Econometric modelling with time series: Specification, estimation and testing

Econometric Modelling with Time Series: Specification, Estimation and Testing

Volumn , Issue , 2010, Pages 1-887

  Martin, Vance ^a   Hurn, Stan ^b   Harris, David ^c  

^a UNIVERSITY OF MELBOURNE   (Australia)

^b QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

^c MONASH UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84925610773     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1017/CBO9781139043205     Document Type: Book

References (247)

1. Abramowitz, M., and Stegun, I.A. 1965. Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. New York: Dover.
2. Ahn, S.K., and Reinsel, G.C. 1990. Estimation for partially nonstationary multivariate autoregressive models. Journal of the American Statistical Association, 85, 813–823.
3. Aigner, D., Lovell, C.A.K., and Schmidt, P. 1977. Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6, 21–37.
4. Aït-Sahalia, Y. 1996. Testing continuous-time models of the spot interest rate. Review of Financial Studies, 9, 385–426.
5. Akaike, H. 1974. A new look at the statistical model identification. I.E.E.E. Transactions on Automatic Control, 19, 716–723.
6. Akaike, H. 1976. Canonical correlation analysis of time series and the use of an information criterion. Pages 52–107 of: Mehra, R., and Lainotis, D.G. (eds), System Identification: Advances and Case Studies. New York: Academic Press.
7. Al-Osh, M.A., and Alzaid, A.A. 1987. First-order integer valued autoregressive (INAR(1)) process. Journal of Time Series Analysis, 8, 261–275.
8. Andel, J., and Barton, T. 1986. A note on the threshold AR(1) model. Journal of Time Series Analysis, 7, 1–5.
9. Andersen, T.G., Bollerslev, T., Diebold, F.X., and Labys, P. 2001. The distribution of exchange rate volatility. Journal of the American Statistical Association, 96, 42–55.
10. Andersen, T.G., Bollerslev, T., Diebold, F.X., and Labys, P. 2003. Modeling and forecasting realized volatility. Econometrica, 71, 579–62.
11. Anderson, H.M., Anthansopoulos, G., and Vahid, F. 2007. Nonlinear autoregressive leading indicator models of output in G-7 countries. Journal of Applied Econometrics, 22, 63–87.
12. Anderson, T.W. 1971. The Statistical Analysis of Time Series. New York: Wiley.
13. Anderson, T.W. 1984. An Introduction to Multivariate Statistical. John Wiley and Sons, Inc.
14. Andrews, D.W.K. 1984. Non-strong mixing autoregressive processes. Journal of Applied Probability, 21, 930–934.
15. Andrews, D.W.K., and Monahan, J.C. 1992. An improved heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 60, 953–966.
16. Bai, J., and Ng, S. 2002. Determining the number of factors in approximate factor models. Econometrica, 70, 191–221.
17. Bai, J., and Ng, S. 2004. A PANIC attack on unit roots and cointegration. Econometrica, 72, 1127–1177.
18. Baillie, R.T., Bollerslev, T., and Mikkelsen, H.O. 1996. Fractionally integrated generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 74, 3–30.
19. Banbura, M., Giannone, D., and Reichlin, L. 2010. Large Bayesian vector autoregressions. Journal of Applied Econometrics, 25, 71–92.
20. Banerjee, A., Dolado, J.J., Galbraith, J.W., and Hendry, D.F. 1993. Co-integration, Error-Correction, and the Econometric Analysis of Non-Stationary. Advanced Texts in Econometrics. Oxford: Oxford University Press.
21. Barro, R.J. 1978. Unanticipated money, output, and the price level in the United States. Journal of Political Economy, 86, 549–580.
22. Beach, C.M., and MacKinnon, J.G. 1978. A maximum likelihood procedure for regression with autocorrelated errors. Econometrica, 46, 51–58.
23. Beaumont, M.A., Cornuet, J-M., Marin, J-M., and Robert, C.P. 2009. Adaptive approximate Bayesian computation. Biometrika, 96, 983–990.
24. Bera, A.K., Ghosh, A., and Xiao, Z. 2010. Smooth test for equality of distributions. Mimeo.
25. Bernanke, B.S., and Blinder, A.S. 1992. The Federal funds rate and the channels of monetary transmission. American Economic Review, 82, 901–921.
26. Berndt, E., Hall, B., Hall, R., and Hausman, J. 1974. Estimation and inference in nonlinear structural models. Annals of Social Measurement, 3, 653–665.
27. Beveridge, S., and Nelson, C.R. 1981. 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, 151–174.
28. Billingsley, P. 1968. Convergence of Probability Measures. New York: Wiley.
29. Blanchard, O.J., and Quah, D. 1989. The dynamic effects of aggregate demand and supply disturbances. The American Economic Review, 79, 655–673.
30. Bollerslev, T., and Wooldridge, J.M. 1992. Quasi-maximum likelihood estimation and inference in dynamic model with time-varying covariances. Econometric Reviews, 11, 143–172.
31. Boswijk, P. 1995. Efficient inference on cointegration parameters in structural error correction models. Journal of Econometrics, 69, 133–158.
32. Breitung, J. 2002. Nonparametric tests for unit roots and cointegration. Journal of Econometrics, 108, 343–363.
33. Broyden, C.G. 1970. The convergence of a class of double-rank minimization algorithms. Journal of the Institute of Mathematical Applications, 6, 76–90.
34. Bu, R., McCabe, B.P.M., and Hadri, K. 2008. Maximum likelihood estimation of higher-order integer-valued autoregressive processes. Journal of Time Series Analysis, 29, 973–994.
35. Butler, R.J., McDonald, J.B., Nelson, R.D., and White, S.B. 1990. Robust and partially adaptive estimation of regression models. Review of Economics and Statistics, 72, 321–327.
36. Campbell, J.Y., and Shiller, R.J. 1987. Cointegration and tests of present value models. Journal of Political Economy, 95, 1062–1088.
37. Canova, F., and de Nicolo, G. 2002. Monetary disturbances matter for business fluctuations in the G7. Journal of Monetary Economics, 49, 1131–1159.
38. Carrion-i Silvestre, J.L., Kim, D., and Perron, P. 2009. GLS-based unit root tests with multiple structural breaks under both the null and the alternative hypothesis. Econometric Theory, 25, 1754–1792.
39. Carter, C.K., and Kohn, R. 1994. On Gibbs sampling for state space models. Biometrika, 81, 541–553.
40. Cavaliere, G., Rahbek, A., and Taylor, A.M.R. 2010. Cointegration rank testing under conditional heteroskedasticity. Econometric Theory, 26, 1719–1760.
41. Chan, K.C., Karolyi, G.A., Longstaff, F.A., and Sanders, A.B. 1992. An empirical comparison of alternative models of the short term interest rate. Journal of Finance, 52, 1209–1227.
42. Chang, Y., and Park, J.Y. 2002. On the asymptotics of ADF tests for unit roots. Econometric Reviews, 21, 431–447.
43. Chapman, D. A., and Pearson, N.D. 2000. Is the short rate drift actually nonlinear? Journal of Finance, 55, 355–388.
44. Chen, X., and Fan, Y. 1999. Consistent hypothesis testing in semiparametric and nonparametric models for econometric time series. Journal of Econometrics, 91, 373–401.
45. Cheng, X., and Phillips, P.C.B. 2009. Semiparametric cointegrating rank selection. Econometrics Journal, 12, S83–S104.
46. Chib, S. 2001. Markov chain Monte Carlo methods: computation and inference. Pages 3569–3649 of: Heckman, J.J., and Leamer, E. (eds), Handbook of Econometrics, Volume 5. Amsterdam: North Holland.
47. Chib, S. 2008. MCMC methods. In: 2 (ed), New Palgrave Dictionary of Economics. New York: Palgrave Macmillan.
48. Chib, S., and Greenberg, E. 1996. Markov chain Monte Carlo simulation methods in econometrics. Econometric Theory, 12, 409–431.
49. Chib, S., Nardari, F., and Shephard, N. 2002. Markov chain Monte Carlo methods for stochastic volatility models. Journal of Econometrics, 108, 281–316.
50. Cochrane, J.H., and Piazzesi, M. 2009. Decomposing the yield curve. Unpublished manuscript.
51. Conley, T.G., Hansen, L.P., Luttmer, E.G.J., and Scheinkman, J.A. 1997. Shortterm interest rates as subordinated diffusions. Review of Financial Studies, 10, 525–577.
52. Cox, J.C., Ingersoll, J.E., and Ross, S.A. 1985. A theory of the term structure of interest rates. Econometrica, 53, 385–407.
53. Craine, R., and Martin, V.L. 2008. International monetary policy surprise spillovers. Journal of International Economics, 75, 180–196.
54. Craine, R., and Martin, V.L. 2009. The interest rate conundrum. Unpublished manuscript.
55. Creedy, J., and Martin, V.L. 1994. Chaos and Non-linear Models in Economics: Theory and Applications. Cheltenham: Edward Elgar.
56. Davidson, J. 1994. Stochastic Limit Theory. Oxford: Oxford University Press.
57. Davidson, J. 1998. Structural relations, cointegration and identification: Some simple results and their application. Journal of Econometrics, 87, 87–113.
58. D.E. Rapach. 2001. Macro shocks and real stock prices. Journal of Economics and Business, 53, 5–26.
59. Dickey, D.A., and Fuller, W.A. 1979. Distributions of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74, 427–431.
60. Dickey, D.A., and Fuller, W.A. 1981. Likelihood ratio statistics for autogressive time series with a unit root. Econometrica, 49, 1057–1072.
61. Diebold, F.X., and Nerlove, M. 1989. The dynamics of exchange rate volatility: A multivariate latent-factor ARCH model. Journal of Applied Econometrics, 4, 1–22.
62. Diebold, F.X., and Rudebusch, G.D. 1996. Measuring business cycles: A modern perspective. Review of Economics and Statistics, 78, 67–77.
63. Diebold, F.X., and Yilmaz, K. 2009. Measuring financial asset return and volatility spillovers, with application to global equity. Economic Journal, 119, 158–171.
64. DiNardo, J., and Tobias, J.L. 2001. Nonparametric density and regression estimation. Journal of Economic Perspectives, 15, 11–28.
65. Drovandi, C.C., Pettitt, A.N., and Faddy, M.J. 2011. Approximate Bayesian computation using indirect inference. Journal of the Royal Statistical Society (Series C), 60, 1–21.
66. Duffie, D., and Singleton, K.J. 1993. Simulated moments estimation of Markov models of asset prices. Econometrica, 61, 929–952.
67. Dungey, M., and Martin, V.L. 2007. Unravelling financial market linkages during crises. Journal of Applied Econometrics, 22, 89–119.
68. Durlauf, S.N., and Phillips, P.C.B. 1988. Trends versus random walks in time series analysis. Econometrica, 56, 1333–1354.
69. Efron, B., and Tibshirani, R.J. 1993. An Introduction to the Bootstrap. New York: Chapman and Hall.
70. Elliot, G. 1999. Efficient tests for a unit root when the initial observation is drawn from its unconditional distribution. International Economic Review, 40, 767–783.
71. Elliot, G., Rothenberg, T.J., and Stock, J.H. 1996. Efficient tests for an autoregressive unit root. Econometrica, 64, 813–836.
72. Engel, C., and Hamilton, J.D. 1990. Long swings in the dollar: Are they in the data and do markets know it? American Economic Review, 80, 689–713.
73. Engle, R.F. 1982. Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50, 987–1008.
74. Engle, R.F. 2002. Dynamic conditional correlation. A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20, 339–350.
75. Engle, R.F., and González-Rivera, G. 1991. Semiparametric ARCH models. Journal of Business and Economic Statistics, 9, 345–359.
76. Engle, R.F., and Granger, C.W.J. 1987. Cointegration and error correction: Representation, estimation and testing. Econometrica, 55, 251–276.
77. Engle, R.F., and Kelly, B. 2009. Dynamic equicorrelation. Unpublished manuscript.
78. Engle, R.F., and Kroner, K.F. 1995. Multivariate simultaneous generalized ARCH. Econometric Theory, 11, 122–150.
79. Engle, R.F., and Russell, J. R. 1998. Autoregressive conditional duration: A new model for irregularly spaced transaction data. Econometrica, 66, 1127–1162.
80. Engle, R.F., and Sheppard, K. 2001. Theoretical and empirical properties of dynamic conditional correlation multivariate GARCH. Working Paper 8554. NBER.
81. Ericsson, N.R., Hendry, D.F., and Prestwich, K.M. 1998. The demand for broad money in the United Kingdom. Scandinavian Journal of Economics, 100, 289–324.
82. Favero, C.A., and Giavazzi, F. 2002. Is the international propagation of financial shocks non-linear? Evidence from the ERM. Journal of International Economics, 57, 231–246.
83. Fletcher, R. 1970. A new approach to variable metric algorithms. Computer Journal, 13, 317–322.
84. Forchini, G. 2006. On the bimodality of the exact distribution of the TSLS estimator. Econometric Theory, 22, 932–946.
85. Früthwirth-Schnatter, S., and Wagner, H. 2006. Auxiliary mixture sampling for parameter-driven models of time series of small counts with applications to state space modelling. Biometrika, 93, 827–841.
86. Fry, R., Hocking, J., and Martin, V.L. 2008. The role of portfolio shocks in a SVAR model of the Australian economy. Economic Record, 84, 17–33.
87. Fry, R.A., and Pagan, A.R. 2011. Some issues in using sign restrictions for identifying structural VARs. Journal of Economic Literature, 49, 938–960.
88. Gali, J. 1992. How well does the IS-LM model fit postwar U.S. data? Quarterly Journal of Economics, 107, 709–738.
89. Gallant, A.R., and Tauchen, G. 1996. Which moments to match? Econometric Theory, 12, 657–681.
90. Getmansky, M., Lo, A.W., and Makarov, I. 2004. An econometric model of serial correlation and illiquidity in hedge fund returns. Journal of Financial Econometrics, 74, 529–609.
91. Geweke, J. 1999. Using simulation methods for Bayesian econometric models: inference, development and communication. Econometric Reviews, 18, 1–74.
92. Geweke, J. 2005. Contemporary Bayesian Econometrics and Statistics. New Jersey: John Wiley and Sons, Inc.
93. Ghysels, E., Santa-Clara, P., and Valkanov, R. 2005. There is a risk-return trade-off after all. Journal of Financial Economics, 76, 509–548.
94. Gill, P.E., Murray, W., and Wright, M.H. 1981. Practical Optimization. New York: Academic Press.
95. Goldfarb, D. 1970. A family of variable metric methods derived by variational means. Mathematics of Computation, 24, 23–26.
96. González-Rivera, G., and Drost, F.C. 1999. Efficiency comparisons of maximum-likelihood-based estimators in GARCH models. Journal of Econometrics, 93, 93–111.
97. Gouriéroux, C., Monfort, A., and Renault, E. 1993. Indirect inference. Journal of Applied Econometrics, 8, 85–118.
98. Granger, C.W.J. 2008. Non-linear models: where do we go next - time varying parameter models? Studies in Nonlinear Dynamics and Econometrics, 12, 1–9.
99. Granger, C.W.J., and Anderson, A.P. 1978. An Introduction to Bilinear Time Series Models. Gottingen: Vandenhoeck and Ruprecht.
100. Greenberg, E. 2008. An Introduction to Bayesian Econometrics. New York: Cambridge University Press.
101. Gurkaynak, R.S., Sack, B., and Swanson, E. 2005. The sensitivity of long-term interest rates to economic news: Evidence and implications for macroeconomic models. American Economic Review, 95, 425–436.
102. Hall, P., and Heyde, C. C. 1980. Martingale Limit Theory and its Application. New York: Academic Press Inc. [Harcourt Brace Jovanovich Publishers].
103. Hamilton, J.D. 1988. Rational expectations econometric analysis of changes in regime: An investigation of the term structure of interest rates. Journal of Economic Dynamics and Control, 12, 385–423.
104. Hamilton, J.D. 1989. A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica, 57, 357–384.
105. Hamilton, J.D. 1994. Time Series Analysis. Princeton, New Jersey: Princeton University Press.
106. Hamilton, J.D., and Jordà, Ò. 2002. A model of the Federal funds rate target. Journal of Political Economy, 110, 1135–1167.
107. Hamilton, J.D., and Susmel, R. 1994. Autoregressive conditional heteroskedasticity and changes in regime. Journal of Econometrics, 64, 307–333.
108. Han, H., and Park, J.Y. 2008. Time series properties of ARCH processes with persistent covariates. Journal of Econometrics, 146, 275–292.
109. Hannan, E.J. 1980. The estimation of the order of an ARMA process. Annals of Statistics, 8, 1071–1081.
110. Hannan, E.J., and Quinn, B.G. 1979. The determination of the order of an autoregression. Journal of the Royal Statistical Society (Series B), 41, 190–195.
111. Hansen, B.E. 1996. Inference when a nuisance parameter is not identified under the null hypothesis. Econometrica, 64, 413–430.
112. Hansen, L.P. 1982. Large sample properties of generalised method of moments estimators. Econometrica, 50, 1029–1054.
113. Hansen, L.P., and Singleton, K.J. 1982. Generalized instrumental variables estimation of nonlinear rational expectations models. Econometrica, 50, 1269–1286.
114. Hansen, L.P., Heaton, J., and Yaron, A. 1996. Finite-sample properties of some alternative GMM estimators. Journal of Business and Economic Statistics, 14, 262–280.
115. Harding, D., and Pagan, A.R. 2002. Dissecting the cycle: a methodological investigation. Journal of Monetary Economics, 49, 365–381.
116. Harris, D., and Poskitt, D.S. 2004. Determination of cointegration rank in partially nonstationary processes via a generalised von-Neumann criterion. Econometrics Journal, 7, 191–217.
117. Harris, D., Harvey, D.I., Leybourne, S.J., and Taylor, A.M.R. 2009. Testing for a unit root in the presence of a possible break in trend. Econometric Theory, 25, 1545–1588.
118. Harvey, A.C. 1989. Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge: Cambridge University Press.
119. Harvey, A.C. 1990. The Econometric Analysis of Time Series, 2nd Edition. London: Philip Allan.
120. Harvey, A.C., and Jaeger, A. 1993. Detrending, stylized facts and the business cycle. Journal of Applied Econometrics, 8, 231–247.
121. Harvey, D.I., Leybourne, S.J., and Taylor, A.M.R. 2009. Unit root testing in practice: Dealing with uncertainty over trend and initial condition. Econometric Theory, 25, 587–636.
122. Hatanaka, M. 1974. An efficient two-step estimator for the dynamic adjustment model with autoregressive errors. Journal of Econometrics, 2, 199–220.
123. Hillier, G. 2006. Yet more on the exact properties of IV estimators. Econometric Theory, 22, 913–931.
124. Hodrick, R.J., and Prescott, E.C. 1997. Postwar U.S. business cycles: An empirical investigation. Journal of Money, Credit and Banking, 24, 1–16.
125. Horowitz, J.L. 1997. Bootstrap methods in econometrics: theory and numerical performance. In: Kreps, D.M., and Wallis, K.F. (eds), Advances in Economics and Econometrics: Theory and Applications. Cambridge: Cambridge University Press.
126. Hsiao, C. 1997. Cointegration and dynamic simultaneous equations model. Econometrica, 65, 647–670.
127. Hurn, A.S., Jeisman, J., and Lindsay, K.A. 2007. Seeing the wood for the trees: A critical evaluation of methods to estimate the parameters of stochastic differential equations. Journal of Financial Econometrics, 5, 390–455.
128. Jacquier, E., Polson, N.G., and Rossi, P.E. 2002. Bayesian analysis of stochastic volatility models. Journal of Business and Economic Statistics, 20, 69–87.
129. Jacquier, E., Polson, N.G., and Rossi, P.E. 2004. Bayesian analysis of stochastic volatility models with fat-tails and correlated errors. Journal of Econometrics, 122, 185–212.
130. Johansen, S. 1988. Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control, 12, 231–254.
131. Johansen, S. 1991. Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica, 59, 1551–1580.
132. Johansen, S. 1995a. Identifying restrictions of linear equations: with applications to simultaneous equations and cointegration. Journal of Econometrics, 69, 111–132.
133. Johansen, S. 1995b. Likelihood-based Inference in Cointegrated Vector Autoregressive Models. Oxford: Oxford University Press.
134. Johansen, S. 2005. Interpretation of cointegrating coefficients in the cointegrated autoregressive model. Oxford Bulletin of Economics and Statistics, 67, 93–104.
135. Johansen, S., and Juselius, K. 1992. Testing structural hypotheses in a multivariate cointegration analysis of the PPP and UIP for the U.K. Journal of Econometrics, 53, 211–244.
136. Johansen, S., Mosconi, R., and Nielsen, B. 2000. Cointegration analysis in the presence of structural breaks in the deterministic trend. Econometrics Journal, 3, 216–249.
137. Jung, R.C., Ronning, G., and Tremayne, A.R. 2005. Estimation in conditional first order autoregression with discrete support. Statistical Papers, 46, 195–224.
138. Kendall, M., and Stuart, A. 1973. The Advanced Theory of Statistics. London: Griffin.
139. Kennan, J. 1985. The duration of contract strikes in U.S. manufacturing. Journal of Econometrics, 28, 5–28.
140. Kim, C-J. 1994. Dynamic linear models with Markov switching. Journal of Econometrics, 60, 1–22.
141. Kim, S., and Roubini, N. 2000. Exchange rate anomalies in the industrial countries: A solution with a structural VAR approach. Journal of Monetary Economics, 45, 561–586.
142. Klein, L.R. 1950. Economic Fluctuations in the United States 1921–1941. Monograph 11. Cowles Commission.
143. Klimko, L.A., and Nelson, P.I. 1978. On conditional least squares estimation for stochastic processes. Annals of Statistics, 6, 629–642.
144. Knez, P., Litterman, R., and Scheinkman, J. 1994. Explorations into factors explaining money market returns. Journal of Finance, 49, 1861–1882.
145. Konstas, P., and Khouja, M.W. 1969. The Keynesian demand-for-money function. Journal of Money, Credit and Banking, 1, 765–777.
146. Koop, G. 2003. Bayesian Econometrics. Chichester: Wiley.
147. Koop, G. 2012. Forecasting with medium and large Bayesian VARs. Journal of Applied Econometrics, forthcoming.
148. Koop, G., Pesaran, M.H., and Potter, S.M. 1996. Impulse response analysis in nonlinear multivariate models. Journal of Econometrics, 74, 119–147.
149. Koop, G., Poirier, D.J., and Tobias, J.L. 2007. Bayesian Econometric Methods. Cambridge: Cambridge University Press.
150. Kuan, C.M., and White, H. 1994. Adaptive learning with nonlinear dynamics driven by dependent processes. Econometrica, 62, 1087–1114.
151. Kwiatkowski, D.P., Phillips, P.C.B., Schmidt, P., and Shin, Y. 1992. Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic series have a unit root? Journal of Econometrics, 54, 159–178.
152. Lee, T-H., and Tse, Y. 1996. Cointegration tests with conditional heteroskedasticity. Journal of Econometrics, 73, 401–410.
153. Lee, T-H., White, H., and Granger, C.W.J. 1993. Testing for neglected nonlinearity in time-series models: A comparison of neural network methods and standard tests. Journal of Econometrics, 56, 269–290.
154. Li, H., and Maddala, G.S. 1996. Bootstrapping time series models. Econometric Reviews, 15, 115–158.
155. Lorenz, H-W. 1989. Nonlinear Dynamical Economics and Chaotic Motion. Lecture Notes in Economics and Mathematical Systems 334. Springer-Verlag.
156. Luukkonen, R., Saikkonen, P., and Teräsvirta, T. 1988. Testing linearity against smooth transition autoregressive models. Biometrika, 75, 491–499.
157. Lye, J.N., and Martin, V.L. 1994. Nonlinear time series modelling and distributional flexibility. Journal of Time Series Analysis, 15, 65–84.
158. Maddala, G.S., and Kim, I-M. 1998. Unit Roots, Cointegration and Structural Change. Cambridge: Cambridge University Press.
159. Maddala, G.S., and Li, H. 1996. Bootstrap based tests in financial models. Pages 463–488 of: Maddala, G.S., and Rao, C.R. (eds), Statistical Methods in Finance. Handbook of Statistics, vol. 14. Elsevier.
160. Marinucci, D., and Robinson, P.M. 2001. Finite sample improvements in statistical inference with I(1) processes. Journal of Applied Econometrics, 16, 431–444.
161. Martin, V.L., Tremayne, A.R., and Jung, R.C. 2011. Efficient method of moments estimators for integer time series models. In: Econometric Society Australasian Meeting.
162. McCabe, B.P.M., and Martin, G.M. 2005. Bayesian predictions of low count time series. International Journal of Forecasting, 21, 315–330.
163. McKenzie, E. 1988. Some ARMA models for dependent sequences of Poisson counts. Advances in Applied Probability, 20, 822–835.
164. Mehra, R., and Prescott, E.C. 1985. The equity premium: a puzzle. Journal of Monetary Economics, 15, 145–162.
165. Müller, U.K., and Elliot, G. 2001. Tests for unit roots and the initial observation. Discussion Paper 2001-19. University of California, San Diego.
166. Nelder, J.A., and Mead, R. 1965. A simplex method for function minimization. Computer Journal, 7, 308–313.
167. Nelsen, R.B. 1999. An Introduction to Copulas. New York: Springer-Verlag.
168. Nelson, C.R., and Plosser, C.I. 1982. Trends and random walks in macroeconmic time series: Some evidence and implications. Journal of Monetary Economics, 10, 139–162.
169. Nelson, D.B. 1991. Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59, 347–370.
170. Newey, W.K., and McFadden, D.L. 1994. Large sample estimation and hypothesis testing. In: Engle, R.F., and McFadden, D.L. (eds), Newey, W.K., and McFadden, D.L 4. Elsevier.
171. Newey, W.K., and West, K.D. 1987. A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix. Econometrica, 55, 703–708.
172. Newey, W.K., and West, K.D. 1994. Automatic lag selection in covariance matrix estimation. Review of Economic Studies, 61, 631–654.
173. Neyman, J. 1937. Smooth test for goodness of fit. Skandinaviske Aktuarietidskrift, 20, 150–199.
174. Ng, S., and Perron, P. 2001. Lag length selection and the construction of unit root tests with good size and power. Econometrica, 69, 1519–1554.
175. Nowak, S. 2008. How do public announcements affect the frequency of trading in U.S. airline stocks? Working Paper 38. CAMA.
176. Pagan, A.R., and Pesaran, M.H. 2008. Econometric analysis of structural systems with permanent and transitory shocks. Journal of Economic Dynamics and Control, 32, 3376–3395.
177. Pagan, A.R., and Robertson, J.C. 1989. Structural models of the liquidity effect. Review of Economics and Statistics, 80, 202–217.
178. Pagan, A.R., and Ullah, A. 1999. Nonparametric Econometrics. New York: Cambridge University Press.
179. Park, J.Y. 1992. Canonical cointegrating regressions. Econometrica, 60, 119–143.
180. Park, J.Y., and Phillips, P.C.B. 1988. Statistical inference in regressions with integrated processes: Part 1. Econometric Theory, 4, 468–498.
181. Peersman, G. 2005. What caused the early millenium slowdown? Evidence based on vector autoregressions. Journal of Applied Econometrics, 20, 185–207.
182. Perron, P. 1989. The Great Crash, the oil price shock, and the unit root hypothesis. Econometrica, 57, 1361–1401.
183. Perron, P., and Ng, S. 1996. Useful modifications to some unit root tests with dependent errors and their local asymptotic properties. Review of Economic Studies, 63, 435–463.
184. Perron, P., and Ng, S. 1998. An autoregressive spectral density estimator at frequency zero for nonstationarity tests. Econometric Theory, 14, 560–603.
185. Perron, P., and Rodriguez, G. 2003. GLS detrending efficient unit root tests and structural change. Journal of Econometrics, 115, 1–27.
186. Pesaran, M.H., and Shin, Y. 2002. Long run structural modelling. Econometric Reviews, 21, 49–87.
187. Phillips, P.C.B. 1986. Understanding spurious regressions in econometrics. Journal of Econometrics, 33, 311–340.
188. Phillips, P.C.B. 1987. Time series regression with a unit root. Econometrica, 55, 277–301.
189. Phillips, P.C.B. 1991a. Optimal inference in cointegrated systems. Econometrica, 59, 283–306.
190. Phillips, P.C.B. 1991b. Spectral regression for cointegrated time series. In: Barnett, W. (ed), Nonparametric and Semiparametric Methods in Economics and Statistics. Cambridge: Cambridge University Press.
191. Phillips, P.C.B. 1991c. To criticize the critics: an objective Bayesian analysis of stochastic trends. Journal of Applied Econometrics, 6, 333–364.
192. Phillips, P.C.B. 1998. Impulse response and forecast error variance asymptotics in nonstationary VARs. Journal of Econometrics, 83, 21–56.
193. Phillips, P.C.B. 2006. A remark on bimodality and weak instrumentation in structural equation estimation. Econometric Theory, 22, 947–960.
194. Phillips, P.C.B., and Hansen, B.E. 1990. Statistical inference in instrumental variables regressions with I(1) errors. Review of Economic Studies, 57, 99–125.
195. Phillips, P.C.B., and Lee, C.C. 1995. Efficiency gains from quasi-differencing under nonstationarity. Pages 300–314 of: Athens Conference on Applied Probability and Time Series Analysis. Lecture Notes in Statistics, vol. 115. New York: Springer.
196. Phillips, P.C.B., and Perron, P. 1988. Testing for a unit root in time series regression. Biometrika, 75, 335–346.
197. Poskitt, D.S. 2000. Strongly consistent determination of cointegrating rank via canonical correlations. Journal of Business and Economic Statistics, 18, 77–90.
198. Poskitt, D.S., and Tremayne, A.R. 1980. Testing the specification of a fitted autoregressive-moving average model. Biometrika, 67, 359 – 363.
199. Rice, J. 1984. Bandwidth choice for nonparametric regression. Annals of Statistics, 12, 1215–1230.
200. Robinson, P.M. 1983. Nonparametric estimators for time series. Journal of Time Series Analysis, 4, 185–207.
201. Robinson, P.M. 1988. Root-N-consistent semiparametric regression. Econometrica, 56, 931–954.
202. Rudebusch, G.D. 2002. Term structure evidence on interest rate smoothing and monetary policy inertia. Journal of Monetary Economics, 49, 1161–1187.
203. Saikkonen, P. 1991. Asymptotically efficient estimation of cointegration regressions. Econometric Theory, 7, 1–21.
204. Sargan, J.D. 1964. Wages and prices in the United Kingdom: A study in econometric methodology. In: Hart, P.E., Mills, G., and Whitaker, J.K. (eds), Econometric Analysis for National Economic Planning. Colston Papers, vol. 16. London: Butterworth Co.
205. Sarkar, S., Kanto, A., and Martin, V.L. 2012. Modelling nonlinearities in equity returns: The mean impact curve. Tech. rept. Unpublished manuscript. Forthcoming in Studies in Nonlinear Dynamics and Econometrics.
206. Schmidt, P., and Phillips, P.C.B. 1992. LM tests for a unit root in the presence of deterministic trends. Oxford Bulletin of Economics and Statistics, 54, 257–287.
207. Schwarz, G. 1978. Estimating the dimension of a model. Annals of Statistics, 6(461– 464).
208. Scott, D.W. 1992. Multivariate Density Estimation Theory, Practice, and Visualization. New York: John Wiley and Sons, Inc.
209. Severini, T.A. 2005. Likelihood Methods in Statistics. New York: Oxford University Press.
210. Shanno, D.F. 1970. Conditioning of quasi-Newton methods for function minimization. Mathematics of Computation, 24, 647–657.
211. Shenton, L.R., and Johnson, W.L. 1975. Moments of a serial correlation coefficient. Journal of the Royal Statistical Society (Series B), 27, 308–320.
212. Shephard, N. 2005. Stochastic Volatility: Selected Readings. Oxford: Oxford University Press.
213. Sims, C.A. 1972. Money, income, and causality. American Economic Review, 62, 540–552.
214. Sims, C.A. 1980. Macroeconomics and reality. Econometrica, 48, 1–48.
215. Skalin, J., and Teräsvirta, T. 2002. Modelling asymmetries and moving equilibria in unemployment rates. Macroeconomic Dynamics, 6, 202–241.
216. Smith, A.A. 1993. Estimating nonlinear time-series models using simulated vector autoregressions. Journal of Applied Econometrics, 8, S63–S84.
217. Stachurski, J., and Martin, V.L. 2008. Computing the distributions of economic models via simulation. Econometrica, 76, 443–450.
218. Steutel, F.W., and Van Harn, K. 1979. Discrete analogues of self-decomposability and stability. Annals of Probability, 7, 893–899.
219. Stock, J.H. 1987. Asymptotic properties of least squares estimators of cointegrating vectors. Econometrica, 55, 1035–1056.
220. Stock, J.H. 1994. Unit roots, structural breaks and trends. Pages 2739–2841 of: Engle, R.F., and McFadden, D.L. (eds), Handbook of Econometrics, Volume 4. Amsterdam: North Holland.
221. Stock, J.H. 1999. A class of tests for integration and cointegration. In: Engle, R.F., and White, H. (eds), Cointegration, Causality, and Forecasting: Festschrift in Honour of Clive W. J. Granger. Oxford: Oxford University Press.
222. Stock, J.H., and Watson, M.W. 1993. A simple estimator of cointegration vectors in higher order integrated systems. Econometrica, 61, 783–820.
223. Stock, J.H., and Watson, M.W. 2002. Forecasting using principal components from a large number of predictors. Journal of the American Statistical Association, 97, 1167–1179.
224. Stock, J.H., and Watson, M.W. 2005. Implications of dynamic factor models for VAR analysis. Working Paper 11467. NBER.
225. Stock, J.H., Wright, J.H., and Yogo, M. 2002. A survey of weak instruments and weak identification in generalized method of moments. Journal of Business and Economic Statistics, 20, 518–529.
226. Stroud, J.R., Muller, P., and Polson, N.G. 2003. Nonlinear state-space models with state dependent variance. Journal of the American Statistical Association, 98, 377–386.
227. Stuart, A., and Ord, J.K. 1994. The Advanced Theory of Statistics, Volume 1 Distribution Theory, 6th Edition. London: Hodder Arnold.
228. Stuart, A., Ord, J.K., and Arnold, S. 1999. The Advanced Theory of Statistics, Volume 2A Classical Inference and the Linear Model, 6th Edition. London: Hodder Arnold.
229. Subba Rao, T., and Gabr, M.M. 1984. An Introduction to Bispectral Analysis and Bilinear Time Series Models. Berlin: Springer-Verlag.
230. Taylor, J.B. 1993. Discretion versus policy rules in practice. Carnegie-Rochester Conference Series on Public Policy, 39, 195–214.
231. Taylor, S.J. 1982. Financial returns modelled by the product of two stochastic processes — a study of daily sugar prices 1961–79. In: Anderson, O.D. (ed), Time Series Analysis: Theory and Practice. Amsterdam: North Holland.
232. Teräsvirta, T. 1994. Specification, estimation and evaluation of smooth transition autoregressive models. Journal of the American Statistical Association, 89, 208–218.
233. Tong, H. 1983. Threshold Models in Non-linear Time Series Analysis. Lecture Notes in Statistics 21. Springer-Verlag.
234. Trenkler, C., Saikkonen, P., and Lütkephol, H. 2007. Testing for the cointegration rank of a VAR process with level shift and trend break. Journal of Time Series Analysis, 29, 331–358.
235. Uhlig, H. 2005. What are the effects of monetary policy on output? Journal of Monetary Economics, 52, 381–419.
236. Vasicek, O. 1977. An equilibrium characterization of the term structure. Journal of Finance, 5, 177–188.
237. Vuong, Q.H. 1989. Likelihood ratio tests for model selection and non-nested hypotheses. Econometrica, 57, 307–333.
238. Wald, A. 1949. Note on the consistency of the maximum likelihood estimate. Annals of Mathematical Statistics, 20, 595–601.
239. Wand, M.P, and Jones, M.C. 1995. Kernel Smoothing. New York: Chapman and Hall.
240. Wang, Q., and Phillips, P.C.B. 2009. Asymptotic theory for local time density estimation and nonparametric cointegrating regression. Econometric Theory, 25, 710–738.
241. White, H. 1980. A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(817–838).
242. White, H. 1982. Maximum likelihood estimation of misspecified models. Econometrica, 50, 1–26.
243. White, H. 1984. Asymptotic Theory for Econometricians. Orlando: Academic Press.
244. White, H. 1989. Learning in artificial neural networks: A statistical perspective. Neural Computation, 1, 425–464.
245. White, H. 1994. Estimation, Inference and Specification Analysis. New York: Cambridge University Press.
246. Yatchew, A. 2003. Semiparametric Regression for the Applied Econometrician. New York: Cambridge University Press.
247. Zhao, Z. 2010. Density estimation for nonlinear parametric models with conditional heterskedasticity. Journal of Econometrics, 155, 71–82.