James Stock chairs the Department of Economics at Harvard University. His research focuses on empirical macroeconomics, forecasting, and econometric methods. Among other things, he has served on the economics panel at the National Science Foundation, on the Academic Advisory Group of the Federal Reserve Bank of Boston, and as a consultant to the European Central Bank. He received his Bachelor’s degree from Yale and holds advanced degrees in statistics and economics from the University of California, Berkeley.
Mark Watson is the Howard Harrison and Gabrielle Snyder Beck Professor of Economics and Public Affairs at Princeton University and a research associate at the National Bureau of Economic Research. He is a fellow of the American Academy of Arts and Sciences and of the Econometric Society. His research focuses on time-series econometrics, empirical macroeconomics, and macroeconomic forecasting. He has served as a consultant for the Federal Reserve Banks of Chicago and Richmond. Before coming to Princeton, Watson served on the economics faculty at Harvard and Northwestern. Watson did his undergraduate work at Pierce Junior College and California State University at Northridge, completed his Ph.D. at the University of California at San Diego, and holds on honorary doctorate from the University of Bern.
In keeping with their successful introductory econometrics text, Stock and Watson motivate each methodological topic with a real-world policy application that uses data, so that readers apply the theory immediately. Introduction to Econometrics, Brief, is a streamlined version of their text, including the fundamental topics, an early review of statistics and probability, the core material of regression with cross-sectional data, and a capstone chapter on conducting empirical analysis. Introduction and Review: Economic Questions and Data; Review of Probability; Review of Statistics. Fundamentals of Regression Analysis: Linear Regression with One Regressor; Regression with a Single Regressor: Hypothesis Tests and Confidence Intervals in the Single-Regressor Model; Linear Regression with Multiple Regressors; Hypothesis Tests and Confidence Intervals in the Multiple Regressor Model; Nonlinear Regression Functions; Assessing Studies Based on Multiple Regression; Conducting a Regression Study Using Economic Data. MARKET : For all readers interested in econometrics.
讲述清晰,透彻。 覆盖的内容比伍德里奇的那本书稍微少一点,比如面板数据只讲了固定效应模型,没有讲随机效应模型;受限因变量中没有讲Tobit模型、truncated 和censored 模型。 但是所有的内容都讲清楚了,尤其是时间序列部分,比伍德里奇的书说的明白。 目前只用过这本书,不...
评分目前只用过这本书,不好与别的教材比较,只能谈谈学习过后的感受。 总体来说不错,有点是案例选择合理,契合了每个阶段的学习内容,课后练习中的实证练习也反映出了这本教材注重应用的特点。 缺点也很明显,跟国内教材有些类似的是,本书对理论的阐述还是较为模...
评分目前只用过这本书,不好与别的教材比较,只能谈谈学习过后的感受。 总体来说不错,有点是案例选择合理,契合了每个阶段的学习内容,课后练习中的实证练习也反映出了这本教材注重应用的特点。 缺点也很明显,跟国内教材有些类似的是,本书对理论的阐述还是较为模...
评分首先要说,这本书整体还是不错的,翻译的也还可以。 然而,就本科生使用该书学习初级计量来看,明显不如使用伍德里奇的《计量经济学导论:现代观点》一书。 我觉得其主要原因在于:初级计量经济学应该把70%的精力放在掌握回归分析(特别是多元回归分析)的思想和方法上,其...
评分首先要说,这本书整体还是不错的,翻译的也还可以。 然而,就本科生使用该书学习初级计量来看,明显不如使用伍德里奇的《计量经济学导论:现代观点》一书。 我觉得其主要原因在于:初级计量经济学应该把70%的精力放在掌握回归分析(特别是多元回归分析)的思想和方法上,其...
great book!
评分中级计量
评分日久生情
评分lolololol Econometrics FTW
评分great book!
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