Estimating cross-industry cross-country models using benchmark industry characteristics

International industry data permits testing whether the industry-specific impact of cross-countrydifferences in institutions or policies is consistent with economic theory. Empirical implementationrequires specifying the industry characteristics that determine impact strength. Most of the literature has been using US proxies of the relevant industry characteristics. We show that usingindustry characteristics in a benchmark country as a proxy of the relevant industry characteristicscan result in an attenuation bias or an amplification bias. We also describe circumstances allowingfor an alternative approach that yields consistent estimates. As an application, we reexamine theinfluential conjecture that financial development facilitates the reallocation of capital from decliningto expanding industries.

Spatial correlations and cross sections of clusters in the A + B -> 0 reaction

We consider the distribution of cross sections of clusters and the density-density correlation functions for the A+B¿0 reaction. We solve the reaction-diffusion equations numerically for random initial distributions of reactants. When both reactant species have the same diffusion coefficients the distribution of cross sections and the correlation functions scale with the diffusion length and obey superuniversal laws (independent of dimension). For different diffusion coefficients the correlation functions still scale, but the scaling functions depend on the dimension and on the diffusion coefficients. Furthermore, we display explicitly the peculiarities of the cluster-size distribution in one dimension.

Spatial correlations and cross sections of clusters in the A + B -> 0 reaction

We consider the distribution of cross sections of clusters and the density-density correlation functions for the A+B¿0 reaction. We solve the reaction-diffusion equations numerically for random initial distributions of reactants. When both reactant species have the same diffusion coefficients the distribution of cross sections and the correlation functions scale with the diffusion length and obey superuniversal laws (independent of dimension). For different diffusion coefficients the correlation functions still scale, but the scaling functions depend on the dimension and on the diffusion coefficients. Furthermore, we display explicitly the peculiarities of the cluster-size distribution in one dimension.

Comparing multiple criteria for species identification in two recently diverged seabirds

Correct species identification is a crucial issue in systematics with key implications for prioritising conservation effort. However, it can be particularly challenging in recently diverged species due to their strong similarity and relatedness. In such cases, species identification requires multiple and integrative approaches. In this study we used multiple criteria, namely plumage colouration, biometric measurements, geometric morphometrics, stable isotopes analysis (SIA) and genetics (mtDNA), to identify the species of 107 bycatch birds from two closely related seabird species, the Balearic (Puffinus mauretanicus) and Yelkouan (P. yelkouan) shearwaters. Biometric measurements, stable isotopes and genetic data produced two stable clusters of bycatch birds matching the two study species, as indicated by reference birds of known origin. Geometric morphometrics was excluded as a species identification criterion since the two clusters were not stable. The combination of plumage colouration, linear biometrics, stable isotope and genetic criteria was crucial to infer the species of 103 of the bycatch specimens. In the present study, particularly SIA emerged as a powerful criterion for species identification, but temporal stability of the isotopic values is critical for this purpose. Indeed, we found some variability in stable isotope values over the years within each species, but species differences explained most of the variance in the isotopic data. Yet this result pinpoints the importance of examining sources of variability in the isotopic data in a case-by-case basis prior to the cross-application of the SIA approach to other species. Our findings illustrate how the integration of several methodological approaches can help to correctly identify individuals from recently diverged species, as each criterion measures different biological phenomena and species divergence is not expressed simultaneously in all biological traits.