Triangulation: Validity and empirically-based hypothesis construction

The essay focuses on the opportunities and strengths of a multi-method approach, widely called methodological triangulation, in which different investigative methods are applied to one research object. In practice, this can be realized with the coupling of quantitative structural data concerning the life course and the interpretation and evaluation of life course data collected with qualitative methods. This approach is examined in order to shed light on the problem that research findings often show different phenomena and not the different aspects of one phenomenon. The discussion of the relationships of the findings to one another (congruent, complementary or divergent) shows that in this context a multi-method approach can nevertheless be used to increase validity and to test hypotheses. Further, its particular strengths are the empirically induced modification of existing models and theories, as well as the development of new explanations.     

Slow adjustment to shocks or true hysteresis?

In Western Europe in the last two decades the unemployment rate has increased during cyclical downturns only to persist at or around the higher level in the following phase of economic recovery. One of the most notable exceptions to this pattern of unemployment persistence, often termed hysteresis, is the United States. The following article examines the empirical evidence and the possible theoretical explanations for this difference.     

An efficient nonparametric estimator for models with nonlinear dependence

We provide a convenient econometric framework for the analysis of nonlinear dependence in financial applications. We introduce models with constrained nonparametric dependence, which specify the conditional distribution or the copula in terms of a one-dimensional functional parameter. Our approach is intermediate between standard parametric specifications (which are in general too restrictive) and the fully unrestricted approach (which suffers from the curse of dimensionality). We introduce a nonparametric estimator defined by minimizing a chi-square distance between the constrained densities in the family and an unconstrained kernel estimator of the density. We derive the nonparametric efficiency bound for linear forms and show that the minimum chi-square estimator is nonparametrically efficient for linear forms.     

Pitfalls of Normal-Gamma Stochastic Frontier Models

Although conceptually pleasing, normal-gamma frontier models lead to difficult estimation problems. It is shown here that unless the sample size reaches several thousands of observations the shape parameter of the gamma density is hard to estimate, and that this carries over to estimates of the stochastic frontier, the individual inefficiencies, and the allocation of the overall variance to the stochastic frontier and to the inefficiencies.     

The topography of metropolitan employment: Identifying centers of employment in a polycentric urban area

While it is well recognized that US metropolitan areas are polycentric, there is little consensus as to the appropriate method for identifying concentrations of employment within them. Existing methods suffer from strong assumptions about parametric form, misspecification, or reliance on local knowledge to calibrate model parameters. This paper introduces a new nonparametric method for identifying subcenters. Results indicate that this, more flexible, nonparametric approach yields greater accuracy with regard to both urban and suburban centers compared with other approaches. This approach should provide better data for the numerous topics that depend on the spatial accounting of employment within metropolitan areas.