1. Abraham, B. and Ledolter, J. 91983). Statistical Methods for Forecasting. New York: Wiley.

2. Akaike, H. (1973). "Information Theory and an Extension of the Maximum Likelihood Principle". Proceedings of the second International Symposium on Information Theory: 267-281. Ed. B. N. Petrov and F. Csaki. Budapest; Akademiai Kiado.

3. Akaike, H. (1974). "A New Look at the Statistical Model Identification". IEEE Transactions on Automatic Control, AC-19: 716-723.

4. Box, G.E.P. and Jenkins, G.M. (1970, 1976). Time Series Analysis: Forecasting and Control. San Francisco: Holden Day.

5. Box, G.E.P., Jenkins, G.M. and Reinsel, G.C. (1994). Time Series Analysis: Forecasting and Control. Third Edition. Prentice Hall.

6. Brown, R. G. (1962). Smoothing, Forecasting and Prediction of Discrete Time-series. Englewood Cliffs: Prentice Hall.

7. Chen, C. and Liu, L.-M. (1993). "Forecasting Time Series with Outliers". Journal of Forecasting 12: 13-35.

8. Chow, G. C. (1981). Econometric Analysis by Control Methods. New York: Wiley.

9. Fox, A.J. (1972). "Outliers in Time Series". Journal of the Royal Statistical Society, Series B 34: 350-363.

10. Granger, C.W.J. (1969). "Prediction with a Generalized Cost of Error Function". Operational Research Quarterly 20: 199-207.

11. Hillmer, S.C. (1984). "Monitoring and Adjusting Forecasts in the Presence of Additive Outliers". Journal of Forecasting 3: 205-215.

12. Liu, L.-M., Hudak, G.B., Box, G.E.P., Muller, M.E. and Tiao, G.C. (1983). The SCA Statistical System: Reference Manual for Forecasting and Time Series Analysis. Chicago: Scientific Computing Associates Corp.

13. Liu, L.-M. and Lin, M.-W. (1991). "Forecasting Residential Consumption of Natural Gas Using Monthly and Quarterly Time Series." International Journal of Forecasting 7: 3-16.

14. Liu, L.-M. and Hudak, G.B. (1992). Forecasting and Time Series Analysis Using the SCA Statistical System: Volume 1. Chicago: Scientific Computing Associates Corp.

15. Liu, L.-M. (1999). Forecasting and Time Series Analysis Using the SCA Statistical System: Volume 2. Chicago: Scientific Computing Associates Corp.

Chapter 2. Autoregressive Integrated Moving Average Models

 

 

1. Abraham, B. and Ledolter, J. (1983). Statistical Methods for Forecasting. New York: Wiley.

2. Akaike, H. (1973). "Information Theory and an Extension of the Maximum Likelihood Principle". Proceedings of the Second International Symposium on Information Theory: 267-281. Ed. B. N. Petrov and F. Csaki. Budapest; Akademiai Kiado.

3. Akaike, H. (1974). "A New Look at the Statistical Model Identification". IEEE Transactions on Automatic Control, AC-19: 716-723.

4. Ansley, C.F. and Newbold, P. (1979). "On the Finite Sample Distribution of Residual autocorrelations in Autoregressive-Moving Average Models". Biometrika 66. 547-554.

5. Bartlett, M.S. (1946). "On the Theoretical Specification and Sampling Properties of Autocorrelated Time-series". Journal of Royal Statistical Society B8: 27-41.

6. Box, G.E.P. and Cox, D.R. (1964). "An Analysis of Transformations". Journal of Royal Statistical Society B26: 211-243.

7. Box, G.E.P. and Jenkins, G.M. (1976). Time Series Analysis: Forecasting and Control. San Francisco: Holden Day.

8. Box, G.E.P., Jenkins, G.M. and Reinsel, G.C. (1994). Time Series Analysis: Forecasting and Control. Third Edition. Prentice Hall.

9. Box, G.E.P. and Pierce, D.A. (1970). "Distribution of Residual Autocorrelations in Autoregressive-Integrated Moving Average Time Series Models". Journal of American Statistical Association 65: 1509-1526.

10. Box, G.E.P., and Tiao, G.C. (1975). "Comparison of Forecasts and Actuality". Technical Report #402, Department of Statistics, University of Wisconsin-Madison.

11. Chatfield, C. (1979). "Inverse Autocorrelations". Journal of the Royal Statistical Society 142: 363-377.

12. Cleveland, W.S. (1972). "The Inverse Autocorrelations of a Time Series and Their Applications". Technometrics 14: 277-298.

13. Dickey, D., Bell, B., and Miller, R. (1986). "Unit Roots in Time Series Models: Tests and Implications". The American Statistician 40: 12-26.

14. Dickey, D. and Fuller, W.A. (1979). "Distribution of Estimates for Autoregressive Time Series with a Unit Root". Journal of the American Statistical Association 74: 427-431.

15. Dickey, D. and Fuller, W.A. (1981). "Likelihood Ratio Tests for Autoregressive Time Series with a Unit Root". Econometrics 49: 1057-1072.

16. Hillmer, S.C., and Tiao, G.C. (1979). "Likelihood Function of Stationary Multiple Autoregressive Moving Average Models". Journal of the American Statistical Association 74: 652-660.

17. Liu, L.-M. and Hudak, G.B. (1992). Forecasting and Time Series Analysis Using the SCA Statistical System: Volume 1. Chicago: Scientific Computing Associates Corp.

18. Liu, L.-M. (1999). Forecasting and Time Series Analysis Using the SCA Statistical System: Volume 2. Chicago: Scientific Computing Associates Corp.

19. Ljung, G.M., and Box, G.E.P. (1976). "Maximum Likelihood Estimation in the Autoregressive-Moving Average Model". Technical Report 476. Department of Statistics, University of Wisconsin, Madison, Wisconsin.

20. Ljung, G.M., and Box, G.E.P. (1978). "On a Measure of Lack of Fit in time Series Models." Biometrika 65: 297-304.

21. Ljung, G.M., and Box, G.E.P. (1979). "The Likelihood Function of Stationary Autoregressive-Moving Average Models". Biometrika 66: 265-270.

22. MACC (1965). GAUSHAUS -- Nonlinear Least Squares. Madison, WI: Madison Academic Computing Center, University of Wisconsin.

23. Makridakis, S. and Wheelwright, S. (1978). Interactive Forecasting: Univariate and Multivariate Methods. San Francisco: Holden-Day.

24. Marquardt, D.W. (1963). "An Algorithm for Least Squares Estimation of Non-Linear Models". J. Soc. Ind. Appl. Math. 11: 431-441.

25. Muth, J. F. (1960). "Optimal Properties of Exponentially Weighted Forecasts". Journal of the American Statistical Association 55: 290-306.

26. Phillips, P. and Perron, P. (1988). "Testing for a Unit Root in Time Series Regression". Biometrica 75: 335-346.

27. Quenouille, M.H. (1949). "Approximate Tests of Correlation in Time-series". Journal of the Royal Statistical Society B11: 68-84.

28. Schwarz, G. (1978). "Estimating the Dimension of a Model". Annals of Statistics 6: 461-464.

29. Tiao, G.C. and Ali, M.M. (1971). "Analysis of Correlated Random Effects: Linear Model with Two Random Components". Biometrika 58: 37-51.

30. Tsay, R.S. and Tiao, G.C. (1984). "Consistent Estimates of Autoregressive Parameters and Extended Sample Autocorrelation Function for Stationary and Non-stationary ARMA Models". Journal of the American Statistical Association 79: 84-96.

31. Tsay, R.S. and Tiao, G.C. (1985). "Use of Canonical Analysis in Time Series Model Identification". Biometrika 72: 299-315.

32. Yamamoto, T. (1976). "Asymptotic Mean Square Prediction Error for an Autoregressive Model with Estimated Coefficients". Applied Statistics 25:123-127.

33. Yule, G.U. (1921). "On the Time-Correlation Problem with Special Reference to the Variate Difference Correlation Method." Journal of the Royal Statistical Society 84: 497-526.

34. Yule, G.U. (1927). "On a Method of Investigating Periodicities in Disturbed Series, with Special Reference to Wölfer’s Sunspot Numbers." Philosophical Transactions of the Royal Society of London, Series A, 226: 267-298.

Chapter 3. Seasonal ARIMA Models

 

 

1. Box, G.E.P., and Jenkins, G.M. (1976). Time Series Analysis: Forecasting and Control. San Francisco: Holden Day.

2. Brown, R. G. (1962). Smoothing, Forecasting and Prediction of Discrete Time-series. Englewood Cliffs: Prentice Hall.

3. Feige, E.L. and Pearce, D.K. (1979). "The Casual Causal Relationship Between Money and Income: Some Caveats for Time Series Analysis". The Review of Economics and Statistics LXI: 521-533.

4. Hillmer, S.C., and Tiao, G.C. (1979). "Likelihood Function of Stationary Multiple Autoregressive Moving Average Models". Journal of the American Statistical Association 74: 652-660.

5. Liu, L.-M. (1989). "Identification of Seasonal ARIMA Models Using a Filtering Method". Communication in Statistics A18: 2279-2288.

6. Liu, L.-M., Bhattacharyya, S., Sclove, S., Chen, R. and Lattyak, W. (2001). "Data Mining on Time Series: An Illustration Using Fast-Food Restaurant Franchise Data." Computational Statistics and Data Analysis 37: 455-476.

7. Liu, L.-M. and Hudak, G.B. (1992). Forecasting and Time Series Analysis Using the SCA Statistical System: Volume 1. Chicago: Scientific Computing Associates Corp.

8. Tsay, R.S. and Tiao, G.C. (1984). "Consistent Estimates of Autoregressive Parameters and Extended Sample Autocorrelation Function for Stationary and Non-stationary ARMA Models". Journal of the American Statistical Association 79: 84-96.

Chapter 4. ARIMA Modeling Using Expert Systems

 

 

1. Box, G.E.P. and Jenkins, G.W. (1976). Time Series Analysis: Forecasting and Control. San Francisco: Holden Day.

2. Feige, E.L. and Pearce, D.K. (1979). "The Casual Causal Relationship Between Money and Income: Some Caveats for Time Series Analysis". The Review of Economics and Statistics LXI: 521-533.

3. Liu, L.-M. (1980). "Analysis of Time Series with Calendar Effects". Management Science 26: 106-112.

4. Liu, L.-M. (1986). "Identification of Time Series Models in the Presence of Calendar Variation". International Journal of Forecasting 2: 357-372.

5. Liu, L.-M. (1989). "Identification of Seasonal ARIMA Models Using a Filtering Method". Communication in Statistics A18: 2279-2288.

6. Liu, L.-M. and Hudak, G.B. (1992). Forecasting and Time Series Analysis Using the SCA Statistical System, Volume 1. Chicago, IL: Scientific Computing Associates Corp.

7. Liu, L.-M. (1999). Forecasting and Time Series Analysis Using the SCA Statistical System: Volume 2. Chicago: Scientific Computing Associates Corp.

8. Roberts, H.V. (1974). Conversational Statistics. Palo Alto: The Scientific Press.

Chapter 5. Transfer Function Models

 

 

1. Baker, G.A. (1975). Essential of Pad'e Approximation. New York: Academic Press.

2. Box, G.E.P. and Jenkins, G.M. (1976). Time Series Analysis: Forecasting and Control. San Francisco: Holden Day.

3. Box, G.E.P. and Tiao, G.C. (1975). "Intervention Analysis with Application to Economic and Environmental Problems". Journal of the American Statistical Association 70: 70-79.

4. Box, G.E.P., Jenkins, G.M. and Reinsel, G.C. (1994). Time Series Analysis: Forecasting and Control. Third Edition. Prentice Hall.

5. Cochrane, D. and Orcutt, G.H. (1949). "Application of Least Square Regression to Relations Containing Autocorrelated Error Terms". Journal of the American Statistical Association 44: 32-61.

6. Hillmer, S.C. (1982). "Forecasting Time Series with Trading Day Variation". Journal of Forecasting 1: 385-395.

7. Koyck, L.M. (1954). Distributed Lags and Investment Analysis. Amsterdam: North Holland.

8. Liu, L.-M. (1986). "Identification of Time Series Models in the Presence of Calendar Variation". International Journal of Forecasting 2: 357-372.

9. Liu, L.-M. (1987). "Sales Forecasting Using Multi-Equation Transfer Function Models". Journal of Forecasting 6: 223-238.

10. Liu, L.-M. (1991). "Use of Linear Transfer Function Analysis in Econometric Time Series Modeling". Statistica Sinica 1: 503-525.

11. Liu, L.-M. (1997). Forecasting and Time Series Analysis Using the SCA Statistical System: Volume 2. Chicago, IL: Scientific Computing Associates Corp.

12. Liu, L.-M. and Hanssens, D.M. (1982). "Identification of Multiple-Input Transfer Function Models". Communications in Statistics A11: 297-314.

13. Liu, L.-M. and Hudak, G.B. (1985). "Unified Econometric Model Building Using Simulations Transfer Function Equations". Time Series Analysis: Theory and Practice 7: 277-288. Amsterdam: Elsevier Science Publishing.

14. Liu, L.-M., Hudak, G.B., Box, G.E.P., Muller, M.E. and Tiao, G.C. (1983). The SCA Statistical System: Reference Manual for Forecasting and Time Series Analysis. Chicago, IL: Scientific Computing Associates Corp.

15. Liu, L.-M. and Hudak, G.B. (1992). Forecasting and Time Series Analysis Using the SCA Statistical System: Volume 1. Chicago: Scientific Computing Associates Corp.

16. Pankratz, A. (1991). Forecasting with Dynamic Regression Models. New York: Wiley.

17. Wall, K.D. (1976). "FIML Estimation of Rational Distributed Lag Structural Form Models". Annals of Economic and Social Measurement 5: 53-64.

Chapter 6. Analysis of Time Series with Calendar Effects

 

 

1. Anderson, R.L. (1954). "The Problem of Autocorrelation in Regression Analysis". Journal of the American Statistical Association 49: 113-129.

2. Armstrong J.S. and Lusk, E.J. (1983). "Commentary on the Makridakis Time Series Competition (M-Competition)“. Journal of Forecasting 2: 259-311.

3. Bell, W.R. and Hillmer, S.C. (1983). "Modeling Time Series with Calendar Variation". Journal of the American Statistical Association 78: 526-534.

4. Box, G. E. P. and Jenkins, G.M. (1976). Time Series Analysis: Forecasting and Control. San Francisco: Holden Day.

5. Cleveland, W.S. and Devlin, S.J. (1980). "Calendar Effects in Monthly Time Series: Detection by Spectrum Analysis and Graphic Methods". Journal of the American Statistical Association 75: 487-496.

6. Cleveland. W.S. and Devlin, S.J. (1982). "Calendar Effects in Monthly Time Series: Modeling and Adjustment". Journal of the American Statistical Association 77: 520-528.

7. Cleveland, W.P. and Grupe, H.R.(1981). "Modeling Time Series When Calendar Effects Are Present". Proceedings of the Conference on Applied Time Series Analysis of Economic Data. Ed. Arnold Zellner. U.S. Department of Commerce, Bureau of the Census: 57-67.

8. Fuller, W., (1976). Introduction to Statistical Time Serie. New York: John Wiley and Sons.

9. Gallant, A.R. and Goebel, J.J. (1976). "Non-Linear Regression with Autocorrelation Errors". Journal of the American Statistical Association 71: 961-967.

10. Hannan, E.J. (1971). "Non-Linear Time Series Regression". Journal of Applied Probability 8: 767-780.

11. Hillmer, S.C., Bell, W.R. and Tiao G.C. (1981). "Modeling Considerations in the Seasonal Adjustment of Economic Time Series". Proceedings of the Conference on Applied Time Series Analysis of Economic Data. Ed. Arnold Zellner. U.S. Department of Commerce, Bureau of the Census: 74-100.

12. Hillmer, S.C. (1982). "Forecasting Time Series with Trading Day Variation". Journal of Forecasting 1: 385-395.

13. Liu, L.-M. (1980). "Analysis of Time Series with Calendar Effects". Management Science 26: 106-112.

14. Liu, L.-M. (1986). "Identification of Time Series Models in the Presence of Calendar Variation". International Journal of Forecasting 2: 357-372.

15. Liu, L.-M. and Hanssens, D.M (1982). "Identification of Multiple-Input Transfer Function Models". Communications in Statistics A11: 297-314.

16. Liu, L.-M. and Hudak, G.B. (1992). Forecasting and Time Series Analysis Using the SCA Statistical System: Volume 1. Chicago: Scientific Computing Associates Corp.

17. Makridakis, Spyros, Andersen, A., Carbone, R., Fildes, R., Hibon, M., Lewandowski, R., Newton, J., Parzen, E. and Winkler, R. (1982). "The Accuracy of Extrapolation (Time Series) Methods: Results of A Forecasting Competition”. Journal of Forecasting 1: 111-153.

18. Pfefferman, D. and Fisher, J. (1980). "Festival and Working Days Prior Adjustments in Economic Time Series". Time Series. Ed. O.D. Anderson. New York: North-Holland.

19. Pierce, D.A. (1971). "Least Squares Estimation in the Regression Model with Autoregressive-Moving Average Errors". Biometrika 58: 299-312.

20. Shiskin, J., Young, A.M. and Musgrave, J.C. (1967). "The X-11 Variant of the Census Method II Seasonal Adjustment Program". Bureau of the Census Technical Paper. U.S. Department of Commerce.

21. Thompson, H.E. and Tiao, G.C. (1971). "Analysis of Telephone Data: A Case Study of Forecasting Seasonal Time Series". The Bell Journal of Economics and Management Science 2: 515-541.

22. Young, A.H. (1965). "Estimating Trading-Day Variation in Monthly Economic Time Series". Technical Paper 12. Bureau of the Census.

Chapter 7. Intervention Analysis and Outlier Detection

 

 

1. Abraham, B., and Ledolter, J. (1983). Statistical Methods for Forecasting. New York: Wiley.

2. Alwan, L.C. and Roberts, H.V. (1985). "Time Series Modeling for Statistical Process Control". Journal of Business & Economic Statistics 6: 87-95.

3. Box, G.E.P., and Tiao, G.C. (1965). "A Change in Level of a Non-Stationary Time Series". Biometrika 52: 181-192.

4. Box, G.E.P. and Jenkins, G.M. (1976). Time Series Analysis: Forecasting and Control. San Francisco: Holden Day. (Revised edition published in 1976).

5. Box, G.E.P., Jenkins, G.M. and Reinsel, G.C. (1994). Time Series Analysis: Forecasting and Control. Third Edition. Prentice Hall.

6. Box, G.E.P. and Tiao, G.C. (1975). "Intervention Analysis with Application to Economic and Environmental Problems". Journal of the American Statistical Association 70: 70-79.

7. Chang, I., Tiao, G.C. and Chen, C. (1988). "Estimation of Time Series Parameters in the Presence of Outliers". Technometrics 30: 193-204.

8. Chen, C. and Liu, L.-M. (1993a). "Joint Estimation of Model Parameters and Outlier Effects in Time Series". Journal of the American Statistical Association 88: 284-297.

9. Chen, C. and Liu, L.-M. (1993b). "Forecasting Time Series with Outliers". Journal of Forecasting 12: 13-35.

10. Fox, A.J. (1972). "Outliers in Time Series". Journal of the Royal Statistical Society, Series B 34: 350-363.

11. Hillmer, S.C. (1984). "Monitoring and Adjusting Forecasts in the Presence of Additive Outliers". Journal of Forecasting 3: 205-215.

12. Hillmer, S.C., Bell, W.R. and Tiao, G.C. (1983). "Modeling Considerations in the Seasonal Adjustment of Economic Time Series". Applied Time Series Analysis of Economic Data, Washington, D.C.: US Bureau of the Census, 74-100.

13. Ledolter, J. (1987). "The Effect of Outliers on the Estimates in and the Forecasts from ARIMA Time Series Models", American Statistical Association 1987 Proceedings of the Business and Economic Statistics Section, 453-458.

14. Ledolter, J. (1989). "The Effect of Additive Outliers on the Forecasts from ARIMA Models". International Journal of Forecasting 5: 231-240.

15. Liu, L.-M. and Tiao, G.C. (1980). "Parameter Estimation in Dynamic Models". Communication in Statistics A9: 501-517.

16. Liu, L.-M., and Chen, C. (1991). "Recent Developments of Time Series Analysis in Intervention in Environmental Impact Studies". Journal of Environmental Science and Health A 26: 1217-1252.

17. Liu, L.-M. and Hudak, G.B. (1992). Forecasting and Time Series Analysis Using the SCA Statistical System: Volume 1. Chicago: Scientific Computing Associates Corp.

18. Ljung, G.M. (1989). "A Note on the Estimation of Missing Values in Time Series". Communications in Statistics, B 17: 459-465.

19. Pankratz, A. (1991). Forecasting with Dynamic Regression Models. New York: John Wiley & Sons.

20. Tsay, R.S. (1988). "Outliers, Level Shifts, and Variance Changes in Time Series". Journal of Forecasting 7: 1-20.

21. Wei, W.W.S. (1990). Time Series Analysis: Univariate and Multivariate Methods. Redwood City, CA: Addison-Wesley.

Chapter 8. Forecasting Using Exponential Smoothing Methods

 

 

1. Abraham, B. and Ledolter, J. (1983). Statistical Methods for Forecasting. New York: Wiley.

2. Abraham, B. and Ledolter, J. (1986). "Forecast Functions Implied by Autoregressive Moving Average Models and Other Related Forecast Procedures". International Statistical Review 54: 51-66.

3. Berry, W.L. and Bliemel, F.W. (1974). "Selecting Exponential Smoothing Constants: An Application of Pattern Search". International Journal of Production Research 12: 483-499.

4. Bowerman, B.L. and O'Connell, R.T. (1993). Time Series Forecasting: Unified Concepts and Computer Implementation, 3rd edition. North Scituate, MA: Duxbury.

5. Box, G.E.P., and Jenkins, G.M. (1976). Time Series Analysis: Forecasting and Control. San Francisco: Holden Day.

6. Brown, R.G. (1962). Smoothing, Forecasting and Prediction of Discrete Time Series. Englewood Cliffs, NJ: Prentice-Hall.

7. Brown, R.G. and Meyer, R.F. (1961). "The Fundamental Theorem of Exponential Smoothing". Operations Research 9: 534-538.

8. DeLurgio, S.A. (1998). Forecasting Principles and Applications. New York: McGraw-Hill.

9. Flowers, A.D. (1980). "A Simulation Study of Smoothing Constant Limits for An Adaptive Forecasting System". Journal of Operations Management 2: 85-94.

10. Gardner, E.S. (1985). "Exponential Smoothing: The State of the Art". Journal of Forecasting 4: 1-28.

11. Harvey, A.C. (1984). "A Unitied View of Statistical Forecasting Procedures". Journal of Forecasting 3: 245-275.

12. Holt, C.C. (1957). "Forecasting Seasonal and Trends by Exponentially Weighted Moving Averages". O.N.R. Memorandum, No.52, Carnegie Institute of Technology.

13. Ledolter, J., and Abraham, B. (1984). "Some Comments on the Initialization of Exponential Smoothing". Journal of Forecasting 3: 79-84.

14. Makridakis, S. and Wheelwright, S.C. (1978). Interactive Forecasting. San Francisco: Holden Day.

15. Makridakis, S., Wheelwright, S.C. and Hyndman, R. (1998). Forecasting Methods and Applications. New York: Wiley.

16. Makridakis, S., Wheelwright, S.C., and McGee, V.E. (1986). Forecasting Methods and Applications. 2nd edition. New York: Wiley.

17. McKenzie, E. (1976). "An Analysis of General Exponential Smoothing". Operations Research 24: 131-140.

18. McKenzie, E. (1984). "General Exponential Smoothing and the Equivalent ARMA Process". Journal of Forecasting 3: 333-444.

19. Montgomery, D.C. and Johnson, L.A. (1976). Forecasting and Time Series Analysis. New York: McGraw-Hill.

20. Muth, J.F. (1960). "Optimal Properties of Exponentially Weighted Forecasts". Journal of the American Statistical Association 55: 299-306.

21. Wheelwright, S.C., and Makridakis, S. (1980). Forecasting Methods for Management. New York: Wiley.

22. Winters, P.R. (1960). "Forecasting Sales by Exponentially Weighted Moving Averages". Management Science 6: 324-342.

Chapter 9. Time Series Data Mining

 

 

1. Al-Zayer, J. and Al-Ibrahim, A.A. (1996). "Modelling the Impact of Temperature on Electricity Consumption in the Eastern Province of Saudi Arabia". Journal of Forecasting, 15, 97-106.

2. Box, G.E.P. and Jenkins, G.M. (1976). Time Series Analysis: Forecasting and Control. San Francisco: Holden Day.

3. Chaudhuri, S. and Dayal, U. (1997). "An Overview of Data Warehousing and OLAP Technology". ACM SIGMOD Record 26(1), March 1997.

4. Chen, C. and Liu, L.-M. (1993a). "Joint Estimation of Model Parameters and Outlier Effects in Time Series". Journal of the American Statistical Association 88: 284-297.

5. Chen, C. and Liu, L.-M. (1993b). "Forecasting Time Series with Outliers". Journal of Forecasting 12: 13-35.

6. Dransfield, S.B., Fisher, N.I., and Vogel, N.J. (1999). "Using Statistics and Statistical Thinking to Improve Organisational Performance". International Statistical Review 67: 99-150 (with Discussion and Response).

7. Engle, R.F., Granger, C.W.J., Rice, J. and Weiss, A. (1986). "Semiparametric Estimates of the Relation Between Weather and Electricity Sales". Journal of the American Statistical Association 81: 310-320.

8. Fayyad, U. M. (1997). "Editorial". Data Mining and Knowledge Discovery 1: 5-10.

9. Friedman, J. H. (1997). "Data Mining and Statistics: What’s the Connection?". Proceedings of the 29-th Symposium on the Interface: Computing Science and Statistics: 3-9.

10. Glymour, C., Madigan, D, Pregibon, D. and Smyth, P. (1997). "Statistical Themes and Lessons for Data Mining". Data Mining and Knowledge Discovery 1: 11-28.

11. Gupta, P.C. (1985). "Adaptive Short-term Forecasting of Hourly Loads Using Weather Information". Bunn, D.W. and Farmer, ed., Comparative Models for Electrical Load Forecasting, John Wiley & Sons: New York.

12. Hand, D.J. (1998). "Data Mining: Statistics and More?". The American Statistician 52: 112-118.

13. Hsu, Y. and Yang, C. (1995). "Electricity Load Forecasting". Applications of Neural Networks, ed. A. Murray Boston: Kluwer: 157-189.

14. Hueter, J., and Swart, W. (1998). "An Integrated Labor-Management System for Taco Bell". Interfaces 28: 75-91.

15. Liu, L-M. (1980). "Analysis of Time Series with Calendar Effect". Management Science 26: 106 112.

16. Liu, L-M. (1986). "Identification of Time Series Models in the Presence of Calendar Variation". International Journal of Forecasting 2: 357-372.

17. Liu, L.-M., Bhattacharyya, S., Sclove, S., Chen, R. and Lattyak, W. (2001). "Data Mining on Time Series: An Illustration Using Fast-Food Restaurant Franchise Data". Computational Statistics and Data Analysis 37: 455-476.

18. Liu, L.-M. and Lin, M.-W. (1991). "Forecasting Residential Consumption of Natural Gas Using Monthly and Quarterly Time Series". International Journal of Forecasting 7: 3-16.

19. Liu, L.-M. and Hudak, G.B. (1992). Forecasting and Time Series Analysis Using the SCA Statistical System: Volume 1. Chicago: Scientific Computing Associates Corp.

20. Liu, L.-M. (1999). Forecasting and Time Series Analysis Using the SCA Statistical System: Volume 2. Chicago: Scientific Computing Associates Corp.

21. Mendenhall, W. and Sincich, T. (1996). A Second Course in Statistics-Regression Analysis. Prentice Hall.

22. Thompson, H.E. and Tiao, G.C. (1971). "Analysis of Telephone Data: A Case Study of Forecasting Seasonal Time Series". The Bell Journal of Economics and Management Science 2: 515-541.

23. Weiss, S. M. and Indurkhya, N. (1998). Predictive Data Mining. San Francisco: Morgan Kaufmann Publishers.

Chapter 10. Power Transformations and Forecasting

 

 

1. Ansley, C.F., Spivey, W.A. and Wrobleski, W.J. (1977). "A class of transformations for Box-Jenkins seasonal models". Applied Statistics 26: 173-178.

2. Box, G.E.P. and Cox, D.R. (1964). "An analysis of transformations". Journal of the Royal Statistical Society B26: 211-243.

3. Box, G.E.P. and Jenkins, G.M. (1976). Time Series Analysis Forecasting and Control. Holden Day.

4. Chatfield, C. and Prothero, D.L. (1973). "Box-Jenkins Seasonal Forecasting: Problems in a Case-study". Journal of the Royal Statistical Society A136: 295-315.

5. Guerrero, V.M. (1993). "Time-series analysis supported by power transformations". Journal of Forecasting 12: 37-48.

6. Liu, L.-M. and Hudak, G.B. (1992). Forecasting and Time Series Analysis Using the SCA Statistical System, Volume 1. Chicago: Scientific Computing Associates Corp.

7. Makridakis, S. (1978). "Time Series Analysis and Forecasting: an Update and Evaluation". International Statistical Review 46: 255-278.

8. Pankratz, A. and Dudley, U. (1987). "Forecasts of power-transformed series". Journal of Forecasting 6: 239-248

Chapter 11. Time Series Models with Heteroscedasticity

 

 

1. Black, F. (1976). "Studies of Stock Price Volatility Changes". Proceeding of the 1976 Meetings of the Business and Economics Statistics Section, American Statistical Association, 177-181.

2. Bollerslev, T. (1986). "Generalized Autoregressive Conditional Heteroscedasticity". Journal of Econometrics 31: 307-327.

3. Bollerslev, T. (1987). "A Conditionally Hetroskedastic Time Series Model for Speculative Prices and Rates of Return". Review of Economics and Statistics 69: 542-546.

4. Bollerslev, T. and Ghysels, E. (1996). "Periodic Autoregressive Conditional Heteroscedasticity". Journal of Business and Economic Statistics 14: 139-151.

5. Bollerslev, T., Chou, R., and Kroner, K. (1992). "ARCH Modeling in Finance: A Review of the Theory and Empirical Evidence". Journal of Econometrics 52: 5-59.

6. Bollerslev, T., Engle, R.F., and Nelson, D.B. (1999). "ARCH Models". Handbook of Econometrics, Volume 4: 2959-3038. Amsterdam: Elsevier Science.

7. Davidian, M. and Carroll, R.J. (1987). "Variance Function Estimation". Journal of the American Statistical Association 82: 1079-1091.

8. Engle, R. (1982). "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation". Econometrica 55: 987-1007.

9. Engle, R., Lilien, D. and Robins, R. (1987). "Estimating Time Varying Risk Premia in the Term Structure: The ARCH-M Model". Econometrica 55: 391-407.

10. Engle, R. (1995). ARCH Selected Readings. Oxford: Oxford University Press.

11. Glosten, L., Jagannathan, R., and Runkle, D. (1993). "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks". Journal of Finance 48: 1779-1801.

12. Harvey, A.C., Ruiz, E., and Shephard, N. (1994). "Multivariate Stochastic Variance Models". Review of Economic Studies 61: 247-264.

13. Jacquier, E., Polson, N.G., and Rossi, P. (1994). "Bayesian Analysis of Stochastic Volatility Models" (with discussion). Journal of Business & Economic Statistics 12: 371-417.

Liu, L.-M. and Hudak, G.B. (1992). Forecasting and Time Series Analysis Using the SCA Statistical System: Volume 1. Chicago: Scientific Computing Associates Corp.

14. Longerstaey, J., and More, L. (1995). "Introduction to RiskMetrics". 4th edition. New York: Morgan Guaranty Trust Company.

15. McCullough, B.D. and Renfro, C. (1998). "Benchmarks and software standards: A case study of GARCH procedures". Journal of Economic and Social Measurement 25: 59-71.

16. McLeod, A.I., and Li, W.K. (1983). "Diagnostic Checking ARMA Time Series Models Using Squared-Residual Autocorrelations". Journal of Time Series Analysis 4: 269-273.

17. Melino, A., and Turnbull, S.M. (1990). "Pricing Foreign Currency Options with Stochastic Volatility". Journal of Econometrics 45: 239-265.

18. Nelson, D.B. (1990). "Stationarity and Persistence in the GARCH(1,1) Model". Econometric Theory 6: 318-334.

19. Nelson, D.B. (1991). "Conditional Heteroskedasticity in Asset Returns: A New Approach". Econometrics 59: 347-70.

20. Rabemananjara, R. and Zakoian, J-M. (1993). "Threshold ARCH Models and Asymmetries in Volatility". Journal of Applied Econometrics 8: 31-49.

21. Schwert, G.W. (1989). "Why Does Stock Market Volatility Change Over Time?". Journal of Finance XLIV: 1115-1153.

22. Stokes, H.H. (1997). Specifying and Diagnostically Testing Econometric Models. Second edition. New York: Quorum Books.

23. Stokes, H.H., Liu, L.-M., and Lattyak, W.J. (2002). General Autoregressive Conditional Heteroscedastic (GARCH) Modeling Using the SCAB34S NONLIN and SCA WorkBench. Chicago: Scientific Computing Associates Corp.

24. Taylor, S.J. (1986). Modeling Financial Time Series. New York: John Wiley.

25. Taylor, S.J. (1994). "Modeling Stochastic Volatility". Mathematical Finance 4: 183-204.

26. Tsay, R.S. (1987). "Conditional Heteroscedastic Time Series Models". Journal of the American Statistical Association 82: 590-604.

27. Tsay, R.S. (2002). Analysis of Financial Time Series. New York: John Wiley.

28. Weiss, A.A. (1984). "ARMA Models with ARCH Errors". Journal of Time Series Analysis 5: 129-143.

29. Zakoian, J-M. (1994). "Threshold Heteroskedastic Models". Journal of Economic Dynamics and Control 18: 931-955.

Chapter 12. Segmented Time Series Modeling and Forecasting

 

 

1. Box, G.E.P. and Jenkins, G.M. (1970, 1976). Time Series Analysis: Forecasting and Control. San Francisco: Holden Day.

2. Brock, W., Dechert, W.D., and Scheinkman, J. (1987). "A Test for Independence Based on the Correlation Dimension". Working paper, Department of Economics, University of Wisconsin, Madison.

3. Chen, R. and Tsay, R.S. (1991). "On the Ergodicity of TAR(1) Processes". Annals of Applied Probability 1: 613-634.

4. Chen, R. and Tsay, R.S. (1993). "Functional-Coefficient Autoregressive Models". Journal of the American Statistical Association 88: 298-308

5. Hinich, M.J. (1982). "Testing for Gaussianity and Linearity of a Stationary Time Series". Journal of Time Series Analysis 3: 169-176.

6. Hinich, M.J. and Patterson, D.M. (1985). "Evidence of Nonlinearity in Daily Stock Returns". Journal of Business and Economic Statistics 3: 69-77.

7. Jolliffe, I.T. and Kumar, K. (1985). "Discussion of the Paper by Lawrance and Lewis". Journal of the Royal Statistical Society B, 47: 190-191.

8. Keenan, D.M. (1985). "A Turkey Nonadditivity-Type Test for Time Series Nonlinearity". Biometrika 72: 39-44.

   Lai, T.L. and Wei, C.Z. (1983). "Asymptotic Properties of General Autoregressive Models and Strong Consistency of Least Squares Estimates of Their Parameters". Journal of Mult Anal 13: 1-23.

9. Lewis, P.A.W. and Stevens, J.G. (1991). "Nonlinear Modeling of Time Series Using Multivariate Adaptive Regression Splines (MARS)". Journal of American Statistical Association 86: 864-877.

10. Liu, L.-M. and Hudak, G.B. (1992). Forecasting and Time Series Analysis Using the SCA Statistical System: Volume 1. Chicago: Scientific Computing Associates Corp.

11. Luukkonen, R., Saikkonen, P. and Terasvirta, T. (1988). "Testing Linearity Against Smooth Transition Autoregressive Models". Biometrika 75: 491-499.

12. Maravell, A. (1983). "An Application of Nonlinear Time Series Forecasting". Journal of Business and Economic Statistics 1: 66-74.

13. Petruccelli, J. and Davies, N. (1986). "A Portmanteau Test for Self-Exciting Threshold Autoregressive-Type Nonlinearity in Time Series". Biometrika 73: 687-694.

14. Ramsey, J.B. (1969). "Tests for Specification Errors in Classical Linear Least Squares Regression Analysis". Journal of the Royal Statistical Society B31: 350-371.

15. Subba Rao, T. and Gabr, M.M. (1980). "A Test for Linearity of Stationary Time Series". Journal of Time Series Analysis 1: 145-158.

16. Tiao, G.C. and Tsay, R.S. (1994). "Some Advances in Non-linear and Adaptive Modelling in Time Series". Journal of Forecasting 13: 109-131.

17. Tong, H. (1978). "On a Threshold Model". In Pattern Recognition and Signal Processing, (ed. C.H. Chen). Sijthoff and Noordhoff, Amsterdam.

18. Tong, H. (1983). “Threshold Models in Nonlinear Time Series Analysis”. Lecture Notes in Statistics 21, Springer, Heidelberg.

19. Tong, H. and Lim, K.S. (1980). "Threshold Autoregression, Limit Cycles and Cyclical Data (with Discussion)". Journal of the Royal Statistical Society B 42: 245-292.

20. Tsay, R.S. (1986). "Nonlinearity Tests for Time Series". Biometrika 73: 461-466.

21. Tsay, R.S. (1988). "Non-linear Time Series Analysis of Blowfly Population". Journal of Time Series Analysis 9: 247-263.

22. Tsay, R.S. (1989). "Testing and Modeling Threshold Autoregressive Processes". Journal of the American Statistical Association 84: 231-240.

23. Tsay, R.S. (1991). "Detecting and Modeling Nonlinearity in Univariate Time Series Analysis". Statistica Sinica 1: 431-461.

24. Tsay, R.S. (2002). Analysis of Financial Time Series. New York: John Wiley.

25. Wang, W-Y., Du, J-G, and Xiang, J-T. (1984). "Threshold Autoregressive Moving Average Model". Computational Mathematics (in Chinese) 4: 414-419.

26. Wecker, W.E. (1981). "Asymmetric Time Series". Journal of the American Statistical Association 76: 16-21.

Chapter 13. Nonlinear Time Series Models

 

 

1. Box, G.E.P. and Jenkins, G.M. (1970, 1976). Time Series Analysis: Forecasting and Control. San Francisco: Holden Day.

2. Brock, W., Dechert, W.D., and Scheinkman, J. (1987). "A Test for Independence Based on the Correlation Dimension". Working paper, Department of Economics, University of Wisconsin, Madison.

3. Chen, R. and Tsay, R.S. (1991). "On the Ergodicity of TAR(1) Processes". Annals of Applied Probability 1: 613-634.

4. Chen, R. and Tsay, R.S. (1993). "Functional-Coefficient Autoregressive Models". Journal of the American Statistical Association 88: 298-308

5. Hinich, M.J. (1982). "Testing for Gaussianity and Linearity of a Stationary Time Series". Journal of Time Series Analysis 3: 169-176.

6. Hinich, M.J. and Patterson, D.M. (1985). "Evidence of Nonlinearity in Daily Stock Returns". Journal of Business and Economic Statistics 3: 69-77.

7. Jolliffe, I.T. and Kumar, K. (1985). "Discussion of the Paper by Lawrance and Lewis". Journal of the Royal Statistical Society B, 47: 190-191.

8. Keenan, D.M. (1985). "A Turkey Nonadditivity-Type Test for Time Series Nonlinearity". Biometrika 72: 39-44.

9. Lai, T.L. and Wei, C.Z. (1983). "Asymptotic Properties of General Autoregressive Models and Strong Consistency of Least Squares Estimates of Their Parameters." Journal of Mult Anal 13: 1-23.

10. Lewis, P.A.W. and Stevens, J.G. (1991). “Nonlinear Modeling of Time Series Using Multivariate Adaptive Regression Splines (MARS)”. Journal of American Statistical Association 86: 864-877.

11. Liu, L.-M. and Hudak, G.B. (1992). Forecasting and Time Series Analysis Using the SCA Statistical System: Volume 1. Chicago: Scientific Computing Associates Corp.

12. Luukkonen, R., Saikkonen, P. and Terasvirta, T. (1988). "Testing Linearity Against Smooth Transition Autoregressive Models". Biometrika 75: 491-499.

13. Maravell, A. (1983). "An Application of Nonlinear Time Series Forecasting". Journal of Business and Economic Statistics 1: 66-74.

14. Petruccelli, J. and Davies, N. (1986). "A Portmanteau Test for Self-Exciting Threshold Autoregressive-Type Nonlinearity in Time Series". Biometrika 73: 687-694.

15. Ramsey, J.B. (1969). "Tests for Specification Errors in Classical Linear Least Squares Regression Analysis". Journal of the Royal Statistical Society B31: 350-371.

16. Subba Rao, T. and Gabr, M.M. (1980). "A Test for Linearity of Stationary Time Series". Journal of Time Series Analysis 1: 145-158.

17. Tiao, G.C. and Tsay, R.S. (1994). "Some Advances in Non-linear and Adaptive Modelling in Time Series". Journal of Forecasting 13: 109-131.

18. Tong, H. (1978). "On a Threshold Model". In Pattern Recognition and Signal Processing, (ed. C.H. Chen). Sijthoff and Noordhoff, Amsterdam.

19. Tong, H. (1983). "Threshold Models in Nonlinear Time Series Analysis". Lecture Notes in Statistics 21, Springer, Heidelberg.

20. Tong, H. and Lim, K.S. (1980). "Threshold Autoregression, Limit Cycles and Cyclical Data (with Discussion)". Journal of the Royal Statistical Society B 42: 245-292.

21. Tsay, R.S. (1986). "Nonlinearity Tests for Time Series". Biometrika 73: 461-466.

22. Tsay, R.S. (1988). "Non-linear Time Series Analysis of Blowfly Population". Journal of Time Series Analysis 9: 247-263.

23. Tsay, R.S. (1989). "Testing and Modeling Threshold Autoregressive Processes". Journal of the American Statistical Association 84: 231-240.

24. Tsay, R.S. (1991). "Detecting and Modeling Nonlinearity in Univariate Time Series Analysis". Statistica Sinica 1: 431-461.

25. Tsay, R.S. (2002). Analysis of Financial Time Series. New York: John Wiley.

26. Wang, W-Y., Du, J-G, and Xiang, J-T. (1984). "Threshold Autoregressive Moving Average Model". Computational Mathematics (in Chinese) 4: 414-419.

27. Wecker, W.E. (1981). "Asymmetric Time Series". Journal of the American Statistical Association 76: 16-21.

Chapter 14. Multivariate Time Series Analysis and Forecasting Using Vector ARMA Models

 

 

1. Barsky, R.B. and Summers, L.H. (1988). "Gibson's Paradox and the Gold Standard". Journal of Political Economy 96: 528-550.

2. Bartlett, M.S. (1938). "Further Aspects of the Theory of Multiple Regression". Proceding Cambr. Phil. Soc. 34, 33.

3. Box, G.E.P., Erjavec, J., Hunter, W.G. and MacGregor, J.F. (1973). "Some Problems Associated with the Analysis of Multiresponse Data". Technometrics 15: 33.

4. Box, G.E.P. and Haugh, L. (1977). "Identification of Dynamic Regression Models Connecting Two Time Series". Journal Amer. Statist. Assoc. 72: 121.

5. Box, G.E.P., Hillmer, S. and Tiao, G.C. (1978). "Analysis and Modeling of Seasonal Time Series". Seasonal Analysis of Economic Time Series, Department of Commerce, Bureau of the Census ER-1, A. Zellner, Ed. 309-33.

6. Box, G.E.P. and Jenkins, G.M. (1976). Time Series Analysis Forecasting and Control. San Francisco: Holden-Day.

7. Box, G.E.P. and Tiao, G.C. (1975). "Intervention Analysis with Applications to Environmental and Economic Problems". Journal of the American Statistical Association 70: 70.

8. Box, G.E.P. and Tiao, G.C. (1977). "A Canonical Analysis of Multiple Time Series". Biometrika 64: 355.

9. Chen, C. and Lee, C.J. (1990). "A VARMA Test on the Gibson Paradox". Review of Economics and Statistics 72: 96-107.

10. Coen, P.G., Gomme, E.D. and Kendall, M.G. (1969). "Lagged Relationships in Economic Forecasting". J. Roy. Statist. Soc. A 132: 133.

11. Fisher, I. (1907). The Theory of Interest. New York: MacMillan.

12. Friedman, M and Schwartz, A. (1982). Monetary Trends in the United States and the United Kingdom. Chicago: University of Chicago Press.

13. Granger, C.W.J. (1969). "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods". Econometrica 37: 424-438.

14. Granger, C.W.J. and Newbold, P. (1986). Forecasting Economic Time Series. 2nd edition. San Diego: Academic Press.

15. Hannan, E.J. (1970). Multiple Time Series. New York: Wiley.

16. Hillmer, S.C. (1976). "Time Series Estimation, Smoothing and Seasonal Adjustment". Ph.D. Thesis. Department of Statistics, University of Wisconsin.

17. Hillmer, S.C. and Tiao, G.C. (1979). "Likelihood Function of Stationary Multiple Autoregressive Moving Average Models". Journal of the American Statistical Association 74: 652.

18. Keynes, J.M. (1930). A Treatise on Money. London: MacMillan.

19. Lee, C.J. and Petruzzi, C. (1986). "The Gibson Paradox and Monetary Standard". The Review of Economics and Statistics 68: 189-196.

20. Liu, L.-M. (1986). "Multivariate Time Series Analysis Using Vector ARMA Models". Chicago: Scientific Computing Associates Corp.

21. Liu, L.-M., Hudak, G.B. (1992). Forecasting and Time Series Analysis Using the SCA Statistical System, Volume 1. Chicago: Scientific Computing Associates Corp.

22. Liu, L.-M. (1999). Forecasting and Time Series Analysis Using the SCA Statistical System: Volume 2. Chicago: Scientific Computing Associates Corp.

23. Lutkepohl, H. (1993). Introduction to Multiple Time Series Analysis. 2nd edition. Berlin: Springer-Verlag.

24. Mills, T.C. (1990). Time Series Techniques for Economists. Cambridge: Cambridge University Press.

25. Nelson, C.R. and Schwertz, G.B. (1982). "Tests for Predictive Relationships Between Time Series Variables: A Monte Carlo Investigation". Journal of the American Statistical Association 77: 11-18.

26. Pena, D., Tiao, G.C. and Tsay, R.S. (2001). A Course in Time Series Analysis. New York: Wiley.

27. Quenouille, M.H. (1957). The Analysis of Multiple Time Series. London: Griffin.

28. Reinsel, G.C. (1997). Elements of Multivariate Time Series Analysis. 2nd edition. New York: Springer-Verlag.

29. Sargent, T.J. (1973). "Interest Rates and Prices in the Long Run". Journal of Money, Credit and Banking: 385-463.

30. Searle, S.R. (1982). Matrix Algebra Useful for Statistics. New York: Wiley.

31. Shiller, R.J. and Siegel, J.J. (1997). "The Gibson Paradox and Historical Movement in Real Interest Rates". Journal of Political Economy 85: 891-907.

32. Tiao, G.C., and Box, G.E.P. (1981). "Modeling Multiple Time Series with Applications". Journal of the American Statistical Association 76: 802-816.

33. Tiao, G.C., Box, G.E.P., Grupe, M.R., Hudak, G.B., Bell, W.R., and Chang, I. (1979). The Wisconsin Multiple Time Series Program, A Preliminary Guide. Department of Statistics, University of Wisconsin, Madison.

34. Tiao, G.C., and Wei, W.S. (1976). "Effect of Temporal Aggregation on the Dynamic Relationship of Two Time Series Variables". Biometrika 63: 513.

35. Tiao, G.C. and Tsay, R.S. (1983). "Multiple Time Series Modeling and Extended Sample Cross Correlations". Journal of Business and Economic Statistics 1: 43-56.

36. Tiao, G.C. and Tsay, R.S. (1985). "A Canonical Correlation Approach to Modeling Multivariate Time Series". American Statistical Association 1985 Proceedings of the Business and Economic Statistics Section: 112-120.

37. Tiao, G.C. and Tsay, R.S. (1989). "Model Specification in Multivariate Time Series" (with discussion). Journal of the Royal Statistical Society, Series B, 51: 157-213.

38. Tsay, R.S. (1989a). "Identifying Multivariate Time Series Models". Journal of Time Series Analysis 10: 357-372.

39. Tsay, R.S. (1989b). "Parsimonious Parameterization of Vector Autoregressive Moving Average Models". Journal of Business & Economic Statistics 7: 327-341.

40. Tsay, R.S. and Tiao, G.C. (1984). "Consistent Estimates of Autoregressive Parameters and Extended Sample Autocorrelation Function for Stationary and Non-stationary ARMA Models". Journal of the American Statistical Association 79: 84-96.

41. Wallis, K.F. (1977). "Multiple Time Series Analysis and the Final Form of Econometric Models". Econometrika 45: 1481-1497.

42. Wei, W.W.S. (2006). Time Series Analysis: Univariate and Multivariate Methods. 2nd edition. Redwood: Addison-Wesley.

43. Wicksell, K. (1907). "The Influence of the Rate of Interest on Prices". Economic Journal 17: 213-220.

44. Zellner, A. and Palm, F. (1974). "Time Series Analysis and Simultaneous Equation Econometric Models". Journal of Econometrics 2: 17-54.

Chapter 15. Multivariate Time Series Analysis and Forecasting Using Simultaneous Transfer Function Models

 

 

1. Box, G.E.P. and Jenkins, G.M. (1976). Time Series Analysis, Forecasting and Control. San Francisco: Holden-Day.

2. Brundy, J.M. and Jorgenson, D.W. (1974). "The Relative Efficiency of Instrumental Variables Estimators of Systems of Simultaneous Equations". Annals of Econometric and Social Measurement 3: 679-700.

3. Chow, G.C. and Fair, R.C. (1973). "Maximum Likelihood Estimation of Linear Equation Systems with Autoregressive Residuals". Annals of Economic and Social Measurement 2: 17-28.

4. Fair, R.C. (1970). "The Estimation of Simultaneous Equation Models with Lagged Endogenous Variables and First Order Serially Correlated Errors". Econometrica 37: 507-516.

5. Granger, C.W.J. and Newbold, P. (1977). Forecasting Economic Time Series. New York: Academic Press.

6. Greene, W.H. (2000). Econometric Analysis. Fourth Edition. Upper Saddle River: Prentice Hall.

7. Hall, B.H. and Hall, R.E. (1981). Time Series Processor, User's Manual (Version 35). Stanford, California.

8. Hannan, E.J. (1971). "The Identification Problem for Multiple Equation System with Moving Average Errors". Econometrica 39: 751-765.

9. Hanssens, D.M. and Liu, L.-M. (1983). "Lag Specification in Rational Distributed Lag Structural Models". Journal of Business and Economic Statistics 1: 316-325.

10. Hausman, J.A. (1974). "Full Information Instrumental Variables Estimation of Simultaneous Equations Systems". Annals of Economic and Social Measurement 3/4: 641-652.

11. Hendry, D.F. (1971). "Maximum Likelihood Estimation of Systems of Simultaneous Regression Equations with Errors Generated by a Vector Autoregressive Process". International Economic Review 12: 257-272.

12. Johnston, J. (1984). Econometric Methods. Third Edition. New York: MeGraw-Hill.

13. Joreskog, K.G. and Sorbom, D. (1978). "LISREL IV, Analysis of Linear Structural Relationships by the Method of Maximum Likelihood". SPSS.

14. Judge, G.G., Hill, R.C., Griffths, W., Lutkepohl, H. and Lee, T-C. (1982). Introduction to the Theory and Practice of Econometrics. New York: Wiley.

15. Klein, L.R. (1950). Economic Fluctuations in the United States, 1921-41. Cowles Commission Monograph 11. New York: Wiley.

16. Kmenta, J. (1971). Elements of Econometrics. New York: Macmillan.

17. Kohn, R. (1979). "Identification Results for ARMAX Structures". Econometrica 47: 1295-1304.

18. Liu, L.-M. (1985). "Sales Forecasting and Production Planning Using Multi-Variable Time Series Methods". Working Paper No.113. Chicago: Scientific Computing Associates.

19. Liu, L.-M. (1987). "Sales Forecasting Using Multi-Equation Transfer Function Models". Journal of Forecasting 6: 223-238.

20. Liu, L.-M. (1991). "Use of Linear Transfer Function Analysis in Econometric Time Series Modeling". Statistica Sinica 1: 503-525.

21. Liu, L.-M. (1999). Forecasting and Time Series Analysis Using the SCA Statistical System, Volume 2. Chicago: Scientific Computing Associates Corp.

22. Liu, L.-M. and Hanssens, D.M. (1982). "Identification of Multiple-Input Transfer Function Models". Communications in Statistics A11: 297-314.

23. Liu, L.-M. and Hudak, G.B. (1985). "Unified Econometric Model Building Using Simultaneous Transfer Function Equations". Time Series Analysis: Theory and Practice 7: 277-288. Ed: O.D. Anderson. Amsterdam: North-Holland.

24. Liu, L.-M. and Hudak, G.B. (1992). Forecasting and Time Series Analysis Using the SCA Statistical System, Volume 1. Chicago: Scientific Computing Associates Corp.

25. Maddala, G.S. (1977). Econometrics. New York: McGraw-Hill.

26. Palm, F. and Zellner, A. (1980). "Large Sample Estimation and Testing Procedures for Dynamic Equation Systems". Journal of Econometrics 12: 251-283.

27. Reinsel, G. (1979). "FIML Estimation of the Dynamic Simultaneous Equations Model with ARMA Disturbances". Journal of Econometrics 9: 263-281.

28. Sargan, J.D. (1961). "The Maximum Likelihood Estimation of Economic Relationships with Auto- regressive Residuals". Econometrica 19: 414-426.

29. Tiao, G.C. and Box, G.E.P. (1981). "Modeling Multiple Time Series with Application". Journal of American Statistical Association 76: 802-816.

30. Troll (1980). GREMLIN: Estimation of Equation Systems. MIT Information Processing Services.

31. Wall, K.D. (1976). FIML Estimation of Rational Distributed Lag Structural Form Models. Annals of Economic and Social Measurement 5: 53-64.

32. Zellner, A. (1962). "A Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias". Journal of the American Statistical Association 57: 348-368.

33. Zellner, A. and Palm, F. (1974). "Time Series Analysis and Simultaneous Equation Econometric Models". Journal of Econometrics 2: 17-54.

34. Zellner, A. (1979). "Statistical Analysis of Econometric Models". Journal of American Statistical Association 74: 628-651.

Chapter 16. Causality Testing

 

 

1. Barsky, R.B. and Summers, L.H. (1988). “Gibson’s Paradox and the Gold Standard”. Journal of Political Economy 96: 528-550.

2. Box, G.E.P. and Jenkins, G.M. (1976). Time Series Analysis Forecasting and Control. San Francisco: Holden-Day.

3. Chen, C. and Lee, C.J. (1990). “A VARMA Test on the Gibson Paradox”. Review of Economics and Statistics 72: 96-107.

4. Feige, E.L. and Pearce, D.K. (1976). “Economically Rational Expectations: Are Innovations in the Rate of Inflation Independent of Innovations in Measures of Monetary and Fiscal Policy?” Journal of Political Economy 84: 499-522.

5. Fisher, I. (1907). The Theory of Interest. New York: MacMillan.

6. Granger, C.W.J. (1969). “Investigating Causal Relations by Econometric Models and Cross-Spectral Methods”. Econometrica 37: 424-438.

7. Granger, C.W.J. and Newbold, P. (1974). “Spurious Regressions in Econometrics”. Journal of Econometrics 1: 111-120.

8. Haugh, L.D. (1976). “Checking the Independence of Two Covariance-stationary Time Series: A Univariate Residual Cross-correlation Approach”. Journal of the American Statistical Association 71: 378-385.

9. Hillmer, S.C. and Tiao, G.C. (1979). “Likelihood Function of Stationary Multiple Autoregressive Moving Average Models”. Journal of the American Statistical Association 74: 652.

10. Hsiao, C. (1979). “Autoregressive Modeling of Canadian Money and Income Data”. Journal of the American Statistical Association 74: 553-560.

11. Kang, H. (1981). “Necessary and Sufficient Conditions for Causality Testing in Multivariate ARMA Models”. Journal of Time Series Analysis 2: 95-101.

12. Keynes, J.M. (1930). A Treatise on Money. London: MacMillan.

13. Koreisha, S.G. (1983). “Causal Implications: The Linkage between Time Series and Econometric Modeling”. Journal of Forecasting 2: 151-168.

14. Leamer, E.E. (1983). “Let’s Take the Con Out of Econometrics”. American Economic Review 73: 31-43.

15. Leamer, E.E. (1985). “Sensitivity Analyses Would Help”. American Economic Review 75: 308-313.

16. Lee, C.J. and Petruzzi, C. (1986). “The Gibson Paradox and Monetary Standard”. The Review of Economics and Statistics 68: 189-196.

17. Liu, L.-M. (1999). Forecasting and Time Series Analysis Using the SCA Statistical System: Volume 2. Chicago: Scientific Computing Associates Corp.

18. Lutkepohl, H. (1993). Introduction to Multiple Time Series Analysis. 2nd edition. Berlin: Springer-Verlag.

19. Nelson, C.R. and Schwertz, G.B. (1982). “Tests for Predictive Relationships Between Time Series Variables: A Monte Carlo Investigation”. Journal of the American Statistical Association 77: 11-18.

20. Pierce, D.A. and Haugh, L.D. (1977). “Causality in Temporal Systems: Characterizations and Survey”. Journal of Econometrics 5: 265-293.

21. Sargent, T.J. (1973). “Interest Rates and Prices in the Long Run”. Journal of Money, Credit and Banking: 385-463.

22. Shiller, R.J. and Siegel, J.J. (1997). “The Gibson Paradox and Historical Movement in Real Interest Rates”. Journal of Political Economy 85: 891-907.

23. Sims, C.A. (1972). “Money, Income and Causality”. American Economic Review 62: 540-552.

24. Sims, C.A. (1980). “Macro-Economics and Reality”. Econometrica 48: 1-48.

25. Tiao, G.C., and Box, G.E.P. (1981). “Modeling Multiple Time Series with Applications”. Journal of the American Statistical Association 76: 802-816.

26. Wicksell, K. (1907). “The Influence of the Rate of Interest on Prices”. Economic Journal 17: 213-220.

27. Zellner, A. and Palm, F. (1974). “Time Series Analysis and Simultaneous Equation Econometric Models”. Journal of Econometrics 2: 17-54.