000			03952nam a22007817a 4500
003			MN-UlNUM
005			20220905143651.0
008			220829b2020 mp ||||| |||| 00| 0 mon d
020			_a978-1-337-55886-0
040			_afirst lib
082			_a510
084			_2Garin awlaga _q2 _a22.172 _bW 83
100			_aWooldridge J.M
240			_a22.172 W 83
245			_aIntroductory econometrics _bA modern approach
250			_a7th ed
260			_aMA _bCengage Learning _c2020
300			_a826
500			_aГФ 20471
505			_aWooldridge recognizes that modern econometrics involves much more than ordinary least squares (OLS) with a few extensions to handle the special cases commonly encountered in econometric data. In addition to chapters on OLS, he includes chapters on current techniques of estimation and inference for time-series data, panel data, limited dependent variables, and sample selection. In his treatments of OLS and two-stage least squares, Wooldridge breaks new ground by concentrating on advanced statistical concepts instead of matrix algebra. A traditional approach to introductory econometrics would use advanced sections to explain matrix algebra and its applications in econometrics. In contrast, Wooldridge uses the advanced sections of his text to introduce recently developed statistical concepts and techniques. This approach leads to a text with greater breadth than is usual in books of this type. This book is equally useful for advanced undergraduate study, as the basis of a survey course at the graduate level, or as a conceptual supplement to advanced courses.
546			_aEnglish
653			_amathematical statistics
653			_aeconomic statistics
653			_aregression
740			_aThe Nature of Econometrics and Economic Data
740			_aWhat Is Econometrics?
740			_aSteps in Empirical Economic Analysis
740			_aThe Structure of Economic Data
740			_aCross-Sectional Data
740			_aTime Series Data
740			_aPooled Cross Sections
740			_aPanel or Longitudinal Data
740			_aA Comment on Data Structures
740			_aCausality, Ceteris Paribus, and Counterfactual Reasoning
740			_aSummary
740			_aKey Terms
740			_aProblems
740			_aComputer Exercises
740			_aRegression Analysis with Cross-Sectional Data Chapter
740			_aThe Simple Regression Model
740			_aDefinition of the Simple Regression Model
740			_aDeriving the Ordinary Least Squares Estimates
740			_aA Note on Terminology
740			_aProperties of OLS on Any Sample of Data
740			_aFitted Values and Residuals
740			_aAlgebraic Properties of OLS Statistics
740			_aGoodness-of-Fit
740			_aUnits of Measurement and Functional Form
740			_aThe Effects of Changing Units of Measurement on OLS Statistics
740			_aIncorporating Nonlinearities in Simple Regression
740			_aThe Meaning of "Linear" Regression
740			_aExpected Values and Variances of the OLS Estimators
740			_aUnbiasedness of OLS
740			_aVariances of the OLS Estimators
740			_aEstimating the Error Variance
740			_aRegression through the Origin and Regression on a Constant
740			_aRegression on a Binary Explanatory Variable
740			_aCounterfactual Outcomes, Causality, and Policy Analysis
740			_aMultiple Regression Analysis: Estimation
740			_aMotivation for Multiple Regression
740			_aThe Model with Two Independent Variables
740			_aThe Model with k Independent Variables
740			_aMechanics and Interpretation of Ordinary Least Squares
740			_aObtaining the OLS Estimates
740			_aInterpreting the OLS Regression Equation
740			_aOn the Meaning of "Holding Other Factors Fixed" in Multiple Regression
942			_cBK
999			_c127009 _d127009