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When Is Sticky Information More Information?

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  • PIERRE‐DANIEL SARTE

Abstract

This paper uses sectoral data to study survey‐based balance indices designed to capture changes in the business cycle in real time. The empirical framework recognizes that when answering survey questions regarding their firm's output, respondents potentially rely on infrequently updated information. The analysis then suggests that their answers reflect notable information lags, on the order of 71/2 months on average. Moreover, information stickiness implies that noisy output fluctuations will be attenuated in survey answers and, consequently, helps explain why balance indices successfully track business cycles. Conversely, in an environment populated by fully informed identical firms, as in the standard RBC framework, for example, balance indices instead become degenerate. Finally, information regarding changes in aggregate output tends to be sectorally concentrated. The paper, therefore, illustrates how this feature of the data may be relevant for the construction of balance indices.

Suggested Citation

  • Pierre‐Daniel Sarte, 2014. "When Is Sticky Information More Information?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(7), pages 1345-1379, October.
    • Handle: RePEc:wly:jmoncb:v:46:y:2014:i:7:p:1345-1379
    DOI: 10.1111/jmcb.12143
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    References listed on IDEAS

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    1. Andrew T. Foerster & Pierre-Daniel G. Sarte & Mark W. Watson, 2011. "Sectoral versus Aggregate Shocks: A Structural Factor Analysis of Industrial Production," Journal of Political Economy, University of Chicago Press, vol. 119(1), pages 1-38.
    2. Acemoglu, Daron & Scott, Andrew, 1997. "Asymmetric business cycles: Theory and time-series evidence," Journal of Monetary Economics, Elsevier, vol. 40(3), pages 501-533, December.
    3. Ivaldi, Marc, 1992. "Survey Evidence on the Rationality of Expectations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(3), pages 225-241, July-Sept.
    4. David E. Runkle, 1998. "Revisionist history: how data revisions distort economic policy research," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 22(Fall), pages 3-12.
    5. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    6. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1295-1328.
    7. Gourio, Francois & Kashyap, Anil K, 2007. "Investment spikes: New facts and a general equilibrium exploration," Journal of Monetary Economics, Elsevier, vol. 54(Supplemen), pages 1-22, September.
    8. McQueen, Grant & Thorley, Steven, 1993. "Asymmetric business cycle turning points," Journal of Monetary Economics, Elsevier, vol. 31(3), pages 341-362, June.
    9. Jeong, Jinook & Maddala, G S, 1996. "Testing the Rationality of Survey Data Using the Weighted Double-Bootstrapped Method of Moments," The Review of Economics and Statistics, MIT Press, vol. 78(2), pages 296-302, May.
    10. Christopher D. Carroll, 2003. "Macroeconomic Expectations of Households and Professional Forecasters," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(1), pages 269-298.
    11. Horvath, Michael, 2000. "Sectoral shocks and aggregate fluctuations," Journal of Monetary Economics, Elsevier, vol. 45(1), pages 69-106, February.
    12. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    13. Pagan, Adrian, 1984. "Econometric Issues in the Analysis of Regressions with Generated Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 25(1), pages 221-247, February.
    14. Michael Horvath, 1998. "Cyclicality and Sectoral Linkages: Aggregate Fluctuations from Independent Sectoral Shocks," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 1(4), pages 781-808, October.
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    Cited by:

    1. Angeletos, G.-M. & Lian, C., 2016. "Incomplete Information in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 1065-1240, Elsevier.

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