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TOPIC #TOPICSREADINGS
1Univariate Time Series
1.1Introduction, stochastic processes, stationarity, models for trends and detrending.
  • P. Brockwell., and R. Davis. Time Series: Theory and Methods. Second edition. New York: Springer-Verlag, 1991. Chapter 1.
  • J. Hamilton. Time Series Analysis. Princeton: Princeton University Press, 1994. Chapter 3.
  • W. Enders. Applied Econometric Time Series. New York: Wiley, 1995. 2-3.
  • C. Nelson, and C. Plosser. “Trends and Random Walks in Macroeconomic Time Series." In Journal of Monetary Economics 10 (1982): 139-162.
1.2Stationary time series models, ARMA models, ACF, PACF, lag operators, linear difference equations.
  • P. Brockwell., and R. Davis. Time Series: Theory and Methods. Second edition. New York: Springer-Verlag, 1991. Chapters 2, 3.
  • J. Hamilton. Time Series Analysis. Princeton: Princeton University Press, 1994. Chapters 1-3.
  • W. Enders. Applied Econometric Time Series. New York: Wiley, 1995. 1-2.
1.3Spectral representation, spectral densities of ARMA models.
  • J. Hamilton. Time Series Analysis. Princeton: Princeton University Press, 1994. Chapter 6.
  • P. Brockwell., and R. Davis. Time Series: Theory and Methods. Second edition. New York: Springer-Verlag, 1991. Chapter 4.
1.4Wald decomposition and prediction of stationary time series.
  • J. Hamilton. Time Series Analysis. Princeton: Princeton University Press, 1994. Chapter 4.
  • P. Brockwell., and R. Davis. Time Series: Theory and Methods. Second edition. New York: Springer-Verlag, 1991. Chapter 5.
1.5Estimation of time series models. Least squares, ML and frequency domain techniques.
  • J. Hamilton. Time Series Analysis. Princeton: Princeton University Press, 1994. Chapter 5.
  • P. Brockwell., and R. Davis. Time Series: Theory and Methods. Second edition. New York: Springer-Verlag, 1991. Chapters 8 and 10.
1.6Specification testing, order selection.
  • P. Brockwell., and R. Davis. Time Series: Theory and Methods. Second edition. New York: Springer-Verlag, 1991. Chapter 9.
  • Andrews and Ploberger. “Testing for Serial Correlation Against an ARMA (1, 1) Process.” In Journal of the American Statistical Association 91 (1996): 1331-1342.
  • Breusch. “Testing for Autocorrelation in Dynamic Linear Models.” In Australian Economic Papers 17 (1978): 534-355.
  • Godfrey. “Testing Against General Autoregressive and Moving Average Error Models when the Regressors include Lagged Dependent Variables.” In Econometrica 46 (1978): 1293-1303.
  • B.M. Pötscher. ”Estimation of Autoregressive Moving-Average Order Given an Infinite Number of Models and Approximation Of Spectral Densities.” In Journal of Time Series Analysis Vol. 11, No 2 (1990): 165-179.
2Multivariate Models
2.1Vector autoregressions, impulse response functions, variance decomposition, identification, exogeneity, causality.
  • J. Hamilton. Time Series Analysis. Princeton: Princeton University Press, 1994. Chapter 11.
  • P. Brockwell., and R. Davis. Time Series: Theory and Methods. Second edition. New York: Springer-Verlag, 1991. Chapter 11.
  • W. Enders. Applied Econometric Time Series. New York: Wiley, 1995. Chapter 5.
  • O. Blanchard,  and D.Quah. "The Dynamic Effects of Aggregate Demand and Supply Disturbances.” In The American Economic Review (1989): 655-672.
  • C. A. Sims. “Money, Income and Causality.” In American Economic Review 62 (1972): 540-552.
2.2Multivariate nonlinear models, GMM estimation, covariance matrix estimation.
  • J. Hamilton. Time Series Analysis. Princeton: Princeton University Press, 1994. Chapter 14.
  • L.P. Hansen. “Large Sample Properties of Generalized Method of Moments Estimators.” In Econometrica 50 (1982): 1029-1053.
  • L.P. Hansen, and K.J. Singleton. “Generaliuzed Instrumental Variables Estimation of Nonlinear Rational Expectation Models.” In Econometrica 50:5 (1982):  1269-1286.
  • W. Newey, and K.West. “A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covaiance Matrix.” In Econometrica 55 (3) (1987): 703-708.
3Time Series Models for Integrated Processes
3.1Regressions with integrated regressors, testing for unit roots.
  • J. Hamilton. Time Series Analysis. Princeton: Princeton University Press, 1994. Chapter 17.
  • P.C.B. Phillips. “Understanding Spurious Regressions in Econometrics.” In Journal of Econometrics 33 (1986): 311-340.
  • P.C.B. Phillips. “Time Series Regression with a Unit Root.” In Econometrica 55 (1987): 277-302.
  • P.C.B. Phillips, and P. Perron. “Testing for a Unit Root in Time Series Regression." In Biometrika 75 (1987): 335-346.
  • Schmidt, and P.C.B. Phillips. “LM Tests for a Unit Root in the Presence of Deterministic Trends.” In Oxford Bulletin of Economics and Statistics 54 (1992): 257-289.
3.2Multiple time series with unit roots, cointegration, estimation and cointegrating vectors.
  • J. Hamilton. Time Series Analysis. Princeton: Princeton University Press, 1994. Chapters 18, 20.
  • R. Engle, and C. Granger. ”Cointegration and Error Correction, Representation, Estimation and Testing.” In Econometrica 55 (1987): 251-276.
  • S. Johansen. “Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models.” In Econometrica 59 (1991): 1551-1580.
3.3Testing for Cointegration.
  • J. Hamilton. Time Series Analysis. Princeton: Princeton University Press, 1994. Chapter 19.
  • P.C.B. Phillips, and S. Ouliaris. “Asymptotic Properties of Residual Based Tests for Cointegration.” In Econometrica 58 (1990): 165-193.
  • J. Stock, and M. Watson. “Testing for Common Trends.” In Journal of the American Statistical Association 83(404) (1988): 1097-1107.
  • J.Y. Campbell, and R.J. Shiller. “Cointegration and Tests of Present Value Models.” In Journal of Political Economy 95 (1987): 1062-1088.




 
 


 



 








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