Bayesian estimation of a random coefficient model

This paper carries out a Bayesian analysis of the Hildreth-Houck (1968) random coefficient model and applies it to some cross-section production function data. Posterior distributions for mean coefficients, actual coefficients, variances and variance ratios are derived. The variance ratio posteriors are largely uninformative but they do lead to relatively informative densities on the variances, and the problem of negative variance estimates, obtained with previous techniques, is overcome. Posterior densities for the mean coefficients are not extremely sensitive to the variance ratios.     

An application and test for a random coefficient model in Bangladesh agriculture

This paper deals with efficiency question by estimating four production functions for four different regions in connection with Bangladesh agriculture. Hildreth and Houck's (1968) random coefficient method was found more suitable than OLS after conducting an appropriate test for this. In contrast to earlier studies, 24 piece-wise regressions have been fitted for each index of efficiency considering all four regions and six different ranges of farm size instead of a single regression so that the relationship could be studied more closely. The study clearly indicates higher efficiency for smaller farms.     

An alternative model for fair share allocation of lower income housing

A linear programming model was developed and presented for fair-share allocation of lower income housing as an alternative to existing heuristic models. The model is applied for the Middlesex County region in pursuit of a regional fair-share of lower income housing needs for the year 1975 for each township in the county. The results are presented and compared with those of the Court's allocation, held by the Superior Court of New Jersey in May 1976 for the Middlesex County region.     

An alternative model for the analysis of variance with random effects

The standard model for the analysis of variance with random effects implies, for the case of two independent variables, that single effects must be tested not against the error, but against the interaction mean squares. This causes, in comparison with the fixed effects AV, a considerable loss of test power, particularly for the 2 × 2 table. An alternative modelling of the interaction effect is proposed which completely avoids the loss of power.     

An alternative procedure for taking a random sample

Summary The procedure proposed consists in going through the population to be sampled item by item deciding each time with probability p whether the item at hand shall be incorporated in the sample. The "distances" between successive items in the sample will then form a random sample from a geometric distribution. A series of these random distances can easily be produced on a computer and can be conveniently used for taking the sample required. In some cases this method may have its advantages over the conventional use of a table of random numbers.     

Testing for a unit root in a random coefficient panel data model

This paper proposes new unit root tests in the context of a random autoregressive coefficient panel data model, in which the null of a unit root corresponds to the joint restriction that the autoregressive coefficient has unit mean and zero variance. The asymptotic distributions of the test statistics are derived and simulation results are provided to suggest that they perform very well in small samples.     

A bayesian analysis of a random coefficient model in a simple keynesian system

The marginal propensity to consume in a simple Keynesian model is treated as a random coefficient. This gives rise to the problem of quotient of random variables, i.e., the Fieller-Creasy problem. The Bayesian and maximum likelihood estimators are compared in sampling experiments. The Bayesian estimators have smaller mean squared errors than the maximum likelihood estimators. Marginal posterior probability density functions for a given sample are also presented.     

Estimating intergenerational schooling mobility on censored samples: consequences and remedies

In this paper we estimate the impact of parental schooling on child schooling, focus on the problem that children who are still in school constitute censored observations, and evaluate three solutions to it: replacement of observed with expected years of schooling, maximum likelihood approach, and elimination of all school‐aged children. Using intergenerational data from the Wisconsin Longitudinal Study we test how the three correction methods deal with censored observations. The one that treats parental expectations as if they were realizations seems to fix the censoring problem quite well. Copyright © 2009 John Wiley & Sons, Ltd.     

A structural analysis of the correlated random coefficient wage regression model

We estimate a dynamic programming model of schooling decisions in which the log wage regression function is set within a correlated random coefficient model. We show that estimates of the dynamic programming model can be used to obtain a number of treatment effects, including the local average treatment effect (LATE). However, unlike LATE parameters obtained in a standard IV framework, our LATE estimates are obtained without imposing separability between individual specific heterogeneity and schooling choices and are therefore not subject to a “monotonicity” restriction. We find that returns to schooling are characterized by a high degree of dispersion across individuals.     

Certificate-of-need regulation and the diffusion of innovations: A random coefficient model

In this paper, we examine empirically the effect that certificate-of-need regulation by state health planning organizations has had on the speed of diffusion of a relatively new medical technology—haemodialysis. Specifically, we test the hypothesis that a requirement that investments be subject to certificate-of-need review has significantly slowed the rate of adoption of this particular treatment modality. In subjecting this hypothesis to empirical verification, we estimate a random coefficient model. This approach allows us to make more efficient use of the available data than the traditional two-stage approach to modelling diffusion processes wherein separate logistic functions are first estimated over the time series observations followed by hypothesis tests conducted over the cross-sectional observations. We find evidence that certificate-of-need regulation slows the spread of haemodialysis technology.     

Estimation of sons' intergenerational earnings mobility in the presence of censoring

Based on intergenerational data from the Panel Study of Income Dynamics, I provide estimates of income mobility across generations for men. Special attention is paid to issues of censoring caused by a son's unemployment. Employing non‐parametric bounds estimates, I illustrate that previous income mobility estimates rely heavily on (unjustified) assumptions of exogenous selection. Assuming a son's potential income is instead a function of his reason for unemployment and work history, I re‐estimate mobility. Allowing for sampling variability, the range of feasible slopes consistent with these modified bounds restrictions is 0.27 to 0.55. Copyright © 2002 John Wiley & Sons, Ltd.     

Urban spatial structure: An analysis with a varying coefficient model

This paper proposes a varying coefficient model (VCM) to introduce city- and tract-specific variables into the exponential density functions used to study urban spatial structure. Since the selected city- and tract-specific characteristics may be subject to control by policy action and themselves comparatively easily projected on the basis of time, the VCM model can be used for both forecasting and policy analysis even though estimated from cross-sectional data. The results show that questions about the appropriateness of the exponential functional form and specification errors associated with the omission of city- and tract-specific variables can be handled by the VCM model. The paper demonstrates the usefulness of the VCM model as a tool for policy analysis and projection.     

A link between random coefficient autoregressive models and some agent based models

An agent based model (ABM), where each agent makes decisions by using the sum of two signals, is proposed. The first is related to the fundamental information while the second comes from trader’s idiosyncratic noise. This model entails the switching between two groups called fundamentalist and noise traders. Additionally, if the price impact function is log-linear, then the dynamic of log asset prices belongs to the class of random coefficient autoregressive RCA(p) models, which are known to share important stylized facts of financial prices.     

基于修正Nash谈判模型的科技创新合作收益分配研究

科技创新合作收益的分配对合作的可持续发展至关重要,目前还缺乏行之有效的模型和方案。文章利用NASH博弈的思想对两人收益分配问题展开讨论,进而扩展到多人收益分配问题,得出多人收益分配博弈的一个Nash均衡解。为反映各主体在科技创新收益分配中的权重,对收益分配的Nash谈判模型进行调整,从而得出修正的纳什均衡解。由此展开科技创新合作收益分配的方案探讨,为科技创新合作的可持续发展奠定理论基础。     

A note on the unbiasedness of Swamy's estimator for the random coefficient regression model

In this note the estimator proposed by Swamy (1970) for the random coefficient regression model is proved to be unbiased under fairly general conditions. In addition, the conditions under which the mean of the estimator exists are derived.