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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.


Papers
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Book ChapterDOI
31 Dec 2011
TL;DR: This article summarized and evaluated recent empirical research on education and family background, focusing on two related but distinct motivations for this topic: equality of opportunity and the child development perspective, and explored which types of economic policy, and what timing of the policy in relation to children's social and cognitive development, are conducive to childrens performance and adult outcomes.
Abstract: In every society for which we have data, people's educational achievement is positively correlated with their parents' education or with other indicators of their parents' socio-economic status. This topic is central in social science, and there is no doubt that research has intensified during recent decades, not least thanks to better data having become accessible to researchers. The purpose of this chapter is to summarize and evaluate recent empirical research on education and family background. Broadly speaking, we focus on two related but distinct motivations for this topic. The first is equality of opportunity. Here, the major research issues are: How important a determinant of educational attainment is family background, and is family background—in the broad sense that incorporates factors not chosen by the individual—a major, or only a minor, determinant of educational attainment? What are the mechanisms that make family background important? Have specific policy reforms been successful in reducing the impact of family background on educational achievement? The second common starting point for recent research has been the child development perspective. Here, the focus is on how human-capital accumulation is affected by early childhood resources. Studies with this focus address the questions: What types of parental resources or inputs are important for children's development, why are they important, and when are they important? In addition, this literature focuses on exploring which types of economic policy, and what timing of the policy in relation to children's social and cognitive development, are conducive to children's performance and adult outcomes. The policy interest in this research is whether policies that change parents' resources and restrictions have causal effects on their children.

153 citations

Journal ArticleDOI
TL;DR: It is concluded that the p -chlorophenylalanine-resistant B-type neurone is a morphologically and histochemically well-defined and separate entity.

152 citations

Journal ArticleDOI
TL;DR: In this paper, the authors compared the long-run earnings between the United States and Nordic countries (Denmark, Finland, Norway and Sweden) and concluded that the family and community factors are more important determinants of long-term earnings in the U.S. than in the Nordic countries.
Abstract: The correlation in economic status among siblings is a useful “omnibus measure” of the overall impact of family and community factors on adult economic status. In this study we compare brother correlations in long-run (permanent) earnings between the United States, on one hand, and the Nordic countries (Denmark, Finland, Norway and Sweden) on the other. Our base case results, based on very similar sample criteria and definitions for all countries, show that this correlation is above 0.40 in the United States and in the range 0.14–0.26 in the Nordic countries. Even though these results turn out to be somewhat sensitive to some assumptions that have to be made, we conclude that the family and community factors are more important determinants of long-run earnings in the United States than in the Nordic countries.

151 citations

Journal ArticleDOI
TL;DR: It is concluded that the immortalized neural progenitors have a number of advantageous properties that make them highly useful experimental tools for gene transfer to the adult CNS.
Abstract: A CNS-derived conditionally immortalized temperature-sensitive neural progenitor (CINP) cell line was used to generate NGF-secreting cells suitable for intracerebral transplantation. The cells were transduced by repeated retroviral infection, using a vector containing the mouse NGF cDNA under the control of the LTR promoter. Subcloning at the permissive temperature (33 degrees C) identified a highly NGF-secreting clone (NGF-CINP), which contained multiple copies of the transgene and released NGF at a rate of 2 ng/hr/10(5) cells in vitro, both at 33 and 37 degrees C, which was approximately 1 order of magnitude higher than what was possible to achieve in the heterogeneously infected cell cultures. After transplantation to the brain, the NGF-CINPs differentiated into cells with a predominant glia-like morphology and migrated for a distance of 1–1.5 mm from the implantation site into the surrounding host tissue, without any signs of overgrowth and tumor formation. Grafts of NGF-CINP cells implanted into the septum of adult rats with complete fimbria-fornix lesion blocked over 90% of the cholinergic cell loss in the medial septum and grafts placed in the intact striatum induced accumulation of low-affinity NGF receptor positive fibers around the implantation site. Expression of the NGF transgene in vivo was demonstrated by RT-PCR at 2 weeks after grafting. It is concluded that the immortalized neural progenitors have a number of advantageous properties that make them highly useful experimental tools for gene transfer to the adult CNS.

150 citations

Journal ArticleDOI
TL;DR: The results suggest that the fetal striatal cell suspension grafts will give rise to a fairly normal range of striatal neuron and receptor types and that they develop at least some of the striosomal features characteristic for the normal striatum.

149 citations


Cited by
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Book
01 Jan 2001
TL;DR: This is the essential companion to Jeffrey Wooldridge's widely-used graduate text Econometric Analysis of Cross Section and Panel Data (MIT Press, 2001).
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.

28,298 citations

28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组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�ly.
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。

18,940 citations

Book
28 Apr 2021
TL;DR: In this article, the authors proposed a two-way error component regression model for estimating the likelihood of a particular item in a set of data points in a single-dimensional graph.
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.

10,363 citations

Journal ArticleDOI
11 Sep 2003-Neuron
TL;DR: PD models based on the manipulation of PD genes should prove valuable in elucidating important aspects of the disease, such as selective vulnerability of substantia nigra dopaminergic neurons to the degenerative process.

4,872 citations