Compositional explanatory variables should not be directly used in a linear regression model because any inference statistic can become misleading. While various approaches for this problem were proposed, here an approach based on the isometric logratio (ilr) transformation is used. It turns out that the resulting model is easy to handle, and that parameter estimation can be done like in usual ...

We study the implications of microeconomic heterogeneity for aggregate technology, showing that the aggregate elasticity of substitution between capital and labor can be expressed as a simple function of plant level structural parameters and sufficient statistics for plant heterogeneity. This allows for a new approach to estimating the aggregate elasticity using microeconomic data and allows us...

We propose a timescale decomposition approach to measurement-based admission control (MBAC). We identify a critical timescale f T h such that: 1) aggregate traac uctuation slower than f T h can be tracked by the admission controller and compensated for by ow admissions and departures; 2) uctuations faster than f T h have to be absorbed by reserving spare bandwidth on the link. The critical time...

Electricity is cited as one of the biggest impediments to firm growth in developing countries. In the World Bank Enterprise Survey (2006), 35.2% of Indian firms list electricity as the single biggest obstacle to business and report that power outages result in losses equivalent to 6.6% of annual sales. However, some businesses can adjust their means of production to cope with electricity shorta...

This paper evaluates the effects of job creation schemes on the participating individuals in Germany. Since previous empirical studies of these measures have been based on relatively small datasets and focussed on East Germany, this is the first study which allows to draw policy-relevant conclusions. The very informative and exhaustive dataset at hand not only justifies the application of a mat...

Magnetic Resonance Imaging (MRI) is the standard of care in the clinic for diagnosis and follow up of Soft Tissue Sarcomas (STS) which presents an opportunity to explore the heterogeneity inherent in these rare tumors. Tumor heterogeneity is a challenging problem to quantify and has been shown to exist at many scales, from genomic to radiomic, existing both within an individual tumor, between t...

Shrinking methods in regression analysis are usually designed for metric predictors. If independent variables are categorial some modifications are necessary. In this article two L1-penalty based methods for factor selection and clustering of categories are presented and investigated. The first approach is designed for nominal scale levels, the second one for ordinal predictors. All methods are...

Adjustment for covariates is a time-honored tool in statistical analysis and is often implemented by including the covariates that one intends to adjust as additional predictors in a model. This adjustment often does not work well when the underlying model is misspecified. We consider here the situation where we compare a response between two groups. This response may depend on a covariate for ...