Empirical Version Research Articles

Imputing Input Characteristic Values from Optimal Commercial Breed or Variety Choice Decisions: Comment

American Journal of Agricultural EconomicsVolume 77, Issue 4 p. 1054-1058 Comments and Replie Imputing Input Characteristic Values from Optimal Commercial Breed or Variety Choice Decisions: Comment Peter Amer, Peter Amer animal breeding specialist with the Scottish Agricultural College EdinburghSearch for more papers by this authorGlenn Fox, Glenn Fox associate professor of agricultural economics and business University of GuelphSearch for more papers by this author Peter Amer, Peter Amer animal breeding specialist with the Scottish Agricultural College EdinburghSearch for more papers by this authorGlenn Fox, Glenn Fox associate professor of agricultural economics and business University of GuelphSearch for more papers by this author First published: 01 November 1995 https://doi.org/10.2307/1243829Citations: 4AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume77, Issue4November 1995Pages 1054-1058 RelatedInformation

An experimental calibration of the ?Nickel in Garnet? geothermometer with applications

The partitioning of Ni between olivine and garnet in two multi-component compositions was studied as a function of temperature and pressure in a 6–8 type multi-anvil apparatus. Weighted least squares regression of the experimental results for both compositions give a temperature dependence for Ni partitioning between olivine (Ol) and garnet (Gt) of the form: T=−10210(±114)/[lnD Gt/Ol Ni −3.59(±67)] where DGt/Ol/Ni=Ni content of Gt/Ni content of olivine (by weight) and Tis in Kelvin. The pressure effect on Ni exchange between olivine and garnet is estimated to be ∼0.13 J/bar, and should therefore have a negligible effect on the geothermometer, as is demonstrated in the experiments. The experimentally derived “Ni in Gt” geothermometer is in agreement with an extant empirical version between 1100 to 900°C, but the two thermometers produce significantly different results outside of this temperature range.

Performance Attribution Using a Multivariate Intertemporal Asset Pricing Model with One State Variable

AbstractThe stock‐picking and market‐timing abilities of Canadian mutual fund managers were tested using the Jensen (1968) and Lehmann and Modest (1987) tests. The benchmark was Chamberlain's (1988) conditional intertemporal APM with one state variable. Compared to previous tests of the CAPM for Canadian equities, this intertemporal APM explained the conditional expected returns of size‐sorted portfolios of Canadian equities well. Significantly negative stock‐picking and market‐timing abilities were identified. Like Lehmann and Modest (1987), an invariancy problem was identified. The performance inferences are sensitive to the choice of the timevarying risk premia estimates.RésuméCette étude présente une évaluation de la capacitédes gestionnaires de fonds mutuels à identifier les firmes suret/ou sous‐évaluées et à anticiper les mouvements du marchéà partir des tests de Jensen (1968) et Lehmann et Modest (1987). Ces tests s'appuient sur le modèle intertemporel de Chamberlain (1988) fondésur une variable d'état. Comparativement aux études précédentes du modèle CAPM en contexte canadien, le modèle intertemporel explique relativement bien le rendement espéréde portefeuilles construits à partir de la valeur de capitalisation des firmes canadiennes sous‐jacentes. Les résultats, statistiquement significatifs, indiquent que les gestionnaires possèdent des habilités négatives à identifier les firmes sur‐ et/ou sous‐évaluées et à anticiper les mouvements du marché. Comme pour Lehmann et Modest (1987), un problème de robustesse existe puisque différentes estimations d'une prime de risque variable dans le temps amènent différentes conclusions.

A TEST OF A GENERAL EQUILIBRIUM STOCK OPTION PRICING MODEL

An empirical version of the Cox, Ingersoll, and Ross (1985a) call option pricing model is derived, assuming execution price uncertainty in the options market. the pricing restrictions come in the form of moment conditions in the option pricing error. These can be estimated and tested using a version of the method of simulated moments (MSM). Simulation estimates, obtained by discretely approximating the risk‐neutral processes of the underlying stock price and the interest rate, are substituted for analytically unknown call prices. the asymptotics and other aspects of the MSM estimator are discussed. the model is tested on transaction prices at 15‐minute intervals. It substantially outperforms the Black‐Scholes model. the empirical success of the Cox‐Ingersoll‐Ross model implies that the continuous‐time interest rate implicit in synchronous transaction quotes of 90‐day Treasury‐bill futures contracts is an‐albeit noisy‐proxy for the instantaneous volatility on common stock. the process of the instantaneous volatility is found to be close to nonstationary. It is well approximated by a heteroskedastic unit‐root process. With this approximation, the Cox‐Ingersoll‐Ross model only slightly overprices long‐maturity options.

Human gene therapy: down the slippery slope?

The strength of a slippery slope argument is a matter of some dispute. Some see it as a reasonable argument pointing out what probably or inevitably follows from adopting some practice, others see it as essentially a fallacious argument. However, there seems to be a tendency emerging to say that in many cases, the argument is not actually fallacious, although it may be unsubstantiated. I shall not try to settle this general discussion, but merely seek to assess the strength of the slippery slope argument applied to human gene therapy. The structure of my argument will be the following. First, I shall distinguish between three different versions of the slippery slope argument; two logical versions and an empirical one. Next, I will address human gene therapy in terms of each of the three versions, partly relying on slippery slope arguments against this practice that have already surfaced in the literature. I shall argue that neither version pulls through. The logical versions fail primarily because relevant distinctions can be made between different uses of gene therapy, contrary to what the proponents of the arguments claim. The empirical version fails because there seems to be no evidence supporting the claim that we shall in fact slide down the slope if we engage in gene therapy, and because if we accepted the conclusion that we should not allow gene therapy on the basis of the empirical argument, we should have to make very far-reaching and undesirable modifications in health care in general, in order to be consistent. Or at least so I shall argue.

A Landfill Site Evaluation Model That Includes Public Preferences Regarding Natural Resources And Nearby Communities

This paper develops a model that provides an objective framework for evaluating the concerns often cited by members of nearby communities and other state residents when potential sites for solid waste landfills are evaluated. An empirical version of the model is estimated using preference data collected in a paired comparison survey of Rhode Island residents, in which participants identify a preferred site and location for a landfill among two alternatives. The estimated model is used to assign scores to each characteristic describing the natural resources present at a site and the characteristics of the nearby community. The model estimates the proportion of voters who would choose each candidate site in a referendum that includes the complete set of alternatives. This simulated voting mechanism can be used to reduce a long list of technically desirable sites to a shorter list of sites that rank highly according to public preferences regarding natural resources and local community impacts.

A Landfill Site Evaluation Model That Includes Public Preferences Regarding Natural Resources and Nearby Communities

This paper develops a model that provides an objective framework for evaluating the concerns often cited by members of nearby communities and other state residents when potential sites for solid waste landfills are evaluated. An empirical version of the model is estimated using preference data collected in a paired comparison survey of Rhode Island residents, in which participants identify a preferred site and location for a landfill among two alternatives. The estimated model is used to assign scores to each characteristic describing the natural resources present at a site and the characteristics of the nearby community. The model estimates the proportion of voters who would choose each candidate site in a referendum that includes the complete set of alternatives. This simulated voting mechanism can be used to reduce a long list of technically desirable sites to a shorter list of sites that rank highly according to public preferences regarding natural resources and local community impacts.

Time-to-Build, Delivery Lags, and the Equilibrium Pricing of Capital Goods

This paper characterizes the behavior of investment expenditures, optimal capital stocks, and real interest rates in the time-to-build model of investment. The paper derives equilibrium pricing relationships involving the prices of new and used capital and uses these relationships to obtain simple tests of the underlying investment technology. The paper also demonstrates that empirical versions of the delivery lag model are misspecified because the term structure of interest rates over the time horizon for which investment yields productive capital are omitted and that the use of stock market data to measure Tobin's q is inappropriate within the time-to-build model. Copyright 1993 by Ohio State University Press.

Ordering Directional Data: Concepts of Data Depth on Circles and Spheres

Three notions of depth for directional data, angular simplicial depth (ASD), angular Tukey's depth (ATD) and arc distance depth (ADD), are developed and studied. The empirical versions of these depths give rise to center-outward rankings of angular data which may be regarded as extensions of the usual center-outward ranking on the line. Three medians derived from these depths are examined and compared. Applications in nonparametric classification and in implementing the bootstrap to construct confidence regions for directional parameters are briefly discussed.

Boston Naming Test: shortened versions for use in Alzheimer's disease.

Four new 15-item versions of the Boston Naming Test (BNT), a 15-item version used by the Consortium To Establish a Registry for Alzheimer's Disease (CERAD), and three 30-item BNT versions were studied in 26 subjects with Alzheimer's disease (AD) and 26 nondemented, neurologically normal controls. The four 15-item versions were statistically equivalent. On each version, controls performed significantly better than AD subjects, and scores on each could be extrapolated to a complete 60-item BNT score. The CERAD version also differentiated between AD and control subjects, but it was not equivalent to our four versions and could not be as easily extrapolated to a 60-item score. Even and Odd 30-item BNT versions were confirmed to be equivalent, and we further validated a 30-item Empirical Version designed to maximally discriminate between AD and normal subjects. Equivalent 15- or 30-item versions of the BNT will be useful in repeated assessments requiring independent forms of a naming task, as well as in situations where administration of the complete BNT is not practical.

The Asymptotic Joint Distribution of Self-Normalized Censored Sums and Sums of Squares

Empirical versions of appropriate centering and scale constants for random variables which can fail to have second or even first moments are obtainable in various ways via suitable modifications of the summands in the partial sum. This paper discusses a particular modification, called censoring (which is a kind of winsorization), where the (random) number of summands altered tends to infinity but the proportion altered tends to zero as the number of summands increases. Some analytic advantages inherent in this approach allow a fairly complete probabilistic and empirical theory to be developed, the latter involving the study of studentized or self-normalized sums. In particular, the joint asymptotic distributions of the empirically censored quantities of center and scale are determined as well as precise criteria for convergence to each of the allowable limit laws. Applications to the Feller class and domains of attraction are also considered.

An efficiency result for the empirical characteristic function in stationary time‐series models

AbstractIt is shown under general conditions that arbitrarily high asymptotic efficiencies can be obtained when the parameters of a stationary time series are estimated by fitting the characteristic functions of the process to their empirical versions. A consistency and a central limit result are also given.

Empirical Laplace transform and approximation of compound distributions

Letbe i.i.d. non-negative random variables with d.f.Fand Laplace transformL.LetNbe integer valued and independent ofIn many applications one knows that fory→ ∞ and a functionφwhere in turnτis the solution of an equationOn the basis of a sample of sizenwe derive an estimatorτnfor τ by solvingψ(τn, Ln(τn),L′n(τn), · ··) = 0 whereLnis the empirical version ofL.This estimator is then used to derive the asymptotic behaviour ofφ(y, τn, Ln(τn),L′n(τn), · ··). We include five examples, some of which are taken from insurance mathematics.

Empirical Laplace transform and approximation of compound distributions

Let be i.i.d. non-negative random variables with d.f. F and Laplace transform L. Let N be integer valued and independent of In many applications one knows that for y → ∞ and a function φ where in turn τ is the solution of an equation On the basis of a sample of size n we derive an estimator τ n for τ by solving ψ (τ n, Ln(τ n), L′n(τ n), · ··) = 0 where Ln is the empirical version of L. This estimator is then used to derive the asymptotic behaviour of φ (y, τ n, Ln(τ n), L′n(τ n), · ··). We include five examples, some of which are taken from insurance mathematics.

On a Notion of Data Depth Based on Random Simplices

For a distribution $F$ on $\mathbb{R}^p$ and a point $x$ in $\mathbb{R}^p$, the simplical depth $D(x)$ is introduced, which is the probability that the point $x$ is contained inside a random simplex whose vertices are $p + 1$ independent observations from $F$. Mathematically and heuristically it is argued that $D(x)$ indeed can be viewed as a measure of depth of the point $x$ with respect to $F$. An empirical version of $D(\cdot)$ gives rise to a natural ordering of the data points from the center outward. The ordering thus obtained leads to the introduction of multivariate generalizations of the univariate sample median and $L$-statistics. This generalized sample median and $L$-statistics are affine equivariant.

Model-based Bayesian methods for estimating cell proportions in cross-classification tables having ordered categories

Bayesian methods are suggested for estimating proportions in the cells of cross-classification tables having at least one classification with ordered categories. These methods utilize models for cell proportions that incorporate the category orderings. The resulting estimators are smoother and can be much more efficient that the sample proportions, yet they are consistent even if the model chosen for the smoothing does not hold. Two approaches are considered: (1) Bayes estimators using a Dirichlet prior distribution for the proportions: (2) Bayes estimators based on normal prior distributions for association parameters in the saturated loglinear model. In each case, the means of the prior distributions are chosen to satisfy a model for ordered categorical data, such as the uniform association model. Empirical Bayes versions of the two analyses are also given.

Boston naming test in Alzheimer's disease

The 60-item Boston Naming Test (BNT) was administered to 55 subjects: 15 mildly-to-moderately demented patients meeting NINCDS-ADRDA criteria for “probable” Alzheimer's disease (AD), 15 age-equivalent normal control (NC) subjects, and—for purposes of validation—25 additional subjects with other forms of dementia (OD). A cutting score of 51 correctly classified 80% of AD patients and 86% of NC subjects. To facilitate rapid screening of confrontation-naming performance in these populations, three 30-item shortened versions of the BNT were constructed. Even and Odd Versions were equivalent for AD, NC, and OD subjects; high correlations between these two and the 60-item BNT permit easy extrapolation to a total BNT score. A new Empirical Version, derived from performance of our AD and NC reference groups, maintained most of the intergroup discrimination of the full BNT.

On the small sample properties of norm-restricted maximum likelihood estimators for logistic regression models

This paper develops alternatives to maximum likelihood estimators (MLE) for logistic regression models and compares the mean squared error (MSE) of the estimators. The MLE for the vector of underlying success probabilities has low MSE only when the true probabilities are extreme (i.e., near 0 or 1). Extreme probabilities correspond to logistic regression parameter vectors which are large in norm. A competing “restricted” MLE and an empirical version of it are suggested as estimators with better performance than the MLE for central probabilities. An approximate EM-algorithm for estimating the restriction is described. As in the case of normal theory ridge estimators, the proposed estimators are shown to be formally derivable by Bayes and empirical Bayes arguments. The small sample operating characteristics of the proposed estimators are compared to the MLE via a simulation study; both the estimation of individual probabilities and of logistic parameters are considered.

On a notion of simplicial depth

For a distribution F on R(p) and a point x in R(p) the simplicial depth D(x), which is the probability that x be inside a random simplex whose vertices are p + 1 independent observations from F, is introduced. D(x) can be viewed as a measure of depth of the point x relative to F, and its empirical version gives rise to a natural ordering of the data points from the center outward. This ordering provides an approach for detecting outliers in a multivariate data cloud and leads to the introduction of affine equivariant multivariate generalizations of the univariate sample median and L-statistics. This sample median is shown to be consistent for the center of any angularly symmetric distribution.

HOUSEHOLD INCOME AND EXPENDITURE IN EXTENDED INPUT‐OUTPUT MODELS: A COMPARATIVE THEORETICAL AND EMPIRICAL ANALYSIS*

ABSTRACT At the regional level in‐migrant and indigenous workers are likely to have different income levels and consumption propensities. The effects that these differences have upon a local economy are explored within an extended input‐output modeling framework. Two iterative input‐output models, due to Miernyk et al. and Blackwell, are recast as systems of simultaneous equations and are shown to produce identical results. A detailed analysis is made of model structure and a method is outlined for the decomposition of income multipliers. Empirical versions of the two models, for Boulder and Cork, are reconstructed with data from the original studies and are used to make comparisons of the two local economies.