competitive effects. Our results also confirm that spillover effects occur among branches across counties via a social connection and geographical network. The third chapter is on the identification and inference of a discrete choice model with partially unobserved attributes. It is motivated by the observation that consumers often do not account for unplanned purchases in their store choice when planning grocery trips. I show that the model is partially identified, and the sharp identified set is characterized via both moment-based inequalities and likelihood-based criteria. Using household grocery shopping data, I show that point estimation from the standard multinomial choice model assuming no unplanned purchases is rejected.
  • Thumbnail Image
    Item
    Essays on Econometrics of Social Networks and Productivity Estimation
    (2023-12-01) Shao, Kieran (Qiran); Tang, Xun
    This dissertation comprises three chapters within the fields of Econometrics of Social Networks and Productivity Estimation. The first chapter studies the estimation of demand with social network effects, where individuals' product choices are affected by the choices of their friends. I construct a sequential game choice model that captures the impact of large-scale network effects on consumers' product choices and propose a tractable Bayesian MCMC estimation procedure. Using granular data from the Steam online video game platform, I estimate the impact of friends' choices on individual gaming decisions. My findings reveal a positive network effect on game choices, with multiplayer games exhibiting a significantly larger effect. The empirical results highlight the importance of considering network effects in demand estimation, as failure to do so can result in an overestimation of the coefficients associated with game characteristics. This suggests the presence of demand amplification effects arising from social networks. Lastly, I conduct counterfactual analyses to examine demand elasticity and explore pricing and marketing strategies leveraging network effects. The second chapter is a collaborative work that estimates firms’ production functions using a novel correlated random coefficient methodology. To incorporate firms’ endogenous decisions on input choices, we specify firm-specific and time-varying productivity parameters while allowing arbitrary correlations between productivity parameters and input variables. Applying the methodology to panel data from manufacturing industries in Chile and India, we estimate the average and dispersion of productivity across firms and use the estimates to decompose the aggregated productivity growth. In the third chapter, I explore a specialized case related to the first chapter, where agents possess private information on links and payoffs. To address this scenario, I propose a two-stage model. The first stage involves network formation, where agents follow an incentive-compatible mechanism to form network links. In the second stage, given the endogenously formed links, agents engage in a continuous-action network game with incomplete information. To jointly estimate the two stages and account for the endogeneity of links, I utilize a latent variable and adopt a tractable Bayesian MCMC approach.
  • Thumbnail Image
    Item
    Essays on Fair Division and Monopoly Pricing
    (2015-11-10) Li, Jin; Dudey, Marc; Tang, Xun; Veech, William
    The first chapter is based on a paper with Jingyi Xue in fair division problems. In this chapter, we consider the problem of fairly dividing a finite number of divisible goods among agents with the generalized Leontief preferences. We propose and characterize the class of generalized egalitarian rules which satisfy efficiency, group strategy-proofness, anonymity, resource monotonicity, population monotonicity, envy-freeness and consistency. On the Leontief domain, our rules generalize the egalitarian-equivalent rules with reference bundles. We also extend our rules to agent-specific and endowment-specific egalitarian rules. The former is a larger class of rules satisfying all the previous properties except anonymity and envy-freeness. The latter is a class of efficient, group strategy-proof, anonymous and individually rational rules when the resources are assumed to be privately owned. The second chapter is about monopoly pricing with social learning. In this chapter, we consider a two-period monopolistic model in which the consumers who purchase in the first period would reveal the unknown quality of the product through their experiences to the consumers in the second period. Due to this effect, some consumers would strategically choose to delay to the second period in order to take this informational free-ride. We show that there always exists a unique symmetric equilibrium of consumers for each price set by the monopolist. Then we further investigate the seller’s optimization pricing problem. In a range of moderate patience, the seller would be likely to induce the consumers to effectively transmit information. We also discuss the impact of information disclosure on the monopolistic profit.
  • Thumbnail Image
    Item
    Essays on Industrial Organization
    (2023-04-19) Jang, Shinjae; Tang, Xun
    In the first chapter, I quantify consumer inertia in the Korean mobile phone service market. Two sources of the inertia, consumer inattention, and incumbent brand effect are separately estimated by estimating a two-stage discrete choice model using individual-level mobile plan choice data in Korea from 2016 to 2018. I find that the probability of an incumbent's plan subscriber being attentive to alternative plans is only 13.8 percent, compared to 44 percent for an entrant's (Mobile Virtual Network Operator, or MVNO) plan subscriber. Consumers also associate the brand effect with incumbents' plans over MVNOs' offerings. Based on these findings, I explain the stagnant growth of MVNOs' market share in the Korean mobile phone service market. In the counterfactual analysis, I demonstrate that a hypothetical information intervention can increase consumer surplus. In the second chapter, I study how consumers react to advertising on an innovative nondurable grocery product, a plant-based meat alternative (henceforth PBMA) burger patty in the Texas market. Using a panel random-effects binary logit model, I empirically distinguish the informative and prestige effects of advertising. I find that the two effects appear on Patty A's purchasing behavior, while the informative effect is more prominent than the prestige effect. Interestingly, the advertising spillover effect from within PBMA brands group dominates the impact of its own advertising in terms of magnitude. This implies that consumers tend to perceive PBMA patty products as a group much more than compartmentalizing the advertising exposure experience by brands. The number of previous product purchase experiences of the product is also an important factor to consider, as product purchase experience accumulation positively affects Patty A purchase odds, while the impact diminishes as the accumulation increases. I also find empirical evidence that supports substitutional relationship between Patty A and animal patty competitors, and the impact of household demographics on the purchase decision. Based on the empirical results, I derive a few suggestions for the PBMA producers. The third chapter defines the burger patty market in Texas. This is an auxiliary chapter that provides further market insights on ongoing market issues based on the empirical product market definition result derived from demand and markup estimations. From a "small but significant and nontransitory increase (SSNIP)" test, I figure that PBMA patties should be included in the same market as animal meat patties.
  • Thumbnail Image
    Item
    Essays on Matching Markets
    (2023-04-13) Kutasi, Kristof; Tang, Xun; He, YingHua
    This dissertation consists of three chapters addressing several matching market questions applied to school choice, vaccine allocation and job search problems. In the first chapter, I study the role of information uncertainty in a many-to-one matching problem in a centralized college admissions system. I find that the mistakes of excluding almost surely out-of-reach programs from the rank-order list (ROL) do not change the allocation outcome significantly but using the observed ROLs as the true preferences would lead to biased estimates of student preference and misleading counterfactual results. I build a model where students are allowed to make certain mistakes in their ROLs when they face uncertainties in their priority scores. I argue that stability of the admission outcome is satisfied asymptotically. I estimate student preferences based on stability using a Gibbs sampler. I analyze two counterfactual policies in which students from rural high schools receive benefits in a form of additional priorities and seats. The policies would not hurt the welfare of the urban students significantly more than they would benefit the welfare of rural students. The second chapter (co-authored with Júlia Koltai, Ágnes Szabó-Morvai, Gergely Röst, M\'arton Karsai, Péter Biró, Balázs Lengyel) studies the vaccine acceptance and the assessment of five vaccines during the end of the third wave Covid-19 pandemic in Hungary based on a nationally representative survey. Individuals could reject the assigned vaccine to wait for a more preferred alternative that enables us to quantify revealed preferences across vaccine types. We find that hesitancy is heterogenous across vaccine types and is mostly driven by individuals’ trusted source of information. We argue that the greater selection of available vaccines and individuals’ free choice of vaccines create desirable conditions to increase the vaccination rate in societies. In the third chapter I study one-to-one matching markets in a labor setting, where applicants and firms’ pay wasteful costs to search and screen, respectively. Unlike in Arnosti et al. (2021) firms might receive a biased signal about the applicant’s compatibility. I ask the research question: How much additional cost would the applicants be willing to pay to eliminate firms’ biased screening?
  • Thumbnail Image
    Item
    Heterogeneous Preferences and Optimal Release Timing in the U.S. Film Industry
    (2018-04-12) Copeland, Nicholas Marhsall; Tang, Xun
    I develop and estimate a discrete choice structural model of demand to address the unique challenges of the domestic film industry. Then, using the model estimates, I setup the release date scheduling problem and solve for the optimal timing of release dates. The industry is marked by highly seasonal demand fluctuations and features products with clearly defined characteristics and short periods of viability. The model described herein, which is built upon the framework of BLP (1995), accounts for utility decay over time, seasonal effects, and heterogeneous consumer preferences over genre, MPAA rating, and critic reviews. I approximate the optimal instruments in a nonlinear setting, enabling the identification and precise estimation of the random coefficient parameters. These parameters shape characteristic-driven substitution patterns, a feature of the market largely ignored in past work. Using the model estimates, I identify the most over- and under-used markets in the industry by simulating the potential revenue of a hypothetical film across potential release dates. I find that the Christmas holiday season and the early portion of the year are often underutilized, while the fall markets are generally oversaturated. The paper concludes by constructing the film studios' release date scheduling problem and solving the inherent integer-programming problem. I find a restructured release schedule that increases revenue by 17% at the firm level.
  • Thumbnail Image
    Item
    Regulation and Capacity Competition in Health Care: Evidence from U.S. Dialysis Markets
    (MIT Press, 2015) Dai, Mian; Tang, Xun
    This paper studies entry and capacity decisions by dialysis providers in the United States. We estimate a structural model where providers make continuous strategic choices of capacity based on their private information about own costs and knowledge of the distribution of competitors’ private information. We evaluate the impact on the market structure and providers’ profits under counterfactual regulatory policies that increase the costs or reduce the payment per unit of capacity. We find that these policies reduce the market capacity as measured by the number of dialysis stations. However, the downward-sloping reaction curve shields some providers from negative profit shocks in certain markets. The paper also has a methodological contribution in that it proposes new estimators for Bayesian games with continuous actions.