Anders Björklund

Bio: Anders Björklund is an academic researcher from Lund University. The author has contributed to research in topics: Transplantation & Dopamine. The author has an hindex of 165, co-authored 769 publications receiving 84268 citations. Previous affiliations of Anders Björklund include University of Washington & Institute for the Study of Labor.

Cerebellum, basal ganglia, olfactory system

Abstract: The Cerebellum, Chemoarchitecture and Anatomy (J. Voogd, D. Jaarsma, E. Marani). 1. Introduction. 2. Cytology of the cerebellar cortex. 3. Chemical anatomy of the cerebellar cortex. 4. Gross anatomy of the mammalian cerebellum. 5. The cerebellar nuclei. 6. Efferent and afferent connections of the cerebellar cortex: corticonuclear, olivocerebellar and mossy fiber connections and cytochemical maps. 7. Postscript. 8. Acknowledgements. 9. References. II. The Basal Ganglia (C.R. Gerfen, C.J. Wilson). 1. Introduction. 2. Organizational overview. 3. Cerebral cortex input to striatum. 4. Striatum. 5. Globus pallidus (external segment). 6. Subthalamic nucleus. 7. Substantia nigra/entopeduncular nucleus. 8. Connectional organization of basal ganglia. 9. Relationship between cortex and basal ganglia. 10. Striatal patch/matrix compartments. 11. Direct/indirect striatal output system. 12. Acknowledgements. 13. References. III. The Olfactory System (M.T. Shipley, J.H. McLean, L.A. Zimmer, M. Ennis). 1. Introduction. 2. The main olfactory bulb. 3. Primary olfactory cortex. 4. Integration of the main olfactory system with other functions. 5. The accessory olfactory system. 6. "Non-olfactory" modulatory inputs to the olfactory system. 7. Acknowledgements. 8. Abbreviations. 9. References. Subject Index.

The Evolution of Income Inequality During the Rise of the Swedish Welfare State 1951 to 1973

Abstract: We analyse the change in family gross income inequality between 1951 and 1973. We use two new samples of the Swedish population from 1951 and 1956 containing tax register data, and compare the results with those obtained from the Swedish Level of Living survey from 1967 and 1973. Gini coefficients, four different Generalised entropy measures as well as decile group shares of total income are calculated. We also do two different decompositions: one between different demographic groups and one between the male and female component of family income. Finally, we examine to what extent zero family income records really reflect low economic welfare by using interview data from the 1968 Swedish Level of Living Survey.

What More Than Parental Income? An Exploration of What Swedish Siblings Get from Their Parents

Abstract: Sibling correlations are used as overall measures of the impact of family background and community influences on individual outcomes. While most correlation studies show that siblings are quite similar in terms of future achievement, we lack specific knowledge of what it is about family background that really matters. Studies on intergenerational income mobility show that parental income matters to some extent, but they also show that more than half of the family background and community influences that siblings share are not even correlated with parental income. In this paper, we employ a data set that contains rich information about families in order to explore what factors in addition to parental income can explain why siblings tend to have such similar outcomes. Our results show that measures of family structure and social problems account for very little of sibling similarities in adult income above and beyond that already accounted for by parental income. However, when we add a set of indicators for parental involvement and attitudes, the explanatory power of all our variables increased from about a third (using only traditional indicators of socio-economic status) to just over half. Interestingly, indicators of parents' patience, i.e., propensity to plan ahead and willingness to postpone benefits to the future, are particularly important.

The Impact of Family Background on the Returns on and Length of Schooling in Sweden

Abstract: It is a common observation in most societies that children of parents with high incomes, extensive schooling and high-status occupations tend to emulate the behaviour of their parents and in particular invest more in schooling than other children. This pattern is often considered a problem from both equity and efficiency points of views. It represents inequality of opportunity and possibly also inefficiency if the intellectual capacity of all children is not fully exploited. A variety of educational policies have been advocated to reduce the importance of family background for schooling decisions. No country seems, however, to have been very successful in this respect.

Econometric Analysis of Cross Section and Panel Data

Abstract: The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Econometric Analysis of Panel Data

Abstract: Preface.1. Introduction.1.1 Panel Data: Some Examples.1.2 Why Should We Use Panel Data? Their Benefits and Limitations.Note.2. The One-way Error Component Regression Model.2.1 Introduction.2.2 The Fixed Effects Model.2.3 The Random Effects Model.2.4 Maximum Likelihood Estimation.2.5 Prediction.2.6 Examples.2.7 Selected Applications.2.8 Computational Note.Notes.Problems.3. The Two-way Error Component Regression Model.3.1 Introduction.3.2 The Fixed Effects Model.3.3 The Random Effects Model.3.4 Maximum Likelihood Estimation.3.5 Prediction.3.6 Examples.3.7 Selected Applications.Notes.Problems.4. Test of Hypotheses with Panel Data.4.1 Tests for Poolability of the Data.4.2 Tests for Individual and Time Effects.4.3 Hausman's Specification Test.4.4 Further Reading.Notes.Problems.5. Heteroskedasticity and Serial Correlation in the Error Component Model.5.1 Heteroskedasticity.5.2 Serial Correlation.Notes.Problems.6. Seemingly Unrelated Regressions with Error Components.6.1 The One-way Model.6.2 The Two-way Model.6.3 Applications and Extensions.Problems.7. Simultaneous Equations with Error Components.7.1 Single Equation Estimation.7.2 Empirical Example: Crime in North Carolina.7.3 System Estimation.7.4 The Hausman and Taylor Estimator.7.5 Empirical Example: Earnings Equation Using PSID Data.7.6 Extensions.Notes.Problems.8. Dynamic Panel Data Models.8.1 Introduction.8.2 The Arellano and Bond Estimator.8.3 The Arellano and Bover Estimator.8.4 The Ahn and Schmidt Moment Conditions.8.5 The Blundell and Bond System GMM Estimator.8.6 The Keane and Runkle Estimator.8.7 Further Developments.8.8 Empirical Example: Dynamic Demand for Cigarettes.8.9 Further Reading.Notes.Problems.9. Unbalanced Panel Data Models.9.1 Introduction.9.2 The Unbalanced One-way Error Component Model.9.3 Empirical Example: Hedonic Housing.9.4 The Unbalanced Two-way Error Component Model.9.5 Testing for Individual and Time Effects Using Unbalanced Panel Data.9.6 The Unbalanced Nested Error Component Model.Notes.Problems.10. Special Topics.10.1 Measurement Error and Panel Data.10.2 Rotating Panels.10.3 Pseudo-panels.10.4 Alternative Methods of Pooling Time Series of Cross-section Data.10.5 Spatial Panels.10.6 Short-run vs Long-run Estimates in Pooled Models.10.7 Heterogeneous Panels.Notes.Problems.11. Limited Dependent Variables and Panel Data.11.1 Fixed and Random Logit and Probit Models.11.2 Simulation Estimation of Limited Dependent Variable Models with Panel Data.11.3 Dynamic Panel Data Limited Dependent Variable Models.11.4 Selection Bias in Panel Data.11.5 Censored and Truncated Panel Data Models.11.6 Empirical Applications.11.7 Empirical Example: Nurses' Labor Supply.11.8 Further Reading.Notes.Problems.12. Nonstationary Panels.12.1 Introduction.12.2 Panel Unit Roots Tests Assuming Cross-sectional Independence.12.3 Panel Unit Roots Tests Allowing for Cross-sectional Dependence.12.4 Spurious Regression in Panel Data.12.5 Panel Cointegration Tests.12.6 Estimation and Inference in Panel Cointegration Models.12.7 Empirical Example: Purchasing Power Parity.12.8 Further Reading.Notes.Problems.References.Index.