Voting between tax regimes to fund a public good

We study experimentally how taxpayers choose between an income tax and a commodity tax to fund a public good. We implement conditions such that a rational and self-interested subject would prefer the commodity-tax regime. We find that voters overwhelmingly support the income-tax regime. We discuss and evaluate empirically alternative behavioral accounts to explain voting behavior. We find that inequality aversion and efficiency concerns matter for voting. We find no evidence for opportunism or for cognitive ability to affect voting.     

DECISION THEORY UNDER AMBIGUITY

Abstract We review recent advances in the field of decision making under uncertainty or ambiguity. We start with a presentation of the general approach to a decision problem under uncertainty, as well as the ‘standard’ Bayesian treatment and issues with this treatment. We present more general approaches (Choquet expected utility, maximin expected utility, smooth ambiguity and so forth) that have been developed in the literature under the name of models of ambiguity sensitive preferences. We draw a distinction between fully subjective models and models incorporating explicitly some information. We review definitions and characterizations of ambiguity aversion in these models. We mention the challenges posed by some of the models presented. We end with a review of part of the experimental literature and applications of these models to economic settings.     

Allocating chances of success in finite and infinite societies: The utilitarian criterion

We study a particular collective choice problem, that of allocating chances of success. We argue that many problems of interest have this nature, from small scale problems like medical triage to large scale ones like the allocation of opportunities in society. We consider both finite and infinite societies. We characterise utilitarian-type criteria by means of new properties tailored to the probabilistic structure of the alternatives.     

Multivariate Hill Estimators

We propose two classes of semi‐parametric estimators for the tail index of a regular varying elliptical random vector. The first one is based on the distance between a tail probability contour and the observations outside this contour. We denote it as the class of separating estimators. The second one is based on the norm of an arbitrary order. We denote it as the class of angular estimators. We show the asymptotic properties and the finite sample performances of both classes. We also illustrate the separating estimators with an empirical application to 21 worldwide financial market indexes.     

The influence of calculative (“hard”) and collaborative (“soft”) HRM on the layoff‐performance relationship in high performance workplaces

We investigate the effect of employment systems on the layoff‐performance relationship. We construct a typology of two types of HPWS (Calculative or “hard” HRM and Collaborative or “soft” HRM) and two non‐high performance systems (Traditional HRM and Low HRM). We use attribution theory as a framework from which to draw hypotheses. We examine survey responses from two waves of panel data. We employ cluster analysis to identify distinctive configurations of employment practices used in UK workplaces. We use the cluster outcomes as explanatory variables in moderator regression analysis. Following layoffs, we find that Calculative workplaces experience lower subsequent performance than Collaborative workplaces. Over the next five years, Calculative and Collaborative workplaces experience equivalent amounts of performance change but Calculative workplaces fail to make a full recovery.     

Analysis of Covariance with Non-normal Errors

Analysis of covariance techniques have been developed primarily for normally distributed errors. We give solutions when the errors have non-normal distributions. We show that our solutions are efficient and robust. We provide a real-life example.     

The relationship between power and level for generic unit root tests in finite samples

We show that the maximum power of a generic unit root test against any stationary alternative is equal to the true level of the test. We then use Monte Carlo methods to investigate the implications for several such tests. We show patterns of rejection probabilities over a variety of unit root and stationary processes. We discuss the implications of these results for some of the uses of unit root tests in applied work.     

Convergence to Walrasian equilibrium with minimal information

We consider convergence to Walrasian equilibrium in a situation where firms know only market price and their own cost function. We term this a situation of minimal information. We model the problem as a large population game of Cournot competition. The Nash equilibrium of this model is identical to the Walrasian equilibrium. We apply the best response (BR) dynamic as our main evolutionary model. This dynamic can be applied under minimal information as firms need to know only the market price and the their own cost to compute payoffs. We show that the BR dynamic converges globally to Nash equilibrium in an aggregative game like the Cournot model. Hence, it converges globally to the Walrasian equilibrium under minimal information. We extend the result to some other evolutionary dynamics using the method of potential games.

     

Education choice under uncertainty: Implications for public policy

We analyse how progressive taxation and education subsidies affect schooling decisions when the returns to education are stochastic. We use the theory of real options to solve the problem of education choice in a dynamic stochastic model. We show that education attainment will be an increasing function of the risk associated with education. Furthermore, this result holds regardless of the degree of risk aversion. We also show that progressive taxes will tend to increase education attainment.     

Some strange properties of panel data estimators

We study the biases that are likely to arise in practice with panel data when parameters vary across individuals, but this is not allowed for in estimation. We consider both stationary and non-stationary regressors. We find that biases can be severe for relatively small parameter variation, and that this problem is hard to detect. We study in some detail by Monte-Carlo the performance of the Anderson-Hsiao estimator in the presence of this particular mis-specification.     

Multivariate realised kernels: Consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading

We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement error of certain types and can also handle non-synchronous trading. It is the first estimator which has these three properties which are all essential for empirical work in this area. We derive the large sample asymptotics of this estimator and assess its accuracy using a Monte Carlo study. We implement the estimator on some US equity data, comparing our results to previous work which has used returns measured over 5 or 10 min intervals. We show that the new estimator is substantially more precise.     

Cost sharing: efficiency and implementation

We study environments where a production process is jointly shared by a finite group of agents. The social decision involves the determination of input contribution and output distribution. We define a competitive solution when there is decreasing-returns-to-scale which leads to a Pareto optimal outcome. Since there is a finite number of agents, the competitive solution is prone to manipulation. We construct a mechanism for which the set of Nash equilibria coincides with the set of competitive solution outcomes. We define a marginal-cost-pricing equilibrium (MCPE) solution for environments with increasing returns to scale. These solutions are Pareto optimal under certain conditions. We construct another mechanism that realizes the MCPE.     

Utility of wealth with many indivisibilities

We introduce a class of utility of wealth functions, called knapsack utility functions, which are appropriate for agents who must choose an optimal collection of indivisible goods subject to a spending constraint. We investigate the concavity/convexity and regularity properties of these functions. We find that convexity–and thus a demand for gambling–is the norm, but that the incentive to gamble is more pronounced at low wealth levels. We consider an intertemporal version of the problem in which the agent faces a credit constraint. We find that the agent’s utility of wealth function closely resembles a knapsack utility function when the agent’s saving rate is low.     

On the properties of a multiple sequential test

We consider a multiple testing problem based on an i.i.d. sample of K-dimensional observations. We want to test whether at least one of the unknown means is positive. We propose a sequential test which is of the nature of a multiple truncated sequential probability ratio test. We asymptotically analyse the expected sample size and compare it to the sample sizes which arise when one looks at effects separately.     

Micro versus macro cointegration in heterogeneous panels

We consider the issue of cross-sectional aggregation in nonstationary and heterogeneous panels where each unit cointegrates. We derive asymptotic properties of the aggregate estimate, and necessary and sufficient conditions for cointegration to hold in the aggregate relationship. We then analyze the case when cointegration does not carry through the aggregation process, and we investigate whether the violation of the formal conditions for perfect aggregation can still lead to an aggregate equation that is observationally equivalent to a cointegrated relationship. We derive a measure of the degree of noncointegration of the aggregate relationship and we explore its asymptotic properties. We propose a valid bootstrap approximation of the test. A Monte Carlo exercise evaluates size and power properties of the bootstrap test.     

Relief aid stocking decisions under bilateral agency cooperation

We aim to quantify the benefits of cooperation between humanitarian relief agencies in terms of stocking decisions. We consider two agencies that stock the same type of relief item at different locations prone to individual disaster risks and agree to transship the shortage amount from available stocks in case of a disaster. We incorporate the disaster risk to the Newsvendor model by conditioning the stock quantity decisions on the event that a major disaster occurs within the lifetime of the stocked relief item. We optimize the stock quantity for each agency in response to the other's quantity and compute a Nash Equilibrium solution numerically. We apply this game theoretic approach to the case of earthquake preparedness in Istanbul to optimize the stocking decisions of an agency for shelter units in cooperation with another agency. We investigate the characteristics of the solutions under various parameter settings and identify cases in which cooperation may be beneficial to one or both of the agencies.     

Selling goods of unknown quality: forward versus spot auctions

We consider an environment where the sale can take place so early that both the seller and potential buyers have the same uncertainty about the quality of the good. We present a simple model that allows the seller to offer the good for sale before or after this uncertainty is resolved, namely via forward auction or spot auction, respectively. We solve for the equilibrium of these two auctions and then compare the resulting expected revenues. We also consider the revenue implications of insurance in forward auctions.     

Buying cooperation in an asymmetric environmental differential game

We consider a two-player asymmetric differential game of pollution control. One player is non-vulnerable to pollution, or unwilling to consider damages when choosing her production policy in a non-cooperative game. We characterize the feedback-Nash equilibrium and the cooperative solution. We establish conditions under which the vulnerable player can buy the cooperation of the non-vulnerable player to control her emissions. We further use the Nash bargaining solution to allocate the total cooperative dividend between the two players and propose a time-consistent decomposition overtime of the total payoff.     

Generalizations of the KPSS-test for stationarity

We propose automatic generalizations of the KPSS-test for the null hypothesis of stationarity of a univariate time series. We can use these tests for the null hypotheses of trend stationarity, level stationarity and zero mean stationarity. We introduce the asymptotic null distributions and we determine consistency against relevant nonstationary alternatives. We compare the properties of the tests with those of other proposed tests for stationarity. Monte Carlo simulations support the relevance of the tests when an autoregressive process with large positive autocorrelations is likely under the null hypothesis.     

Core and competitive equilibria: An approach from discrete convex analysis

We extend the assignment market (Shapley and Shubik, 1972; Kaneko, 1976, 1982) by utilizing discrete convex analysis. We consider the market in which buyers and sellers trade indivisible commodities for money. Each buyer demands at most one unit of commodity. Each seller produces multiple units of several types of commodities. We make the quasi-linearity assumption on the sellers, but not on the buyers. We assume that the cost function of each seller is M^♮-convex, which is a concept in discrete convex analysis. We prove that the core and the competitive equilibria exist and coincide in our market model.