Empirical Economics

, Volume 40, Issue 3, pp 581–600 | Cite as

A demand system for input factors when there are technological changes in production

  • Håvard Hungnes


In a system with n input factors there are n − 1 independent cost shares. An often-used approach in estimating factor demand systems is to (implicitly or explicitly) assume that there is a (independent) cointegrating relationship for each of the n − 1 independent cost shares. However, due to technological changes, there might not be as many cointegrating relationships as there are (independent) cost shares. This article presents a flexible demand system that allows for both factor neutral technological changes as well as technological changes that affect the relative use of the different factors. The empirical tests indicate that there are fewer cointegrating relationships than usually implied using conventional estimation approaches. This result is consistent with technological changes that affect the relative use of the different input factors. I argue that, since such unexplained technological changes are likely to affect input factor decisions, a demand system that allows for such changes should be preferred.


Factor demand Technological changes Growth rates 

JEL Classification

C32 C52 D24 


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  1. Abadir KM, Magnus JR (2005) Matrix algebra. Econometric exercises 1. Cambridge University Press, New YorkGoogle Scholar
  2. Allen C, Urga G (1999) Interrelated factor demands from dynamic cost functions: an application to the non-energy business sector. Economica 66: 403–413CrossRefGoogle Scholar
  3. Doornik JA (1998) Approximations to the asymptotic distribution of cointegration tests. J Econ Surveys 12:573–593. [Reprinted in McAleer M, Oxley L (1999) Practical issues in cointegration analysis. Blackwell Publishing, Oxford, pp 157–178]Google Scholar
  4. Doornik JA (2003) Asymptotic tables for cointegration tests based on the Gamma-distribution approximation. Accompanying note to Doornik (1998). Accessed 24 November 2009
  5. Harbo I, Johansen S, Nielsen B, Rahbek A (1998) Asymptotic inference on cointegrating rank in partial systems. J Bus Econ Stat 16: 388–399CrossRefGoogle Scholar
  6. Harvey AC, Marshall P (1991) Inter-substitution, technical change and the demand for energy in the UK economy. Appl Econ 23: 1077–1086CrossRefGoogle Scholar
  7. Hungnes H (2002) Restricting growth rates in cointegrated VAR models. Revised version of Discussion Paper No. 309, Statistics, Norway. Accessed 24 November 2009
  8. Hungnes H (2005) Identifying the deterministic components in GRaM for Ox Professional: user manual and documentation, Accessed 24 November 2009
  9. Hungnes H (2010) Identifying structural breaks in cointegrated VAR models. Oxford Bull Econ Stat. forthcomingGoogle Scholar
  10. Jin H, Jorgenson DW (2008) Econometric modelling of technical change. Mimeo dated August 13, 2008. (Available on Jorgensons homepage July 29, 2009 from Accessed 24 November 2009
  11. Johansen S (1996) Likelihood-based inference in cointegrated vector autoregressive models. Oxford University Press, OxfordGoogle Scholar
  12. Klump R, McAdam P, Willman A (2007) The long-term sucCESs of the neoclassical growth model. Oxford Rev Econ Pol 23: 94–114CrossRefGoogle Scholar
  13. Raknerud A, Skjerpen T, Swensen AR (2007) A linear demand system within a seemingly unrelated time series equation framework. Empir Econ 32: 105–124CrossRefGoogle Scholar
  14. Richard JF (1980) Models with several regimes and changes in exogeneity. Rev Econ Stud 47: 1–20CrossRefGoogle Scholar
  15. Saikkonen P, Lütkepohl H (1999) Local power of likelihood ratio tests for the cointegrating rank of a VAR process. Econom Theory 15: 50–78CrossRefGoogle Scholar
  16. Slade ME (1989) Modeling stochastic and cyclical components of technical change: an application of the Kalman filter. J Econom 41: 363–383CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.Research DepartmentStatistics NorwayOsloNorway

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