Portfolio choice in the model of expected utility with a safety-first component

Decisions in Economics and Finance - The standard problem of portfolio choice between one risky and one riskless asset is analyzed in the model of expected utility with a safety-first component...     

Discrete choice models and the housing price and travel to work elasticities of location demand

Multinomial logit and nested logit models of mode choice in travel to work and housing location choice are estimated from 1970 U.S. census data aggregated to small zones of the Chicago SMSA. The estimated models are then used to derive the “housing rent,” “travel time,” and “travel cost” elasticities of location demand. The effects of sampling variation, sample size, attribute inclusion, model specification, and estimation method on the estimated elasticities are evaluated and found to be important. The elasticities are also compared and found to agree with those obtained from other discrete choice models and, in the case of “housing rent,” with estimates obtained from models based on other theoretical structure.     

Maximum score estimation of the stochastic utility model of choice

This paper introduces a class of robust estimators of the parameters of a stochastic utility function. Existing maximum likelihood and regression estimation methods require the assumption of a particular distributional family for the random component of utility. In contrast, estimators of the ‘maximum score’ class require only weak distributional assumptions for consistency. Following presentation and proof of the basic consistency theorem, additional results are given. An algorithm for achieving maximum score estimates and some small sample Monte Carlo tests are also described.     

Graphical procedures for identifying functional form in binary discrete choice models: A Case Study of Revealed Tenure Choice

This paper introduces procedures for plotting and analysing partial residuals for binary logit choice models. Seen within the general context of a movement away from purely inferential statistical model-building towards more ‘data-analytical’ or exploratory approaches, these graphical methods are presented as offering significant advantages over established methods of identifying the functional forms of discrete choice models. An empirical example is developed in the context of revealed tenure choices in London, England, in which a number of revisions are made to the functional form in the light of the analysis of partial residual plots. These results are discussed in relation to the dynamic and policy-dominated British housing market.     

Information criteria for impulse response function matching estimation of DSGE models

We propose new information criteria for impulse response function matching estimators (IRFMEs). These estimators yield sampling distributions of the structural parameters of dynamic stochastic general equilibrium (DSGE) models by minimizing the distance between sample and theoretical impulse responses. First, we propose an information criterion to select only the responses that produce consistent estimates of the true but unknown structural parameters: the Valid Impulse Response Selection Criterion (VIRSC). The criterion is especially useful for mis-specified models. Second, we propose a criterion to select the impulse responses that are most informative about DSGE model parameters: the Relevant Impulse Response Selection Criterion (RIRSC). These criteria can be used in combination to select the subset of valid impulse response functions with minimal dimension that yields asymptotically efficient estimators. The criteria are general enough to apply to impulse responses estimated by VARs, local projections, and simulation methods. We show that the use of our criteria significantly affects estimates and inference about key parameters of two well-known new Keynesian DSGE models. Monte Carlo evidence indicates that the criteria yield gains in terms of finite sample bias as well as offering tests statistics whose behavior is better approximated by the first order asymptotic theory. Thus, our criteria improve existing methods used to implement IRFMEs.     

Indeterminacy in discrete-time infinite-horizon models with non-linear utility and endogenous labor

We consider a discrete-time two-sector model with sector specific externalities in which the technologies are given by CES functions with asymmetric elasticities of capital–labor substitution, and the preferences of the representative agent are given by a CES additively separable utility function defined over consumption and leisure. We first show that when the labor supply is infinitely elastic, the steady state is always saddle-point stable, no matter what the elasticity of intertemporal substitution in consumption and the size of externalities are. We then prove that when the elasticity of intertemporal substitution in consumption is sufficiently large, local indeterminacy requires a low enough elasticity of the labor supply.     

Asymptotic results and tests for the choice of approximative models in nonlinear two-phases regression models, heteroscedatic case

This paper is devoted to the study of the least squares estimator of f for the classical, fixed design, nonlinear model X (t _i)=f(t _i)+ε(t _i), i=1,2,…,n, where the (ε(t _i))_i=1,…,n are independent second order r.v.. The estimation of f is based upon a given parametric form. In Brodeau (1993) this subject has been studied in the homoscedastic case. This time we assume that the ε(t _i) have non constant and unknown variances σ²(t _i). Our main goal is to develop two statistical tests, one for testing that f belongs to a given class of functions possibly discontinuous in their first derivative, and another for comparing two such classes. The fundamental tool is an approximation of the elements of these classes by more regular functions, which leads to asymptotic properties of estimators based on the least squares estimator of the unknown parameters. We point out that Neubauer and Zwanzig (1995) have obtained interesting results for connected subjects by using the same technique of approximation. Received: February 1996     

Calculation of scale elasticities in DEA models: direct and indirect approaches

The qualitative characterisation of returns to scale in DEA has been a research issue the last decade. However, quantitative information provides the ultimate information. This paper presents two ways of obtaining numerical values of scale elasticity by an indirect approach using efficiency scores and dual variables for radial projections of inefficient points to the frontier, and a direct approach that is more general and powerful and directly evaluates numerically scale elasticity at any point on the DEA surface along intersections with planes. The direct and indirect approaches are compared using real data and a very high correspondence is found.     

Place utility,attribute tradeoff,and choice behavior in an intra-urban migration context

This study develops a unique methodology for analyzing intraurban migration with emphasis on housing and neighborhood attributes and preferences. When applied to a typical midwestern metropolitan area, the methodology reveals that safety and security from crime and quality of construction are the most important attributes to the home buyer. Property tax rates and nearness to work were much less important. Analysis of the intra-urban migration process through attribute satisfaction ratings for different homes revealed that the greatest increases in satisfaction were expected for those variables previously considered most important in an abstract sense.     

MBTI性格类型与旅行社部门职能岗位的匹配研究

文章首先对MBTI理论的国内外研究情况进行了简单阐述,接着对互联网+时代背景下旅行社各部门的职能岗位进行了较为全面的解析,最后,在构建岗位与性格类型匹配理论模型的基础之上,分析了旅行社各部门职能岗位与人才性格特征的匹配状况。     

Tests of seasonal integration and cointegration in multivariate unobserved component models

This paper considers tests of seasonal integration and cointegration for multivariate unobserved component models. First, the locally best invariant (LBI) test of the null hypothesis of a deterministic seasonal pattern against the alternative of seasonal integration is derived for a model with Gaussian i.i.d. disturbances and deterministic trend. Then the null hypothesis of seasonal cointegration is considered and a test for common nonstationary components at the seasonal frequencies is proposed. The tests are subsequently generalized to account for stochastic trends, weakly dependent errors and unattended unit roots. Asymptotic representations and critical values of the tests are provided, while the finite sample performance is evaluated by Monte Carlo simulation experiments. Finally, the tests are applied to the series of industrial production of the four largest countries of the European Monetary Union. It is found that Germany does not appear to cointegrate with the other countries at most seasonal frequencies, while there seems to exist a common nonstationary seasonal component between France, Italy and Spain. Copyright © 2006 John Wiley & Sons, Ltd.     

On rankings and top choices in random utility models with dependent utilities

Different aggregate preference orders based on rankings and top choices have been defined in the literature to describe preferences among items in a fixed set of alternatives. A useful tool in this framework is constituted by random utility models, where the utility of each alternative, or object, is represented by a random variable, indexed by the object, which, for example, can capture the variability of preferences over a population. Applications are derived in diverse research fields, including computer science, management science and reliability. Recently, some stochastic ordering conditions have been provided for comparing alternatives by means of some aggregate preference orders in the case of independent random utility variables by Joe (Math Soc Sci 43:391–404, 2002). In this paper we provide new conditions, based on some joint stochastic orderings, for aggregate preference orders among the alternatives in the case of dependent random utilities. We also provide some examples of application in different research fields.      

The optimal choice of moments in dynamic panel data models

This paper derives an approximation of the mean square error (MSE) of the GMM estimator in dynamic panel data models. The approximation is based on higher-order asymptotic theory under double asymptotics. While first-order theory under double asymptotics provides information about the bias, it does not provide enough information about the variance of the estimator. Higher-order theory enables us to obtain information about the variance. From this result, a procedure for choosing the number of instruments is proposed. The simulations confirm that the proposed procedure improves the precision of the estimator.     

Monte Carlo evidence on the choice between sample selection and two-part models

This Monte Carlo study examines the relative performance of sample selection and two-part models for data with a cluster at zero. The data are drawn from a bivariate normal distribution with a positive correlation. The alternative estimators are examined in terms of means squared error, mean bias and pointwise bias. The sample selection estimators include LIML and FIML. The two-part estimators include a naive (the true specification, omitting the correlation coefficient) and a data-analytic (testimator) variant.In the absence of exclusion restrictions, the two-part models are no worse, and often appreciably better than selection models in terms of mean behavior, but can behave poorly for extreme values of the independent variable. LIML had the worst performance of all four models. Empirically, selection effects are difficult to distinguish from a non-linear (e.g., quadratic) response. With exclusion restrictions, simple selection models were significantly better behaved than a naive two-part model over subranges of the data, but were negligibly better than the data-analytic version.     

Forecasting accuracy and the choice of first difference or percentage change regression models

Regression models used by forecasters are often formulated in terms of the first differences or percentage changes of the variables. A recently developed maximum likelihood procedure permits the researcher to determine whether the first difference or percentage change model is superior. In this paper we apply this new method to several forecasting models from the literature and then determine whether or not the correct functional form improves forecasting accuracy. Results indicate that when either the first difference or percentage change model can he rejected in favor of the other, then superior forecasts can be obtained by using the correct form.     

Simple tests for sample selection bias in censored and discrete choice models

This paper presents two simple tests of sample selection bias for models where the primary equation of interest has a censored or discrete dependent variable. The first test is derived as a conditional moment test and can be implemented in a regression-based framework. The second test is an extension of the testing procedures proposed by Heckman (1979) and Vella (1993) and is a t-test on a constructed variable in an auxiliary equation. The utility of the tests is illustrated in a model determining the receipt of work conditioned nonwage labour income over a subsample of working women.     

The asymptotic distribution of the sum of weighted squared residuals in binary choice models

It is claimed by some authors that the distribution of the sum of weighted squared residuals, used as a goodness of fit measure in binary choice models, behaves for large n as a x²_n– k–1 distribution. This claim seems to be based on a false analogy with the well–known Pearson x² statistic for frequency tables with a fixed number of cells and cell sizes tending to infinity. We derive the asymptotic (normal) distribution and show that the approximation by the x² distribution in general will not be valid. A new x² test is proposed based on the asymptotic normality of the measure.     

A note on an application of the trade-off method in evaluating a utility function

In this note we suggest a possible use for the trade-off technique to exclude possible forms of the utility function that are common to the same set of assumptions. Out discussion is focused on the specific case of two attributes. This case is becoming more common in coping with practical problems in the healthcare field, where the two attributes are life years and health status.