Skip to main content
Log in

Adjustment costs and time-to-build in factor demand in the U.S. manufacturing industry

  • Modelling of Multivariate Economic Time Series
  • Published:
Empirical Economics Aims and scope Submit manuscript

Abstract

In order to explain cyclical behavior of factor demand, the static neoclassical model of the firm has been extended to include either adjustment costs (e.g. Lucas (1967)) or time-to-build considerations as in Kydland and Prescott (1982). This paper presents an intertemporal factor demand model which accounts for adjustment costs and gestation lags. The closed form solution of the model is a highly restricted vector ARMA-process that is estimated using quarterly data for the manufacturing industry in the U.S., 1960–1988.

The main conclusion is that both sources of dynamics of factor demand are identifiable and found to be empirically of importance.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Blanchard OJ, Kahn CM (1980) The solution of linear difference models under rational expectations. Econometrica 48:1305–11

    Google Scholar 

  • Boudjellaba H, Dufour J-M, Roy R (1992) Testing causality between two vectors in multivariate ARMA models. Journal of the American Statistical Association 87:1082–1090

    Google Scholar 

  • Engle RF, Hendry DF, J-F Richard (1983) Exogeneity. Econometrica 51:277–304

    Google Scholar 

  • Hosking JRM (1980) The multivariate portmanteau statistic. Journal of the American Statistical Association 75:602–608

    Google Scholar 

  • Jarque CM, Bera AK (1980) Efficient, tests for normality, homoscedasticity and serial independence of regression residuals. Economics Letters 6:255–259

    Google Scholar 

  • Johansen S (1991) The role of the constant term in cointegration analysis of nonstationary variables. Mimeo, Copenhagen

  • Johansen S, Juselius K (1990) Maximum likelihood estimation and inference on cointegration—with applications to the demand for money. Oxford Bulletin of Economics and Statistics 52:169–210

    Google Scholar 

  • Kodde DA, Palm FC, Pfann GA (1990) Asymptotic least-squares estimation — efficiency considerations and applications. Journal of Applied Econometrics 5:229–243

    Google Scholar 

  • Kydland FE, Prescott EC (1982) Time to build and aggregate fluctuations. Econometrica 50:1345–70

    Google Scholar 

  • Lippi M, Reichlin L (1990) Diffusion of technical change and the identification of the trend component in real GNP. Observatoire Français des Conjonctures Economiques, Paris, Document de travail no. 90-94

  • Liu LM, Hudak GB, Box GEP, Muller ME, Tiao GC (1986) The SCA Statistical System — Reference Manual for Forecasting and Time Series Analysis. Illinois: SCA-Press

    Google Scholar 

  • Lucas RE (1967) Adjustment costs and the theory of supply. Journal of Political Economy 75:321–34

    Google Scholar 

  • Mayer Th (1960) Plant and equipment lead times. The Journal of Business 33:127–132

    Google Scholar 

  • Nickell SJ (1985) Error correction, partial adjustment and all that: an expository note. Oxford Bulletin of Economics and Statistics 47:119–129

    Google Scholar 

  • Palm FC, Pfann GA (1990) Interrelated demand rational expectations models for two types of labour. Oxford Bulletin of Economics and Statistics 52:45–68

    Google Scholar 

  • Palm FC, Pfann GA (1991) Interrelation, structural changes, and cointegration in a model for manufacturing factor demand in the Netherlands. Recherches Economiques de Louvain 51:221–243

    Google Scholar 

  • Park JA (1984) Gestation lags with variable plans: An empirical study of aggregate investment. Ph.D. dissertation, Carnegie-Mellon University

  • Pfann GA (1990) Stochastic Adjustment Models of Labour Demand, Berlin Springer-Verlag

  • Pötscher BM (1989) Model selection under nonstationarity; autoregressive models and stochastic linear regressions models. The Annals of Statistics 17:1257–1274

    Google Scholar 

  • Rossi PE (1988) Comparison of dynamic factor demand models. In: Barnett WA, Berndt ER, White H (eds) Dynamic econometric modeling, proceedings of the third international symposium in economic theory & econometrics, Cambridge, Cambridge University Press 357–376

    Google Scholar 

  • Rouwenhorst KG (1991) Time to build and aggregate fluctuations. Journal of Monetary Economics 27:241–254

    Google Scholar 

  • Schwarz G (1978) Estimating the dimension of a model. Annals of Statistics 6:461–464

    Google Scholar 

  • Toda HY, Phillips PCB (1991) Vector autoregression and causality: A theoretical overview and simulation study. Cowles Foundation Discussion Paper no 1001, Yale University

Download references

Author information

Authors and Affiliations

Authors

Additional information

This research was sponsored by the Economics Research Foundation, which is part of the Netherlands, Organization for Scientific Research (NWO) and by the Royal Netherlands Academy of Arts and Sciences (K.N.A.W.).

Rights and permissions

Reprints and permissions

About this article

Cite this article

Palm, F.C., Peeters, H.M.M. & Pfann, G.A. Adjustment costs and time-to-build in factor demand in the U.S. manufacturing industry. Empirical Economics 18, 639–671 (1993). https://doi.org/10.1007/BF01205415

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01205415

Key Words

JEL Classification System-Numbers

Navigation