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.

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Econometric Analysis of Cross Section and Panel Data

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。

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

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.

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Econometric Analysis of Panel Data

Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

Parkinson's disease: Mechanisms and models

Clinical use of allografts of fetal ventral mesencephalic tissue as a treatment to replace dopaminergic neurons in patients with Parkinson's disease was first done more than 20 years ago. Since then, many patients have received transplants, with variable results. During this time, our knowledge of Parkinson's disease has changed and the nature and extent of problems associated with the disorder have been better defined. Our understanding on how best to implement this cell-replacement strategy for patients has grown, but gaining this insight has entailed critical reappraisal of data from transplant trials that have already been undertaken.

https://www.thelancet.com/pdfs/journals/laneur/PIIS1474-4422(12)70295-8.pdf

Fetal dopaminergic transplantation trials and the future of neural grafting in Parkinson's disease

In rats, striatal neuronal destruction by so-called excitotoxic amino acids, kainic acid or ibotenic acid (IA) produce neuropathological and neurochemical changes in the basal ganglia which resemble those seen in patients with Huntington's chorea. Such lesioned animals show a behavioural syndrome which is reminiscent of the cardinal symptoms of the disease, accompanied by a substantial increase in local cerebral metabolic activity in several striatal target structures within the extrapyramidal motor system. The study was designed to explore the potential of grafted fetal striatal neurones implanted into the IA-lesioned striatum to compensate for the structural, neurochemical, metabolic and behavioural defects of IA-lesioned rats. Extending previous studies, we report here that such striatal implants can significantly ameliorate the lesion-induced locomotor hyperactivity and at least partly normalize the metabolic hyperactivity in the extrapyramidal neuronal system.

Functional neuronal replacement by grafted striatal neurones in the ibotenic acid-lesioned rat striatum

IN A SERIES of morphological and biochemical investigations (BAUMGARTEN & LACHENMAYER, 1972; BAUMGARTEN et al., 1973a; BJORKLUND et al., 1973a; BAUMGARTEN et al., 1973b; JACOBY et al., 1974) 5,7-dihydroxytryptamine (5,7-DHT) has been shown to induce extensive axonal degeneration of central serotonin neurons after intraventricular or intracerebral injections in the rat. A major drawback of 5,7-DHT as a tool for chemical lesioning of serotonin meurons is, however, its poor discrimination between 5-HT and NA neurons, and thus both 5-HT and NA axons in the CNS are lesioned by the drug (BAUMGARTEN et al., 1973a; BJORKLUND et al., 1973a; JACOBY et al., 1974). In fact, in lower doses (less than 75 p g intraventriculary) the depletion of brain NA is asgreat as that of serotonin (BAUMGARTEN et al., 1973a). As the action of the neurotoxic indolamines is due to its intraneuronal accumulation by the membrane uptake mechanisms of the monoamine neurons (for discussion, see BJORKLUND eta!., 1974) one possibility to improve the selectivity of 5,7-DHT for serotonin neurons would be to block the uptake of the drug into NA neurons without affecting the uptake into the serotonin neurons. Desipramine has been reported to be more efficient in blocking the membrane pump of NA than of serotonin neurons (FUXE & UNGERSTEDT, 1968; CARLSSON et al., 1969). In the present study we report that pretreatment of the animals with desipramine efficiently counteracts the long-term effects of 5,7DHT on NA neurons while the neurotoxic effects on the serotonin neurons are unimpaired.

5,7-Dihydroxytryptamine: improvement of its selectivity for serotonin neurons in the CNS by pretreatment with desipramine

http://link.springer.com/content/pdf/10.1007/978-1-4684-3183-4_4.pdf

Anders Björklund

Papers

Fetal dopaminergic transplantation trials and the future of neural grafting in Parkinson's disease

Functional neuronal replacement by grafted striatal neurones in the ibotenic acid-lesioned rat striatum

5,7-Dihydroxytryptamine: improvement of its selectivity for serotonin neurons in the CNS by pretreatment with desipramine

Organization of Catecholamine Neurons in the Rat Central Nervous System

Progressive decline in spatial learning and integrity of forebrain cholinergic neurons in rats during aging.