マクロ数量分析特研I
第 1回 | 4月 | 11日 | Objectives of analyzing multiple time series, some basics, vector autoregressive processes, stable VAR(p) processes | |
第 2回 | 18日 | The moving average represenation of a VAR process, stationary processes, computation of autocovariances and autocorrelations of stable VAR processes, | ||
the loss function, point forecasts, interval forecasts and forecast regions | ||||
第 3回 | 25日 | Gragner causality, instantaneous causality, multi-step causality, impulse response analysis | ||
第 4回 | 5月 | 2日 | Impulse response analysis, forecast error variance decomposition, multivariate least squares estimation, asymptotic properties of the least squares estimator | |
第 5回 | 9日 | Small sample properties of the LS estimator, least squares estimation with mean-adjusted data and Yule-Walker estimation, maximum likelihood estimation | ||
第 6回 | 16日 | Forecasting with estimated processes, testing for causality | ||
第 7回 | 23日 | cancelled | ||
第 8回 | 30日 | The asymptotic distribution of the impulse responses by simulation techniques, a sequence of tests for determining the VAR order | ||
第 9回 | 6月 | 6日 | A testing scheme for VAR order determination, criteria for VAR order selection | |
the asymptotic distributions of the autocovariances and autocorrelations of a white noise process | ||||
第10回 | 13日 | The asymptotic distributions of the residual autocovariances and autocorrelations of an estimated VAR process, testing for nonnormality, tests for structural change | ||
第11回 | 20日 | VAR processes with parameter constraints, linear constraints, LS/GLS/EGLS/ML estimation, constraints for individual equations, restrictions for the white noise covariance matrix | ||
第12回 | 27日 | Forecasting, impulse response analysis and forecast error variance decomposition, specification of subset VAR models, model checking | ||
第13回 | 7月 | 4日 | Integrated processes, VAR processes with integrated variables, cointegrated processes, common stochastic trends, vector error correction models | |
第14回 | 11日 | Deterministic terms in cointegrated processes, forecasting integrated and cointegrated variables, causality analysis, impulse response analysis | ||
第15回 | 25日 | Review | ||