Location decisions and welfare under spatial price discrimination

The welfare effects of regulation are of crucial importance to policy makers. To this end, we present a model of n firms with differentiated costs competing in a linear market within the framework of spatial price discrimination. We prove that the Nash equilibrium locations of firms are always socially optimal irrespective of the number of competitors, the distribution of consumers, firms' cost heterogeneity, the level of privatization, and the number and/or the varieties of the produced goods. We also provide an algorithm on how to find the unique Nash equilibrium in the case of uniformly distributed consumers.     

The Information Content of Stock Prices,Legal Environments,and Accounting Standards: International Evidence

Abstract

In this paper, we investigate the impact of accounting standards on the information content of stock prices using a sample of 44 countries from around the world. We find that the adoption of International Financial Reporting Standards or US Generally Accepted Accounting Principles per se does not make stock prices more informative, but that better accounting standards are helpful only in countries having effective legal environments. In particular, we find a significantly negative relationship between stock price synchronicity and the quality of accounting standards in countries with a common-law legal origin and generally better shareholder protection. Our findings are consistent with the theoretical prediction in Zhang [(2013). Accounting standards, cost of capital, resource allocation, and welfare in a large economy. The Accounting Review, 88(4), 1459–1488] that improving accounting standards effectively would increase social welfare in general.     

Pricing Experience Goods: The Effects of Customer Recognition and Commitment

In a two‐period model of nondurable experience goods, we compare the profit and social welfare effects of behavior‐based price discrimination (BBPD) and price commitment (PC) (relative to time‐consistent pricing) in a monopoly. We find that when the static, full‐information monopoly price is higher (lower) than the mean consumer valuation, PC yields higher (lower) profits and social welfare than BBPD. We also identify the market conditions under which BBPD does not increase firm profits and provide an explanation as to when the firm should discriminate against its first‐time and repeat customers, respectively.     

From constrained optimization to constrained dynamics: extending analogies between economics and mechanics

Economic equilibrium models have been inspired by analogies to stationary states in classical mechanics. To extend these mathematical analogies from constrained optimization to constrained dynamics, we formalize economic (constraint) forces and economic power in analogy to physical (constraint) forces and the reciprocal value of mass. Agents employ forces to change economic variables according to their desire and their power to assert their interest. These ex-ante forces are completed by constraint forces from unanticipated system constraints to yield the ex-post dynamics. The differential-algebraic equation framework seeks to overcome some restrictions inherent to the optimization approach and to provide an out-of-equilibrium foundation for general equilibrium models. We transform a static Edgeworth box exchange model into a dynamic model with procedural rationality (gradient climbing) and slow price adaptation, and discuss advantages, caveats, and possible extensions of the modeling framework.

     

Can boundedly rational sellers learn to play Nash?

How does Nash pricing compare to pricing with adaptive sellers using reinforcement learning (RL)? We consider a market game similar to Varian’s model (Am Econ Rev 70:651–659, 1980) with two types of consumers differing by the size of their fixed sample search rule and derive the Nash search equilibrium (NSE) strategy (the density, the mean and the variance of the posted price distribution). Our findings are twofold. First, we find that the RL price distribution does not converge in a statistical sense to the NSE one except when competition is à la Bertrand. Second, we show that the qualitative properties of the NSE with respect to a change in buyers‘ search behavior are still valid for the RL distribution. The average price and the variance of both price distributions exhibit similar variations to a change in buyers’ search.     

Social support among heterogeneous partners: an experimental test

This paper studies how dyadic social support is affected by heterogeneity of the partners. We distinguish heterogeneity with respect to three parameters the likelihood of needing support; the benefits from receiving support; and the costs of providing support. Hypotheses are based on a game-theoretic analysis of an iterated support game. First, we predict that heterogeneity in one of the parameters hampers social support. Second, we predict that under heterogeneity with respect to two of the parameters, support is most likely if there is a specific heterogeneous distribution such that heterogeneity in one parameter ‘compensates’ for heterogeneity in the other parameter. If there is no compensation social support is even more hampered. The hypotheses have been tested by experimental data with a mixed within-subject, between-subject design. The data gives support to the hypotheses.     

Income taxation when markets are incomplete

We investigate the welfare effects of proportional income taxation in a standard general equilibrium model with incomplete markets (GEI). Formally, our analysis is on the allocative effects of state-contingent income tax reforms. Tax reforms are restricted to be anonymous, publicly and truthfully announced before markets open, and they are required to result in an ex-post constrained efficient allocation. Our main result is to show that there do typically exist contingent tax reforms that are Pareto improving. These reforms, acting directly on the asset span, modify private risk-sharing opportunities. Thus, unlike most of the GEI literature, the type of policy transmission mechanism considered does not rely on second-order, relative spot price effects. Yet, the key welfare effects of our tax reforms are substantially equivalent to those induced through changes in relative spot prices, as, for example, in Geanakoplos and Polemarchakis (1986), Geanakoplos et al. (1990), or in Citanna et al. (2001). Mathematics Subject Classification (2000): 58E17, 46N10, 93B29 Journal of Economic Literature Classification: D52, H21, H24, H25     

A two-step approach to account for unobserved spatial heterogeneity

A two-step approach to account for unobserved spatial heterogeneity. Spatial Economic Analysis. Empirical analysis in economics often faces the difficulty that the data are correlated and heterogeneous in some unknown form. Spatial econometric models have been widely used to account for dependence structures, but the problem of directly dealing with unobserved spatial heterogeneity has been largely unexplored. The problem can be serious particularly if we have no prior information justified by economic theory. In this paper we propose a two-step procedure to identify endogenously spatial regimes in the first step and to account for spatial dependence in the second step. This procedure is applied to hedonic house price analysis.     

Price Discrimination in Input Markets: Downstream Entry and Efficiency

The extant theory on price discrimination in input markets takes the structure of the downstream industry as exogenously given. This paper endogenizes the structure of the downstream industry and examines the effects of permitting third‐degree price discrimination on market structure and welfare. We identify situations where permitting price discrimination leads to either higher or lower wholesale prices for all downstream firms. These findings are driven by upstream profits being discontinuous due to costly entry. Moreover, permitting price discrimination fosters entry which often improves welfare. Nevertheless, entry can also reduce welfare because it may lead to a severe inefficiency in production.     

Do size and unobservable company factors explain stock price reversals?

We use daily price data from the Egyptian stock market and a Loser portfolio of 20 IPOs from the late 1990s that experienced dramatic 1-day price falls in the period 2004 to 2007 to estimate a 2-way fixed effects model of CARs. Observable covariates are company size and turnover growth and unobservables company and period fixed effects. Our results provide evidence of significant price reversal over the first 40 post-event days. Firm size is negatively correlated with post-event CARs, consistently with the argument that small firms have a stronger tendency to price-reverse due to greater informational opacity. But permanent, unobservable company-specific factors, account for a much larger percentage of post-event variation in stock prices and indicate an underlying heterogeneity in investor responses to initial price falls not uncovered before in the literature. Strong negative company effects following a price fall are found to presage reinforcing ‘long term’ price falls and strong positive company effects to presage countervailing ‘long term’ price reversals. At the extremes these company effects are sufficiently large to suggest that a trading strategy based on them would be profitable.     

Fixed effects demeaning in the presence of interactive effects in treatment effects regressions and elsewhere

The present paper shows that cross-section demeaning with respect to time fixed effects is more useful than commonly appreciated, in that it enables consistent and asymptotically normal estimation of interactive effects models with heterogeneous slope coefficients when the number of time periods, T, is small and only the number of cross-sectional units, N, is large. This is important when using OLS but also when using more sophisticated estimators of interactive effects models whose validity does not require demeaning, a point that to the best of our knowledge has not been made before in the literature. As an illustration, we consider the problem of estimating the average treatment effect in the presence of unobserved time-varying heterogeneity. Gobillon and Magnac (2016) recently considered this problem. They employed a principal components-based approach designed to deal with general unobserved heterogeneity, which does not require fixed effects demeaning. The approach does, however, require that T is large, which is typically not the case in practice, and the results reported here confirm that the performance can be extremely poor in small-T samples. The exception is when the approach is applied to data that have been demeaned with respect to fixed effects.     

The no-arbitrage condition and financial markets with heterogeneous information

This paper examines the role of the no-arbitrage condition in financial markets with heterogeneous expectations. We consider a single-period, state-contingent claims model, withM risky securities andS states. There exist two types of heterogeneously informed investors, where the information heterogeneity is defined with respect to either the security payoff matrix, the state probability vector, or state partitions. When the information heterogeneity is defined with respect to either the security payoff matrix or state partitions, the no-arbitrage condition imposes a constraint on the dispersion of information between informed and uninformed investors. Further, the no-arbitrage condition is useful in ascertaining the patterns of heterogeneity among investors that are consistent with equilibrium. However, when the information heterogeneity is defined with respect to state probabilities, the role of the no-arbitrage condition is severely restricted. Finally, the no-arbitrage condition may have important implications for the (necessary and sufficient) conditions for the existence of an equilibrium price vector in financial markets with heterogeneous expectations.     

Aggregation of Heterogeneous Interacting Agents: The Variant Representative Agent Framework

In this paper we have presented a variant of the stochastic aggregation approach which basically consists in exploring the evolution over time of higher moments of the economic units’ distribution. In a sense therefore, we propose to focus on the behavior of a Variant Representative Agent. An application to a classical growth model shows that changes in aggregate output usually associated with Total Factor Productivity in the aggregative interpretation of the framework may be due to changes in the distribution of agents in terms of capital intensity. The application to a model by Gatti et al. (Interaction and market structure, Springer, 2000) shows the efficacy of the method in capturing the evolution over time of the distribution of firms in terms of financial solidity (equity ratio). The method seems general enough to cover a wide range of economic situations in which heterogeneity is relevant and persistent. It seems also simple enough to deserve the attention of the macroeconomist dissatisfied with the RA who wants to derive meaningful and microfounded macroeconomic results.     

The interplay between the Bayesian and frequentist approaches: a general nesting spatial panel data model

The interplay between the Bayesian and Frequentist approaches: a general nesting spatial panel-data model. Spatial Economic Analysis. An econometric framework mixing the Frequentist and Bayesian approaches is proposed in order to estimate a general nesting spatial model. First, it avoids specific dependency structures between unobserved heterogeneity and regressors, which improves mixing properties of Markov chain Monte Carlo (MCMC) procedures in the presence of unobserved heterogeneity. Second, it allows model selection based on a strong statistical framework, characteristics that are not easily introduced using a Frequentist approach. We perform some simulation exercises, finding good performance of the properties of our approach, and apply the methodology to analyse the relation between productivity and public investment in the United States.     

House prices and consumer welfare

We develop a new approach to measuring changes in consumer welfare due to changes in the price of owner-occupied housing. In our approach, an agent's welfare adjustment is defined as the transfer required to keep expected discounted utility constant given a change in current house prices. We demonstrate that, up to a first-order approximation, there is no aggregate change in welfare due to price increases in the existing housing stock. This follows from a simple market clearing condition where capital gains experienced by sellers are exactly offset by welfare losses to buyers. We show that this result holds (approximately) even in a model that accounts for changes in consumption and investment plans prompted by current house price changes. There can, however, be changes in welfare due to additions to the stock of housing, or to changes in the price of renovating and upgrading the existing stock of housing. For the United States, we estimate the welfare cost of house price appreciation to be an average of $127 per household per year over the 1984–1998 period.     

The dynamics of job separation: The case of federal employees

In this paper we develop a model of workers' quit decisions. Using panel data on a sample of US Federal government employees we use maximum-likelihood techniques to determine how much of the observed decline in quits with job tenure is a result of declining individual quit propensities (‘state dependence’) rather than dynamic sample self-selection (‘heterogeneity’). The latter is found to be much more important than the former. The effects of relative Federal government wages and other variables on quits are also estimated. The results are useful for analysing Federal compensation policies.     

Real‐time forecast combinations for the oil price

Baumeister and Kilian (Journal of Business and Economic Statistics, 2015, 33(3), 338–351) combine forecasts from six empirical models to predict real oil prices. In this paper, we broadly reproduce their main economic findings, employing their preferred measures of the real oil price and other real‐time variables. Mindful of the importance of Brent crude oil as a global price benchmark, we extend consideration to the North Sea‐based measure and update the evaluation sample to 2017:12. We model the oil price futures curve using a factor‐based Nelson–Siegel specification estimated in real time to fill in missing values for oil price futures in the raw data. We find that the combined forecasts for Brent are as effective as for other oil price measures. The extended sample using the oil price measures adopted by Baumeister and Kilian yields similar results to those reported in their paper. Also, the futures‐based model improves forecast accuracy at longer horizons.     

Modelling Group Heterogeneity for Small Area Estimation Using M‐Quantiles

Small area estimation typically requires model‐based methods that depend on isolating the contribution to overall population heterogeneity associated with group (i.e. small area) membership. One way of doing this is via random effects models with latent group effects. Alternatively, one can use an M‐quantile ensemble model that assigns indices to sampled individuals characterising their contribution to overall sample heterogeneity. These indices are then aggregated to form group effects. The aim of this article is to contrast these two approaches to characterising group effects and to illustrate them in the context of small area estimation. In doing so, we consider a range of different data types, including continuous data, count data and binary response data.     

Penalized Quantile Regression with Semiparametric Correlated Effects: An Application with Heterogeneous Preferences

This paper proposes new ?₁‐penalized quantile regression estimators for panel data, which explicitly allows for individual heterogeneity associated with covariates. Existing fixed‐effects estimators can potentially suffer from three limitations which are overcome by the proposed approach: (i) incidental parameters bias in nonlinear models with large N and small T ; (ii) lack of efficiency; and (iii) inability to estimate the effects of time‐invariant regressors. We conduct Monte Carlo simulations to assess the small‐sample performance of the new estimators and provide comparisons of new and existing penalized estimators in terms of quadratic loss. We apply the technique to an empirical example of the estimation of consumer preferences for nutrients from a demand model using a large transaction‐level dataset of household food purchases. We show that preferences for nutrients vary across the conditional distribution of expenditure and across genders, and emphasize the importance of fully capturing consumer heterogeneity in demand modeling. Copyright © 2016 John Wiley & Sons, Ltd.