Conceptual and empirical status of mental constructs in the analysis of action

A basic methodological difficulty in the study of psychological processes is how to conceptualize and observe mental events. Part of the difficulty resides in the terminology which frequently involved implicit transitions from one, general, usage to a very specific interpretation which may not be adequate to test the proposed hypotheses. Earlier denials of the possibility of studying such events have now been replaced by an eclectic, but little analyzed and articulated, attitude. As a consequence of this state of affairs it is not uncommon to encounter cases of models being widely accepted in spite of superficial handling of some of the key concepts and a lack of pertinent data to test the models. Several examples are discussed to illustrate these general propositions, taken from psychophysics, personality, judgement, attribution theory and the study of the effects of reward on intrinsic motivation.     

An Approximate Test for Homogeneity of Correlated Correlation Coefficients

This paper develops and evaluates an approximate procedure for testing homogeneity of an arbitrary subset of correlation coefficients among variables measured on the same set of individuals. The sample may have some missing data. The simple test statistic is a multiple of the variance of Fisher r-to-z transformed correlation coefficients relevant to the null hypothesis being tested and is referred to a chi-square distribution. The use of this test is illustrated through several examples. Given the approximate nature of the test statistics, the procedure was evaluated using a simulation study. The accuracy in terms of the nominal and the actual significance levels of this test for several null hypotheses of interest were evaluated. This revised version was published online in June 2006 with corrections to the Cover Date.     

考虑结构突变的单位根检验程序研究——基于“新息异常值模型”的Perron检验分析

Perron检验是一种考虑结构突变的单位根检验方法,检验统计量的分布依赖于数据生成过程中所包含的确定性趋势和所选取的检验回归式;而在实证分析中真实的数据生成过程是未知的,这使得单位根检验缺乏必要依据,因而探寻科学有效的单位根检验程序是受到广泛关注的问题。基于此,本文在"IO模型"分析框架下,依据Perron检验提出了一套考虑结构突变的单位根检验程序,并通过蒙特卡洛模拟分析了该程序在有限样本情形下的表现。本研究完善了带有结构突变的单位根检验理论,为实证分析提供了有益的建议和参考。     

A martingale approach for testing diffusion models based on infinitesimal operator

I develop an omnibus specification test for diffusion models based on the infinitesimal operator. The infinitesimal operator based identification of the diffusion process is equivalent to a “martingale hypothesis” for the processes obtained by a transformation of the original diffusion model. My test procedure is then constructed by checking the “martingale hypothesis” via a multivariate generalized spectral derivative based approach that delivers a N(0,1) asymptotical null distribution for the test statistic. The infinitesimal operator of the diffusion process is a closed-form function of drift and diffusion terms. Consequently, my test procedure covers both univariate and multivariate diffusion models in a unified framework and is particularly convenient for the multivariate case. Moreover, different transformed martingale processes contain separate information about the drift and diffusion specifications. This motivates me to propose a separate inferential test procedure to explore the sources of rejection when a parametric form is rejected. Simulation studies show that the proposed tests have reasonable size and excellent power performance. An empirical application of my test procedure using Eurodollar interest rates finds that most popular short-rate models are rejected and the drift misspecification plays an important role in such rejections.     

Exact permutation tests for non-nested non-linear regression models

This paper proposes exact distribution-free permutation tests for the specification of a non-linear regression model against one or more possibly non-nested alternatives. The new tests may be validly applied to a wide class of models, including models with endogenous regressors and lag structures. These tests build on the well-known J test developed by Davidson and MacKinnon [1981. Several tests for model specification in the presence of alternative hypotheses. Econometrica 49, 781–793] and their exactness holds under broader assumptions than those underlying the conventional J test. The J-type test statistics are used with a randomization or Monte Carlo resampling technique which yields an exact and computationally inexpensive inference procedure. A simulation experiment confirms the theoretical results and also shows the performance of the new procedure under violations of the maintained assumptions. The test procedure developed is illustrated by an application to inflation dynamics.     

Assessing the presence of harmful collinearity and other forms of weak data through a test for signal-to-noise

Data weaknesses (such as collinearity) reduce the quality of least-squares estimates by inflating parameter variances. Standard regression diagnostics and statistical tests of hypothesis are unable to indicate such variance inflation and hence cannot detect data weaknesses. In this paper, then, we consider a different means for determining the presence of weak data based on a test for signal-to-noise in which the size of the parameter variance (noise) is assessed relative to the magnitude of the parameter (signal). This test is combined with other collinearity diagnostics to provide a test for the presence of harmful collinearity and/or short data. The entire procedure is illustrated with an equation from the Michigan Quarterly Econometric Model. Tables of critical values for the test are provided in an appendix.     

Test of Bernoulli success probability in inverse sampling for nearer alternatives using adaptive allocation

This paper provides a test procedure for the problem of testing Bernoulli success probability in the case of costly trials when an inverse sampling is carried out. The proposed test is based on a two population adaptive sampling scheme used in clinical trials. Some exact and asymptotic results related to the test are studied. The proposed procedure is applicable where the alternatives are not too far from the null hypothetical value.     

土地使用与交通的整合:新城市主义和理性增长

文章的主要目标是评论美国交通与土地利用整合的实践,同时试图针对中国的城市规划实践提出建议.文章由三个部分组成.第一部分介绍城市理性增长作为区域尝试来促进土地利用与交通的整合;第二部分简要评述用以土地利用和交通整合的定量模型和评价可以用于土地利用与交通整合的指标体系;第三部分介绍新城市主义.     

MANAGERIAL AND ORGANIZATIONAL FACTORS ASSOCIATED WITH COMPANY PERFORMANCE PART I

T his paper utilizes information collected on more than eighty British companies and on about 800 senior managers working in them. It is in two parts. Part I starts by outlining problems involved in identifying influences on company performance. It then describes the sources of data analysed in the paper. The remainder of Part I examines the view that certain managerial and organizational attributes will tend to raise levels of performance whatever the type of company and its operating circumstances. Another approach takes the view that what makes for good performance is contingent upon the type of company and the prevailing situation. This is examined against our data in Part II of the paper. Part II concludes with an assessment of present knowledge on the managerial and organizational concomitants of company performance and the practical implicatons to be drawn from it.     

Explosive Asset Price Bubble Detection with Unknown Bubble Length and Initial Condition

Recent research has proposed a method of detecting explosive processes that is based on forward recursions of OLS, right‐tailed, Dickey–Fuller [DF] unit root tests. In this paper, an alternative approach using GLS DF test statistics is considered. We derive limiting distributions for both mean‐invariant and trend‐invariant versions of OLS and GLS‐based Phillips, Wu and Yu (2011, International Economic Review 52, 201–226) [PWY] test statistics under a temporary, locally explosive alternative. These limits are shown to be dependent on both the value of the initial condition and the start and end points of the temporary explosive regime. Local asymptotic power simulations show that a GLS version of the PWY statistic offers superior power when a large proportion of the data is explosive, but that the OLS approach is preferred for explosive periods of short duration as a proportion of the total sample. These power differences are magnified by the presence of an asymptotically non‐negligible initial condition. We propose a union of rejections procedure that capitalizes on the respective power advantages of both OLS and GLS‐based approaches. This procedure achieves power close to the effective envelope provided by the two individual PWY tests across all settings of the initial condition and length of the explosive period considered in this paper. These results are shown to be robust to the point in the sample at which the temporary explosive regime occurs. An application of the union procedure to NASDAQ prices confirms the empirical value of this testing strategy.     

A generalization of Friedman's rank statistic

Abstract  In this paper a very natural generalization of the two-way analysis of variance rank statistic of F riedman is given. The general distribution-free test procedure based on this statistic for the effect of J treatments in a random block design can be applied in general two-way layouts without interactions and with different numbers of the continuous observations per cell provided the design scheme is connected. The asymptotic distribution under the null hypothesis of the test statistic is derived. A comparison with the method of m rankings of B enard and van E lteren is made. The disadvantage of B enard and van E lteren's test procedure is that the number of observations per block does influence the statistic twice, namely firstly by the number itself, as it should, and see ondly by the level of the ranks which will be different in different blocks if the numbers of observations per block are different. The proposed test statistic is not sensitive to differences in the levels of the ranks caused by the different numbers of observations per block. The test is derived from considerhg the K ruskal -W allis statistics per block.
Finally, the results of simulation experiments are given. The simulation is carried out for three designs and a number of normal location alternatives and gives some information about the power of the suggested test procedure. A comparison is made with B enard and van E lteren's test and with the classical analysis of variance technique. For some simple orthogonal designs the exact null distributions of B enard and van E lteren's test and the proposed test are compared.     

Statistical inference on restricted partial linear regression models with partial distortion measurement errors

We consider the estimation and hypothesis testing problems for the partial linear regression models when some variables are distorted with errors by some unknown functions of commonly observable confounding variable. The proposed estimation procedure is designed to accommodate undistorted as well as distorted variables. To test a hypothesis on the parametric components, a restricted least squares estimator is proposed under the null hypothesis. Asymptotic properties for the estimators are established. A test statistic based on the difference between the residual sums of squares under the null and alternative hypotheses is proposed, and we also obtain the asymptotic properties of the test statistic. A wild bootstrap procedure is proposed to calculate critical values. Simulation studies are conducted to demonstrate the performance of the proposed procedure, and a real example is analyzed for an illustration.     

Testing the specification of multivariate models in the presence of alternative hypotheses

In this paper we propose a non-nested hypothesis test for testing the specification of a multivariate econometric model in the presence of an alternative model which purports to explain the same phenomenon. We demonstrate that the new test statistic tends to minus the same random variable as the CPD test statistic introduced by Pesaran and Deaton (1978), provided that the truth is ‘close’ to the null hypothesis. Since the new test is simpler to compute than the multivariate CPD test, it would seem to be the procedure of choice.     

A COMPARISON OF THE POWERS OF A GENERALIZED FRIEDMAN'S RANK TEST AND AN ALIGNED RANK PROCEDURE BASED ON SIMULATION

This paper presents the results of an experimental determination by Monte Carlo techniques of the power functions of a generalized Friedman's rank test based on "standardized" ranks and a proposed test procedure based on aligned ranks for orthogonal designs. The simulation is carried out for five orthogonal designs and a number of Normal location alternatives and gives some information about the difference in power of the two test procedures for some orthogonal designs.     

Testing nested or non-nested hypotheses

This paper presents a test procedure for nested or non-nested hypotheses. The test statistic is based on the difference between two estimators of the pseudo-true value as defined for instance by Sawa. This statistic is similar to the usual Wald statistic in the case of nested hypotheses and it can be replaced by an asymptotically equivalent one deduced from the score function.     

The part-period balancing algorithm and its look ahead-look back feature: A theoretical and experimental analysis of a single stage lot-sizing procedure

This paper investigates the discrete Part-Period Balancing (PPB) lot-sizing algorithm and its optional feature, the Look Ahead-Look Back tests. PPB is the most commonly used dynamic lot-sizing procedure in practice and it has also been tested extensively in simulation experiments. Although its overall cost performance, relative to other heuristics, have been fairly good, a fundamental flaw with the model has been noted in the literature. This deficiency leads to poor performance under certain conditions.In this paper a simple adjustment to the main algorithm is analytically derived under the assumptions of a constant demand rate and an infinite planning horizon. The adjustment leads to an optimal behavior for the PPB heuristic under the stated conditions. Subsequent experimental analysis through simulation of lot-sizing performance in environments with time-varying, discrete demand shows that the proposed adjustment leads to significant cost reductions.This paper also analyzes the Look Ahead-Look Back tests which is the distinguishing feature between the PPB procedure and the Least Total Cost algorithm. The tests were devised to improve the cost performance of the PPB heuristic by marginally adjusting each tentative lot-size. The effect of the Look Ahead-Look Back tests have, however, never been verified in the literature. The tests have undergone some changes over time, when they have been included in commercial software packages for inventory management. We suggest yet another modified version in this paper.In the last portion of the paper, the cost effectiveness of the Look Ahead-Look Back tests is confirmed through simulation. That is, when used together with the original PPB procedure, they lead to an improved cost performance. It is also shown that a combination of these tests and the adjustment to the PPB procedure mentioned earlier leads to an even lower average total cost. All cost improvements are statistically significant. It is finally noted that the Look Ahead-Look Back tests perform poorly in certain constant demand situations. Additional analytic and experimental analysis shows that these results stem from a dominance of the Look Back test over the Look Ahead test, leading to the former test being performed more often. This can easily be corrected, however, by checking for sufficient variability in the data before the Look Back test is employed.     

Bootstrap and Asymptotic Tests of Long-run Relationships in Cointegrated Systems

Hypothesis testing on cointegrating vectors based on the asymptotic distributions of the test statistics are known to suffer from severe small sample size distortion. In this paper an alternative bootstrap procedure is proposed and evaluated through a Monte Carlo experiment, finding that the Type I errors are close to the nominal signficance levels but power might be not entirely adequate. It is then shown that a combined test based on the outcomes of both the asymptotic and the bootstrap tests will have both correct size and low Type II error, therefore improving the currently available procedures.     

Another look at the Tail Area Influence Function

A new way of computing the Tail Area Influence Function (TAIF) exactly is proposed and a new finite sample robustness measure, based on the TAIF, is introduced. The main properties of this robustness measure are also studied, for both finite and asymptotic sample sizes. Next, a very accurate approximation to the finite sample power function of a test is obtained; this is based on the TAIF plus an iterative procedure. The results are valid when there are no nuisance parameters.     

The behaviour of the Lagrangian multiplier test in testing the orders of an ARMA-model

Summary The Lagrange multiplier test for testing the order of an ARMA-model is investigated. It is shown that it exhibits some pathologies stemming from the special properties of parameter spaces of ARMA-models. As a consequence one has to be careful in using the LM-test in this context. Furthermore results of this paper are used in a subsequent paper [Pötscher, 1983], to show the consistency of an order estimation procedure based on Lagrange multiplier tests, described there.     

The power of four tests of autocorrelation in the linear regression model

The power of each of four tests of first-order autocorrelation in the linear regression model is determined for a simple and multiple regression model whose parameters are presumed to be known. The tests are: Durbin-Watson bounds test, a test based on Theil's best linear unbiased scalar estimator, a test devised by Abrahamse, Koerts and Louter, and an exact test devised by Durbin.For positive values of the coefficient of autocorrelation the Durbin-Watson bounds test is generally better than the tests based on the estimator proposed by Abrahamse, Koerts and Louter, the best linear unbiased scalar estimator, and the Durbin exact test. For negative values of the coefficient of autocorrelation, the pattern of results is mixed for all four test procedures. A byproduct of these experiments is the demonstrated feasibility of enumerating the distribution of the Durbin-Watson test statistic for any regression matrix and thus eliminating the region of indeterminacy from the Durbin-Watson test procedure.