A tutorial on rank-based coefficient estimation for censored data in small- and large-scale problems

The analysis of survival endpoints subject to right-censoring is an important research area in statistics, particularly among econometricians and biostatisticians. The two most popular semiparametric models are the proportional hazards model and the accelerated failure time (AFT) model. Rank-based estimation in the AFT model is computationally challenging due to optimization of a non-smooth loss function. Previous work has shown that rank-based estimators may be written as solutions to linear programming (LP) problems. However, the size of the LP problem is O(n ²+p) subject to n ² linear constraints, where n denotes sample size and p denotes the dimension of parameters. As n and/or p increases, the feasibility of such solution in practice becomes questionable. Among data mining and statistical learning enthusiasts, there is interest in extending ordinary regression coefficient estimators for low-dimensions into high-dimensional data mining tools through regularization. Applying this recipe to rank-based coefficient estimators leads to formidable optimization problems which may be avoided through smooth approximations to non-smooth functions. We review smooth approximations and quasi-Newton methods for rank-based estimation in AFT models. The computational cost of our method is substantially smaller than the corresponding LP problem and can be applied to small- or large-scale problems similarly. The algorithm described here allows one to couple rank-based estimation for censored data with virtually any regularization and is exemplified through four case studies.     

Erosion oder Stabilität der Beruflichkeit?

Regarding the changing patterns of mobility processes in the German labor market, this paper takes up the scientific debate on the declining significance of occupational qualifications. By comparing several labor market entry cohorts, the matching of the learned occupation and the practiced occupation is analyzed in both the horizontal and the vertical dimension of occupational mobility. In doing so, the question of a successful utilization of the skills acquired in the educational process can be addressed. Changes of occupations will be operationalized on the basis of a new professional classification by using the data set “Working and Learning in a Changing World” (ALWA). First, the Kaplan Meier survival curves show that the risks of horizontal occupational mobility have increased across cohorts. This indicates that the formerly close relationship between the education system and the employment system has weakened. Furthermore, according to our multivariate Cox regression analysis, the mobility towards inadequate status positions has increased. Thus, due to the expansion of atypical forms of employment and the increased volatility of the markets, altered mobility patterns of the younger cohorts entering the labor market can be shown. Consequently, the increase of unsuccessful transfers of skills in inter-firm mobility suggests a weakened cohesiveness between professionalism and a growing risk to loose professional qualifications.     

The effect of accounting standards on Big Bath behavior

This paper investigates the influence of accounting standards on systematic earnings understatement. To isolate the effect of reporting regulations from those of other institutional drivers of earnings management, Holthausen (2003) proposes analyzing reporting practices in a country undergoing a transition in accounting standards. We respond to this call by analyzing earnings management practices of large German-listed companies before and after their transitions from German GAAP to IFRS. Specifically, we focus on Big Bath behavior following Chief Financial Officer turnovers between 1999 and 2006. Our findings provide evidence of the effect of accounting standards on the existence of this particular earnings understatement pattern. However, while we detect Big Bath behavior for our sample of German GAAP firms, we find no such indication for those firms reporting under IFRS. Controlling for alternative explanations such as self-selection bias does not change our findings. We conclude that accounting standards seem to have a considerable influence on earnings management behavior, independent of managers’ and auditors’ incentives.     

The Strategic Management of Innovation: A Systematic Review and Paths for Future Research

Strategic management scholars have long emphasized the importance of innovation for a firm's competitive advantage and performance. However, the current state of knowledge about the strategic management of innovation is characterized by conflicting theoretical predictions, persisting knowledge gaps and theoretical inconsistencies. Adopting a ‘systematic’ approach to reviewing the literature, this paper combines different quantitative methods – co‐word analysis, cluster analysis and frequency analysis – to review 342 articles on the strategic management of innovation published in seven journals from 1992 to 2010. On the basis of these analyses, suggestions are developed for future research which could help to promote future theory development and provide relevant material for policy decisions that managers and executives have to make when they manage innovation.     

Child mortality and fertility decline: Does the Barro-Becker model fit the facts?

I compare the predictions of three variants of the altruistic parent model of Barro and Becker for the relationship between child mortality and fertility. In the baseline model fertility choice is continuous, and there is no uncertainty over the number of surviving children. The baseline model is contrasted to an extension with discrete fertility choice and stochastic mortality and a setup with sequential fertility choice. The quantitative predictions of the models are remarkably similar. While in each model the total fertility rate falls as child mortality declines, the number of surviving children increases. The results suggest that factors other than declining infant and child mortality are responsible for the large decline in net reproduction rates observed in industrialized countries over the last century. Financial support by the National Science Foundation (grant SES-0217051) and the UCLA Academic Senate is gratefully acknowledged. I thank Sebnem Kalemli-Oczan, Rodrigo Soares, and two anonymous referees for comments that helped to substantially improve the paper. Olesya Baker and Ilya Berger provided excellent research assistance. Responsible editor: Junsen Zhang.     

The Institutional Challenge of the ACP/EU Economic Partnership Agreements

The Economic Partnership Agreements between the African, Caribbean and Pacific countries and the European Union should serve as an opportunity to accelerate ACP global and regional trade integration and as an important tool for development and the eradication of poverty. There are, however, a number of preconditions. This article argues that institutional quality plays a key role in successful trade liberalisation. In fact, only countries with high‐quality institutions, partly in the form of good government regulation, are likely to benefit from trade. Unfortunately, the vast majority of African countries have excessive regulation that hinders them from taking advantage of trade. The necessary reforms to resolve this problem pose significant challenges, implying major risks for these countries in the EPA process.     

Tukey-Type Distributions in the Context of Financial Data

Abstract

In one-parameter (θ) families, we were not aware of explicit hypothesis testing scenarios where maximal invariant statistics failed to distinguish the models. We start with a concrete example (Sec. 2.2) to highlight such a hypothesis testing problem involving markedly different models. In this problem, because of the absence of a nontrivial uniformly most powerful invariant (UMPI) test, we briefly suggest two approaches to test the hypothesis. The first resolution (Sec. 3.1) is frequentist in nature. It utilizes a weight function on the parameter space and compares “average” distributions obtained under the null and alternative models in the sense of Wald (1947 Wald , A. ( 1947 ). Sequential Analysis . New York : Wiley . [Google Scholar] 1950 Wald , A. ( 1950 ). Statistical Decision Functions . New York : Wiley . [Google Scholar]). In contrast, a fully Bayesian resolution (Sec. 3.2) is also included. The note ends with a series of other interesting examples involving one-parameter families where maximal invariant statistics fail to distinguish the hypothesized models. The examples include easy-to-construct families of probability models involving only a single location or scale parameter θ.     

Bounded influence estimation for regression and scale

Bednarski and Müller [Optimal bounded influence regression and scale M-estimators in the context of experimental design, Statistics 35 (2001), pp. 349–369] introduced a class of bounded influence M estimates for the simultaneous estimation of regression and scale in the linear model with normal errors by solving the corresponding normal location and scale problem at each design point. This limits the proposal to regressor distributions with finite support. Based on their approach, we propose a slightly extended class of M estimates that is not restricted to finite support and is numerically easier to handle. Moreover, we employ the even more general class of asymptotically linear (AL) estimators which, in addition, is not restricted to normal errors. The superiority of AL estimates is demonstrated by numerical comparisons of the maximum asymptotic mean-squared error over infinitesimal contamination neighbourhoods.     

On- and offline detection of structural breaks in thermal spraying processes

We investigate and develop methods for structural break detection, considering time series from thermal spraying process monitoring. Since engineers induce technical malfunctions during the processes, the time series exhibit structural breaks at known time points, giving us valuable information to conduct the investigations. First, we consider a recently developed robust online (also real-time) filtering (i.e. smoothing) procedure that comprises a test for local linearity. This test rejects when jumps and trend changes are present, so that it can also be useful to detect such structural breaks online. Second, based on the filtering procedure we develop a robust method for the online detection of ongoing trends. We investigate these two methods as to the online detection of structural breaks by simulations and applications to the time series from the manipulated spraying processes. Third, we consider a recently developed fluctuation test for constant variances that can be applied offline, i.e. after the whole time series has been observed, to control the spraying results. Since this test is not reliable when jumps are present in the time series, we suggest data transformation based on filtering and demonstrate that this transformation makes the test applicable.