Normal tests for unit roots based on instrumental variable estimators

For estimating unit roots of autoregressive processes, we introduce a new instrumental variable (IV) method which discounts large values of regressors corresponding to the unit roots. Based on the IV estimator, we propose new unit root tests whose limiting null distributions are standard normal. Observation at time t is adjusted for mean recursively by the sample mean of observations up to the time t. The powers of the proposed tests are better than those of the Dickey–Fuller tests and are comparable to those of the tests based on the weighted symmetric estimator, which are known to have the best power against stationary alternatives.     

Bayes least squares linear estimation of densities

Linear, least squares statistical methods in which the "parameters" are interpreted as random variables were introduced by Whittle, and further developed by Hartigan and others. They are applied here to the problem of estimating the coefficients in an orthogonal expansion of a multivariate density, given a simple random sample.     

Maximum likelihood estimation for arma models in the presence of ARMA errors

An ARMA(p, q) process observed with an ARMA(c, d) error has an ARMA (p + c, k) representation with k = max(c + q, p + d) whose parameters satisfy some nonlinear constraints. Identification of the model is discussed. We develop Newton-Raphson estimators for the ARMA(p + c, k) process which take advantage of the information contained in the nonlinear restrictions. Explicit expressions for the derivatives of the restrictions are derived.     

Entropy-Based Moment Selection in the Presence of Weak Identification

Hall et al. (2007 Hall , A. R. , Inoue , A. , Jana , K. , Shin , C. (2007). Information in generalized method of moments estimation and entropy based moment selection. Journal of Econometrics 138:488–512.[Crossref] , [Google Scholar]) propose a method for moment selection based on an information criterion that is a function of the entropy of the limiting distribution of the Generalized Method of Moments (GMM) estimator. They establish the consistency of the method subject to certain conditions that include the identification of the parameter vector by at least one of the moment conditions being considered. In this article, we examine the limiting behavior of this moment selection method when the parameter vector is weakly identified by all the moment conditions being considered. It is shown that the selected moment condition is random and hence not consistent in any meaningful sense. As a result, we propose a two-step procedure for moment selection in which identification is first tested using a statistic proposed by Stock and Yogo (2003 Stock , J. H. , Yogo , M. ( 2003 ). Testing for weak instruments in linear IV regression . Discussion paper, Kennedy School of Government, Harvard University, Cambridge, MA . [Google Scholar]) and then only if this statistic indicates identification does the researcher proceed to the second step in which the aforementioned information criterion is used to select moments. The properties of this two-step procedure are contrasted with those of strategies based on either using all available moments or using the information criterion without the identification pre-test. The performances of these strategies are compared via an evaluation of the finite sample behavior of various methods for inference about the parameter vector. The inference methods considered are based on the Wald statistic, Anderson and Rubin's (1949 Anderson , T. W. , Rubin , H. ( 1949 ). Estimation of the parameters of a single equation in a complete system of stochastic equations . Annals of Mathematical Statistics 20 : 46 – 63 .[Crossref] , [Google Scholar]) statistic, Kleibergen (2002 Kleibergen , F. ( 2002 ). Pivotal statistics for testing structural parameters in instrumenatl variables regression . Econometrica 70 : 1781 – 1803 .[Crossref], [Web of Science ®] , [Google Scholar]) K statistic, and combinations thereof in which the choice is based on the outcome of the test for weak identification.     

Precarious work: A global perspective

Precarious work is universal, though its forms and consequences vary across countries due to institutional, cultural, and historical differences. This article reviews recent research on precarious work from a global perspective, emphasizing the comparative and interdisciplinary research needed for a comprehensive understanding of the structural transformations in contemporary capitalism that promote precarious work. The article has three foci. First, research that details the diverse forms of precarious work, which have become increasingly heterogeneous as national labor markets have been interwoven with global production networks. Second, research on precarious work that emphasizes its disparate impacts for women, youth, the elderly, racial and ethnic minority groups, and migrants, revealing an articulation of precarity and social cleavages. Third, research on the politics associated with precarious work and how some precarious workers have successfully organized and mobilized their interests, such as by unionizing and becoming involved in electoral politics. Still, questions remain regarding precarious work: how precarious workers differ from regular workers in representing their interests and demands and whether precarious workers are a new, independent social class or remain part of a changing working class. Finally, topics for future research on the global dimensions of precarious work are discussed.     

Disclosures and Asset Returns

Public information in financial markets often arrives through the disclosures of interested parties who have a material interest in the reactions of the market to the new information. When the strategic interaction between the sender and the receiver is formalized as a disclosure game with verifiable reports, equilibrium prices can be given a simple characterization in terms of the concatenation of binomial pricing trees. There are a number of empirical implications. The theory predicts that the return variance following a poor disclosed outcome is higher than it would have been if the disclosed outcome were good. Also, when investors are risk averse, this leads to negative serial correlation of asset returns. Other points of contact with the empirical literature are discussed.