The Influence of Role Models on Immigrant Self-Employment: A Spatial Analysis for Switzerland

Theoretical and empirical research suggests a connection between the presence of role models and the emergence of entrepreneurs. Existing entrepreneurs may act as role models for self-employment candidates by providing successful examples. By explicitly considering the self-employment rates of the natives, which may influence locally the decisions of immigrants towards entrepreneurship, we develop a simple model that explains immigrant self-employment rates for a sample of 2,490 Swiss municipalities. In addition, we accommodate for the presence of spatial spillovers in the distribution of rates, and test a spatial autoregressive model which takes into account the average self-employment rates of immigrants living in nearby municipalities. Our evidence shows a significant (positive) effect of such spatial network effects, which are characterized by a quick distance decay, suggesting spatial spillovers at the household and social network level. Additionally, we show that local conditions and immigrant pool characteristics differ, with respect to self-employment choices, when examining separately urban and rural contexts.immigrants, self-employment, role models, Switzerland, spatial lag

Inferring rate coefficents of biochemical reactions from noisy data with KInfer

Dynamical models of inter- and intra-cellular processes contain the rate constants of the biochemical reactions. These kinetic parameters are often not accessible directly through experiments, but they can be inferred from time-resolved data. Time resolved data, that is, measurements of reactant concentration at series of time points, are usually affected by different types of error, whose source can be both experimental and biological. The noise in the input data makes the estimation of the model parameters a very difficult task, as if the inference method is not sufficiently robust to the noise, the resulting estimates are not reliable. Therefore "noise-robust" methods that estimate rate constants with the maximum precision and accuracy are needed. In this report we present the probabilistic generative model of parameter inference implemented by the software prototype KInfer and we show the ability of this tool of estimating the rate coefficients of models of biochemical network with a good accuracy even from very noisy input data

A stochastic model for early placental development

In the human, placental structure is closely related to placental function and consequent pregnancy outcome. Studies have noted abnormal placental shape in small-for-gestational age infants which extends to increased lifetime risk of cardiovascular disease. The origins and determinants of placental shape are incompletely under-stood and are difficult to study in vivo. In this paper we model the early development of the placenta in the human, based on the hypothesis that this is driven by dynamics dominated by a chemo-attractant effect emanating from proximal spiral arteries in the decidua. We derive and explore a two-dimensional stochastic model for these events, and investigate the effects of loss of spiral arteries in regions near to the cord insertion on the shape of the placenta. This model demonstrates that placental shape is highly variable and disruption of spiral arteries can exert profound effects on placental shape, particularly if this disruption is close to the cord insertion. Thus, placental shape reflects the underlying maternal vascular bed. Abnormal placental shape may reflect an abnormal uterine environment, which predisposes to pregnancy complications

Positional information, positional error, and read-out precision in morphogenesis: a mathematical framework

The concept of positional information is central to our understanding of how cells in a multicellular structure determine their developmental fates. Nevertheless, positional information has neither been defined mathematically nor quantified in a principled way. Here we provide an information-theoretic definition in the context of developmental gene expression patterns and examine which features of expression patterns increase or decrease positional information. We connect positional information with the concept of positional error and develop tools to directly measure information and error from experimental data. We illustrate our framework for the case of gap gene expression patterns in the early Drosophila embryo and show how information that is distributed among only four genes is sufficient to determine developmental fates with single cell resolution. Our approach can be generalized to a variety of different model systems; procedures and examples are discussed in detail

Sectorial Border Effects in the European Single Market: an Explanation through Industrial Concentration

The purpose of this paper is to explain the relation between the Border Effect and industrial concentration. This is achieved by founding this relation on the Home Market Effect and testing the robustness of this foundation through an application to the European Single Market. A sectorial Gravity Equation is estimated using different econometric estimators, in particular we discuss a recently suggested technique for the estimation of log-linear CES models. Overall, our findings suggest a steady relation between the Border Effect and industrial concentration. Besides, the analysis of industrial concentration through a synthetic index provides us with valuable insights into the structure of the European industry. JEL Classification: F10, F12, F15.Border Effect, European Single Market, Home Market Effect, Industrial Concentration, Trade