An iterative method for determining the internal rate of return

This paper presents an alternative to the usual iterative method for determining the approximate internal rate of return in capital budgeting. The method developed is based on the standard numerical analysis technique of successive approximations or iterations. The iterations converge to the true internal rate of return provided only that the initial cash outflow is greater than the salvage value. A comparison is made of the rates of convergence of the iteration method, Newton's method and the bisection method. Under certain restrictive conditions, the payback reciprocal is seen to play an important role in all three methods.     

Consumption optimization for recursive utility in a jump-diffusion model

In this paper, we consider a market model with prices and consumption following a jump-diffusion dynamics. In this setting, we first characterize the optimal consumption plan for an investor with recursive stochastic differential utility on the basis of his/her own beliefs, then we solve the inverse problem to find what beliefs make a given consumption plan optimal. The problem is viewed in general for a class of homogeneous recursive utility, and later we choose a logarithmic model for the utility aggregator as an explicitly computable example. When beliefs, represented via Girsanov’s theorem, get incorporated into the model, the change of measure gives rise, up to a transformation, to a backward stochastic differential equation whose generator exhibits a quadratic behavior in the Brownian component and a locally Lipschitz one in the jump component, which is solvable on the basis of some recent results.     

Analysis of a mixed model for ordinal data by iterative re-weighted REML

An estimation procedure will be presented for a class of threshold models for ordinal data. These models may include both fixed and random effects with associated components of variance on an underlying scale. The residual error distribution on the underlying scale may be rendered greater flexibility by introducing additional shape parameters, e.g. a kurtosis parameter or parameters to model heterogeneous residual variances as a function of factors and covariates. The estimation procedure is an extension of an iterative re-weighted restricted maximum likelihood procedure, originally developed for generalized linear mixed models. This procedure will be illustrated with a practical problem involving damage to potato tubers and with data from animal breeding and medical research from the literature.     

Precise computation of a competitive equilibrium of the discrete land market model

This paper provides a finite algorithm to compute a competitive equilibrium of the Alonso-type discrete land market model (known as bid-rent equilibrium) without assuming any condition on the spatial configuration such as monocentricity. The existence of the finite algorithm implies that the discrete land market model is sufficiently tractable for computer simulation analysis (sensitivity analysis) even if the spatial configuration is variable. Specifically, we can evaluate numerically the effects of new routes in a transportation network upon equilibrium rents and commuting mode.     

High-order PLS path model for multi-group analysis: the prosumership service quality model

Quality & Quantity - This study deepening the analysis of prosumership service quality model (PROSERV), a new model for assessing the customer satisfaction developed in order to take...     

Estimating a generalized correlation coefficient for a generalized bivariate probit model

In this paper we consider semiparametric estimation of a generalized correlation coefficient in a generalized bivariate probit model. The generalized correlation coefficient provides a simple summary statistic measuring the relationship between the two binary decision processes in a general framework. Our semiparametric estimation procedure consists of two steps, combining semiparametric estimators for univariate binary choice models with the method of maximum likelihood for the bivariate probit model with nonparametrically generated regressors. The estimator is shown to be consistent and asymptotically normal. The estimator performs well in our simulation study.     

An exact test for a column of the covariance matrix based on a single observation

In this paper, we derive an exact test for a column of the covariance matrix. The test statistic is calculated by using a single observation. The exact distributions of the test statistic are derived under both the null and alternative hypotheses. We also obtain an analytical expression of the power function of the test for the equality of a column of the covariance matrix to a given vector. It is shown that the information contained in a single vector is large enough to ensure a good performance of the test. Moreover, the suggested test can be applied for time-dependent multivariate Gaussian processes.     

An upper bound for the correlation ratio of records

We obtain an upper bound for a measure of the performance of the least squares predictor of the jth record of a sequence of continuous i.i.d random variables as a function of the ith record. We show also that such bound is attainable, except for location and scale parameters, by exponential distributions. This work was supported in part by Ministerio de Educación y Ciencia through Grants PB96-1416-CO2-02 and HA 1997-0123.     

Formulating wald tests of the restrictions implied by the rational expectations hypothesis

In this paper, we examine the small sample properties of alternative formulations of Wald tests of non-linear restrictions implied by the rational expectations hypothesis. A Monte Carlo analysis is presented as well as an example using Canadian aggregate time series data. The evidence indicates that Wald test results are extremely sensitive in small samples to the way in which the non-linear restrictions in such models are parameterized, with a multiplicative form yielding tests of most accurate size. Least squares degrees of freedom adjustments also improve the sample performance of the tests.     

Necessary conditions for admissibility of matrix linear estimators in a multivariate linear model

This article provides necessary conditions for the admissibility of matrix linear estimators of an estimable parameter matrix linear function under two kinds of quadratic matrix loss functions in a multivariate linear model following a family of matrix normal distributions, where the covariance matrix associated is completely unknown. Further it is demonstrated that if a more concrete condition supplied for one of the subdivided conditions is satisfied, then the special condition concerning the Stein problem is necessary for the admissibility of the kind of estimators under each of the loss functions.     

Testing for heteroskedasticity and serial correlation in a random effects panel data model

This paper considers a panel data regression model with heteroskedastic as well as serially correlated disturbances, and derives a joint LM test for homoskedasticity and no first order serial correlation. The restricted model is the standard random individual error component model. It also derives a conditional LM test for homoskedasticity given serial correlation, as well as, a conditional LM test for no first order serial correlation given heteroskedasticity, all in the context of a random effects panel data model. Monte Carlo results show that these tests along with their likelihood ratio alternatives have good size and power under various forms of heteroskedasticity including exponential and quadratic functional forms.     

An iterative approach to the estimation of the abatement costs of harmful emissions

The ability to quantify tradeoffs involved in the process of reducing harmful emissions is essential to successful policy-making in the environmental planning area. The approach by Färe et al. (J Econom 126: 469–492, 2005) to computing point estimates of the marginal abatement costs (MACs) of reducing pollution by estimating the directional output distance function has been gaining popularity in recent years. The contribution of this study is to compute MACs as slopes of the iterated parametric production possibilities frontier (PPF) estimated on the basis of the set of efficient projections of observable output combinations obtained from the parameters of directional output distance function. Policy makers are thus provided with the general shape of the production possibilities set for a polluting technology rather than with a set of point estimates of the MACs. We apply our methodology to a balanced panel of seven Korean manufacturing sectors spanning the period between 1999 and 2009, obtaining theoretically consistent concave PPFs based on a large set of directional output distance vectors. Finally, we estimate the parameters of a directional output distance function corresponding to the iterated PPF.     

权益结合法的发展路径分析

本文以权益结合法在美国的兴衰和在我国的兴起为视角,探讨分析了权益结合法在我国的发展前景。认为应研究确定我国的会计概念框架并用以指导准则的制定,并在制定准则时明确国外准则制定中非技术因素的分量以及相应利益集团的博弈过程和结果,考虑我国的准则是否应受此类非技术因素的影响,并在此基础上对企业合并征求意见稿中的相关问题提出管见。     

An empirical test of a decision theory model for entrepreneurial acts

A decision theory model is presented where the decision to start a firm is assumed to be a rational economic decision of a utility maximizer. The model is tested using data for business births in 82 Mississippi counties over the period 1979-1987. Results of the aggregated model are encouraging but suggest that the alternative to a risky venture is not riskless wage labour. Rather, wage labour also carries a risk which is important in determining whether to start a business. The results indicate that there is a strong economic motivation in entrepreneurial ventures which must be considered in addition to psychological factors. The model suggests that encouragement of entrepreneurial ventures can be based upon lowering thc costs of start-ups and policies that increase the probability of success.     

Asymptotic properties of a correlation coefficient type statistic connected with the general linear model

It is proved that under certain conditions the conditional distribution of the sample multiple correlation coefficient given the ‘other’ observations in a multivariate normal distribution is asymptotically normal. Moreover a second-order approximation for the first moment is given.     

Efficiency of iterative estimators in the regression model with AR(1) disturbances

The mean square error approximation method of Nagar is applied to the iterated Prais-Winsten and (iterated) maximum likelihood estimators of regression coefficients in the model with AR(1) disturbances. Their mean square errors are found to equal that of the two-stage Prais-Winsten estimator at the second-order level of approximation.     

An availability model for the evaluation of equipment alternatives

An availability based model for the evaluation of alternatives in equipment replacement analysis is presented. The expected annual cost of an equipment alternative is developed as a function of availability. The least cost alternative for the desired availability is identified from cost vs. availability curves of the alternatives. A simulation approach is used to determine the availability of existing equipment. The methodology is applied to the evaluation of alternate equipment for the analysis of serum samples in a hospital laboratory.     

An analytical model for the formation of economic clusters

A simple spatial economy derived from microeconomic foundations is presented to gain insight into the formation of economic clusters. In this model, the formation of economic clusters is a consequence of the competition between economic forces that are consistent with atomistic agents maximizing their utility. An analytic approach is used to obtain the evolution of economic clusters. With this approach, the number of clusters which will grow can be predicted. These results are derived in the traditional one-dimensional geometry and extended to the more realistic two-dimensional landscape.     

An investigation of the parameters of a simple mean-field model

In a recent work Gallo et al. (Math Models Methods Appl. Sci. 19:1427–1439, 2009) examined the parameters for a simple mean-field model of social interactions. Their work presented the model, raw data and parameter estimates with associated confidence intervals for a 4-year period. Here the problem is re-examined in greater mathematical detail and associated estimates evaluated. In particular exact results are obtained for a selection of any 3 years and parameters estimated for a 7-year period, the full extent of the data.     

An existence theorem of intertemporal recursive utility in the presence of Lévy jumps

This paper presents an existence theorem for a class of backward stochastic integral equations. The main contribution is a generalization of Duffie and Epstein's [Duffie, D., Epstein, L., 1992. Stochastic differential utility, (Appendix C with Skiadas C.), Econometrica 60, 353–394.] existence theorem of intertemporal recursive utility to allow the information structure to be driven by a Lévy jump process. The existence theorem applies also for a more general class of utility functions, such as recursive utility with habit-formation, and can be used to prove the existence of an equilibrium asset price process as a unique solution to the stochastic Euler equation derived by Ma [Ma, C., 1993b. Valuation of Derivative Securities with Mixed Poisson–Brownian Information and Recursive Utility, McGill University, mimeo.].