Pooled Panel Unit Root Tests and the Effect of Past Initialization

This paper analyzes the role of initialization when testing for a unit root in panel data, an issue that has received surprisingly little attention in the literature. In fact, most studies assume that the initial value is either zero or bounded. As a response to this, the current paper considers a model in which the initialization is in the past, which is shown to have several distinctive features that makes it attractive, even in comparison to the common time series practice of making the initial value a draw from its unconditional distribution under the stationary alternative. The results have implications not only for theory, but also for applied work. In particular, and in contrast to the time series case, in panels the effect of the initialization need not be negative but can actually lead to improved test performance.     

The Local Power of the CADF and CIPS Panel Unit Root Tests

Very little is known about the local power of second generation panel unit root tests that are robust to cross-section dependence. This article derives the local asymptotic power functions of the cross-section argumented Dickey–Fuller Cross-section Augmented Dickey-Fuller (CADF) and CIPS tests of Pesaran (2007), which are among the most popular tests around.     

Small-Sample Improved Seasonal Unit Root Tests for Trending and Breaking Series

In this article three unit root tests that allow for a break in both the seasonal mean and linear trend of the data are proposed. The tests, which can be seen as small-sample corrected versions of already known asymptotic tests, are shown to perform very well in simulations, and much better than their asymptotic counterparts.     

Does Formal Education for Older Workers Increase Earnings? — Evidence Based on Rich Data and Long‐term Follow‐up

Governments in Europe, Canada and the USA have expressed an ambition to stimulate education of older. In this paper, we analyse if there are effects on annual earnings of formal education for participants aged 42–55 at the time of enrolment in 1994–95. The analysis explores longitudinal population register data stretching from 1982 to 2007. The method used is difference‐in‐differences propensity score matching based on a rich set of covariates, including indicators of health and labor market marginalization. Our findings underline the importance of long follow up periods and imply positive effects for women, especially so for women with children, and no significant average earnings effects for men. These results differ from earlier studies but are stable to several alternative assumptions regarding unobservable characteristics. Data further indicate that the gender gap in our estimates may stem from differences in underlying reasons for enrolment.     

Rethinking the Univariate Approach to Panel Unit Root Testing: Using Covariates to Resolve the Incidental Trend Problem

In an influential article, Hansen showed that covariate augmentation can lead to substantial power gains when compared to univariate tests. In this article, we ask if this result extends also to the panel data context? The answer turns out to be yes, which is maybe not that surprising. What is surprising, however, is the extent of the power gain, which is shown to more than outweigh the well-known power loss in the presence of incidental trends. That is, the covariates have an order effect on the neighborhood around unity for which local asymptotic power is negligible.     

A panel study of migration,self-selection and household real income

The impact of migration on income for Swedish multi-adult households is examined using panel data pertaining to a sample of stable household constellations during the period 1980–1990. In contrast to previous studies, data on household disposable income is employed in estimating the income function. The empirical results indicate no significant effect on real disposable income from migration. In addition, the hypothesis of no self-selection, or zero correlation between the errors in the decision function and the income function, cannot be rejected. Received: 10 May 1995 / Accepted: 14 August 1996     

A Parametric Estimation Procedure for Relapse Time Distributions

In a relapse clinical trial patients who have recovered from some recurrent disease (e.g.,ulcer or cancer) are examined at a number of predetermined times. A relapse can be detected either at one of these planned inspections or at a spontaneous visit initiated by the patient because of symptoms. In the first case the observations of the time to relapse, X, is interval-censored by two predetermined time-points. In the second case the upper endpoint of the interval is an observation of the time to symptoms,Y . To model the progression of the disease we use a partially observable Markov process. This approach results in a bivariate phase-type distribution for the joint distribution of (X,Y). It is a flexible model which contains several natural distributions for X, and allows the conditional distributions of the marginals to smoothly depend on each other. To estimate the distributions involved we develop an EM-algorithm. The estimation procedure is evaluated and compared with a non-parametric method in a couple of examples based on simulated data.     

The potential power of social policy programmes: income redistribution,economic resources and health

Lundberg O, Fritzell J, Åberg Yngwe M, Kölegård ML. The potential power of social policy programmes: income redistribution, economic resources and health Int J Soc Welfare 2010: ??: ??–??© 2010 The Author(s), Journal compilation © 2010 Blackwell Publishing Ltd and International Journal of Social Welfare. This Supplement includes a number of articles dealing with the role of social policy schemes for public health across the life course. As a key social determinant of health, poverty and its consequences have historically been at the forefront of the public health discussion. But also in rich countries today, economic resources are likely to be important for health and survival, both on an individual and an aggregate level. This introductory article serves as a background for the more specific analyses that follow. The focus is on why income and income inequality could have an effect on individual and population health. We discuss relationships between the individual and population levels and between income and health, and some of the possible mechanisms involved. We also present arguments for why welfare state institutions may matter.