Joint inventory and transshipment decisions with consumer behavioral heterogeneity

Transshipment is an effective method for reducing mismatches between supply and demand among retailers. Consumers attempting to purchase out-of-stock items may wait for transshipment, purchase at another store, or choose not to buy. In this paper, the consumer behavioral heterogeneity is characterized using the transshipment request rate and consumer switching rate. It affects the replenishment and transshipment decisions, as well as the system profits. The inventory replenishment and transshipment decisions are studied in both centralized and decentralized two-location inventory systems with consumer behavioral heterogeneity. We characterize optimal replenishment decisions in a centralized system, prove the existence of a unique Nash equilibrium in a decentralized system with a specific demand distribution, and determine the coordinating transshipment price for some decentralized systems. In numerical studies, the performance of various systems is analyzed for consumers with identical (symmetric) or differing (asymmetric) behavior between retailers. For scenarios with symmetric consumers, a higher transshipment request rate and consumer switching rate resulted in increased total profit in all systems. For scenarios with asymmetric consumers, the retailer with the higher consumer switching rate should reduce ordering in a centralized system but increase ordering in a decentralized system. Moreover, the retailer with the higher transshipment request rate reduces ordering to increase profit, whereas the other retailer increases order quantity yet earns less profit.     

Bayesian estimation of inefficiency heterogeneity in stochastic frontier models

Estimation of the one sided error component in stochastic frontier models may erroneously attribute firm characteristics to inefficiency if heterogeneity is unaccounted for. However, unobserved inefficiency heterogeneity has been little explored. In this work, we propose to capture it through a random parameter which may affect the location, scale, or both parameters of a truncated normal inefficiency distribution using a Bayesian approach. Our findings using two real data sets, suggest that the inclusion of a random parameter in the inefficiency distribution is able to capture latent heterogeneity and can be used to validate the suitability of observed covariates to distinguish heterogeneity from inefficiency. Relevant effects are also found on separating and shrinking individual posterior efficiency distributions when heterogeneity affects the location and scale parameters of the one-sided error distribution, and consequently affecting the estimated mean efficiency scores and rankings. In particular, including heterogeneity simultaneously in both parameters of the inefficiency distribution in models that satisfy the scaling property leads to a decrease in the uncertainty around the mean scores and less overlapping of the posterior efficiency distributions, which provides both more reliable efficiency scores and rankings.     

Structural estimation of jump-diffusion processes in macroeconomics

This paper shows how to solve and estimate a continuous-time dynamic stochastic general equilibrium (DSGE) model with jumps. It also shows that a continuous-time formulation can make it simpler (relative to its discrete-time version) to compute and estimate the deep parameters using the likelihood function when non-linearities and/or non-normalities are considered. We illustrate our approach by solving and estimating the stochastic AK and the neoclassical growth models. Our Monte Carlo experiments demonstrate that non-normalities can be detected for this class of models. Moreover, we provide strong empirical evidence for jumps in aggregate US data.     

Structural estimation of stock market participation costs

This paper develops and estimates a dynamic model of stock market participation, where consumers' decisions regarding stock market participation are influenced by participation costs. The practical significance of the participation costs is considered as being a channel through which financial education programs can affect consumers' investment decisions. Using household data from the Panel Study of Income Dynamics, I estimate the magnitude of the participation cost, allowing for individual heterogeneity in it. The results show the average stock market participation cost is about 4–6% of labor income; however, it varies substantially over consumers' life. The model successfully predicts the level of the observed participation rate and the increasing pattern of stock market participation over the consumers' life cycle.     

Structural and behavioral robustness in applied best-practice regulation

Benchmarking methods, primarily non-parametric techniques such as Data Envelopment Analysis, have become well-established and informative tools for economic regulation, in particular in energy infrastructure regulation. The axiomatic features of the non-parametric methods correspond closely to the procedural and economic criteria for good practice network regulation. However, critique has been voiced against the robustness of best-practice regulation in presence of uncertainty regarding model specification, data definition and collection. Incorrect data may result from structural sources, such as heterogeneous technologies; deterministic approaches applied to stochastic data generation processes or poorly defined scope of activity. Specifically within regulation, reporting may also be biased through individual gaming or collusive behavior, including the intentional provision of absurd data in order to stall or perturb regulatory process (here called maverick reporting). We review three families of outlier detection methods in terms of their function and application using a data set from Swedish electricity distribution, illustrating the different types of outliers, contrasting with the actual analysis ex post. This paper investigates the foundation of the critique both conceptually and by describing the actual state-of-the-art used in energy network regulation using frontier analysis models in Sweden (2000–2003) and in Germany (2007-). Finally, the paper concludes on the role of outlier detection as a mean to implement regulation with higher robustness.     

Dissecting the myth of the house price in Chinese metropolises: allowing for behavioral heterogeneity among investors

This paper aims to demystify the housing boom in Chinese metropolises by allowing for behavioral heterogeneity among investors. We construct an agent-based model where investors are categorized into two groups: fundamentalists and chartists. In addition, the investment strategy switching is allowed between these two groups contingent on the historical performance. Using the data of five Chinese metropolises over the period 2008–2014, the results suggest that chartists dominate the housing market and make the house price maintain an upward trend, while fundamentalists play a stabilizing role. Specifically, fundamentalists can serve as a “price anchor” in the market, because the proportion of the fundamentalists is negatively associated with both the growth rate of the house price and the deviation relative to the fundamental value. Overall, the impact of the chartists on the house price is much greater than that of the fundamentalists, which contributes to the ever-increasing house price in Chinese metropolises.

     

Structural equation modeling and the latent linearity hypothesis in social and behavioral research

The issue of sensitivity of the structural equation modeling (SEM) methodology to violations of the underlying hypothesis of linear latent relationships is the focus of this paper. The identity of overall goodness-of-fit indices of an initially considered linear latent pattern model and of an equivalent model not making this assumption exemplifies the lack of routinely available global means within the methodology to evaluate the linearity assumption. It is next focused on the sensitivity of SEM to violations of presumed linearity for a general, nonlinear pattern of true relationship. The results of a simulation study are then presented which demonstrate that latent correlations and percentage explained variance as well as parameter standard errors and model residuals can provide critical information about violation of latent linearity, and should therefore also be focused on when examining departures from linear relationships at the latent level in applications of the SEM methodology in social and behavioral research.     

Structural estimation of caloric intake,exercise, smoking,and obesity

The escalating rate of obesity in the US highlights the importance of understanding the causes for this rise. In this paper I employ the First, Second, and Third National Health and Nutrition Examination Surveys to estimate a structural model of the determinants of adult obesity. To control for the potential endogeneity of some explanatory variables, such as caloric intake (adjusted for activity level) and smoking, a set of reduced form equations for these outcomes is estimated simultaneously with the obesity equation. To identify each equation, I use an array of state-level characteristics as instrumental variables. Trends in these variables shed light on the sources of the rapid increase in obesity since 1980.     

The case for heterogeneity of cities

The general similarity of the results of comparative statics in a semiclosed and in a fully closed city have been demonstrated by Pines and Sadka (Journal of Urban Economics 20, 1–20, 1986). The objective of this paper is to determine if the consequences of different forms of public regulation of the urban land market are also invariant with respect to the type of city. The conclusion is that while there are well-defined consequences of such controls on metropolitan area and land values in a semiclosed city, the impacts in a fully closed city are generally ambiguous. Therefore, proposals for the introduction of zoning and density regulation have to be city-specific and take into consideration the pattern of land ownership and the extent of leakage of urban land rent income.     

The behavioral study of accountants: A new school of behavioral research in accounting

Through a series of related studies the behavioral study of accountants has evolved as a body of knowledge focused on the practice of public accounting as a professionalized bureaucracy with special behavioral conditions surrounding the employment accessions (hiring) and separations (turnover). These studies have developed a common core of research findings over the past 25 years and now form the foundation of a new school of behavioral research in accounting.     

Within-group heterogeneity and civil war

This study offers a bargaining model of conflict in which the government offers a transfer to an opposition group to preclude civil war. Members of the opposition are heterogeneous in income and ideology, and heterogeneity generates disagreement about whether to accept the government’s offer. We assume that the probability that the government’s offer will preclude conflict increases continuously with the number of opposition group members who agree to accept it. When within-group heterogeneity is large, the number of members who are receptive to the government’s offer is less responsive to an increase in the transfer level. In this situation, the government must substantially increase its transfer to attract the support of the opposition. Subsequently, as peace becomes more costly for the government, negotiations are likely to break down.     

Technological heterogeneity and corporate investment

We propose an importance-sampling procedure to improve the computational performance of the simulated method of moments (SMM) for the estimation of structural models with fixed parameter heterogeneity. The main advantage of the procedure is that it does not require to simulate observations every time that the structural parameters change during the minimization of the SMM criterion function. We illustrate the use of our method by estimating a neoclassical model of investment for a sample of US manufacturing companies, allowing the technological parameters to vary across firms.     

Consumption-based CAPM with belief heterogeneity

This paper finds that the risk–return relationship of the consumption-based CAPM is robust to the heterogeneity in agents׳ beliefs. First, the effect of disagreement cancels out in the limit as risk tolerance approaches zero. Second, although low risk aversion and large disagreement can significantly distort the security market line (SML) and the effect is amplified in a dynamic model, per capita volatility of consumption growth is implausibly high compared to empirical estimates from microeconomic data. Third, increasing risk aversion and lowering disagreement levels can help to reduce per capita volatility, however the impact of disagreement on the SML also become negligible.     

Agglomeration elasticities and firm heterogeneity

This paper examines three key issues encountered when estimating the relationship between agglomeration and multi factor productivity (‘agglomeration elasticities’): the sorting of heterogeneous firms, the convexity of agglomeration effects, and the challenges of identifying the impact of persistent spatial differences in effective density. We use a firm-level panel containing production data together with detailed information on the geographic location of employment, covering a high proportion of the New Zealand economy. We are able to control for heterogeneity along firm, region, and industry dimensions, and to estimate separate agglomeration elasticities across industries and regions. Sorting leads to upward biased elasticity estimates but using firm fixed effects can lead to downward bias due to the highly persistent nature of agglomeration variables. Our preferred estimates control for sorting across regions and industries. Overall, we find a positive agglomeration elasticity of 0.066. Within industries and, to a lesser extent within regions, there is pronounced variation in the strength of agglomeration effects, and evidence of decreasing returns to agglomeration. High density areas attract firms that benefit most from agglomeration.     

Growth,unemployment and heterogeneity

The paper analyzes unemployment in a medium-run growth model, where aggregate demand and supply interact, using a top-down approach. The aim of the essay is the study of a nonlinear system where both aggregate demand and supply are endogenous and generate bounded unemployment, followed by a methodological effort direct to identify possible lines of convergence with the agent based models (ABM) approach. This is a by-product of the presence of heterogeneity in the model. Heterogeneity acts through two different channels and operates among class of agents: it comes into the aggregate consumption function where households are assumed employed or unemployed; it changes the learning process of pessimists and optimists. The analysis is carried on through simulations. The resulting system is fairly stable to changes in main structural parameters. On one hand, autonomous demand drives the dynamics of the system, while heterogeneity in the consumption function, due to the presence of unemployment, strengthens the links with supply aspects. On the other hand, both the rate of growth of labor productivity and labor supply are endogenous. Two major results are obtained. First, unemployment allows the so called Harrodian reconciliation between aggregate demand and supply. Second, unemployment remains bounded meaning that the interaction between aggregate demand and supply thwarts instability. These results are in keeping with those obtained by means of a bottom-up approach, typical of ABM. Possible explanations and implications of this convergence are put forward and open the venue to further deepening of complementarities among the two modeling strategies.

     

An axiomatic theory of heterogeneity and homogeneity

Summary Indices of heterogeneity and homogeneity are used in biology and ecology as well as in other fields of scientific research, e.g. economics, genetics, antropology, sociology. With respect to these indices, reference is made frequently to information theory. In this paper it is shown that especially recent developments in statistical information theory can contribute to the measurement of heterogeneity and homogeneity. They can lead to a more fundamental and unifying approach and bring together both heterogeneity and homogeneity indices in one axiomatically founded theory. Therefore a generalized heterogeneity index is introduced axiomatically. Algebraic, analytic and geometrical properties are investigated. Special attention is paid to the interpretation of these properties and to the choices of the values of the parameters for practical applications. Based on this generalized heterogeneity index, it is possible to given an axiomatic characterization for a class of homogeneity indices. The properties of this class are the reverse of those of the heterogeneity index. Finally, some potential measures for heterogeneity or homogeneity change are discussed.Presently with Delft University of Technology, Department of Electrical Engineering, Information Theory Group, P.O. Box 5031, 2600 GA Delft, The Netherlands.     

Mean estimation bias in least squares estimation of autoregressive processes

Estimation of the parameters of an autoregressive process with a mean that is a function of time is considered. Approximate expressions for the bias of the least squares estimator of the autoregressive parameters that is due to estimating the unknown mean function are derived. For the case of a mean function that is a polynomial in time, a reparameterization that isolates the bias is given. Using the approximate expressions, a method of modifying the least squares estimator is proposed. A Monte Carlo study of the second-order autoregressive process is presented. The Monte Carlo results agree well with the approximate theory and, generally speaking, the modified least squares estimators performed better than the least squares estimator. For the second-order process we also considered the empirical properties of the estimated generalized least squares estimator of the mean function and the error made in predicting the process one, two and three periods in the future.     

Computation in duration models with heterogeneity

This paper examines the use of Hermite polynomial quadrature to evaluate certain integrals in the maximum likelihood estimation of duration models.     

Unobserved heterogeneity in event history models

This paper demonstrates the effect of unobserved heterogeneity in event history models and discusses parametric methods to include unobserved factors into the models. Using data on career trajectories of German males, the application of models with unobserved heterogeneity is shown.     

Insider,outsider and information heterogeneity

In financial markets, although the insider has superior information relative to the outsider, the outsider may possess some information the insider can’t precisely observe. This work investigates the impacts of information heterogeneity between the insider and outsider based on Foster and Viswanathan (1994). It shows that the less the insider knows about the outsider, the more she commits to aggressive trading, enabling her to earn more at the cost of outsider’s losses. Meanwhile, information heterogeneity improves the liquidity and benefits noise traders.