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PART TWO INTRODUCTION TO PROBABILITY
Random Variables and Probability Distributions
Classical Statistical Inference
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2SLS 2SLS estimator aggregate American Statistical Association analysis assume assumption asymptotic autocorrelation autoregressive Bayesian bias compute confidence intervals consider consistent estimates constant term consumption function covariance matrix defined degrees of freedom demand function denote dependent variable derived discussed Distributed Lag distributed-lag models Durbin econometric Econometrica economic endogenous example exogenous variables explanatory variables forecasts gamma distribution given Hence heteroscedasticity hypothesis income independent instrumental variables iterative lag distribution least-squares estimators likelihood function linear mean measure method minimize ML estimates multicollinearity multiple regression normal distribution number of observations obtained oi oi omitted variables parameters percent plim posterior distribution prediction prior probability distribution problem procedure random variable ratio reduced-form regression coefficients regression equation regression model relationship residual sum restrictions sample serial correlation significant standard errors suggested sum of squares Suppose Table time-series data tion variance a2 vector zero