A Bootstrap Stationarity Test for Predictive Regression Invalidity

In order for predictive regression tests to deliver asymptotically valid inference, account has to be taken of the degree of persistence of the predictors under test. There is also a maintained assumption that any predictability in the variable of interest is purely attributable to the predictors under test. Violation of this assumption by the omission of relevant persistent predictors renders the predictive regression invalid, and potentially also spurious, as both the finite sample and asymptotic size of the predictability tests can be significantly inflated. In response, we propose a predictive regression invalidity test based on a stationarity testing approach. To allow for an unknown degree of persistence in the putative predictors, and for heteroscedasticity in the data, we implement our proposed test using a fixed regressor wild bootstrap procedure. We demonstrate the asymptotic validity of the proposed bootstrap test by proving that the limit distribution of the bootstrap statistic, conditional on the data, is the same as the limit null distribution of the statistic computed on the original data, conditional on the predictor. This corrects a long-standing error in the bootstrap literature whereby it is incorrectly argued that for strongly persistent regressors and test statistics akin to ours the validity of the fixed regressor bootstrap obtains through equivalence to an unconditional limit distribution. Our bootstrap results are therefore of interest in their own right and are likely to have applications beyond the present context. An illustration is given by reexamining the results relating to U.S. stock returns data in Campbell and Yogo (2006 Campbell, J. Y. and Yogo, M. (2006), “Efficient Tests of Stock Return Predictability,” Journal of Financial Economics, 81, 27–60.[Crossref], [Web of Science ®] , [Google Scholar]). Supplementary materials for this article are available online.     

Visual extended enterprise engineering and operation-embedding knowledge management and work execution

This paper describes a new approach to extended enterprise engineering and operation-embedding knowledge management and work-tops for work execution. The approach is based on web technologies and a new technology we call active knowledge models (AKM). By developing and using AKMs of extended enterprises, most methodologies, work environments and business solutions will converge. Enterprises will be integrated by externalized shareable knowledge. During forming and managing of extended enterprises, knowledgesharing infrastructures and the process of generating operational solutions will be simplified and facilitated. Extended enterprises will be engineered and managed as reflective, selfadapting AKMs. By using process-oriented methods to externalize internal and tacit knowledge, the AKM technology provides an environment of work-tops and views to produce, share, cultivate and manage situated knowledge. This knowledge will be applied and managed as competences and skills, and as improved methods. AKMs let us benefit from the intrinsic properties of knowledge. They facilitate convergence of methodologies and integration of technologies.     

A Bayesian View of Nominal Money and Real Output Through a New Classical Macroeconomic Window

This study investigates the empirical evidence on the effects of unanticipated changes in nominal money on real output in 47 countries when viewed through a window (i.e., likelihood function) that assumes the neutrality of anticipated changes. Using a Bayesian predictivist approach, it provides a pedagogical Bayesian analysis of generated regressor models in the face of specification uncertainty involving, among other things, multiple unit roots and trend stationary alternatives.     

Selection of regress or va riables when E(Y) is an unknown honlinear function

We consider the problem of deciding which of a set of p independent variables x₁ X₂J x_s we are to regard as being functionally involved in the mean of a dependent normal random variable Y and estimating E( Y) in terms of the chosen x's. This mean is an unknown function (assumed to be doubly differentiable) of some or all of the x's, so that the problem is of wide relevance. We approximate to the hypersurface in two different ways, and select within each approximation:

(a)For the situation where the mean of Y is assumed to be a linear function of the x's, we use ono of the optimum methods of selection.

(b)More generally, in the space of the X's the function will be approximately linear in a relatively small region. Accordingly this p-dimensional space is subdivided into smaller regions by a clustering procedure, and a hyperplane if fitted with in each region to aproximate to the unknown responce surface.An adaption of an optimum-regressor-selection procedure is then used to assist in the selection of the regressors

Approximate F tests are given to choose between models, including deciding how many x's to retain. Alternatively: the application of Akaike's Extended Maximum Likelihood Principle provides another way of choosing between the models and of selecting regressor variables. The methods are applied to data on glass manufacture.     

Topp–Leone generated family of distributions: Properties and applications

We introduce a new family of distributions based on a one-parameter distribution exhibiting bathtub-shaped hazard rates. We study the mathematical properties of the family and estimate its parameters by the method of maximum likelihood. Finally, the usefulness of the family is illustrated using a real dataset.     

Efficient score tests for heteroskedasticity in micro-economics

Kruskal's theorem is used to provide simple and elegant alternative derivations of the efficiency of some two step estimators (2SE) for models containing anticipated and unanticipated variables. Several new results are established: 2SE is not efficient for a structural equation with current and lagged values of both anticipated and unanticipated variables; 2SE is always efficient for the parameter associated with the current unanticipated variable, and for the parameter associated with the lagged unanticipated variable if there is no lagged dependent variable in the expectations equation; the inclusion of additional regressors in the structural equation and contemporaneous correlation of the structural and expectations errors can both be analysed in a straightforward manner; the single-equation generalized least squares estimator can be as efficient as the systems maximum likelihood estimator.     

Cointegration and direct tests of the rational expectations hypothesis

The paper is concerned with direct tests of the rational expectations hypothesis (REH) in the presence of stationary and non-stationary variables. Alternative methods of converting qualitative survey responses into quantitative expectations series are examined. Testing of orthogonality and the issue of generated regressors for models estimated by two step methods are re-evaluated when the variable to be explained is stationary. A methodological approach for testing the REH is provided for models using qualitative response data when there are unit roots and cointegration, and alternative reasons are examined for rejecting the null hypothesis of orthogonality. The usefulness of cointegration analysis for both the probability and regression conversion procedures is also analysed. Cointegration is found to be directly applicable for the probability conversion approach with uniform, normal and logistic distributions of expectations and for the linear regressicn conversion approach. In the light of new techniques, an existing empirical example testing the REH for British manufacturing firms is re-examined and tested over an extended data set.     

Functional-coefficient cointegration models in the presence of deterministic trends

In this article, we extend the functional-coefficient cointegration model (FCCM) to the cases in which nonstationary regressors contain both stochastic and deterministic trends. A nondegenerate distributional theory on the local linear (LL) regression smoother of the FCCM is explored. It is demonstrated that even when integrated regressors are endogenous, the limiting distribution is the same as if they were exogenous. Finite-sample performance of the LL estimator is investigated via Monte Carlo simulations in comparison with an alternative estimation method. As an application of the FCCM, electricity demand analysis in Illinois is considered.     

Exploring the Quality of Life of People in North Eastern and Southern Thailand

The assumption that development brings not only material prosperity but also a better overall quality of life lies at the heart of the development project. Against this, critics assert that development can undermine social cohesion and threaten cultural integrity. Rarely, however, is the impact of development on well-being rigourously analysed using empirical data. This is what the Wellbeing in Developing Countries Group at the University of Bath aims to do drawing on fieldwork carried out in four developing countries, which addresses the themes of resources, needs, agency and structure, and subjective Quality of life (QoL). The first phase of the QoL research in Thailand aimed to explore the categories and components of quality of life for people from different backgrounds and locations with the aim of developing methods for QoL assessment in the third phase of the WeD QoL research. The study presents data obtained from rural and peri-urban sites in Southern and Northeastern Thailand (two villages in Songkhla and three in Khon Kaen, Mukdaharn, and Roi-et). Participants were divided into six groups by gender and age, and were divided again by religion (Buddhist and Muslim) and wealth status in the South. Data collection was conducted between October and December 2004 using focus group discussions, semi-structured interviews, and the Person Generated Index. Content analysis was used for data analysis. The use of a qualitative approach enabled the gathering of empirical data that reflects the sources of difficulty and happiness in the lives of participants. Respondents identified 26 aspects to their quality of life, including family relations, health and longevity, income and having money, jobs, housing, education, debt, and so on. The results reveal clear similarities and differences in the role of traditions, religious beliefs, and values in the lives of people living in remote rural or peri-urban areas in Northeastern and Southern Thailand. These results, together with the findings from Peru, Ethiopia, and Bangladesh, will inform the rest of the WeD research and be used to develop measures to assess the quality of life of people living in developing countries.     

Cointegration and direct tests of the rational expectations hypothesis

The paper is concerned with direct tests of the rational expectations hypothesis (REH) in the presence of stationary and non-stationary variables. Alternative methods of converting qualitative survey responses into quantitative expectations series are examined. Testing of orthogonality and the issue of generated regressors for models estimated by two step methods are re-evaluated when the variable to be explained is stationary. A methodological approach for testing the REH is provided for models using qualitative response data when there are unit roots and cointegration, and alternative reasons are examined for rejecting the null hypothesis of orthogonality. The usefulness of cointegration analysis for both the probability and regression conversion procedures is also analysed. Cointegration is found to be directly applicable for the probability conversion approach with uniform, normal and logistic distributions of expectations and for the linear regressicn conversion approach. In the light of new techniques, an existing empirical example testing the REH for British manufacturing firms is re-examined and tested over an extended data set.