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.
译者特别喜欢直译,对英语从句从不处理,译文的句子又长又臭。 这种翻译水平,还是别来骗大伙的钱了。 举个例子吧,让大伙开动一下脑筋,杀杀脑细胞。 P430 通货膨胀中包含随机性趋势的原假设对其平稳的备择假设可用检验单位自回归根的ADF检验来进行。 The null hypothesis th...
評分讲述清晰,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。 另外,这本书中文版是...
評分建议看上海人民出版社出的影印版(第二版),全书语言流畅,思想脉络清晰,数学论证非常详细,特别适合对计量经济学的入门和深入理解。
評分首先要说,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...
評分讲述清晰,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。 另外,这本书出了第二...
lolololol Econometrics FTW
评分恩 教材 還好吧~~很易懂但是也很難...哎..
评分很好很受用
评分比伍德裏奇那本簡單一些,但是panel data部分編得更有邏輯一點
评分看瞭前半本
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