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The bond yield conundrum: alternative hypotheses and the state of the economy. (2010). Mahieu, Ronald ; Eijffinger, Sylvester ; Raes, Louis ; Eijffinger, Sylvester C. W., .
In: CEPR Discussion Papers.
RePEc:cpr:ceprdp:8063.

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  1. The contribution of US bond demand to the US bond yield conundrum of 2004–2007: An empirical investigation. (2013). Stewart, Chris ; Goda, Thomas ; Lysandrou, Photis.
    In: Journal of International Financial Markets, Institutions and Money.
    RePEc:eee:intfin:v:27:y:2013:i:c:p:113-136.

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  2. The contribution of us bond demand to the us bond yield conundrum of 2004 to 2007: an empirical investigation. (2011). Stewart, Chris ; Goda, Thomas ; Lysandrou, Photis.
    In: Documentos de Trabajo de Valor Público.
    RePEc:col:000122:010719.

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  1. 3. GDP growth volatility: The GDP growth data are available at quarterly frequency. We took these from Stock and Watson (2008). Growth rates are the log of the year-on-year diïerences. The volatility was obtained by taking the standard deviation over the past 24 months (quarterly frequency). Monthly observations were constructed by interpolation (cubic spline). 4. Volatility of outstanding consumer credit. Consumer credit data is available through the FRED database. The volatility was obtained by taking the standard deviation over the past 12 months (monthly frequency).
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  2. 5. Macroeconomic data on the GDP of China was taken from a study by Rajaguru and Abeysinghe (2004). The volatility was obtained by taking the standard deviation over the past 24 months (quarterly frequency) . Monthly observations were constructed by interpolation (cubic spline). 6. Volatility of loans by commercial banks. Consumer credit data is available through the FRED database. The volatility was obtained by taking the standard deviation over the past 12 months (monthly frequency). 7. Volatility of PCE inïation:: PCEinïation was obtained through the FRED database( Personal Consumption Expenditures: Chain-Type Price Index Less Food and Energy ). The volatility measure was obtained by taking the standard deviation of prices over the past 24 months (monthly frequency). 8. VIX index: Obtained through Datastream.
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  3. 9. Investor sentiment: Obtained from the website of Wurgler. The sentiment index and related issues are discussed in Baker and Wurgler (2007). 10. Volatility of net government spending. Net government spending was obtained through the FRED database. The volatility was obtained by taking the standard deviation over the past 24 months (quarterly frequency). Monthly observations were constructed by interpolation (cubic spline). 11. Volatility of expectations: The expectations are taken form the Michigan Survey. The volatility measure was obtained by taking the standard deviation of prices over the past 12 months (monthly frequency).
    Paper not yet in RePEc: Add citation now
  4. Ang, A., S. Dong, and M. Piazzesi (2005). No-arbitrage taylor rules. Proceedings. Ang, A. and M. Piazzesi (2003, May). A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables. Journal of Monetary Economics 50(4), 745â787.

  5. Backus, D. K. and J. H. Wright (2007). Cracking the conundrum. Brookings Papers on Economic Activity 38(2007-1), 293â329.

  6. Baker, M. and J. Wurgler (2007, Spring). Investor sentiment in the stock market. Journal of Economic Perspectives 21(2), 129â152.

  7. Bansal, R. and H. Zhou (2002, October). Term structure of interest rates with regime shifts. Journal of Finance 57(5), 1997â2043.

  8. Basistha, A. and A. Kurov (2008, December). Macroeconomic cycles and the stock marketâs reaction to monetary policy. Journal of Banking & Finance 32(12), 2606â2616.

  9. Bernanke, B. (2005). The global saving glut and the u.s. current account deïcit. Sandridge Lecture, Virginia Association of Economics, Richmond, Virginia.
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  10. Bernanke, B. S., V. R. Reinhart, and B. P. Sack (2004). Monetary policy alternatives at the zero bound: An empirical assessment. Brookings Papers on Economic Activity 35(2004-2), 1â100.

  11. Bernanke, B., J. Boivin, and P. S. Eliasz (2005, January). Measuring the effects of monetary policy: A factor-augmented vector autoregressive (favar) approach. The Quarterly Journal of Economics 120(1), 387â422.

  12. Boyd, J. H., J. Hu, and R. Jagannathan (2005, 04). The stock marketâs reaction to unemployment news: Why bad news is usually good for stocks. Journal of Finance 60(2), 649â672.

  13. Chauvet, M. and J. Piger (2008, January). A comparison of the real-time performance of business cycle dating methods. Journal of Business & Economic Statistics 26, 42â49.

  14. Cochrane, J. H. (2007). Commentary on âmacroeconomic implications of changes in the term premiumâ. Federal Reserve Bank of St.-Louis: Review (July), 271â282.
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  15. Eijïnger, S. C. and P. M. Geraats (2006, March). How transparent are central banks? European Journal of Political Economy 22(1), 1â21.

  16. Kim, D. H. (2007, December). Challenges in macro-ïnance modeling. BIS Working Papers 240, Bank for International Settlements.
    Paper not yet in RePEc: Add citation now
  17. Marcellino, M., C. A. Favero, and F. Neglia (2005). Principal components at work: the empirical analysis of monetary policy with large data sets. Journal of Applied Econometrics 20(5), 603â620.

  18. Rajaguru, G. and T. Abeysinghe (2004). Quarterly real gdp estimates for china and asean4 with a forecast evaluation. Journal of Forecasting 23(6), 431â447.

  19. Rudebusch, G. D., E. T. Swanson, and T. Wu (2006, December). The bond yield conundrum; from a macro-ïnance perspective. Monetary and Economic Studies 24(S1), 83â109.

  20. The recession probabilities we used, were taken from Chauvet and Piger (2008). The data are available on the website of Jeremy Piger. C Tables and ïgures Constant Loadings Matrix of factor loadings -156.87 0.37-6.81 11.80-3.59 16.34 629.34-1.45 30.99-49.94 11.83-62.10 520.05-1.23 22.10-33.89 1.64-49.57 -62.03 0.15-2.41 3.15 1.67 4.98 40.70-0.10 1.45-1.97 0.40-4.51
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  2. Bond Risk Premia and Gaussian Term Structure Models. (2014). Fontaine, Jean-Sebastien ; Feunou, Bruno.
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  5. Examining the bond premium puzzle with a DSGE model. (2008). Swanson, Eric ; Rudebusch, Glenn.
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  6. Analyzing the Term Structure of Interest Rates using the Dynamic Nelson-Siegel Model with Time-Varying Parameters. (2007). van der Wel, Michel ; Koopman, Siem Jan ; Max I. P. Mallee, .
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  11. The Affine Arbitrage-Free Class of: Nelson-Siegel Term Structure Models. (2007). Rudebusch, Glenn ; Diebold, Francis ; Christensen, Jens ; Jens H. E. Christensen, .
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  12. Global Yield Curve Dynamics and Interactions: A Dynamic Nelson-Siegel Approach. (2007). Yue, Vivian ; Diebold, Francis ; Li, Canlin.
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