Complex Systems in Finance and Econometrics

2011 Edition
| Editors: Robert A. Meyers (Editor-in-Chief)

Macroeconomics, Non-linear Time Series in

  • James Morley
Reference work entry
DOI: https://doi.org/10.1007/978-1-4419-7701-4_30

Article Outline

Glossary

Definition of the Subject

Introduction

Types of Nonlinear Models

Business Cycle Asymmetry

Future Directions

Bibliography

Keywords

Covariance Income Autocorrelation Nash Volatility 
This is a preview of subscription content, log in to check access

Bibliography

Primary Literature

  1. 1.
    Acemoglu D, Scott A (1997) Asymmetric business cycles: Theory and time-series evidence. J Monet Econ 40:501–533Google Scholar
  2. 2.
    Balke NS, Wynne MA (1996) Are deep recessions followed by strong recoveries? Results for the G-7 countries. Appl Econ 28:889–897Google Scholar
  3. 3.
    Ball L, Mankiw NG (1995) Relative price changes as aggregate supply shocks. Q J Econ 110:161–193Google Scholar
  4. 4.
    Bansal R, Yaron A (2004) Risks for the long run: A potential resolution of asset pricing puzzles. J Financ 59:1481–1509Google Scholar
  5. 5.
    Barlevy G (2005) The cost of business cycles and the benefits of stabilization. Econ Perspect 29:32–49Google Scholar
  6. 6.
    Beaudry P, Koop G (1993) Do recessions permanently change output? J Monet Econ 31:149–163Google Scholar
  7. 7.
    Beveridge S, Nelson CR (1981) A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the business cycle. J Monet Econ 7:151–174Google Scholar
  8. 8.
    Boldin MD (1996) A check on the robustness of Hamilton’s Markov switching model approach to the economic analysis of the business cycle. Stud Nonlinear Dyn Econom 1:35–46Google Scholar
  9. 9.
    Breunig R, Najarian S, Pagan A (2003) Specification testing of Markov-switching models. Oxf Bull Econ Stat 65:703–725Google Scholar
  10. 10.
    Brock WA, Dechert WD, Scheinkman JA (1996) A test of independence based on the correlation dimension. Econom Rev 15:197–235Google Scholar
  11. 11.
    Brock WA, Sayers C (1988) Is the business cycle characterized by deterministic chaos? J Monet Econ 22:71–90Google Scholar
  12. 12.
    Bry G, Boschan C (1971) Cyclical analysis of time series: Selected procedures and computer programs. NBER, New YorkGoogle Scholar
  13. 13.
    Burns AF, Mitchell WA (1946) Measuring Business Cycles. NBER, New YorkGoogle Scholar
  14. 14.
    Camacho M (2005) Markov-switching stochastic trends and economic fluctuations. J Econ Dyn Control 29:135–158Google Scholar
  15. 15.
    Carrasco M, Hu L, Ploberger W (2007) Optimal test for Markov switching. Working PaperGoogle Scholar
  16. 16.
    Chalkley M, Lee IH (1998) Asymmetric business cycles. Rev Econ Dyn 1:623–645Google Scholar
  17. 17.
    Chan KS (1991) Percentage points of likelihood ratio tests for threshold autoregression. J Royal Stat Soc Ser B 53:691–696Google Scholar
  18. 18.
    Chan KS, Tong H (1986) On estimating thresholds in autoregressive models. J Tim Ser Analysis 7:179–190Google Scholar
  19. 19.
    Chauvet M (1998) An econometric characterization of business cycle dynamics with factor structure and regime switches. Int Econ Rev 39:969–996Google Scholar
  20. 20.
    Chauvet M, Potter S (2001) Recent changes in the US business cycle. Manch Sch 69:481–508Google Scholar
  21. 21.
    Chib S, Nardari F, Shephard N (2002) Markov chain Monte Carlo methods for stochastic volatility models. J Econom 108:281–316Google Scholar
  22. 22.
    Clarida RH, Taylor MP (2003) Nonlinear permanent-temporary decompositions in macroeconomics and finance. Econ J 113:C125–C139Google Scholar
  23. 23.
    Clements MP, Krolzig HM (1998) A comparison of the forecast performance of Markov-switching and threshold autoregressive models of US GNP. Econ J 1:C47–C75Google Scholar
  24. 24.
    Clements MP, Krolzig HM (2003). Business cycle asymmetries: Characterization and testing based on Markov-switching autoregressions. J Bus Econ Stat 21:196–211Google Scholar
  25. 25.
    Clements MP, Krolzig HM (2004) Can regime-switching models reproduce the business cycle features of US aggregate consumption, investment and output? Int J Financ Econ 9:1–14Google Scholar
  26. 26.
    Cogley T, Sargent TJ (2001) Evolving post-World War II US inflation dynamics. In: Bernanke BS, Rogoff K (eds) NBER Macroeconomics Annual 2001. MIT Press, Cambridge, pp 331–373Google Scholar
  27. 27.
    Cogley T, Sargent TJ (2005) Drift and volatilities: Monetary policies and outcomes in the post WW II US. Rev Econ Dyn 8:262–302Google Scholar
  28. 28.
    Cohen D (2000) A quantitative defense of stabilization policy. Federal Reserve Board Finance and Economics Discussion Series. Paper 2000-34Google Scholar
  29. 29.
    Cooley TF, Prescott EC (1976) Estimation in the presence of stochastic parameter variation. Econometrica 44:167–184Google Scholar
  30. 30.
    Cooper R (1994) Equilibrium selection in imperfectly competitive economies with multiple equilibria. Econ J 104:1106–1122Google Scholar
  31. 31.
    Cover JP (1992) Asymmetric effects of positive and negative money-supply shocks. Q J Econ 107:1261–1282Google Scholar
  32. 32.
    Davies RB (1977) Hypothesis testing when a nuisance parameter is present only under the alternative. Biometrika 64:247–254Google Scholar
  33. 33.
    Davis SJ, Haltiwanger J (2001) Sectoral job creation and destruction responses to oil price changes. J Monet Econ 48:468–512Google Scholar
  34. 34.
    DeJong DN, Liesenfeld R, Richard JF (2005) A nonlinear forecasting model of GDP growth. Rev Econ Stat 87:697–708Google Scholar
  35. 35.
    DeLong JB, Summers LH (1986) Are business cycles symmetrical? In: Gordon RJ (ed) The American Business Cycle. University of Chicago Press, Chicago, pp 166–179Google Scholar
  36. 36.
    DeLong B, Summers L (1988) How does macroeconomic policy affect output? Brook Papers Econ Activity 2:433–480Google Scholar
  37. 37.
    Diebold FX, Chen C (1996) Testing structural stability with endogenous breakpoint: A size comparison of analytic and bootstrap procedures. J Econ 70:221–241Google Scholar
  38. 38.
    Diebold FX, Rudebusch GD (1996) Measuring business cycles: A modern perspective. Rev Econ Stat 78:67–77Google Scholar
  39. 39.
    Diebold FX, Lee JH, Weinbach G (1994) Regime switching with time-varying transition probabilities. In: Hargreaves C (ed) Nonstationary Time Series Analysis and Cointegration. Oxford University Press, Oxford, pp 283–302Google Scholar
  40. 40.
    Durland JM, McCurdy TH (1994) Duration-dependent transitions in a Markov model of US GNP growth. J Bus Econ Stat 12:279–288Google Scholar
  41. 41.
    Durlauf SN (1991) Multiple equilibria and persistence in aggregate fluctuations. Am Econ Rev Pap Proc 81:70–74Google Scholar
  42. 42.
    Elliott G, Müller U (2006) Efficient tests for general persistent time variation in regression coefficients. Rev Econ Stud 73:907–940Google Scholar
  43. 43.
    Elwood SK (1998) Is the persistence of shocks to output asymmetric? J Monet Econ 41:411–426Google Scholar
  44. 44.
    Enders W, Falk BL, Siklos P (2007) A threshold model of real US GDP and the problem of constructing confidence intervals in TAR models. Stud Nonlinear Dyn Econ 11(3):4Google Scholar
  45. 45.
    Engel J, Haugh D, Pagan A (2005) Some methods for assessing the need for non-linear models in business cycles. Int J Forecast 21:651–662Google Scholar
  46. 46.
    Engle RF (1982) Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation. Econometrica 50:987–1007Google Scholar
  47. 47.
    Fernández-Villaverde J, Rubio-Ramírez JF (2007) Estimating macroeconomic models: A likelihood approach. Rev Econ Stud 54:1059–1087Google Scholar
  48. 48.
    Filardo AJ (1994) Business-cycle phases and their transitional dynamics. J Bus Econ Stat 12:299–308Google Scholar
  49. 49.
    French MW, Sichel DE (1993) Cyclical patterns in the variance of economic activity. J Bus Econ Stat 11:113–119Google Scholar
  50. 50.
    Friedman M (1964) Monetary Studies of the National Bureau, the National Bureau Enters Its 45th Year. 44th Annual Report. NBER, New York, pp 7–25; Reprinted in: Friedman M (1969) The Optimum Quantity of Money and Other Essays. Aldine, Chicago, pp 261–284Google Scholar
  51. 51.
    Friedman M (1993) The “plucking model” of business fluctuations revisited. Econ Inq 31:171–177Google Scholar
  52. 52.
    Galvão AB (2002) Can non-linear time series models generate US business cycle asymmetric shape? Econ Lett 77:187–194Google Scholar
  53. 53.
    Garcia R (1998) Asymptotic null distribution of the likelihood ratio test in Markov switching models. Int Econ Rev 39:763–788Google Scholar
  54. 54.
    Garcia R, Schaller H (2002) Are the effects of interest rate changes asymmetric? Econ Inq 40:102–119Google Scholar
  55. 55.
    Gilchrist S, Williams JC (2000) Putty-clay and investment: A business cycle analysis. J Political Econ 108:928–960Google Scholar
  56. 56.
    Goodwin TH (1993) Business-cycle analysis with a Markov-switching model. J Bus Econ Stat 11:331–339Google Scholar
  57. 57.
    Granger CWJ, Andersen AP (1978) An Introduction to Bilinear Time Series Models. Vandenhoek and Ruprecht, GöttingenGoogle Scholar
  58. 58.
    Granger CWJ, Teräsvirta T (1993) Modelling Nonlinear Economic Relationships. Oxford University Press, OxfordGoogle Scholar
  59. 59.
    Hamilton JD (1989) A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 57:357–384Google Scholar
  60. 60.
    Hamilton JD (2005) What’s real about the business cycle? Fed Reserve Bank St. Louis Rev 87:435–452Google Scholar
  61. 61.
    Hansen BE (1992) The likelihood ratio test under nonstandard conditions: Testing the Markov switching model of GNP. J Appl Econ 7:S61–S82Google Scholar
  62. 62.
    Hansen BE (1996) Inference when a nuisance parameter is not identified under the null hypothesis. Econometrica 64:413–430Google Scholar
  63. 63.
    Hansen BE (1997) Inference in TAR models. Stud Nonlinear Dyn Econom 2:1–14Google Scholar
  64. 64.
    Hansen GD, Prescott EC (2005) Capacity constraints, asymmetries, and the business cycle. Rev Econ Dyn 8:850–865Google Scholar
  65. 65.
    Harding D, Pagan AR (2002) Dissecting the cycle: A methodological investigation. J Monet Econ 49:365–381Google Scholar
  66. 66.
    Harding D, Pagan AR (2003) A Comparison of Two Business Cycle Dating Methods. J Econ Dyn Control 27:1681–1690Google Scholar
  67. 67.
    Harding D, Pagan AR (2005) A suggested framework for classifying the modes of cycle research. J Appl Econom 20:151–159Google Scholar
  68. 68.
    Hess GD, Iwata S (1997) Asymmetric persistence in GDP? A deeper look at depth. J Monet Econ 40:535–554Google Scholar
  69. 69.
    Hess GD, Iwata S (1997) Measuring and comparing business-cycle features. J Bus Econ Stat 15:432–444Google Scholar
  70. 70.
    Howitt P, McAfee RP (1992) Animal spirits. Am Econ Rev 82:493–507Google Scholar
  71. 71.
    Hristova D (2005) Maximum likelihood estimation of a unit root bilinear model with an application to prices. Stud Nonlinear Dyn Econom 9(1):4Google Scholar
  72. 72.
    Keynes JM (1936) The General Theory of Employment, Interest, and Money. Macmillan, LondonGoogle Scholar
  73. 73.
    Kiefer NM (1978) Discrete parameter variation: Efficient estimation of a switching regression model. Econometrica 46:413–430Google Scholar
  74. 74.
    Kim CJ (1994) Dynamic linear models with Markov switching. J Econom 60:1–22Google Scholar
  75. 75.
    Kim CJ, Murray CJ (2002) Permanent and transitory components of recessions. Empir Econ 27:163–183Google Scholar
  76. 76.
    Kim CJ, Nelson CR (1998) Business cycle turning points, a new coincident index, and tests of duration dependence based on a dynamic factor model with regime switching. Rev Econ Stat 80:188–201Google Scholar
  77. 77.
    Kim CJ, Nelson CR (1999) State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications. MIT Press, CambridgeGoogle Scholar
  78. 78.
    Kim CJ, Nelson CR (1999) Has the US economy become more stable? A Bayesian approach based on a Markov-switching model of the business cycle. Rev Econ Stat 81:608–616Google Scholar
  79. 79.
    Kim CJ, Nelson CR (1999) Friedman’s plucking model of business fluctuations: Tests and estimates of permanent and transitory components. J Money Credit Bank 31:317–34Google Scholar
  80. 80.
    Kim CJ, Nelson CR (2001) A Bayesian approach to testing for Markov-switching in univariate and dynamic factor models. Int Econ Rev 42:989–1013Google Scholar
  81. 81.
    Kim CJ, Piger JM (2002) Common stochastic trends, common cycles, and asymmetry in economic fluctuations. J Monet Econ 49:1181–1211Google Scholar
  82. 82.
    Kim CJ, Nelson CR, Piger J (2004) The less-volatile US economy: A Bayesian investigation of timing, breadth, and potential explanations. J Bus Econ Stat 22:80–93Google Scholar
  83. 83.
    Kim CJ, Morley J, Piger J (2005) Nonlinearity and the permanent effects of recessions. J Appl Econom 20:291–309Google Scholar
  84. 84.
    Kim CJ, Piger J, Startz R (2007) The dynamic relationship between permanent and transitory components of US business cycles. J Money Credit Bank 39:187–204Google Scholar
  85. 85.
    Kim CJ, Piger J, Startz R (2008) Estimation of Markov regime-switching regression models with endogenous switching. J Econom 143:263–273Google Scholar
  86. 86.
    Kim CJ, Morley J, Piger J (2008) Bayesian Counterfactual Analysis of the Sources of the Great Moderation. J Appl Econom 23:173–191Google Scholar
  87. 87.
    Kim M-J, Yoo J-S (1995) New index of coincident indicators: A multivariate Markov switching factor model approach. J Monet Econ 36:607–630Google Scholar
  88. 88.
    Kim S, Shephard N, Chib S (1998) Stochastic volatility: Likelihood inference and comparison with ARCH models. Rev Econ Stud 65:361–393Google Scholar
  89. 89.
    King TB (2006) Dynamic equilibrium models with time-varying structural parameters. Working PaperGoogle Scholar
  90. 90.
    King TB, Morley J (2007) Maximum likelihood estimation of nonlinear, non-Gaussian state-space models using a multistage adaptive particle filter. Working PaperGoogle Scholar
  91. 91.
    Koop G, Potter S (2003) Bayesian analysis of endogenous delay threshold models. J Bus Econ Stat 21:93–103Google Scholar
  92. 92.
    Koop G, Potter S (2006) The vector floor and ceiling model. In: Milas C, Rothman P, Van Dijk D (eds) Nonlinear Time Series Analysis of Business Cycles. Elsevier, Amsterdam, pp 97–131Google Scholar
  93. 93.
    Koop G, Potter S (2007) Estimation and forecasting in models with multiple breaks. Rev Econ Stud 74:763–789Google Scholar
  94. 94.
    Koop G, Pesaran MH, Potter S (1996) Impulse response analysis in nonlinear multivariate models. J Econometrics 74:119–148Google Scholar
  95. 95.
    Korenok O, Mizrach B, Radchenko S (2009) A note on demand and supply factors in manufacturing output asymmetries. Macroecon Dyn (forthcoming)Google Scholar
  96. 96.
    Lam PS (1990) The Hamilton model with a general autoregressive component: Estimation and comparison with other models of economic time series. J Monet Econ 26:409–432Google Scholar
  97. 97.
    Leamer EE, Potter SM (2004) A nonlinear model of the business cycle. Working PaperGoogle Scholar
  98. 98.
    Leyton AP, Smith D (2000) A further note of the three phases of the US business cycle. Appl Econ 32:1133–1143Google Scholar
  99. 99.
    Lo MC, Piger J (2005) Is the response of output to monetary policy asymmetric? Evidence from a regime-switching coefficients model. J Money Credit Bank 37:865–887Google Scholar
  100. 100.
    Lucas RE (1972) Econometric testing of the natural rate hypothesis. In: Eckstein O (ed) Econometrics of Price Determination. US Federal Reserve Board, Washington DC, pp 50–59Google Scholar
  101. 101.
    Lucas RE (1976) Econometric policy evaluation: A critique. In: Brunner K, Meltzer A (eds) The Phillips Curve and Labor Markets, vol 1. Carnegie-Rochester Ser Public Policy, pp 19–46Google Scholar
  102. 102.
    Lucas RE (1987) Models of Business Cycles. Basil Blackwell, OxfordGoogle Scholar
  103. 103.
    Lucas RE (2003) Macroeconomic Priorities. Am Econ Rev 93:1–14Google Scholar
  104. 104.
    Ma J (2007) Consumption persistence and the equity premium puzzle: New evidence based on improved inference. Working paperGoogle Scholar
  105. 105.
    MacKinnon J (2002) Bootstrap inference in econometrics. Can J Econ 35:615–645Google Scholar
  106. 106.
    MacKinnon J (2006) Bootstrap methods in econometrics. Econ Rec 82:S2–S18Google Scholar
  107. 107.
    McConnell MM, Quiros GP (2000) Output fluctuations in the United States: What has changed since the early 1980s? Am Econ Rev 90:1464–1476Google Scholar
  108. 108.
    McQueen G, Thorley SR (1993) Asymmetric business cycle turning points. J Monet Econ 31:341–362Google Scholar
  109. 109.
    Mitchell WA (1927) Business Cycles: The Problem and Its Setting. NBER, New YorkGoogle Scholar
  110. 110.
    Mizon GE, Richard JF (1986) The encompassing principle and its application to non-nested hypotheses. Econometrica 54:657–678Google Scholar
  111. 111.
    Morley J, Piger J (2006) The Importance of Nonlinearity in Reproducing Business Cycle Features. In: Milas C, Rothman P, Van Dijk D (eds) Nonlinear Time Series Analysis of Business Cycles. Elsevier, Amsterdam, pp 75–95Google Scholar
  112. 112.
    Morley J, Piger J (2008) Trend/cycle decomposition of regime-switching processes. J Econom (forthcoming)Google Scholar
  113. 113.
    Morley J, Piger J (2008) The asymmetric business cycle. Working PaperGoogle Scholar
  114. 114.
    Morley JC, Nelson CR, Zivot E (2003) Why are the Beveridge-Nelson and unobserved-components decompositions of GDP so different? Rev Econ Stat 85:235–243Google Scholar
  115. 115.
    Neftçi SH (1984) Are economic time series asymmetric over the business cycle? J Political Econ 92:307–328Google Scholar
  116. 116.
    Niemira MP, Klein PA (1994) Forecasting Financial and Economic Cycles. Wiley, New YorkGoogle Scholar
  117. 117.
    Öcal N, Osborn DR (2000) Business cycle non-linearities in UK consumption and production. J Appl Econom 15:27–44Google Scholar
  118. 118.
    Owyang MT, Ramey G (2004) Regime switching and monetary policy measurement. J Monet Econ 51:1577–1198Google Scholar
  119. 119.
    Peel D, Davidson J (1998) A non-linear error correction mechanism based on the bilinear model. Econ Lett 58:165–170Google Scholar
  120. 120.
    Pesaran MH, Potter SM (1997) A floor and ceiling model of US output. J Econ Dyn Control 21:661–695Google Scholar
  121. 121.
    Potter SM (1995) A nonlinear approach to US GNP. J Appl Econ 10:109–125Google Scholar
  122. 122.
    Potter SM (2000) A nonlinear model of the business cycle. Stud Nonlinear Dyn Econom 4:85–93Google Scholar
  123. 123.
    Primiceri GE (2005) Time varying structural vector autogressions and monetary policy. Rev Econ Stud 72:821–852Google Scholar
  124. 124.
    Ramsey JB, Rothman P (1996) Time irreversibility and business cycle asymmetry. J Money Credit Bank 28:1–21Google Scholar
  125. 125.
    Ravn MO, Sola M (1995) Stylized facts and regime changes: Are prices procyclical? J Monet Econ 36:497–526Google Scholar
  126. 126.
    Rotemberg JJ, Woodford M (1996) Real-business-cycle Models and the forecastable movements in output, hours, and consumption. Am Econ Rev 86:71–89Google Scholar
  127. 127.
    Rothman P (1991) Further Evidence on the Asymmetric Behavior of Unemployment Rates Over the Business Cycle. J Macroeconom 13:291–298Google Scholar
  128. 128.
    Rothman P (1998) Forecasting asymmetric unemployment rates. Rev Econ Stat 80:164–168Google Scholar
  129. 129.
    Rothman P (2008) Reconsideration of Markov chain evidence on unemployment rate asymmetry. Stud Nonlinear Dyn Econo 12(3):6Google Scholar
  130. 130.
    Rothman P, van Dijk D, Franses PH (2001) A multivariate STAR analysis of the relationship between money and output. Macroeconom Dyn 5:506–532Google Scholar
  131. 131.
    Schumpeter J (1942) Capitalism, socialism, and democracy. Harper, New YorkGoogle Scholar
  132. 132.
    Sensier M, van Dijk D (2004) Testing for volatility changes in US macroeconomic time series. Rev Econ Stat 86:833–839Google Scholar
  133. 133.
    Sichel DE (1993) Business cycle asymmetry: A deeper look. Econ Inq 31:224–236Google Scholar
  134. 134.
    Sichel DE (1994) Inventories and the three phases of the business cycle. J Bus Econ Stat 12:269–277Google Scholar
  135. 135.
    Sims CA (2001) Comment on Sargent and Cogley’s: Evolving Post-World War II US Inflation Dynamics. In: Bernanke BS, Rogoff K (eds) NBER Macroeconomics Annual 2001. MIT Press, Cambridge, pp 373–379Google Scholar
  136. 136.
    Sims CA, Zha T (2006) Were there regime switches in US monetary policy? Am Econ Rev 96:54–81Google Scholar
  137. 137.
    Sinclair TM (2008) Asymmetry in the business cycle: Friedman’s plucking model with correlated innovations. Working PaperGoogle Scholar
  138. 138.
    Stock JH, Watson MW (2002) Has the business cycle changed and why? In: Gertler M, Rogoff K (eds) NBER Macroeconomics Annual 2002. MIT Press, Cambridge, pp 159–218Google Scholar
  139. 139.
    Subba Rao T, Gabr MM (1984) An Introduction to Bispectral Analysis and Bilinear Time Series Models. Lecture Notes in Statistics, vol 24. Springer, New YorkGoogle Scholar
  140. 140.
    Teräsvirta T (1994) Specification, estimation, and evaluation of smooth transition autoregressive models. J Am Stat Assoc 89:208–218Google Scholar
  141. 141.
    Teräsvirta T (1995) Modeling nonlinearity in US Gross National Product 1889–1987. Empir Econ 20:577–598Google Scholar
  142. 142.
    Teräsvirta T (1998) Modelling economic relationships with smooth transition regressions. In: Ullah A, Giles DEA (eds) Handbook of Applied Economic Statistics. Marcel Dekker, New York, pp 507–552Google Scholar
  143. 143.
    Teräsvirta T, Anderson HM (1992) Characterizing nonlinearities in business cycles using smooth transition autoregressive models. J Appl Econom 7:S119–S136Google Scholar
  144. 144.
    Tiao GC, Tsay RS (1994) Some advances in non-linear and adaptive modeling in time- series analysis. J Forecast 13:109–131Google Scholar
  145. 145.
    Tong H (1978) On a threshold model. In: Chen CH (ed) Pattern Recognition and Signal Processing. Sijhoff and Noordhoff, Amsterdam, pp 575–586Google Scholar
  146. 146.
    Tsay RS (1989) Testing and modeling threshold autoregressive processes. J Am Stat Assoc 84:231–240Google Scholar
  147. 147.
    Tsay RS (1998) Testing and modeling multivariate threshold processes. J Am Stat Assoc 93:1188–1202Google Scholar
  148. 148.
    van Dijk D, Franses PH (1999) Modeling multiple regimes in the business cycle. Macroeconom Dyn 3:311–340Google Scholar
  149. 149.
    van Dijk D, Franses PH (2003) Selecting a nonlinear time series model using weighted tests of equal forecast accuracy. Oxf Bull Econ Stat 65:727–744Google Scholar
  150. 150.
    Wynne MA, Balke NS (1992) Are deep recessions followed by strong recoveries? Econ Lett 39:183–189Google Scholar
  151. 151.
    Yellen JL, Akerlof GA (2006) Stabilization policy: A reconsideration. Econ Inq, pp 44:1–22Google Scholar

Books and Reviews

  1. 152.
    Davidson R, MacKinnon JG (2004) Econometric Theory and Methods. Oxford University Press, OxfordGoogle Scholar
  2. 153.
    Diebold FX (1998) The past, present, and future of macroeconomic forecasting. J Econ Perspectives 12:175–192Google Scholar
  3. 154.
    Engle R (2001) GARCH 101: The use of ARCH/GARCH models in applied econometrics. J Econc Perspectives 15:157–168Google Scholar
  4. 155.
    Franses PH (1998) Time Series Models for Business and Economic Forecasting. Cambridge University Press, CambridgeGoogle Scholar
  5. 156.
    Hamilton JD (1994) State-space models. In: Engle RF, McFadden DL (eds) Handbook of Econometrics, vol 4. Elsevier, Amsterdam, pp 041–3080Google Scholar
  6. 157.
    Hamilton JD (1994) Time Series Analysis. Princeton University Press, PrincetonGoogle Scholar
  7. 158.
    Koop G (2003) Bayesian Econometrics. Wiley, ChichesterGoogle Scholar
  8. 159.
    Teräsvirta T, Tjøstheim D, Granger CWJ (1994) Aspects of modeling nonlinear time series. In: Engle RF, McFadden DL (eds) Handbook of Econometrics, vol 4. Elsevier, Amsterdam, pp 2919–2957Google Scholar
  9. 160.
    Tsay RS (2005) Analysis of Financial Time Series. Wiley, HobokenGoogle Scholar

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • James Morley
    • 1
  1. 1.Washington UniversitySt. LouisUSA