Lower bound of cost efficiency measure in DEA with incomplete price information

The conventional cost efficiency model assumes that all the input prices are fixed and known exactly at each decision making unit. In practice, however, exact knowledge of prices is difficult and prices may be subject to variations over very short periods of time. In this paper, we develop a new DEA model, which can be transformed into a special case of bi-level linear program, to calculate the lower bound of CE efficiency from the pessimistic viewpoints based on the shortcomings of the existing approaches. As the input (price) cone of the pessimistic CE model tightens, the objective function converges to the traditional Farrell cost efficiency measure. Numerical examples are used to demonstrate the proposed approach and compare the results with those obtained with the existing approaches.     

Foreign investors and stock price efficiency: Thresholds,underlying channels and investor heterogeneity

This paper examines the relationship between foreign shareholding and stock price efficiency for Malaysian public listed firms over the 2002–2009 sample period. We use stock price delay as an inverse measure of price efficiency, and consider the speed of adjustment to local and global common factor information. The results show that foreign investors accelerate the incorporation of both types of common information into the prices of Malaysian stocks, mainly due to their superior skills in processing systematic market-wide factors. However, we find evidence of optimality in foreign shareholding, suggesting that the efficiency benefit disappears after foreign ownership exceeds a certain threshold level. Further analyses shed lights on the channels and moderating variables driving this non-monotonic relationship. Our disaggregate analysis on foreign investor heterogeneity shows that foreign investors who trade through nominee accounts are elite processors of public market-wide and firm-specific news in the Malaysian stock market.     

Convergence of Prices and Rates of Inflation*

We consider how unit‐root and stationarity tests can be used to study the convergence of prices and rates of inflation. We show how the joint use of these tests in levels and first differences allows the researcher to distinguish between series that are converging and series that have already converged, and we set out a strategy to establish whether convergence occurs in relative prices or just in rates of inflation. Special attention is paid to the issue of whether a mean should be extracted in carrying out tests in first differences and whether there is an advantage to adopting a (Dickey–Fuller) unit‐root test based on deviations from the last observation. The asymptotic distribution of this last test statistic is given and Monte Carlo simulation experiments show that the test yields considerable power gains for highly persistent autoregressive processes with ‘relatively large’ initial conditions. The tests are applied to the monthly series of the consumer price index in the Italian regional capitals over the period 1970–2003.     

Dynamic competitive retail pricing behavior with uncertainty and learning

When competing retailers lack full information about rivals' decision processes, how will dynamic pricing behavior vary from patterns observed in more traditional static or full-information models? We investigate this question in a dynamic alternating-moves duopoly model. Retailers update (linear) conjectures about rivals' future prices in a Bayesian fashion. We show that as observed and expected prices converge, a pricing equilibrium is always achieved, whether or not the conjectured and actual values of the slope of the rival's best response function are consistent. Assuming specific parameter values, we compare equilibrium prices and associated profits in our Bayesian learning model with those obtained under the assumptions of static Nash behavior, collusive behavior and dynamically optimal behavior with full information. We apply the notions of strategic substitutability and strategic complementarity to the analysis and find that when products are strategic complements, conjectures of higher rival price responsiveness lead to higher steady-state prices and profits. The reverse is true for strategic substitutes. We also find that learning about a rival's behavior proceeds more quickly, the less intensely related in demand are products. We find, in general, that equilibrium pricing patterns and profits can vary considerably from those in full-information environments, but that even with grossly wrong beliefs about rival behavior, competing retailers are still attracted to an equilibrium. The analysis suggests not only the value of investigating lessthan-full information situations but also the potential incremental value of signalling greater or less aggressiveness than truly characterizes one's behavior as a strategic option.     

A calibration procedure for analyzing stock price dynamics in an agent-based framework

In this paper we introduce a calibration procedure for validating of agent based models. Starting from the well-known financial model of (Brock and Hommes, 1998), we show how an appropriate calibration enables the model to describe price time series. We formulate the calibration problem as a nonlinear constrained optimization that can be solved numerically via a gradient-based method. The calibration results show that the simplest version of the Brock and Hommes model, with two trader types, fundamentalists and trend-followers, replicates nicely the price series of four different markets indices: the S&P 500, the Euro Stoxx 50, the Nikkei 225 and the CSI 300. We show how the parameter values of the calibrated model are important in interpreting the trader behavior in the different markets investigated. These parameters are then used for price forecasting. To further improve the forecasting, we modify our calibration approach by increasing the trader information set. Finally, we show how this new approach improves the model׳s ability to predict market prices.     

On the Role of Weight Restrictions in Data Envelopment Analysis

This paper examines the role that weight restrictions play in Data Envelopment Analysis (DEA). It is argued that the decision to include a factor (input or output) in a DEA model represents an implicit judgement that the factor has a non-trivial weight. It therefore seems perverse to allow DEA to assign a trivial weight to that factor in assessing the efficiency of a unit. There is therefore a strong case for imposing restrictions on factor weights. However, many existing methods of weight restriction are in practice unwieldy. This paper proposes an alternative approach we term contingent weight restriction which is both practical and intellectually consistent with the DEA philosophy. The paper explores the implications of alternative methods of weight restriction using simulated data from a well known production process.     

Linear and nonlinear dynamic relationships between housing prices and trading volumes

This study applied linear and nonlinear causality tests and estimation models to investigate the efficiency of housing prices and volumes in the United States and its four major regions. The results of this study confirm that housing volumes can function as a price-discovery indicator. According to the nonlinear volatility of housing prices, this study verified numerous hypotheses. Housing returns can also influence housing volume. The results of this study imply that housing price efficiency can vary based on market conditions. Consequently, estimating the behavior of housing prices through a linear model can result in underestimating the information reflected by housing returns.     

Hodges–Lehmann optimality for testing moment conditions

This paper studies the Hodges and Lehmann (1956) optimality of tests in a general setup. The tests are compared by the exponential rates of growth to one of the power functions evaluated at a fixed alternative while keeping the asymptotic sizes bounded by some constant. We present two sets of sufficient conditions for a test to be Hodges–Lehmann optimal. These new conditions extend the scope of the Hodges–Lehmann optimality analysis to setups that cannot be covered by other conditions in the literature. The general result is illustrated by our applications of interest: testing for moment conditions and overidentifying restrictions. In particular, we show that (i) the empirical likelihood test does not necessarily satisfy existing conditions for optimality but does satisfy our new conditions; and (ii) the generalized method of moments (GMM) test and the generalized empirical likelihood (GEL) tests are Hodges–Lehmann optimal under mild primitive conditions. These results support the belief that the Hodges–Lehmann optimality is a weak asymptotic requirement.     

A hybrid DEA-MOLP model for public school assessment and closure decision in the City of Philadelphia

Data envelopment analysis (DEA) is generally used to evaluate past performance and multi objective linear programming (MOLP) is often used to plan for future performance goals. In this study, we establish an equivalence relationship between MOLP problems and combined-oriented DEA models using a direction distance function designed to account for desirable and undesirable inputs and outputs together with uncontrollable variables. This equivalence model can be effectively used to support interactive processes and performance measures designed to establish future performance goals while taking into account the preferences of decision makers (DMs). In particular, it allows DMs to consider different efficiency improvement strategies when subject to budgetary restrictions. The applicability of the proposed method and the efficacy of the procedures and algorithms are demonstrated using a case study where the performance of high schools in the City of Philadelphia is evaluated.     

Farrell efficiency under value and quantity data

In 1957, Farrell introduced a nonparametric method to estimate technical efficiency. His original illustration, however, utilized value-based, rather than quantity-based data (p. 279). This common practice raises the question of how value-based DEA models coincide with quantity-based models. It is well known that the two models coincide when firms face identical prices. In practice, however, prices vary across firms and the two models yield materially different results. We decompose the resulting difference into its technology and firm-related components and then use Farrell’s original data set to show that the expected difference is systematic and one-sided.      

Switching from complete to incomplete information

We construct an elementary mechanism [Dutta, B., Sen, A., Vohra, R., 1995. Nash implementation through elementary mechanisms in economic environments. Review of Economic Design 1, 173–203] that Nash implements the constrained Walrasian correspondence. We extend it to incomplete and non-exclusive information economies by enlarging the message space of agents. In addition, measurability restrictions on allocations with respect to prices proper to constrained rational expectations equilibria are imposed in the outcome function. We show that by imposing such restrictions, the mechanism Bayesian implements the constrained rational expectations equilibrium correspondence. This result shows game-theoretic connections between these two market equilibrium concepts. However, these connections are obtained at the price of strong restrictions on the behavior of agents.     

Random encounters and information diffusion about product quality

This paper explores how social interactions among consumers shape markets. In a two-country model, consumers meet and exchange information about the quality of the goods. As information spreads, demand evolves, affecting the prices and quantities manufactured by profit-maximizing firms. We show that market prices with informational frictions reach the duopoly price with full information at the limit. However, this convergence can take different paths depending on the size asymmetry between countries. In particular, when the country producing the low-quality good is relatively large, the single market does not immediately turn into a duopoly and can be temporarily trapped in a situation of price instability where no Nash equilibrium in pure (but only in mixed) strategies exists and prices can fluctuate between their monopoly and duopoly levels. It follows that the classical price-reducing effects of international trade may take longer to appear. In view of an intense globalization process, understanding how social meetings affect market outcomes is critical for understanding the performance of international economic integration.     

Hierarchies and Groups in DEA

Conventional applications of data envelopment analysis (DEA) presume the existence of a set of similar decision making units, wherein each unit is evaluated relative to other members of the set. Often, however, the DMUs fall naturally into groupings, giving rise first to the problem of how to view the groups themselves as DMUs, and second to the issue of how to deal with several different ratings for any given DMU when groupings can be formed in different ways. In the present paper we introduce the concept of hierarchical DEA, where efficiency can be viewed at various levels. We provide a means for adjusting the ratings of DMUs at one level to account for the ratings received by the groups (into which these DMUs fall) at a higher level. We also develop models for aggregating different ratings for a DMU arising from different possible groupings. An application of these models to a set of power plants is given.     

Piracy and Competition

The effects of (private, small-scale) piracy on the pricing behavior of producers of information goods are studied within a unified model of vertical differentiation. Although information goods are assumed to be perfectly differentiated, demands are interdependent because the copying technology exhibits increasing returns to scale. We characterize the Bertrand–Nash equilibria in a duopoly. Comparing equilibrium prices to the prices set by a multiproduct monopolist, we show that competition drives prices up and may lead to price dispersion. Competition reduces total surplus in the short run but provides higher incentives to create in the long run.     

The influence of seller learning and time constraints on sequential bargaining in an artificial perishable goods market

This paper investigates the formation of prices in a perishable goods market where agents bargain repeatedly through pair-wise interactions. After extensive field observations, we chose to focus on two aspects that seem important to actors of this market: the passage of time and update in judgement when gathering information. The main feature of the market is that a seller bargaining with a buyer has incomplete information about buyer's willingness to pay and is not sure how her trading partner will evaluate an offer or compare it with other options. On the other hand, buyers have limited time to look for goods and cannot meet all possible sellers before making a decision. Hence agents cannot calculate the best price to offer but receive information through limited interactions, and use this information to choose their actions.An agent-based model was built to represent a framework that mimics the observed market institution and where agent's possible behaviors and learning was made as consistent as possible with gathered data. Simulations were run, first for sensitivity analysis concerning main parameters, then to test the dependance of agents’ learning to (a) the time buyers can spend on the market and (b) the frequency of update in learning by sellers. To validate the model, features produced by the simulated market are compared to the stylized facts gathered for negotiation about four goods. We reproduce the main features of the data on the dynamics of offers, transaction prices and agents’ behavior during the bargaining phases.     

A Bayesian approach to imposing curvature on distance functions

The estimated parameters of output distance functions frequently violate the monotonicity, quasi-convexity and convexity constraints implied by economic theory, leading to estimated elasticities and shadow prices that are incorrectly signed, and ultimately to perverse conclusions concerning the effects of input and output changes on productivity growth and relative efficiency levels. We show how a Bayesian approach can be used to impose these constraints on the parameters of a translog output distance function. Implementing the approach involves the use of a Gibbs sampler with data augmentation. A Metropolis–Hastings algorithm is also used within the Gibbs to simulate observations from truncated pdfs. Our methods are developed for the case where panel data is available and technical inefficiency effects are assumed to be time-invariant. Two models—a fixed effects model and a random effects model—are developed and applied to panel data on 17 European railways. We observe significant changes in estimated elasticities and shadow price ratios when regularity restrictions are imposed.     

Short-selling restrictions,takeovers and the wealth of long-run shareholders

In this paper we consider a situation in which a firm may be able to influence the investors’ ability to short-sell its stock. We analyze the effect short-selling restrictions have on the market price and the subsequent effect generated on the market for corporate control. More precisely, we argue that short-selling restrictions may lead to exclusion of pessimistic beliefs and may therefore inflate prices. Thus, if a company is poorly managed and has a stock with strong short-selling restrictions, a profitable takeover will not emerge because of the high stock price. The raider may not have the incentives to acquire the company as its price will be above its fundamental value, conditional on takeover, even accounting for the potential benefits of takeover. We then argue that such effects are detrimental to long-run shareholders and that a value-maximizing strategy is to have a stock with no short-selling restrictions.     

钢材期货价格发现功能研究——基于印度市场信息共享模型的分析

本文借助Johansen协整检验、Granger因果检验、信息共享模型、方差分解等方法进行多层次实证研究,定量地刻画出期货市场在价格发现中作用的大小。研究结果显示：印度板材期货价格和现货价格之间存在长期均衡关系,在价格引导上仅存在现货对期货价格的单向引导关系,期货对现货没有引导关系;通过方差分解发现,现货市场在价格发现功能中处于主导地位,说明印度钢材期货市场效率有待提高,板材期货没有实现其应有的价格发现功能。     

Environmental efficiency measurement and the materials balance condition

The materials balance condition is a fundamental adding up condition, which essentially says that: “what goes in must come out”. In this paper we argue that a number of the recently developed methods of incorporating pollution measures into standard productive efficiency models may be inconsistent with this fundamental condition. We propose an alternative method that involves the incorporation of the materials balance concept into the production model in a similar manner to which price information is normally incorporated. This produces a new environmental efficiency measure that can be decomposed into technical and allocative components, in a similar manner to the conventional cost efficiency decomposition. The approach is illustrated with the case of phosphorus emission on Belgian pig-finishing farms, using data envelopment analysis (DEA) methods. Our results indicate that a substantial proportion of nutrient pollution on these farms can be abated in a cost reducing manner.