Skip to main content

Copulas

  • Reference work entry
  • First Online:
The New Palgrave Dictionary of Economics
  • 79 Accesses

Abstract

Copulas are functional forms that parameterize the joint distribution of random variables based on their stated marginal distributions and a dependence parameter. The approach is based on Sklar’s theorem. Copulas provide a general method for modelling dependence between random variables that may exhibit asymmetric dependence, which is often inadequately captured by measures of linear dependence. Copulas are often generated by using mixtures and convex sums. Although a bivariate distribution is the most commonly encountered specification, higher dimensional joint distributions can also be generated.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 6,499.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 8,499.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Bibliography

  • Cherubini, U., E. Luciano, and W. Vecchiato. 2004. Copula methods in finance. New York: John Wiley.

    Book  Google Scholar 

  • Joe, H. 1997. Multivariate models and dependence concepts. London: Chapman and Hall.

    Book  Google Scholar 

  • Nelsen, R. 1999. An introduction to copulas. New York: Springer.

    Book  Google Scholar 

  • Patton, A. 2006. Estimation of multivariate models for time series of possibly different lengths. Journal of Applied Econometrics 21: 147–173.

    Article  Google Scholar 

  • Sklar, A. 1973. Random variables, joint distributions, and copulas. Kybernetica 9: 449–460.

    Google Scholar 

  • Sklar, A. 1996. Random variables, distribution functions, and copulas – a personal look backward and forward. In Distributions with fixed marginals and related topics, ed. L. Ruschendorf, B. Schweizer, and M. Taylor. Hayward: Institute of Mathematic Statistics.

    Google Scholar 

  • Smith, M. 2003. Modeling selectivity using Archimedean copulas. Econometrics Journal 6: 99–123.

    Article  Google Scholar 

  • Zimmer, D., and P. Trivedi. 2006. Using trivariate copulas to model sample selection and treatment effects: Application to family health care demand. Journal of Business and Economic Statistics 24: 63–76.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Copyright information

© 2018 Macmillan Publishers Ltd.

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Trivedi, P.K. (2018). Copulas. In: The New Palgrave Dictionary of Economics. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-349-95189-5_1960

Download citation

Publish with us

Policies and ethics