Main Content

Bibliography

[1] Ait-Sahalia, Y. “Testing Continuous-Time Models of the Spot Interest Rate.” The Review of Financial Studies. Spring 1996, Vol. 9, No. 2, pp. 385–426.

[2] Ait-Sahalia, Y. "Transition Densities for Interest Rate and Other Nonlinear Diffusions." The Journal of Finance. Vol. 54, No. 4, August 1999.

[3] Akaike, Hirotugu. "Information Theory and an Extension of the Maximum Likelihood Principle.” In Selected Papers of Hirotugu Akaike, edited by Emanuel Parzen, Kunio Tanabe, and Genshiro Kitagawa, 199–213. New York: Springer, 1998. https://doi.org/10.1007/978-1-4612-1694-0_15.

[4] Akaike, Hirotugu. “A New Look at the Statistical Model Identification.” IEEE Transactions on Automatic Control 19, no. 6 (December 1974): 716–23. https://doi.org/10.1109/TAC.1974.1100705.

[5] Almon, S. "The Distributed Lag Between Capital Appropriations and Expenditures." Econometrica. Vol. 33, 1965, pp. 178–196.

[6] Amano, R. A., and S. van Norden. "Unit Root Tests and the Burden of Proof." Bank of Canada. Working paper 92–7, 1992.

[7] Andrews, D. W. K. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation." Econometrica. Vol. 59, 1991, pp. 817–858.

[8] Andrews, D. W. K., and J. C. Monohan. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator." Econometrica. Vol. 60, 1992, pp. 953–966.

[9] Baillie, R. T., and T. Bollerslev. “Prediction in Dynamic Models with Time-Dependent Conditional Variances.” Journal of Econometrics. Vol. 52, 1992, pp. 91–113.

[10] Banerjee, A. N., and J. R. Magnus. "On the Sensitivity of the Usual t- and F-Tests to Covariance Misspecification." Journal of Econometrics. Vol. 95, 2000, pp. 157–176.

[11] Barone-Adesi, G., K. Giannopoulos, and L. Vosper. "VaR without Correlations for Non-Linear Portfolios." Journal of Futures Markets. Vol. 19, 1999, pp. 583–602.

[12] Baxter, Marianne, and Robert G. King. "Measuring Business Cycles: Approximate Band-Pass Filters for Economic Time Series." Review of Economics and Statistics 81, no. 4 (November 1999): 575–93. https://doi.org/10.1162/003465399558454.

[13] Belsley, D. A., E. Kuh, and R. E. Welsh. Regression Diagnostics. New York, NY: John Wiley & Sons, Inc., 1980.

[14] Bera, A. K., and H. L. Higgins. “A Survey of ARCH Models: Properties, Estimation and Testing.” Journal of Economic Surveys. Vol. 7, No. 4, 1993.

[15] Beveridge, Stephen, and Charles R. Nelson. "A New Approach to Decomposition of Economic Time Series into Permanent and Transitory Components with Particular Attention to Measurement of the 'Business Cycle.'" Journal of Monetary Economics 7 (January 1981): 151–74. https://doi.org/10.1016/0304-3932(81)90040-4.

[16] Bohrnstedt, G. W., and T. M. Carter. "Robustness in Regression Analysis." In Sociological Methodology, H. L. Costner, editor, pp. 118–146. San Francisco: Jossey-Bass, 1971.

[17] Bollerslev, T. “A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return.” Review of Economics and Statistics. Vol. 69, 1987, pp. 542–547.

[18] Bollerslev, T. “Generalized Autoregressive Conditional Heteroskedasticity.” Journal of Econometrics. Vol. 31, 1986, pp. 307–327.

[19] Bollerslev, T., R. Y. Chou, and K. F. Kroner. “ARCH Modeling in Finance: A Review of the Theory and Empirical Evidence.” Journal of Econometrics. Vol. 52, 1992, pp. 5–59.

[20] Bollerslev, T., R. F. Engle, and D. B. Nelson. “ARCH Models.” Handbook of Econometrics. Vol. 4, Chapter 49, Amsterdam: Elsevier Science B.V., 1994, pp. 2959–3038.

[21] Bollerslev, T., and E. Ghysels. “Periodic Autoregressive Conditional Heteroscedasticity.” Journal of Business and Economic Statistics. Vol. 14, 1996, pp. 139–151.

[22] Bouye, E., V. Durrleman, A. Nikeghbali, G. Riboulet, and Roncalli, T. "Copulas for Finance: A Reading Guide and Some Applications." Groupe de Rech. Oper., Credit Lyonnais, Paris, 2000.

[23] Box, G. E. P., and D. R. Cox. "An Analysis of Transformations". Journal of the Royal Statistical Society. Series B, Vol. 26, 1964, pp. 211–252.

[24] Box, G. E. P. and D. Pierce. "Distribution of Residual Autocorrelations in Autoregressive-Integrated Moving Average Time Series Models." Journal of the American Statistical Association. Vol. 65, 1970, pp. 1509–1526.

[25] Box, George E. P., Gwilym M. Jenkins, and Gregory C. Reinsel. Time Series Analysis: Forecasting and Control. 3rd ed. Englewood Cliffs, NJ: Prentice Hall, 1994.

[26] Brandolini, D., M. Pallotta, and R. Zenti. "Risk Management in an Asset Management Company: A Practical Case." Presented at EMFA 2001, Lugano, Switzerland. 2000.

[27] Breusch, T.S., and L. G. Godfrey. "A Review of Recent Work on Testing for Autocorrelation in Dynamic Simultaneous Models." In Currie, D., R. Nobay, and D. Peel (Eds.), Macroeconomic Analysis: Essays in Macroeconomics and Econometrics. London: Croom Helm, 1981.

[28] Breusch, T.S., and Pagan, A.R. "Simple test for heteroscedasticity and random coefficient variation". Econometrica. v. 47, 1979, pp. 1287–1294.

[29] Brieman, L., J. H. Friedman, R. A. Olshen, and C. J. Stone. Classification and Regression Trees. Boca Raton, FL: Chapman & Hall/CRC, 1984.

[30] Brockwell, P. J. and R. A. Davis. Introduction to Time Series and Forecasting. 2nd ed. New York, NY: Springer, 2002.

[31] Brooks, C., S. P. Burke, and G. Persand. “Benchmarks and the Accuracy of GARCH Model Estimation.” International Journal of Forecasting. Vol. 17, 2001, pp. 45–56.

[32] Brown, Bryan W., and Roberto S. Mariano. "Predictors in Dynamic Nonlinear Models: Large-Sample Behavior." Econometric Theory, 5 (December 1989): 430–52. https://doi.org/10.1017/S0266466600012603.

[33] Brown, M. B. and Forsythe, A. B. "Robust Tests for Equality of Variances." Journal of the American Statistical Association. 69, 1974, pp. 364–367.

[34] Burke, S. P. "Confirmatory Data Analysis: The Joint Application of Stationarity and Unit Root Tests." University of Reading, UK. Discussion paper 20, 1994.

[35] Burnham, Kenneth P., and David R. Anderson. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach. 2nd ed, New York: Springer, 2002.

[36] Burns, Arthur F., and Wesley C. Mitchell. Measuring Business Cycles. Cambridge, MA: National Bureau of Economic Research, 1946.

[37] Campbell, J. Y., A. W. Lo, and A. C. MacKinlay. Chapter 12. “The Econometrics of Financial Markets.” Nonlinearities in Financial Data. Princeton, NJ: Princeton University Press, 1997.

[38] Caner, M., and L. Kilian. “Size Distortions of Tests of the Null Hypothesis of Stationarity: Evidence and Implications for the PPP Debate.” Journal of International Money and Finance. Vol. 20, 2001, pp. 639–657.

[39] Cecchetti, S. G., and P. S. Lam. “Variance-Ratio Tests: Small-Sample Properties with an Application to International Output Data.” Journal of Business and Economic Statistics. Vol. 12, 1994, pp. 177–186.

[40] Chambers, M. J. "Jackknife Estimation of Stationary Autoregressive Models." University of Essex Discussion Paper No. 684, 2011.

[41] Chauvet, M., and J. D. Hamilton. "Dating Business Cycle Turning Points." In Nonlinear Analysis of Business Cycles (Contributions to Economic Analysis, Volume 276). (C. Milas, P. Rothman, and D. van Dijk, eds.). Amsterdam: Emerald Group Publishing Limited, 2006.

[42] Chow, G. C. "Tests of Equality Between Sets of Coefficients in Two Linear Regressions." Econometrica. Vol. 28, 1960, pp. 591–605.

[43] Christiano, Lawrence J., and Terry J. Fitzgerald. "The Band Pass Filter." International Economic Review 44 (May 2003): 435–65. https://doi.org/10.1111/1468-2354.t01-1-00076.

[44] Christoffersen, P.F. Elements of Financial Risk Management. Waltham, MA: Academic Press, 2002.

[45] Clarke, K. A. "The Phantom Menace: Omitted Variable Bias in Econometric Research." Conflict Management and Peace Science. Vol. 22, 2005, pp. 341–352.

[46] Clark, Peter K. "The Cyclical Component of U. S. Economic Activity." The Quarterly Journal of Economics 102, no. 4 (November 1987): 797–814. https://doi.org/10.2307/1884282.

[47] Clements, Michael P., and Jeremy Smith. "The Performance of Alternative Forecasting Methods for SETAR Models." International Journal of Forecasting, 13 (December 1997): 463–75. https://doi.org/10.1016/S0169-2070(97)00017-4.

[48] Cochrane, J. "How Big is the Random Walk in GNP?" Journal of Political Economy. Vol. 96, 1988, pp. 893–920.

[49] Cogley, Timothy, and James M. Nason. "Effects of the Hodrick-Prescott Filter on Trend and Difference Stationary Time Series Implications for Business Cycle Research." Journal of Economic Dynamics and Control 19, no. 1 (January1995): 253–78. https://doi.org/10.1016/0165-1889(93)00781-X.

[50] Congressional Budget Office, Budget and Economic Data, 10-Year Economic Projections, https://www.cbo.gov/data/budget-economic-data.

[51] Cribari-Neto, F. "Asymptotic Inference Under Heteroskedasticity of Unknown Form." Computational Statistics & Data Analysis. Vol. 45, 2004, pp. 215-233.

[52] Cramér, H. Mathematical Methods of Statistics. Princeton, NJ: Princeton University Press, 1946.

[53] Dagum, E. B. The X-11-ARIMA Seasonal Adjustment Method. Number 12–564E. Statistics Canada, Ottawa, 1980.

[54] Davidson, R., and J. G. MacKinnon. Econometric Theory and Methods. Oxford, UK: Oxford University Press, 2004.

[55] Davidson, R., and E. Flachaire. "The Wild Bootstrap, Tamed at Last." Journal of Econometrics. Vol. 146, 2008, pp. 162–169.

[56] de Jong, Robert M., and Neslihan Sakarya. "The Econometrics of the Hodrick-Prescott Filter." Review of Economics and Statistics 98, no. 2 (May 2016): 310–17. https://doi.org/10.1162/REST_a_00523.

[57] Del Negro, M., Schorfheide, F., Smets, F. and Wouters, R. "On the Fit of New Keynesian Models." Journal of Business & Economic Statistics. Vol. 25, No. 2, 2007, pp. 123–162.

[58] Diebold, F. X. Elements of Forecasting. Mason, OH: Thomson Higher Education, 2007.

[59] Diebold, F.X., and C. Li. "Forecasting the Term Structure of Government Bond Yields." Journal of Econometrics. Vol. 130, No. 2, 2006, pp. 337–364.

[60] Diebold, F. X., G. D. Rudebusch, and B. Aruoba (2006), "The Macroeconomy and the Yield Curve: A Dynamic Latent Factor Approach." Journal of Econometrics. Vol. 131, 2006, pp. 309–338.

[61] Diebold, F.X., and G.D. Rudebusch. Business Cycles: Durations, Dynamics, and Forecasting. Princeton, NJ: Princeton University Press, 1999.

[62] den Haan, W. J., and A. Levin. "A Practitioner's Guide to Robust Covariance Matrix Estimation." In Handbook of Statistics. Edited by G. S. Maddala and C. R. Rao. Amsterdam: Elsevier, 1997.

[63] Dickey, D. A., and W. A. Fuller. “Distribution of the Estimators for Autoregressive Time Series with a Unit Root.” Journal of the American Statistical Association. Vol. 74, 1979, pp. 427–431.

[64] Dickey, D. A., and W. A. Fuller. “Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root.” Econometrica. Vol. 49, 1981, pp. 1057–1072.

[65] Dowd, K. Measuring Market Risk. West Sussex: John Wiley & Sons, 2005.

[66] Durbin J., and S. J. Koopman. “A Simple and Efficient Simulation Smoother for State Space Time Series Analysis.” Biometrika. Vol 89., No. 3, 2002, pp. 603–615.

[67] Durbin J., and S. J. Koopman. Time Series Analysis by State Space Methods. 2nd ed. Oxford: Oxford University Press, 2012.

[68] Durbin, J. and G.S. Watson. "Testing for Serial Correlation in Least Squares Regression." Biometrika. Vol. 37, 1950, pp. 409–428.

[69] Elder, J., and P. E. Kennedy. “Testing for Unit Roots: What Should Students Be Taught?” Journal of Economic Education. Vol. 32, 2001, pp. 137–146.

[70] Embrechts, P., A. McNeil, and D. Straumann. "Correlation and Dependence in Risk Management: Properties and Pitfalls". Risk Management: Value At Risk and Beyond. Cambridge: Cambridge University Press, 1999, pp. 176–223.

[71] Enders, Walter. Applied Econometric Time Series. Hoboken, NJ: John Wiley & Sons, Inc., 1995.

[72] Engle, Robert. F. “Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation.” Econometrica 50 (July 1982): 987–1007. https://doi.org/10.2307/1912773.

[73] Engle, R. F. and C. W. J. Granger. “Co-Integration and Error-Correction: Representation, Estimation, and Testing.” Econometrica. v. 55, 1987, pp. 251–276.

[74] Engle, R. F., D. M. Lilien, and R. P. Robins. “Estimating Time Varying Risk Premia in the Term Structure: The ARCH-M Model.” Econometrica. Vol. 59, 1987, pp. 391–407.

[75] Faust, J. “When Are Variance Ratio Tests for Serial Dependence Optimal?” Econometrica. Vol. 60, 1992, pp. 1215–1226.

[76] Fernández-Villaverde, Jesús, Rubio-Ramírez, Juan F., and Schorfheide, Frank. "Solution and Estimation Methods for DSGE Models." Handbook of Macroeconomics 2 (November 2016) 527–724. https://doi.org/10.1016/bs.hesmac.2016.03.006.

[77] Findley, D. F., B. C. Monsell, W. R. Bell, M. C. Otto, and B.-C. Chen. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program." Journal of Business & Economic Statistics. Vol. 16, Number 2, 1998, pp. 127–152.

[78] Fisher, F. M. "Tests of Equality Between Sets of Coefficients in Two Linear Regressions: An Expository Note." Econometrica. Vol. 38, 1970, pp. 361–66.

[79] Fisher, R. A.. "Frequency Distribution of the Values of the Correlation Coefficient in Samples from an Indefinitely Large Population." Biometrika. Vol. 10, 1915, pp. 507–521.

[80] Fisher, R. A. "On the "Probable Error" of a Coefficient of Correlation Deduced from a Small Sample." Metron. Vol. 1, 1921, pp. 3–32.

[81] Fisher, R. A. "The Distribution of the Partial Correlation Coefficient." Metron. Vol. 3, 1924, pp. 329–332.

[82] Gallager, R.G. Stochastic Processes: Theory for Applications. Cambridge, UK: Cambridge University Press, 2013.

[83] Gallant, A. R. Nonlinear Statistical Models. Hoboken, NJ: John Wiley & Sons, Inc., 1987.

[84] Gilks, W. R., S. Richardson, and D.J. Spiegelhalter. Markov Chain Monte Carlo in Practice. Boca Raton: Chapman & Hall/CRC, 1996.

[85] Glasserman, P. Monte Carlo Methods in Financial Engineering. New York: Springer-Verlag, 2004.

[86] Glosten, L. R., R. Jagannathan, and D. E. Runkle. “On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks.” The Journal of Finance. Vol. 48, No. 5, 1993, pp. 1779–1801.

[87] Godfrey, L. G. Misspecification Tests in Econometrics. Cambridge, UK: Cambridge University Press, 1997.

[88] Gourieroux, C. ARCH Models and Financial Applications. New York: Springer-Verlag, 1997.

[89] Goutte, C. "Note on Free Lunches and Cross-Validation." Neural Computation. Vol. 9, 1997, pp. 1211–1215.

[90] Granger, Clive W. J. "The Typical Spectral Shape of an Economic Variable." Econometrica 34, no. 1 (January 1966): 150–61. https://doi.org/10.2307/1909859.

[91] Granger, C., and P. Newbold. "Forecasting Transformed Series." Journal of the Royal Statistical Society. Series B, Vol. 38, 1976, pp. 189–203.

[92] Granger, C. W. J., and P. Newbold. "Spurious Regressions in Econometrics." Journal of Econometrics. Vol. 2, 1974, pp. 111–120.

[93] Greene, William. H. Econometric Analysis. 6th ed. Upper Saddle River, NJ: Prentice Hall, 2008.

[94] Goldberger, A. T. A Course in Econometrics. Cambridge, MA: Harvard University Press, 1991.

[95] Goldfeld, S. M., and Quandt, R. E. "Some Tests for Homoscedasticity". Journal of the American Statistical Association. v. 60, 1965, pp. 539–547.

[96] Hagerud, G. E. “Modeling Nordic Stock Returns with Asymmetric GARCH.” Working Paper Series in Economics and Finance. No. 164, Stockholm: Department of Finance, Stockholm School of Economics, 1997.

[97] Hagerud, G. E. “Specification Tests for Asymmetric GARCH.” Working Paper Series in Economics and Finance. No. 163, Stockholm: Department of Finance, Stockholm School of Economics, 1997.

[98] Haggstrom, O. Finite Markov Chains and Algorithmic Applications. Cambridge, UK: Cambridge University Press, 2002.

[99] Hamilton, J. D. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle." Econometrica. Vol. 57, 1989, pp. 357–384.

[100] Hamilton, J. D. "Analysis of Time Series Subject to Changes in Regime." Journal of Econometrics. Vol. 45, 1990, pp. 39–70.

[101] Hamilton, J. D. "Macroeconomic Regimes and Regime Shifts." In Handbook of Macroeconomics. (H. Uhlig and J. Taylor, eds.). Amsterdam: Elsevier, 2016.

[102] Hamilton, James D. Time Series Analysis. Princeton, NJ: Princeton University Press, 1994.

[103] Hamilton, James D. "Why You Should Never Use the Hodrick-Prescott Filter." The Review of Economics and Statistics 100 (December 2018): 831–43. https://doi.org/10.1162/rest_a_00706.

[104] Hannan, Edward J., and Barry G. Quinn. “The Determination of the Order of an Autoregression.” Journal of the Royal Statistical Society: Series B (Methodological) 41, no. 2 (January 1979): 190–95. https://doi.org/10.1111/j.2517-6161.1979.tb01072.x.

[105] Hart, J. D. "Kernel Regression Estimation With Time Series Errors." Journal of the Royal Statistical Society. Series B, Vol. 53, 1991, pp. 173–187.

[106] Hastie, T., R. Tibshirani, and J. Friedman. The Elements of Statistical Learning. New York: Springer, 2008.

[107] Haug, A. “Testing Linear Restrictions on Cointegrating Vectors: Sizes and Powers of Wald Tests in Finite Samples.” Econometric Theory. Vol. 18, 2002, pp. 505–524.

[108] Helwege, J., and P. Kleiman. "Understanding Aggregate Default Rates of High Yield Bonds." Federal Reserve Bank of New York Current Issues in Economics and Finance. Vol. 2, No. 6, 1996, pp. 1–6.

[109] Hendry, D. F. Econometrics: Alchemy or Science? Oxford: Oxford University Press, 2001.

[110] Hentschel, L. "All in the Family: Nesting Symmetric and Asymmetric GARCH Models." Journal of Financial Economics. Vol. 39, 1995, pp. 71–104.

[111] Hibbs, D. "Problems of Statistical Estimation and Causal Inference in Dynamic Time Series Models." In Costner, H. (Ed.) Sociological Methodology. San Francisco: Jossey-Bass, 1974.

[112] Hoerl, A. E., and R. W. Kennard. "Ridge Regression: Applications to Nonorthogonal Problems." Technometrics. Vol. 12, No. 1, 1970, pp. 69–82.

[113] Hull, J. C. Options, Futures, and Other Derivatives. 5th ed. Englewood Cliffs, NJ: Prentice Hall, 2002.

[114] Hodrick, Robert J. "An Exploration of Trend-Cycle Decomposition Methodologies in Simulated Data." National Bureau of Economic Research Working Paper No. w26750. Social Science Research Network (February 2020). https://papers.ssrn.com/abstract=3539317.

[115] Hodrick, Robert J., and Edward C. Prescott. "Postwar U.S. Business Cycles: An Empirical Investigation." Journal of Money, Credit and Banking 29, no. 1 (February 1997): 1–16. https://doi.org/10.2307/2953682.

[116] Horn, R., and C. R. Johnson. Matrix Analysis. Cambridge, UK: Cambridge University Press, 1985.

[117] Hyndman, Rob J. "Highest-Density Forecast Regions for Nonlinear and Non-Normal Time Series Models." Journal of Forecasting, 14 (September 1995): 431–41. https://doi.org/10.1002/for.3980140503.

[118] Inder, B. A. "Finite Sample Power of Tests for Autocorrelation in Models Containing Lagged Dependent Variables." Economics Letters. Vol. 14, 1984, pp.179–185.

[119] Jarrow, A. Finance Theory. Englewood Cliffs, NJ: Prentice-Hall, 1988.

[120] Jarvis, J. P., and D. R. Shier. "Graph-Theoretic Analysis of Finite Markov Chains." In Applied Mathematical Modeling: A Multidisciplinary Approach. Boca Raton: CRC Press, 2000.

[121] Johansen, S. Likelihood-Based Inference in Cointegrated Vector Autoregressive Models. Oxford: Oxford University Press, 1995.

[122] Johnson, N. L., S. Kotz, and N. Balakrishnan. Continuous Univariate Distributions. Vol. 2, 2nd ed. New York: John Wiley & Sons, 1995.

[123] Johnston, J. Econometric Methods. New York: McGraw-Hill, 1972.

[124] Jonsson, J. G., and M. Fridson. "Forecasting Default Rates on High Yield Bonds." Journal of Fixed Income. Vol. 6, No. 1, 1996, pp. 69–77.

[125] Judge, G. G., W. E. Griffiths, R. C. Hill, H. Lϋtkepohl, and T. C. Lee. The Theory and Practice of Econometrics. New York, NY: John Wiley & Sons, Inc., 1985.

[126] Juselius, K. The Cointegrated VAR Model. Oxford: Oxford University Press, 2006.

[127] Kennedy, P. A Guide to Econometrics. 6th ed. New York: John Wiley & Sons, 2008.

[128] Keuzenkamp, H. A., and M. McAleer. "Simplicity, Scientific Inference and Economic Modeling." Economic Journal. Vol. 105, 1995, pp. 1–21.

[129] Kiefer, N. M., T. J. Vogelsang, and H. Bunzel. "Simple Robust Testing of Regression Hypotheses." Econometrica. Vol. 68, 2000, pp. 695–714.

[130] Kim, C.-J. "Dynamic Linear Models with Markov Switching." Journal of Econometrics. Vol. 60, 1994, pp. 1–22.

[131] Kimball, M. "The Quantitative Analytics of the Basic Neomonetarist Model." Journal of Money, Credit, and Banking, Part 2: Liquidity, Monetary Policy, and Financial Intermediation. Vol. 27, No. 4, 1995, pp. 1241–1277.

[132] King, M. L. "Robust Tests for Spherical Symmetry and Their Application to Least Squares Regression." Annals of Statistics. Vol. 8, 1980, pp. 1265–1271.

[133] Kole, E. "Regime Switching Models: An Example for a Stock Market Index." Rotterdam, NL: Econometric Institute, Erasmus School of Economics, 2010.

[134] Koyck, L. M. Distributed Lags Models and Investment Analysis. Amsterdam: North-Holland, 1954.

[135] Krolzig, H.-M. Markov-Switching Vector Autoregressions. Berlin: Springer, 1997.

[136] Krolzig, H. -M., and Hendry, D.F. "Computer Automation of General-To-Specific Model Selection Procedures." Journal of Economic Dynamics & Control. Vol. 25, 2001, pp. 831–866.

[137] Kutner, M. H., C. J. Nachtsheim, J. Neter, and W. Li. Applied Linear Statistical Models. 5th Ed. New York: McGraw-Hill/Irwin, 2005.

[138] Kwiatkowski, D., P. C. B. Phillips, P. Schmidt and Y. Shin. “Testing the Null Hypothesis of Stationarity against the Alternative of a Unit Root.” Journal of Econometrics. Vol. 54, 1992, pp. 159–178.

[139] Leybourne, S. J. and B. P. M. McCabe. “A Consistent Test for a Unit Root.” Journal of Business and Economic Statistics. Vol. 12, 1994, pp. 157–166.

[140] Leybourne, S. J. and B. P. M. McCabe. “Modified Stationarity Tests with Data-Dependent Model-Selection Rules.” Journal of Business and Economic Statistics. Vol. 17, 1999, pp. 264–270.

[141] Lin, Jin-Lung, and Clive W. J. Granger. "Forecasting from Non-Linear Models in Practice." Journal of Forecasting, 3 (January 1994): 1–9. https://doi.org/10.1002/for.3980130102.

[142] Litterman, Robert B. "Forecasting with Bayesian Vector Autoregressions: Five Years of Experience." Journal of Business and Economic Statistics 4, no. 1 (January 1986): 25–38. https://doi.org/10.2307/1391384.

[143] Ljung, G. and G. E. P. Box. "On a Measure of Lack of Fit in Time Series Models." Biometrika. Vol. 66, 1978, pp. 67–72.

[144] Lo, A. W., and A. C. MacKinlay. “Stock Market Prices Do Not Follow Random Walks: Evidence from a Simple Specification Test.” Review of Financial Studies. Vol. 1, 1988, pp. 41–66.

[145] Lo, A. W., and A. C. MacKinlay. “The Size and Power of the Variance Ratio Test.” Journal of Econometrics. Vol. 40, 1989, pp. 203–238.

[146] Lo, A. W., and A. C. MacKinlay. A Non-Random Walk Down Wall St. Princeton, NJ: Princeton University Press, 2001.

[147] Loeffler, G., and P. N. Posch. Credit Risk Modeling Using Excel and VBA. West Sussex, England: Wiley Finance, 2007.

[148] Long, J. S., and L. H. Ervin. "Using Heteroscedasticity-Consistent Standard Errors in the Linear Regression Model." The American Statistician. v. 54, 2000, pp. 217-224.

[149] Longstaff, F. A., and E. S. Schwartz. “Valuing American Options by Simulation: A Simple Least-Squares Approach.” The Review of Financial Studies. Spring 2001, Vol. 14, No. 1, pp. 113–147.

[150] Lütkepohl, H. New Introduction to Multiple Time Series Analysis. Berlin: Springer, 2005.

[151] Lütkepohl, Helmut, and Markus Krätzig, editors. Applied Time Series Econometrics. 1st ed. Cambridge University Press, 2004. https://doi.org/10.1017/CBO9780511606885.

[152] MacKinnon, J. G. "Numerical Distribution Functions for Unit Root and Cointegration Tests." Journal of Applied Econometrics. Vol. 11, 1996, pp. 601–618.

[153] MacKinnon, J. G., and H. White. "Some Heteroskedasticity-Consistent Covariance Matrix Estimators with Improved Finite Sample Properties." Journal of Econometrics. Vol. 29, 1985, pp. 305–325.

[154] Maddala, G. S., and I. M. Kim. Unit Roots, Cointegration, and Structural Change. Cambridge, UK: Cambridge University Press, 1998.

[155] Maeshiro, A. "Teaching Regressions with a Lagged Dependent Variable and Autocorrelated Disturbances." Journal of Economic Education. Vol. 27, 1996, pp. 72–84.

[156] Maeshiro, A. "An Illustration of the Bias of OLS for Yt = λYt–1+Ut." Journal of Economic Education. Vol. 31, 2000, pp. 76–80.

[157] Malinvaud, E. Statistical Methods of Econometrics. Amsterdam: North-Holland, 1970.

[158] Marriott, F. and J. Pope. "Bias in the Estimation of Autocorrelations." Biometrika. Vol. 41, 1954, pp. 390–402.

[159] Mashal, R. and A. Zeevi. "Beyond Correlation: Extreme Co-movements between Financial Assets." Columbia University, New York, 2002.

[160] McCullough, B. D., and C. G. Renfro. “Benchmarks and Software Standards: A Case Study of GARCH Procedures.” Journal of Economic and Social Measurement. Vol. 25, 1998, pp. 59–71.

[161] McLeod, A.I. and W.K. Li. “Diagnostic Checking ARMA Time Series Models Using Squared-Residual Autocorrelations.”Journal of Time Series Analysis. Vol. 4, 1983, pp. 269–273.

[162] McNeil, A. and R. Frey. "Estimation of Tail Related Risk Measure for Heteroscedastic Financial Time Series: An Extreme Value Approach." Journal of Empirical Finance. Vol. 7, 2000, pp. 271–300.

[163] Moler, C. Numerical Computing with MATLAB. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2004.

[164] Montgomery, J. Mathematical Models of Social Systems. Unpublished manuscript. Department of Sociology, University of Wisconsin-Madison, 2016.

[165] Morin, N. "Likelihood Ratio Tests on Cointegrating Vectors, Disequilibrium Adjustment Vectors, and their Orthogonal Complements." European Journal of Pure and Applied Mathematics. v. 3, 2010, pp. 541–571.

[166] Morley, James C., Charles R. Nelson, and Eric Zivot. "Why Are the Beveridge-Nelson and Unobserved-Components Decompositions of GDP So Different?" Review of Economics and Statistics 85, no. 2 (May 2003): 235–43. https://doi.org/10.1162/003465303765299765.

[167] National Bureau of Economic Research (NBER), Business Cycle Expansions and Contractions, https://www.nber.org/research/data/us-business-cycle-expansions-and-contractions.

[168] Nelson, D. B. “Conditional Heteroskedasticity in Asset Returns: A New Approach.” Econometrica. Vol. 59, 1991, pp. 347–370.

[169] Nelson, D. B. "Conditional Heteroskedasticity in Asset Returns: A New Approach." Econometrica.. Vol. 59, No. 2, 1991, pp. 347–370.

[170] Nelson, C., and C. Plosser. "Trends and Random Walks in Macroeconomic Time Series: Some Evidence and Implications." Journal of Monetary Economics. Vol. 10, 1982, pp. 130–162.

[171] Nelson, R. C., and A. F. Siegel. "Parsimonious Modeling of Yield Curves." Journal of Business. Vol. 60, No. 4, 1987, pp. 473–489.

[172] Newey, W. K., and K. D. West. “A Simple Positive Semidefinite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix.” Econometrica. Vol. 55, 1987, pp. 703–708.

[173] Newey, W. K, and K. D. West. “Automatic Lag Selection in Covariance Matrix Estimation.” The Review of Economic Studies. Vol. 61, No. 4, 1994, pp. 631–653.

[174] Norris, J. R. Markov Chains. Cambridge, UK: Cambridge University Press, 1997.

[175] Nystrom, K. and J. Skoglund. "Univariate Extreme Value Theory, GARCH and Measures of Risk." Preprint, submitted 2002.

[176] Nystrom, K. and J. Skoglund. "A Framework for Scenario-Based Risk Management." Preprint, submitted 2002.

[177] Pankratz, A. Forecasting with Dynamic Regression Models. John Wiley & Sons, 1991˙.

[178] Park, T. and G. Casella. "The Bayesian Lasso." Journal of American Statistical Association. Vol. 103, 2008, pp. 681–686.

[179] Ng, S., and P. Perron. “Unit Root Tests in ARMA Models with Data-Dependent Methods for the Selection of the Truncation Lag.” Journal of the American Statistical Association. Vol. 90, 1995, pp. 268–281.

[180] Park, R. E. "Estimation with Heteroscedastic Error Terms". Econometrica. 34, 1966 p. 888.

[181] Perron, P. “Trends and Random Walks in Macroeconomic Time Series: Further Evidence from a New Approach.” Journal of Economic Dynamics and Control. Vol. 12, 1988, pp. 297–332.

[182] Pesaran, H. H., and Y. Shin. "Generalized Impulse Response Analysis in Linear Multivariate Models." Economic Letters. Vol. 58, 1998, pp. 17–29.

[183] Peters, J. P. “Estimating and Forecasting Volatility of Stock Indices Using Asymmetric GARCH Models and Skewed Student-t Densities.” Working Paper. Belgium: École d'Administration des Affaires, University of Liège, March 20, 2001.

[184] Phillips, P. “Time Series Regression with a Unit Root.” Econometrica. Vol. 55, 1987, pp. 277–301.

[185] Phillips, P., and P. Perron. “Testing for a Unit Root in Time Series Regression." Biometrika. Vol. 75, 1988, pp. 335–346.

[186] Qin, H., and A. T. K. Wan. "On the Properties of the t- and F-Ratios in Linear Regressions with Nonnormal Errors." Econometric Theory. Vol. 20, No. 4, 2004, pp. 690–700.

[187] Ravn, Morton O., and Harald Uhlig. "On Adjusting the Hodrick-Prescott Filter for the Frequency of Observations." The Review of Economics and Statistics 84 , no. 2 (May 2002): 371–76. https://doi.org/10.1162/003465302317411604.

[188] Rea, J. D. "Indeterminacy of the Chow Test When the Number of Observations is Insufficient." Econometrica. Vol. 46, 1978, p. 229.

[189] Roncalli, T., A. Durrleman, and A. Nikeghbali. "Which Copula Is the Right One?" Groupe de Rech. Oper., Credit Lyonnais, Paris, 2000.

[190] Schwert, W. "Effects of Model Specification on Tests for Unit Roots in Macroeconomic Data." Journal of Monetary Economics. Vol. 20, 1987, pp. 73–103.

[191] Schwarz, Gideon. “Estimating the Dimension of a Model.” The Annals of Statistics 6, no. 2 (March 1978): 461–64. https://doi.org/10.1214/aos/1176344136.

[192] Schwert, W. "Tests for Unit Roots: A Monte Carlo Investigation." Journal of Business and Economic Statistics. Vol. 7, 1989, pp. 147–159.

[193] Shackleton, Robert. "Estimating and Projecting Potential Output Using CBO's Forecasting Growth Model." Congressional Budget Office Working Paper No. 2018-03 (February 2018). https://www.cbo.gov/publication/53558.

[194] Shao, J. "An Asymptotic Theory for Linear Model Selection." Statistica Sinica. Vol. 7, 1997, pp. 221–264.

[195] Sharpe, W. F. "Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk." Journal of Finance. Vol. 19, 1964, pp. 425–442.

[196] Shreve, S. E. Stochastic Calculus for Finance II: Continuous-Time Models. New York: Springer-Verlag, 2004.

[197] Sims, Christopher A. "Solving Linear Rational Expectations Models." Computational Economics 20 (October 2002) 1–20. https://doi.org/10.1023/A:1020517101123.

[198] Sims, C., Stock, J., and Watson, M. "Inference in Linear Time Series Models with Some Unit Roots." Econometrica. Vol. 58, 1990, pp. 113–144.

[199] Smets, F. and Wouters, R. "An Estimated Stochastic Dynamic General Equilibrium Model of the Euro Area." European Central Bank, Working Paper Series. No. 171, 2002.

[200] Smets, F. and Wouters, R. "Comparing Shocks and Frictions in US and Euro Area Business Cycles: A Bayesian DSGE Approach." European Central Bank, Working Paper Series. No. 391, 2004.

[201] Smets, F. and Wouters, R. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach." European Central Bank, Working Paper Series. No. 722, 2007.

[202] Strang, G. Linear Algebra and Its Applications. 4th ed. Pacific Grove, CA: Brooks Cole, 2005.

[203] Stock, James H., and Mark W. Watson. "Forecasting Inflation." Journal of Monetary Economics 44, no. 2 (October 1999): 293–335. https://doi.org/10.1016/S0304-3932(99)00027-6.

[204] Stone, M. "An Asymptotic Equivalence of Choice of Model by Cross-Validation and Akaike's Criterion." Journal of the Royal Statistical Society. Series B, Vol. 39, 1977, pp. 44–47.

[205] Stone, R. "The Analysis of Market Demand." Journal of the Royal Statistical Society. Vol. 108, 1945, pp. 1–98.

[206] Teräsvirta, Tima. "Modelling Economic Relationships with Smooth Transition Regressions." In A. Ullahand and D.E.A. Giles (eds.), Handbook of Applied Economic Statistics, 507–552. New York: Marcel Dekker, 1998.

[207] Tibshirani, R. "Regression Shrinkage and Selection via the Lasso." Journal of Royal Statistical Society. Vol. 58, 1996, pp. 267–288.

[208] Tsay,R.S. Analysis of Financial Time Series. Hoboken, NJ: John Wiley & Sons, Inc., 2005.

[209] Turner, P. M. "Testing for Cointegration Using the Johansen Approach: Are We Using the Correct Critical Values?" Journal of Applied Econometrics. v. 24, 2009, pp. 825–831.

[210] U.S. Federal Reserve Economic Data (FRED), Federal Reserve Bank of St. Louis, https://fred.stlouisfed.org/.

[211] van Dijk, Dick. Smooth Transition Models: Extensions and Outlier Robust Inference. Rotterdam, Netherlands: Tinbergen Institute Research Series, 1999.

[212] Weisberg, S. Applied Linear Regression. Hoboken, NJ: John Wiley & Sons, Inc., 2005.

[213] Wielandt, H. Topics in the Analytic Theory of Matrices. Lecture notes prepared by R. Mayer. Department of Mathematics, University of Wisconsin-Madison, 1967.

[214] White, H. "A Heteroskedasticity-Consistent Covariance Matrix and a Direct Test for Heteroskedasticity." Econometrica. v. 48, 1980, pp. 817–838.

[215] White, J. S. "Asymptotic Expansions for the Mean and Variance of the Serial Correlation Coefficient." Biometrika. Vol 48, 1961, pp. 85–94.

[216] White, H. Asymptotic Theory for Econometricians. New York: Academic Press, 1984.

[217] White, H., and I. Domowitz. “Nonlinear Regression with Dependent Observations.” Econometrica. Vol. 52, 1984, pp. 143–162.

[218] Wilson, A. L. "When is the Chow Test UMP?" The American Statistician. Vol. 32, 1978, pp. 66–68.

[219] Wold, Herman. "A Study in the Analysis of Stationary Time Series." Journal of the Institute of Actuaries 70 (March 1939): 113–115. https://doi.org/10.1017/S0020268100011574.

[220] Wooldridge, J. M. Introductory Econometrics. Cincinnati, OH: South-Western, 2009.