We study beliefs and choices in a repeated normal-form game. In addition to a baseline treatment with common knowledge of the game structure and feedback about choices in the previous period, we run treatments (i) without feedback about previous play, (ii) with no information about the...

In order to address the impact of regulation on ethical concerns of consumers, westudy the e¤ect of a minimum wage. In our experimental market, consumers havemonopsony power, firms engage in Bertrand competition, and workers are passiverecipients of a wage payment. Two treatments are employed,...

This paper offers a new method for estimation and forecasting of the linear and nonlinear time series when the stationarity assumption is violated. Our general local parametric approach particularly applies to general varying-coefficient parametric models, such as AR or GARCH, whose coefficients...

We investigate the matching algorithm used by the German central clearinghouse for university admissions (ZVS) in medicine and related subjects. This mechanism consists of three procedures based on final grades from school (“Abiturbestenverfahren”, “Auswahlverfahren der Hochschulen”) and on...

We perform an experiment where subjects pay for the right to participate in a shareholder vote. We find that experimental subjects are willing to pay a significant premium for the voting right even though there should be no such premium in our setup under full rationality. Private benefits from...

In the ideal Black-Scholes world, financial time series are assumed 1) stationary (time homogeneous) and 2) having conditionally normal distribution given the past. These two assumptions have been widely-used in many methods such as the RiskMetrics, one risk management method considered as...

Over recent years, study on risk management has been prompted by the Basel committee for regular banking supervisory. There are however limitations of some widely-used risk management methods that either calculate risk measures under the Gaussian distributional assumption or involve numerical...

Measuring dependence in a multivariate time series is tantamount to modelling its dynamic structure in space and time. In the context of a multivariate normally distributed time series, the evolution of the covariance (or correlation) matrix over time describes this dynamic. A wide variety of...

In this paper we carry over the concept of reverse probabilistic representations developed in Milstein, Schoenmakers, Spokoiny (2004) for diffusion processes, to discrete time Markov chains. We outline the construction of reverse chains in several situations and apply this to processes which are...

This paper presents a new method for spatially adaptive local likelihood estimation which applies to a broad class of nonparametric models, including the Gaussian, Poisson and binary response models. The main idea of the method is given a sequence of local likelihood estimates ("weak"...