Wild Flowers

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Recent changes in Germany's foreign trade balance

International trade - Germany

Mobility and the Return to Education: Testing a Roy Model with Multiple Markets

Self-selected migration presents one potential explanation for why observed returns to a college education in local labor markets vary widely even though U.S. workers are highly mobile. To assess the impact of self-selection on estimated returns, this paper first develops a Roy model of mobility and earnings where workers choose in which of the 50 states (plus the District of Columbia) to live and work. Available estimation methods are either infeasible for a selection model with so many alternatives or place potentially severe restrictions on earnings and the selection process. This paper develops an alternative econometric methodology which combines Lee's (1983) parametric maximum order statistic approach to reduce the dimensionality of the error terms with more recent work on semiparametric estimation of selection models (e.g., Ahn and Powell, 1993). The resulting semiparametric correction is easy to implement and can be adapted to a variety of other polychotomous choice problems. The empirical work, which uses 1990 U.S. Census data, confirms the role of comparative advantage in mobility decisions. The results suggest that self-selection of higher educated individuals to states with higher returns to education generally leads to upward biases in OLS estimates of the returns to education in state-specific labor markets. While the estimated returns to a college education are significantly biased, correcting for the bias does not narrow the range of returns across states. Consistent with the finding that the corrected return to a college education differs across the U.S., the relative state-to-state migration flows of college- versus high school-educated individuals respond strongly to differences in the return to education and amenities across states.Selection Bias, Polychotomous Choice, Roy Model, Return to Education, Migration

Effects of High and Low Barometric Pressures on Susceptibility and Resistance to Infection Quarterly Status Report, 1 Jul. - 30 Sep. 1966

High and low barometric pressure effects on susceptibility and resistance to infectio

Loss terms in free-piston Stirling engine models

Various models for free piston Stirling engines are reviewed. Initial models were developed primarily for design purposes and to predict operating parameters, especially efficiency. More recently, however, such models have been used to predict engine stability. Free piston Stirling engines have no kinematic constraints and stability may not only be sensitive to the load, but also to various nonlinear loss and spring constraints. The present understanding is reviewed of various loss mechanisms for free piston Stirling engines and how they have been incorporated into engine models is discussed

Computer program for calculation of complex chemical equilibrium compositions

Computer program is described for numerical solution of chemical equilibria in complex systems by using nonlinear algebraic equations. Free-energy minimization technique is used

Radiation noise in a high sensitivity star sensor

An extremely accurate attitude determination was developed for space applications. This system uses a high sensitivity star sensor in which the photomultiplier tube is subject to noise generated by space radiations. The space radiation induced noise arises from trapped electrons, solar protons and other ionizing radiations, as well as from dim star background. The solar activity and hence the electron and proton environments are predicted through the end of the twentieth century. The available data for the response of the phototube to proton, electron, gamma ray, and bremsstrahlung radiations are reviewed and new experimental data is presented. A simulation was developed which represents the characteristics of the effect of radiations on the star sensor, including the non-stationarity of the backgrounds

A Model for Scaling in Firms' Size and Growth Rate Distribution

We introduce a simple agent-based model which allows us to analyze three stylized facts: a fat-tailed size distribution of companies, a `tent-shaped' growth rate distribution, the scaling relation of the growth rate variance with firm size, and the causality between them. This is achieved under the simple hypothesis that firms compete for a scarce quantity (either aggregate demand or workforce) which is allocated probabilistically. The model allows us to relate size and growth rate distributions. We compare the results of our model to simulations with other scaling relationships, and to similar models and relate it to existing theory. Effects arising from binning data are discussed.Comment: accepted for publication in Physica