The New Palgrave Dictionary of Economics

2018 Edition
| Editors: Macmillan Publishers Ltd

Sims, Christopher Albert (Born 1942)

  • Marcel Boumans
Reference work entry
DOI: https://doi.org/10.1057/978-1-349-95189-5_2944

Abstract

Christopher Sims is one of the leaders in time-series econometrics and empirical macroeconomics and is well known for introducing the VAR approach to econometrics and macroeconomic modelling. Sims’ main contribution to empirical macroeconomics was to show how macro-econometric modeling should be revised so as to meet the Lucas Critique test. The VAR approach did not imply the abandoning of theory but only the involvement of theory that is ‘as light as possible.’ It shifted the focus from theoretical identification restrictions to identifying the main characteristics of the time series data, hence a shift of focus from theory to data.

Keywords

Bayesian econometrics Cowles Commission Cowles Foundation DSGE Dynamic stochastic general equilibrium Econometrics Economic policy Forecasting Frisch Granger causality Identification Liu Lucas Macroeconometrics Macroeconomic model Rational expectations Sargent Structural VAR Time series analysis Tinbergen VAR 

JEL Classifications

A11 B31 C11 C22 32 C5 E1 
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Bibliography

  1. Blaug, M., and H.R. Vane (eds.). 2003. Who’s who in economics, 4th ed. Cheltenham: Edward Elgar.Google Scholar
  2. Cooley, T.F., and S.F. LeRoy. 1985. Atheoretical macroeconometrics: A critique. Journal of Monetary Economics 16: 283–308.CrossRefGoogle Scholar
  3. Economic Sciences Prize Committee. 2011. Empirical macroeconomics. Stockholm: Royal Swedish Academy of Sciences. Available at: http://www.nobelprize.org/nobel_prizes/economics/laureates/2011/advanced-economicsciences2011.pdf.Google Scholar
  4. Granger, C.W.J. 1969. Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37: 424–438.CrossRefGoogle Scholar
  5. Haavelmo, T. 1944. The probability approach in econometrics. Econometrica 12 (supplement): iii–vi, 1–115.Google Scholar
  6. Hansen, L.P. 2004. An interview with Christopher A. Sims. Macroeconomic Dynamics 8: 273–294.CrossRefGoogle Scholar
  7. Hoover, K.D. 2006. The methodology of econometrics. In Palgrave handbook of econometrics, volume 1: Econometric theory, ed. T.C. Mills and K. Patterson. Basingstoke: Palgrave Macmillan.Google Scholar
  8. Koopmans, T. 1947. Measurement without theory. Review of Economic Statistics 29(3): 161–172.CrossRefGoogle Scholar
  9. Liu, T.-C. 1960. Underidentification, structural estimation, and forecasting. Econometrica 28: 855–865.CrossRefGoogle Scholar
  10. Lucas, R. 1976. Econometric policy evaluation: A critique. In The Phillips curve and labor markets, Carnegie-Rochester Conference Series on Public Policy, vol. 1, ed. K. Brunner and A.H. Meltzer. Amsterdam: North-Holland.Google Scholar
  11. Pagan, A. 1987. Three econometric methodologies: A critical appraisal. Journal of Economic Surveys 1(1): 3–24.CrossRefGoogle Scholar
  12. Qin, D. 2011. Rise of VAR modelling approach. Journal of Economic Surveys 25(1): 156–174.CrossRefGoogle Scholar
  13. Rolnick, A.J. 2007. Interview with Christopher Sims. The Region, 21(2).Google Scholar
  14. Tinbergen, J. 1939. Statistical testing of business cycle theories, Part II: Business cycles in the United States of America, 1919–1932. Geneva: League of Nations.Google Scholar
  15. Tinbergen, J. 1952. On the theory of economic policy. Amsterdam: North-Holland.Google Scholar
  16. Tinbergen, J. 1956. Economic policy: Principles and design. Amsterdam: North–Holland.Google Scholar
  17. Uhlig, H. 2005. What are the effects of monetary policy on output? Results from an agnostic identification procedure. Journal of Monetary Economics 52: 381–419.CrossRefGoogle Scholar
  18. Zellner, A. 1971. An introduction to Bayesian inference in econometrics. New York: Wiley.Google Scholar

Copyright information

© Macmillan Publishers Ltd. 2018

Authors and Affiliations

  • Marcel Boumans
    • 1
  1. 1.