Subjective health assessments and active labor market participation of older men: evidence from a semiparametric binary choice model with nonadditive correlated individual-specific effects

We use panel data from the U. S. Health and Retirement Study, 1992-2002, to estimate the effect of self-assessed health limitations on the active labor market participation of older men. Self-assessments of health are likely to be endogenous to labor supply due to justification bias and individual-specific heterogeneity in subjective evaluations. We address both concerns. We propose a semiparametric binary choice procedure that incorporates nonadditive correlated individual-specific effects. Our estimation strategy identifies and estimates the average partial effects of health and functioning on labor market participation. The results indicate that poor health plays a major role in labor market exit decisions.

Interviewer and Respondent Survey Quality Effects in a CATI Panel

Especially in panel surveys, respondent attrition, respondent learning, and interviewer experience effects play a crucial role with respect to data quality. We examine three interview survey quality indicators in the same survey in a cross sectional as well as in a longitudinal way. In the cross sectional analysis we compare data quality in the mature original sample with that in a refreshment sample, surveyed in the same wave. Because in the same wave an interviewer survey was conducted, collecting attitudes on their socio demography, survey attitudes and burden measures, we are able to consider interviewer fixed effects as well. The longitudinal analysis gives more insight in the respondent learning effects with respect to the quality indicators considered by considering the very same respondents across waves. The Swiss Household Panel, a CATI survey representative of the Swiss residential population, forms an ideal modelling database: the interviewer - respondent assignment is random, both within and across waves. This design avoids possible confusion with other effects stemming from a non-random assignment of interviewers, e.g. area effects or effects from assigning the best interviewers to the hard cases. In order to separate interviewer, respondent and wave effects, we build cross-classified multilevel models.

Spatial and temporal effects of free-air CO2 enrichment (POPFACE) on leaf growth, cell expansion and cell production in a closed canopy of poplar

Leaf expansion in the fast-growing tree,Populus × euramericana was stimulated by elevated [CO2] in a closed-canopy forest plantation, exposed using a free air CO2 enrichment technique enabling long-term experimentation in field conditions. The effects of elevated [CO2] over time were characterized and related to the leaf plastochron index (LPI), and showed that leaf expansion was stimulated at very early (LPI, 0–3) and late (LPI, 6–8) stages in development. Early and late effects of elevated [CO2] were largely the result of increased cell expansion and increased cell production, respectively. Spatial effects of elevated [CO2] were also marked and increased final leaf size resulted from an effect on leaf area, but not leaf length, demonstrating changed leaf shape in response to [CO2]. Leaves exhibited a basipetal gradient of leaf development, investigated by defining seven interveinal areas, with growth ceasing first at the leaf tip. Interestingly, and in contrast to other reports, no spatial differences in epidermal cell size were apparent across the lamina, whereas a clear basipetal gradient in cell production rate was found. These data suggest that the rate and timing of cell production was more important in determining leaf shape, given the constant cell size across the leaf lamina. The effect of elevated [CO2] imposed on this developmental gradient suggested that leaf cell production continued longer in elevated [CO2] and that basal increases in cell production rate were also more important than altered cell expansion for increased final leaf size and altered leaf shape in elevated [CO2].

Ex-post evaluation of the employment effects of a preferential trade agreement: methodological issues, illustrated with a reference to Chile

Includes bibliography

No sports – no mental health? Analysis of longitudinal effects in SHP data.

Results from the Zurich study have shown lasting associations between sport practice and mental health. The effects are pronounced in people with pre-exising mental health problems. This analysis aims to replicate these results with the large Swiss Household Panel data set and to provide more differentiated results. The analysis covered the interviews 1999-2003 and included 3891 stayers, i.e., participants who were interviewed in all years. The outcome variables are depression / blues / anxiety, weakness / weariness, sleeping problems, energy / optimism. Confounding variables include sex, age, education level, citizenship. The analyses were carried out with mixed models (depression, optimism) and GEE models (weakness, sleep). About 60% of the SHP participants practise weekly or daily an individual or a team sport. A similar proportion enjoys a frequent physical activity (for half an hour minimum) which makes oneself slightly breathless. There are slight age-specific differences but also noteworthy regional differences. Practice of sport is clearly interrelated with self-reported depressive symptoms, optimism and weakness. This applies even though some relevant confounders – sex, educational level and citizenship – were introduced into the model. However, no relevant interaction effects with time could be shown. Moreover, direct interrelations commonly led to better fits than models with lagged variables, thus indicating that delayed effects of sport practice on the self-reported psychological complaints are less important. Model variants resulted for specific subgroups, for example, participants with a high vs. low initial activity level. Lack of sport practice is an interesting marker for serious psychological symptoms and mental disorders. The background of this association may differ in different subgroups, and should stimulate further investigations in this area.

Multiple imputation for missing continuous and dichotomous data: The effects of patterns of missingness and variable correlations on type I error with small samples

The purpose of this study is to investigate the effects of predictor variable correlations and patterns of missingness with dichotomous and/or continuous data in small samples when missing data is multiply imputed. Missing data of predictor variables is multiply imputed under three different multivariate models: the multivariate normal model for continuous data, the multinomial model for dichotomous data and the general location model for mixed dichotomous and continuous data. Subsequent to the multiple imputation process, Type I error rates of the regression coefficients obtained with logistic regression analysis are estimated under various conditions of correlation structure, sample size, type of data and patterns of missing data. The distributional properties of average mean, variance and correlations among the predictor variables are assessed after the multiple imputation process. ^ For continuous predictor data under the multivariate normal model, Type I error rates are generally within the nominal values with samples of size n = 100. Smaller samples of size n = 50 resulted in more conservative estimates (i.e., lower than the nominal value). Correlation and variance estimates of the original data are retained after multiple imputation with less than 50% missing continuous predictor data. For dichotomous predictor data under the multinomial model, Type I error rates are generally conservative, which in part is due to the sparseness of the data. The correlation structure for the predictor variables is not well retained on multiply-imputed data from small samples with more than 50% missing data with this model. For mixed continuous and dichotomous predictor data, the results are similar to those found under the multivariate normal model for continuous data and under the multinomial model for dichotomous data. With all data types, a fully-observed variable included with variables subject to missingness in the multiple imputation process and subsequent statistical analysis provided liberal (larger than nominal values) Type I error rates under a specific pattern of missing data. It is suggested that future studies focus on the effects of multiple imputation in multivariate settings with more realistic data characteristics and a variety of multivariate analyses, assessing both Type I error and power. ^

Determinants and Effects of Maturity Mismatches in Emerging Markets: Evidence from Bank Level Data

Despite the extensive work on currency mismatches, research on the determinants and effects of maturity mismatches is scarce. In this paper I show that emerging market maturity mismatches are negatively affected by capital inflows and price volatilities. Furthermore, I find that banks with low maturity mismatches are more profitable during crisis periods but less profitable otherwise. The later result implies that banks face a tradeoff between higher returns and risk, hence channeling short term capital into long term loans is caused by cronyism and implicit guarantees rather than the depth of the financial market. The positive relationship between maturity mismatches and price volatility, on the other hand, shows that the banks of countries with high exchange rate and interest rate volatilities can not, or choose not to hedge themselves. These results follow from a panel regression on a data set I constructed by merging bank level data with aggregate data. This is advantageous over traditional studies which focus only on aggregate data.

The impact of spatial data redundancy on SOLAP query performance

Geographic Data Warehouses (GDW) are one of the main technologies used in decision-making processes and spatial analysis, and the literature proposes several conceptual and logical data models for GDW. However, little effort has been focused on studying how spatial data redundancy affects SOLAP (Spatial On-Line Analytical Processing) query performance over GDW. In this paper, we investigate this issue. Firstly, we compare redundant and non-redundant GDW schemas and conclude that redundancy is related to high performance losses. We also analyze the issue of indexing, aiming at improving SOLAP query performance on a redundant GDW. Comparisons of the SB-index approach, the star-join aided by R-tree and the star-join aided by GiST indicate that the SB-index significantly improves the elapsed time in query processing from 25% up to 99% with regard to SOLAP queries defined over the spatial predicates of intersection, enclosure and containment and applied to roll-up and drill-down operations. We also investigate the impact of the increase in data volume on the performance. The increase did not impair the performance of the SB-index, which highly improved the elapsed time in query processing. Performance tests also show that the SB-index is far more compact than the star-join, requiring only a small fraction of at most 0.20% of the volume. Moreover, we propose a specific enhancement of the SB-index to deal with spatial data redundancy. This enhancement improved performance from 80 to 91% for redundant GDW schemas.

Non-Spatial Government Policies and Regional Income Inequality in Brazil

Silveira Neto R. Da M. and Azzoni C. R. Non-spatial government policies and regional income inequality in Brazil, Regional Studies. This paper uses both macro- and micro-data to analyse the role of social programmes in the recent reduction in Brazilian regional income inequality. Convergence indicators are presented for different sources of regional income in the period 1995-2006. A decomposition of the Gini indicator allows the identification of the role of each of these income sources with respect to the reduction of regional inequality during the period. The results point out that both labour productivity and government non-spatial policies - mainly minimum wage changes and income transference programmes - do have a role in explaining regional inequality reduction during the period. [image omitted] Silveira Neto R. Da M. et Azzoni C. R. Les politiques gouvernementales non-spatiales et l`ecart des revenus regionaux au Bresil, Regional Studies. Cet article emploie des donnees a la fois macroeconomiques et microeconomiques afin d`analyser le role des programmes d`actions sociales quant a la baisse recente de l`ecart des revenus regionaux au Bresil. On presente des indicateurs de convergence pour diverses sources des revenus regionaux pour la periode allant de 1995 a 2006. Une decomposition du coefficient de Gini permet d`identifier le role de chacune de ces sources des revenus par rapport a la baisse de l`ecart des revenus pendant cette periode. Les resultats indiquent que la productivite du travail et les politiques gouvernementales non-spatiales - notamment la modification du salaire minimum et les programmes visant le transfert des revenus - ont un role a jouer pour expliquer la baisse de l`ecart des revenus regionaux pendant la periode en question. Convergence Productivite du travail Transfert des revenus Salaire minimum Effets spatiaux des politiques non-spatiales Silveira Neto R. Da M. und Azzoni C. R. Nicht raumliche Regierungspolitiken und das regionale Einkommensungleichgewicht in Brasilien, Regional Studies. In diesem Beitrag analysieren wir mit Hilfe von Makro- und Mikrodaten die Rolle von sozialen Programmen bei der unlangst erzielten Verringerung des regionalen Einkommensungleichgewichts in Brasilien. Wir stellen Konvergenz-Indikatoren fur verschiedene regionale Einkommensquellen im Zeitraum von 1995 bis 2006 vor. Eine Dekomposition des Gini-Indikators ermoglicht die Identifizierung der jeweiligen Rolle dieser Einkommensquellen fur die Verringerung des regionalen Ungleichgewichts im betreffenden Zeitraum. Die Ergebnisse weisen darauf hin, dass sowohl die Produktivitat der Arbeitskrafte als auch die nicht raumlichen Regierungspolitiken - in erster Linie Veranderungen beim Mindestlohn und Programme fur Einkommenstransfers - als Grunde fur die Verringerung des regionalen Ungleichgewichts in dieser Periode durchaus eine Rolle spielen. Konvergenz Arbeitsproduktivitat Einkommenstransfer Mindestlohn Raumliche Auswirkungen nicht raumlicher Politiken Silveira Neto R. Da M. y Azzoni C. R. Politicas gubernamentales no espaciales y desigualdades de ingresos regionales en Brasil, Regional Studies. En este articulo utilizamos datos macro y micro para analizar el papel de los programas sociales en la reciente reduccion en las desigualdades de ingresos regionales de Brasil. Presentamos los indicadores de convergencia para diferentes fuentes de ingresos regionales en el periodo de 1995 a 2006. Una descomposicion del indice Gini permite identificar el papel de cada una de estas fuentes de ingresos con respecto a la reduccion de las desiguadades regionales durante este periodo. Los resultados destacan que tanto la productividad laboral como las politicas no espaciales del gobierno - principalmente los cambios de salario minimo y los programas de transferencias de ingresos - desempenan una funcion a la hora de explicar la reduccion de las desigualdades regionales durante este periodo. Convergencia Productividad laboral Transferencias de ingresos Salario minimo Efectos espaciales de politicas no espaciales.

Neuroprotective Effects of Diazepam, Carbamazepine, Phenytoin and Ketamine after Pilocarpine-induced Status Epilepticus

Cell damage and spatial localization deficits are often reported as long-term consequences of pilocarpine-induced status epilepticus. In this study, we investigated the neuroprotective effects of repeated drug administration after long-lasting status epilepticus. Groups of six to eight Wistar rats received microinjections of pilocarpine (2.4 mg/mu l, 1 mu l) in the right dorsal hippocampus to induce a status epilepticus, which was attenuated by thiopental injection (35 mg/kg, i.p.) 3 hrs after onset. Treatments consisted of i.p. administration of diazepam, ketamine, carbamazepine, or phenytoin at 4, 28, 52, and 76 hr after the onset of status epilepticus. Two days after the treatments, rats were tested in the Morris water maze and 1 week after the cognitive tests, their brains were submitted to histology to perform haematoxylin and eosin staining and glial fibrillary acidic protein (GFAP) immunofluorescence detection. Post-status epilepticus rats exhibited extensive gliosis and cell loss in the hippocampal CA1, CA3 (70% cell loss for both areas) and dentate gyrus (60%). Administration of all drugs reduced cell loss in the hippocampus, with best effects observed in brains slices of diazepam-treated animals, which showed less than 30% of loss in the three areas and decreased GFAP immunolabelling. Treatments improved spatial navigation during training trials and probe trial, with exception of ketamine. Interestingly, in the probe trial, only diazepam-treated animals showed preference for the goal quadrant. Our data point to significant neuroprotective effects of repeated administration of diazepam against status epilepticus-induced cell damage and cognitive disturbances.

A stochastic frontier production function with flexible risk properties

This paper considers a stochastic frontier production function which has additive, heteroscedastic error structure. The model allows for negative or positive marginal production risks of inputs, as originally proposed by Just and Pope (1978). The technical efficiencies of individual firms in the sample are a function of the levels of the input variables in the stochastic frontier, in addition to the technical inefficiency effects. These are two features of the model which are not exhibited by the commonly used stochastic frontiers with multiplicative error structures, An empirical application is presented using cross-sectional data on Ethiopian peasant farmers. The null hypothesis of no technical inefficiencies of production among these farmers is accepted. Further, the flexible risk models do not fit the data on peasant farmers as well as the traditional stochastic frontier model with multiplicative error structure.

Capillaries within compartments: Microvascular interpretation of dynamic positron emission tomography data

Measurement of exchange of substances between blood and tissue has been a long-lasting challenge to physiologists, and considerable theoretical and experimental accomplishments were achieved before the development of the positron emission tomography (PET). Today, when modeling data from modern PET scanners, little use is made of earlier microvascular research in the compartmental models, which have become the standard model by which the vast majority of dynamic PET data are analysed. However, modern PET scanners provide data with a sufficient temporal resolution and good counting statistics to allow estimation of parameters in models with more physiological realism. We explore the standard compartmental model and find that incorporation of blood flow leads to paradoxes, such as kinetic rate constants being time-dependent, and tracers being cleared from a capillary faster than they can be supplied by blood flow. The inability of the standard model to incorporate blood flow consequently raises a need for models that include more physiology, and we develop microvascular models which remove the inconsistencies. The microvascular models can be regarded as a revision of the input function. Whereas the standard model uses the organ inlet concentration as the concentration throughout the vascular compartment, we consider models that make use of spatial averaging of the concentrations in the capillary volume, which is what the PET scanner actually registers. The microvascular models are developed for both single- and multi-capillary systems and include effects of non-exchanging vessels. They are suitable for analysing dynamic PET data from any capillary bed using either intravascular or diffusible tracers, in terms of physiological parameters which include regional blood flow. (C) 2003 Elsevier Ltd. All rights reserved.

Structural Interactions in Spatial Panels

Until recently, much effort has been devoted to the estimation of panel data regression models without adequate attention being paid to the drivers of diffusion and interaction across cross section and spatial units. We discuss some new methodologies in this emerging area and demonstrate their use in measurement and inferences on cross section and spatial interactions. Specifically, we highlight the important distinction between spatial dependence driven by unobserved common factors and those based on a spatial weights matrix. We argue that, purely factor driven models of spatial dependence may be somewhat inadequate because of their connection with the exchangeability assumption. Limitations and potential enhancements of the existing methods are discussed, and several directions for new research are highlighted.

The effects of agglomeration on wages: evidence from the micro-level

This paper estimates individual wage equations in order to test two rival non-nested theories of economic agglomeration, namely New Economic Geography (NEG), as represented by the NEG wage equation and urban economic (UE) theory , in which wages relate to employment density. The paper makes an original contribution by evidently being the first empirical paper to examine the issue of agglomeration processes associated with contemporary theory working with micro-level data, highlighting the role of gender and other individual-level characteristics. For male respondents, there is no significant evidence that wage levels are an outcome of the mechanisms suggested by NEG or UE theory, but this is not the case for female respondents. We speculate on the reasons for the gender difference.