Human capital, the structure of production and growth

Do high levels of human capital foster economic growth by facilitating technology adoption? If so, countries with more human capital should have adopted more rapidly the skilled-labor augmenting technologies becoming available since the 1970 s. High human capital levels should therefore have translated into fast growth in more compared to less human-capital-intensive industries in the 1980 s. Theories of international specialization point to human capital accumulation as another important determinant of growth in human-capital-intensive industries. Using data for a large sample of countries, we find significant positive effects of human capital levels and human capital accumulation on output and employment growth in human-capital-intensive industries.

Aggregate fluctuations and the network structure of intersectoral trade

This paper analyzes the flow of intermediate inputs across sectors by adopting a network perspective on sectoral interactions. I apply these tools to show how fluctuationsin aggregate economic activity can be obtained from independent shocks to individualsectors. First, I characterize the network structure of input trade in the U.S. On thedemand side, a typical sector relies on a small number of key inputs and sectors arehomogeneous in this respect. However, in their role as input-suppliers sectors do differ:many specialized input suppliers coexist alongside general purpose sectors functioningas hubs to the economy. I then develop a model of intersectoral linkages that can reproduce these connectivity features. In a standard multisector setup, I use this modelto provide analytical expressions linking aggregate volatility to the network structureof input trade. I show that the presence of sectoral hubs - by coupling productiondecisions across sectors - leads to fluctuations in aggregates.

Structure of bee-flower system in the coastal sand dune of Abaeté, northeastern Brazil

For twelve months (from January to December of 1996) we investigated bee-flower interactions in a sea coastal ecosystem in Bahia, Brazil. Samples were taken three times each month. 3983 individuals belonging to 49 bee species, grouped in 13 morph-functional categories, visited 66 plant species belonging to 39 botanic families. It was observed 310 interactions between bees and plants at species level. The use of floral resources by bees was not homogeneous; most of the plant species received a low number of visitors. No restricted plant-bee species relationship in resource use concerning the subset of analyzed interactions was detected. In Abaeté the generalist relationships predominated.

Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling

The interpretation of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all crossloadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores.

Heritability of left ventricular structure and function in Caucasian families.

AIMS: The aim of this study was to investigate the heritability as well as genetic and environmental correlations of left ventricular (LV) structural and functional traits in complex pedigrees of a Caucasian population. METHODS AND RESULTS: We randomly recruited 459 white European subjects from 52 families (50% women; mean age 45 years). LV structure was measured by M-mode and 2D echocardiography and LV function was measured by conventional Doppler and tissue Doppler imaging (TDI). Other measurements included blood pressure, anthropometric, and biochemical measurements. We estimated the heritability of LV traits while adjusting for covariables, including sex, age, body height and weight, systolic and diastolic blood pressures, and heart rate. With full adjustment, heritability of LV mass was 0.23 (P= 0.025). The TDI-derived mitral annular velocities Ea and Aa showed moderate heritability (h(2)= 0.36 and 0.53, respectively), whereas the mitral inflow A peak had weak heritability (h(2) = 0.25) and the E peak was not heritable (h(2) = 0.11). We partitioned the total phenotypic correlation when it reached significance, into a genetic and an environmental component. The genetic correlations were 0.61 between the E and Ea peaks and 0.90 between the A and Aa peaks. CONCLUSION: Our study demonstrated moderate heritability for LV mass as well as the mitral annular Ea and Aa peaks. We also found significant genetic correlations between the E and Ea peaks and between the A and Aa peaks. Our current findings support the ongoing research to map and detect genetic variants that contribute to the variation in LV mass and other LV structural and functional phenotypes.

Relationships between host plant architecture and gall abundance and survival

The plant architecture hypothesis predicts that variation in host plant architecture influences insect herbivore community structure, dynamics and performance. In this study we evaluated the effects of Macairea radula (Melastomataceae) architecture on the abundance of galls induced by a moth (Lepidoptera: Gelechiidae). Plant architecture and gall abundance were directly recorded on 58 arbitrarily chosen M. radula host plants in the rainy season of 2006 in an area of Cerrado vegetation, southeastern Brazil. Plant height, dry biomass, number of branches, number of shoots and leaf abundance were used as predicting variables of gall abundance and larval survival. Gall abundance correlated positively with host plant biomass and branch number. Otherwise, no correlation (p > 0.05) was found between gall abundance with shoot number or with the number of leaves/plant. From a total of 124 galls analyzed, 67.7% survived, 14.5% were attacked by parasitoids, while 17.7% died due to unknown causes. Larvae that survived or were parasitized were not influenced by architectural complexity of the host plant. Our results partially corroborate the plant architecture hypothesis, but since parasitism was not related to plant architecture it is argued that bottom-up effects may be more important than top-down effects in controlling the population dynamics of the galling lepidopteran. Because galling insects often decrease plant fitness, the potential of galling insects in selecting for less architectural complex plants is discussed.

A 15-year post evaluation of the fire effects on ant community in an area of Amazonian forest

Fire represents an important disturbance to ant communities in areas of fire regime. Otherwise, little is known about the effects of fire on ant communities in areas of non-fire regimes, such as in the Amazonian region. We evaluated the long-term effect of fire on ant species richness in a rain forest (Bacaba Plateau) burned 15-years ago and compare our data with the data of primary unburned forest. A total of 85 ant species distributed in 21 genera and 14 tribes were collected; among them, 72 and 44 species were found on the litter and vegetation, respectively. The fire damaged forest studied supports an intermediate richness of ants when compared to a primary unburned rain forest in the same region. A comparative analysis of ant species richness showed that the Bacaba Plateau presented a different ant fauna when compared with the primary unburned forests, suggesting that fire can alter ant species composition. Although, our results cannot be conclusive on the effects of fire on ant community, they represent a pioneer data on human induced fire in tropical rain forests.

How much structure in empirical models?

This chapter highlights the problems that structural methods and SVAR approaches have when estimating DSGE models and examining their ability to capture important features of the data. We show that structural methods are subject to severe identification problems due, in large part, to the nature of DSGE models. The problems can be patched up in a number of ways but solved only if DSGEs are completely reparametrized or respecified. The potential misspecification of the structural relationships give Bayesian methods an hedge over classical ones in structural estimation. SVAR approaches may face invertibility problems but simple diagnostics can help to detect and remedy these problems. A pragmatic empirical approach ought to use the flexibility of SVARs against potential misspecificationof the structural relationships but must firmly tie SVARs to the class of DSGE models which could have have generated the data.

Stock returns, term structure, inflation and real activity: An international perspective

This paper analyses the empirical interdependences among assetreturns, real activity and inflation from a multicountry and internationalpoint of view. We find that nominal stock returns are significantly relatedto inflation only in the US, that the US term structure of interest ratespredicts both domestic and foreign inflation rates while foreign termstructures do not have this predictive power and that innovations in inflationand exchange rates induce insignificant responses of real and financialvariables. An interpretation of the dynamics and some policy implicationsof the results are provided.