Liability Rules and Evolutionay Dynamics

We consider the convergence properties of behavior under a comparative negligence rule (CN) and under a rule of negligence with contributory negligence (NCN), assuming bilateral care with three care levels. Using an evolutionary model, we show that CN reduces the proportion of the population using low care more rapidly than does NCN. However NCN increases the proportion of the population using high (efficient) care more rapidly than does CN. As a result, the mean care level increases more rapidly and the mean social cost falls more rapidly under CN than under NCN.tort law, evolutionary game, liability rules, economic analysis of law

Rational Legal Decision-Making, Value Judgment and Efficient Precaution in Tort law

By reinterpreting Savage axioms as axioms of the social rationality over resource allocations, we derive a social welfare function encompassing individual social values and a social attitude towards distributional inequality. Wealth maximization becomes the purpose of law only if individuals have equal social values and the society does not care about distributional inequality. In tort law, when the injurer is less socially valued than the victim, the society imposes a stricter due precaution level, and punitive damages will be awarded. Tort law also implicitly transfers wealth from the less socially valued party to the more socially valued party.rationality; value judgement; tort law; punitive damage

Nonlinear Factor Models for Network and Panel Data

Factor structures or interactive effects are convenient devices to incorporate latent variables in panel data models. We consider fixed effect estimation of nonlinear panel single-index models with factor structures in the unobservables, which include logit, probit, ordered probit and Poisson specifications. We establish that fixed effect estimators of model parameters and average partial effects have normal distributions when the two dimensions of the panel grow large, but might suffer of incidental parameter bias. We show how models with factor structures can also be applied to capture important features of network data such as reciprocity, degree heterogeneity, homophily in latent variables and clustering. We illustrate this applicability with an empirical example to the estimation of a gravity equation of international trade between countries using a Poisson model with multiple factors.Comment: 49 pages, 6 tables, the changes in v4 include numerical results with more simulations and minor edits in the main text and appendi

Bidding Behavior in Competing Auctions: Evidence from eBay

Much of the existing auction literature treats auctions as running independently of one another, with each bidder choosing to participate in only one auction. However, in many online auctions, a number of substitutable goods are auctioned concurrently and bidders can bid on several auctions at the same time. Recent theoretical research shows how bidders can gain from the existence of competing auctions, the current paper providing the first empirical evidence in support of competing auctions theory using online auctions data from eBay. Our results indicate that a significant proportion of bidders do bid across competing auctions and that bidders tend to submit bids on auctions with the lowest standing bid, as the theory predicts. The paper also shows that winning bidders who cross-bid pay lower prices on average than winning bidders who do not.Competing Auction, Cross-Bidding, Auction Empirics

Counterfactual: An R Package for Counterfactual Analysis

The Counterfactual package implements the estimation and inference methods of Chernozhukov, Fern\'andez-Val and Melly (2013) for counterfactual analysis. The counterfactual distributions considered are the result of changing either the marginal distribution of covariates related to the outcome variable of interest, or the conditional distribution of the outcome given the covariates. They can be applied to estimate quantile treatment effects and wage decompositions. This paper serves as an introduction to the package and displays basic functionality of the commands contained within.Comment: 15 pages, 4 figure

Research related to high dimensional econometrics

This dissertation consists of three chapters related to high dimensional econometrics dealing with the estimation of nonlinear panel data models and networks models. The first chapter proposes a fixed effects expectation-maximization estimator for a class of nonlinear panel data models with unobserved heterogeneity modeled as individual and/or time effects or an arbitrary interaction of the two. The estimator is obtained through a computationally simple iterative two-step procedure, both steps having a closed form solution. I show that the estimator is consistent in large panels, derive the asymptotic distribution for a probit model with interactive effects, and develop analytical bias corrections to deal with the incidental parameter problem. The second chapter considers estimation and inference for semiparametric nonlinear panel single index models with interactive effects. These include static and dynamic probit, logit, and Poisson models. An iterative two-step procedure to maximize the likelihood is proposed. The estimator is consistent, but has bias due to the incidental parameter problem. Analytical and jackknife bias corrections are developed to remove the bias without increasing variance. The third chapter proposes Quantile Graphical Models (QGMs) to characterize predictive and conditional dependence relationships within a set of random variables in non-Gaussian settings. These characterize the best linear predictor under asymmetric losses and the conditional dependence at each quantile. Estimators based on high-dimensional techniques are proposed. Each QGM represents the tail interdependence and the associated tail risk network and can be used to measure systemic risk contributions for the study of financial contagion and hedging under a market downturn

Optimal Default Retirement Saving Policies: Theory and Evidence from OregonSaves

Many U.S. states are launching state-sponsored auto-enrollment retirement plans, with the goal of boosting retirement savings among private-sector workers lacking access to employersponsored retirement plans. This paper provides an analysis of state-sponsored auto-enrollment plans, and specifically, the plan\u27s default contribution rate. We develop a tractable framework to derive the optimal default contribution rate taking into account workers\u27 decisions on adhering to the default contribution rate. The optimal default contribution rate is shaped by the social benefits of increased savings due to adherence to the default that keeps workers from undersaving, while reducing reliance on means-tested social transfers. The optimal default contribution rate is also counterbalanced by the social benefits of action when an undesirable default option compels workers to make an active decision. To estimate these counterbalancing social welfare forces, we use individual-level administrative and survey data from OregonSaves, the state-sponsored plan offered by the Oregon state government, and suggest the optimal default contribution rate to be 8%

Culture Shock-One of Common Problems in Intercultural Communication

Communicating successfully with people from different cultures can be a real challenge. Cultural differences may lead to tensions, arguments, and even wars between peoples and nations. This paper deals with one of the most common problems in intercultural communication-cultural shock, it introduces its concepts and basic traits, causes and symptoms, stages of adjustment and strategies of overcoming culture shock with the aim of improving intercultural communication competence for smoothing intercultural communication