Price rigidities and institutional variations in markets with posted prices

Summary Standard laboratory posted-offer markets respond slowly and incompletely to demand shocks. In these one-sided markets, where sellers control the setting of prices, very little information is transmitted via the process of exchange. For this reason, traders have trouble distinguishing randomness in their own experience from changes in market fundamentals. This paper reports the results of twelve laboratory markets conducted to assess whether some common variants to standard posted-offer rules can correct the adjustment deficiences. Although discounting, multiple postings and excess demand information all improve performance, we find that response remains poor, and efficiencies low.Support for this research was provided by the National Science Foundation (SBR 9319842 and SBR 9320044), and the University of Virginia Bankard Fund. Data are archived at FTP address: fido.econlab.arizona.edu. We wish to thank Charles Plott and Shyam Sunder for useful comments on an earlier draft of this paper. The usual disclaimer applies.     

A Pearson's test for symmetry with an application to the Spanish business cycle

In this paper, we look for asymmetries in the Spanish business cycle. To that end, we firstly propose an easy nonparametric testing procedure to test for symmetry based on a Pearson's chi-squared statistic, which we call P-test. Then, we test for two popular forms of asymmetry, deepness and steepness, using a battery of nonparametric tests. In addition, we analyse possible complementarities between the tests used in this paper, and we compute p-value adjustments for multiple tests.     

Are Expected Inflation Rates and Expected Real Rates Negatively Correlated? A Long‐Run Test of the Mundell‐Tobin Hypothesis

Some empirical evidence suggests that the expected real interest and expected inflation rates are negatively correlated. This hypothesis of negative correlation is sometimes known as the Mundell‐Tobin hypothesis. In this article we reinvestigate this negative relation from a long‐term point of view using cointegration analysis. The data on the historical interest rate on T‐bills and the inflation rate indicate that the Mundell‐Tobin hypothesis does not hold in the long run for the United States, the United Kingdom, and Canada. We also obtain similar results using the real interest rate on index‐linked gilt traded in the United Kingdom.     

Sunspot fluctuations in dynamics with predetermined variables

Summary. In this paper, I study the existence of Sunspot Equilibria in a general framework whose dynamics allow for the presence of predetermined variables in the system. The main motivation for this research comes from the fact that previous studies did not allow for such predetermined variables which, nevertheless, appear quite naturally in economic models. I show, for a non-negligible subset of dynamics with predetermined variables verifying usual assumptions, the existence of Stationary Sunspot Equilibria fluctuating between an arbitrary finite number of states arbitrarily close to a steady state. Received: March 1, 1995; revised version September 18, 1996     

Quality Competition and Social Welfare in Markets with Partial Coverage: New Results*

We use a vertical product differentiation model under partial market coverage to study the social welfare optimum and duopoly equilibrium when convex costs of quality provision are either fixed or variable in terms of production. We show the following new results. First, under fixed costs, the social planner charges a uniform price for the single variant that just covers costs of quality provision. Like the duopoly equilibrium, this socially optimal pricing entails a partially uncovered market, but a smaller share of the market is served compared with the duopoly equilibrium. Second, for the variable cost case, it is socially optimal to provide both high‐ and low‐quality variants, but market shares need not be equal. This differs from the result in fully covered markets. Third, in the duopoly equilibrium, the quality spread is too wide under variable costs relative to the social optimum. Under fixed costs, the duopoly produces two variants, but quality is too low relative to the social optimum, which has only one variant.     

论4C对产品的导向

现代企业不再是销售已经生产好的产品，而应该是开发生产好卖的产品。好卖的产品，即市场拉动型产品，市场拉动就是以市场为导向，而4C则是对市场导向的全面概括。归根结底．现代企业的产品就是要以4C为导向。     

Partial Horizontal Inequity Orderings: A Non‐parametric Approach*

We provide a partial ordering view of horizontal inequity (HI), based on the Lorenz criterion, associated with different post‐tax income distributions and a (bistochastic) non‐parametric estimated benchmark distribution. As a consequence, several measures consistent with the Lorenz criterion can be rationalized. In addition, we establish the so‐called HI transfer principle, which imposes a normative minimum requirement that any HI measure must satisfy. Our proposed HI ordering is consistent with this principle. Moreover, we adopt a cardinal view to decompose the total effect of a tax system into a welfare gain caused by HI‐free income redistribution and a welfare loss caused by HI, without any additive decomposable restriction on the indices. Hence, more robust tests can be applied. Other decompositions in the literature are seen as particular cases.     

Evaluation of dynamic stochastic general equilibrium models based on distributional comparison of simulated and historical data

We take as a starting point the existence of a joint distribution implied by different dynamic stochastic general equilibrium (DSGE) models, all of which are potentially misspecified. Our objective is to compare “true” joint distributions with ones generated by given DSGEs. This is accomplished via comparison of the empirical joint distributions (or confidence intervals) of historical and simulated time series. The tool draws on recent advances in the theory of the bootstrap, Kolmogorov type testing, and other work on the evaluation of DSGEs, aimed at comparing the second order properties of historical and simulated time series. We begin by fixing a given model as the “benchmark” model, against which all “alternative” models are to be compared. We then test whether at least one of the alternative models provides a more “accurate” approximation to the true cumulative distribution than does the benchmark model, where accuracy is measured in terms of distributional square error. Bootstrap critical values are discussed, and an illustrative example is given, in which it is shown that alternative versions of a standard DSGE model in which calibrated parameters are allowed to vary slightly perform equally well. On the other hand, there are stark differences between models when the shocks driving the models are assigned non-plausible variances and/or distributional assumptions.     

An efficient nonparametric estimator for models with nonlinear dependence

We provide a convenient econometric framework for the analysis of nonlinear dependence in financial applications. We introduce models with constrained nonparametric dependence, which specify the conditional distribution or the copula in terms of a one-dimensional functional parameter. Our approach is intermediate between standard parametric specifications (which are in general too restrictive) and the fully unrestricted approach (which suffers from the curse of dimensionality). We introduce a nonparametric estimator defined by minimizing a chi-square distance between the constrained densities in the family and an unconstrained kernel estimator of the density. We derive the nonparametric efficiency bound for linear forms and show that the minimum chi-square estimator is nonparametrically efficient for linear forms.     

A versatile and robust metric entropy test of time-reversibility,and other hypotheses

We examine the performance of a metric entropy statistic as a robust test for time-reversibility (TR), symmetry, and serial dependence. It also serves as a measure of goodness-of-fit. The statistic provides a consistent and unified basis in model search, and is a powerful diagnostic measure with surprising ability to pinpoint areas of model failure. We provide empirical evidence comparing the performance of the proposed procedure with some of the modern competitors in nonlinear time-series analysis, such as robust implementations of the BDS and characteristic function-based tests of TR, along with correlation-based competitors such as the Ljung–Box Q-statistic. Unlike our procedure, each of its competitors is motivated for a different, specific, context and hypothesis. Our evidence is based on Monte Carlo simulations along with an application to several stock indices for the US equity market.