Necessity and Opportunity Entrepreneurs and their Duration in Self-employment: Evidence from German Micro Data

Using data from the German Socio-Economic Panel Study (GSOEP), we analyze whether necessity entrepreneurs differ from opportunity entrepreneurs in terms of self-employment duration. Using univariate statistics, we find that opportunity entrepreneurs remain in self-employment longer than necessity entrepreneurs. However, after controlling for the entrepreneurs’ education in the professional area where they start their venture, this effect is no longer significant. We therefore conclude that the difference observed is not an original effect but rather is due to selection. We then go on to discuss the implications of our findings for entrepreneurship-policy making, and give suggestions to improve governmental start-up programs

Are Education and Entrepreneurial Income Endogenous and Do Family Background Variables Make Sense as Instruments?: A Bayesian Analysis

Education is a well-known driver of (entrepreneurial) income. The measurement of its influence, however, suffers from endogeneity suspicion. For instance, ability and occupational choice are mentioned as driving both the level of (entrepreneurial) income and of education. Using instrumental variables can provide a way out. However, three questions remain: whether endogeneity is really present, whether it matters and whether the selected instruments make sense. Using Bayesian methods, we find that the relationship between education and entrepreneurial income is indeed endogenous and that the impact of endogeneity on the estimated relationship between education and income is sizeable. We do so using family background variables and show that relaxing the strict validity assumption of these instruments does not lead to strongly different results. This is an important finding because family background variables are generally strongly correlated with education and are available in most datasets. Our approach is applicable beyond the field of returns to education for income. It applies wherever endogeneity suspicion arises and the three questions become relevant.Education, income, entrepreneurship, self-employment, endogeneity, instrumental variables, Bayesian analysis, family background variables

The macroeconomic effects of exogenous fiscal policy shocks in Germany: a disaggregated SVAR analysis

We investigate the short-term effects of fiscal policy shocks on the German economy following the SVAR approach by Blanchard and Perotti (2002). We find that direct government expenditure shocks increase output and private consumption on impact with low statistical significance, while they decrease private investment, though insignificantly. For the sub-category government investment – in contrast to government consumption – a positive output effect is found, which is statistically significant until 12 quarters ahead. Allowing for anticipation effects of fiscal policy does not change the sign of the positive consumption response. Anticipated expenditure shocks have significant effects on output when the shock is realized, but not in the period of anticipation. In sum, effects of expenditure shocks are only short-lived. Government net revenue shocks do not affect output with statistical significance. However, when splitting up this aggregate, direct taxes lower output significantly, while small indirect tax revenue shocks have little effects. Compensation of public employees is equally not effective in stimulating the economy. --Fiscal policy,government spending,net revenue,policy anticipation,structural vector autoregression

Identifying Heavy-Flavor Jets Using Vectors of Locally Aggregated Descriptors

Jets of collimated particles serve a multitude of purposes in high energy collisions. Recently, studies of jet interaction with the quark-gluon plasma (QGP) created in high energy heavy ion collisions are of growing interest, particularly towards understanding partonic energy loss in the QGP medium and its related modifications of the jet shower and fragmentation. Since the QGP is a colored medium, the extent of jet quenching and consequently, the transport properties of the medium are expected to be sensitive to fundamental properties of the jets such as the flavor of the parton that initiates the jet. Identifying the jet flavor enables an extraction of the mass dependence in jet-QGP interactions. We present a novel approach to tagging heavy-flavor jets at collider experiments utilizing the information contained within jet constituents via the \texttt{JetVLAD} model architecture. We show the performance of this model in proton-proton collisions at center of mass energy $\sqrt{s} = 200$ GeV as characterized by common metrics and showcase its ability to extract high purity heavy-flavor jet sample at various jet momenta and realistic production cross-sections including a brief discussion on the impact of out-of-time pile-up. Such studies open new opportunities for future high purity heavy-flavor measurements at jet energies accessible at current and future collider experiments.Comment: 18 pages, 6 figures and 3 tables. Accepted by JINS

Crystal distribution patterns and their anisotropy behaviour in igneous rocks: towards an automated quantification, first results

Since approximately two decades fractal geometry offers tools for the quantification of rock fabrics, and new methods are currently under development to investigate the inhomogeneity of crystal distributions, grain- and phase-boundary patterns as well as their anisotropy behaviour (Kruhl et al. 2004). These methods are now adapted for automated processing and suitable to quantify the inhomogeneity and anisotropy of rock fabrics from macro to microscale. Applications for quantifying inhomogeneity are mainly based on the box-counting and map-counting (Peternell 2002) methods, for anisotropy behaviour mainly based on modified Cantor-dust methods and provide fractal dimensions, fractal-dimension isolines and azimuthal anisotropies of fractal dimension (AAD, Volland & Kruhl 2004). For instance, the results provide information about the local variations of fabric patterns and their prefer orientation behaviour at macro and microscale.conferenc

Fluid dynamics of bacterial turbulence

Self-sustained turbulent structures have been observed in a wide range of living fluids, yet no quantitative theory exists to explain their properties. We report experiments on active turbulence in highly concentrated 3D suspensions of Bacillus subtilis and compare them with a minimal fourth-order vector-field theory for incompressible bacterial dynamics. Velocimetry of bacteria and surrounding fluid, determined by imaging cells and tracking colloidal tracers, yields consistent results for velocity statistics and correlations over two orders of magnitude in kinetic energy, revealing a decrease of fluid memory with increasing swimming activity and linear scaling between energy and enstrophy. The best-fit model parameters allow for quantitative agreement with experimental data.Comment: 5 pages, 4 figure

Mapping functional traits: comparing abundance and presence-absence estimates at large spatial scales

Efforts to quantify the composition of biological communities increasingly focus on functional traits. The composition of communities in terms of traits can be summarized in several ways. Ecologists are beginning to map the geographic distribution of trait-based metrics from various sources of data, but the maps have not been tested against independent data. Using data for birds of the Western Hemisphere, we test for the first time the most commonly used method for mapping community trait composition – overlaying range maps, which assumes that the local abundance of a given species is unrelated to the traits in question – and three new methods that as well as the range maps include varying degrees of information about interspecific and geographic variation in abundance. For each method, and for four traits (body mass, generation length, migratory behaviour, diet) we calculated community-weighted mean of trait values, functional richness and functional divergence. The maps based on species ranges and limited abundance data were compared with independent data on community species composition from the American Christmas Bird Count (CBC) scheme coupled with data on traits. The correspondence with observed community composition at the CBC sites was mostly positive (62/73 correlations) but varied widely depending on the metric of community composition and method used (R2: 5.6×10−7 to 0.82, with a median of 0.12). Importantly, the commonly-used range-overlap method resulted in the best fit (21/22 correlations positive; R2: 0.004 to 0.8, with a median of 0.33). Given the paucity of data on the local abundance of species, overlaying range maps appears to be the best available method for estimating patterns of community composition, but the poor fit for some metrics suggests that local abundance data are urgently needed to allow more accurate estimates of the composition of communities

Network of recurrent events for the Olami-Feder-Christensen model

We numerically study the dynamics of a discrete spring-block model introduced by Olami, Feder and Christensen (OFC) to mimic earthquakes and investigate to which extent this simple model is able to reproduce the observed spatiotemporal clustering of seismicty. Following a recently proposed method to characterize such clustering by networks of recurrent events [Geophys. Res. Lett. {\bf 33}, L1304, 2006], we find that for synthetic catalogs generated by the OFC model these networks have many non-trivial statistical properties. This includes characteristic degree distributions -- very similar to what has been observed for real seismicity. There are, however, also significant differences between the OFC model and earthquake catalogs indicating that this simple model is insufficient to account for certain aspects of the spatiotemporal clustering of seismicity.Comment: 11 pages, 16 figure

Meso-scale turbulence in living fluids

Turbulence is ubiquitous, from oceanic currents to small-scale biological and quantum systems. Self-sustained turbulent motion in microbial suspensions presents an intriguing example of collective dynamical behavior amongst the simplest forms of life, and is important for fluid mixing and molecular transport on the microscale. The mathematical characterization of turbulence phenomena in active non-equilibrium fluids proves even more difficult than for conventional liquids or gases. It is not known which features of turbulent phases in living matter are universal or system-specific, or which generalizations of the Navier-Stokes equations are able to describe them adequately. Here, we combine experiments, particle simulations, and continuum theory to identify the statistical properties of self-sustained meso-scale turbulence in active systems. To study how dimensionality and boundary conditions affect collective bacterial dynamics, we measured energy spectra and structure functions in dense Bacillus subtilis suspensions in quasi-2D and 3D geometries. Our experimental results for the bacterial flow statistics agree well with predictions from a minimal model for self-propelled rods, suggesting that at high concentrations the collective motion of the bacteria is dominated by short-range interactions. To provide a basis for future theoretical studies, we propose a minimal continuum model for incompressible bacterial flow. A detailed numerical analysis of the 2D case shows that this theory can reproduce many of the experimentally observed features of self-sustained active turbulence.Comment: accepted PNAS version, 6 pages, click doi for Supplementary Informatio