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Multi-equational linear quadratic adjustment cost models with rational expectations and cointegration. (English) Zbl 1200.62139

Summary: In this paper the econometric analysis of linear quadratic adjustment cost models with rational expectations and cointegrated variables is extended to the multi-equational SET-UP and the case of second-order adjustment costs. The proposed method is based on the idea of nesting the system of interrelated Euler equations stemming from the intertemporal optimization problem within a cointegrated Vector Equilibrium Correction Model representing the agent forecast tool. Contrary to previous practise a likelihood-based procedure can be set out without appealing to numerical optimization algorithms. Cointegration and generalized least squares techniques can be used to estimate and test the model.

MSC:

62P20 Applications of statistics to economics
62F03 Parametric hypothesis testing
62F10 Point estimation
90C90 Applications of mathematical programming
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
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[1] Binder, M.; Pesaran, M. H., Multivariate rational expectations models and macroeconomic modelling: a review and some new results, (Pesaran, M. H.; Wickens, M., Handbook of Applied Econometrics (1995), Blackwell: Blackwell Oxford), 139-187
[2] Campbell, J. Y.; Shiller, R. J., Cointegration and tests of present-value models, Journal of Political Economy, 95, 1052-1088 (1987)
[3] Dolado, J. J.; Galbraith, W.; Banerjee, A., Estimating intertemporal quadratic adjustment costs with integrated series, International Economic Review, 32, 919-936 (1991) · Zbl 0729.90835
[4] Eichenbaum, M. S., Rational expectations and the smoothing properties of inventories of finished goods, Journal of Monetary Economics, 14, 71-96 (1984)
[5] Engsted, T.; Haldrup, N., The linear quadratic adjustment cost model and the demand for labour, Journal of Applied Econometrics, 9, 145-159 (1994)
[6] Engsted, T.; Haldrup, N., Estimating the LQAC model with \(I(2)\) variables, Journal of Applied Econometrics, 14, 155-170 (1999)
[7] Fanelli, L., A new approach for estimating and testing the linear quadratic adjustment cost model under rational expectations and \(I(1)\) variables, Journal of Economic Dynamics and Control, 26, 117-139 (2002) · Zbl 0990.91047
[8] Gregory, A. W.; Pagan, A. R.; Smith, G. W., Estimating linear quadratic models with integrated processes, (Phillips, P. C.B., Models, Methods and Applications in Econometrics (1993), Basil Blackwell: Basil Blackwell Oxford), 220-239
[9] Hansen, L. P.; Sargent, T. J., Formulating and estimating dynamic linear expectations models, Journal of Economic Dynamics and Control, 2, 7-46 (1980)
[10] Hansen, L. P.; Sargent, T. J., Linear rational expectations models for dynamically interrelated variables, (Lucas, R. E.; Sargent, T. J., Rational Expectations and Econometric Practise (1981), University of Minnesota Press: University of Minnesota Press Minneapolis), 127-156
[11] Hansen, L. P.; Sargent, T. J., Exact linear rational expectations models: specification and estimation, (Hansen, L. P.; Sargent, T. J., Rational expectations Econometrics (1991), Westview Press: Westview Press Boulder), 45-75
[12] Hendry, D. F., Dynamic Econometrics (1995), Oxford University Press: Oxford University Press Oxford · Zbl 0897.62127
[13] Huang, T. S.; Shen, C. H., Seasonal cointegration and cross-equation restrictions on a forward-looking buffer stock model of money demand, Journal of Econometrics, 111, 11-46 (2002) · Zbl 1033.62101
[14] Johansen, S., Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models, Econometrica, 59, 1551-1580 (1991) · Zbl 0755.62087
[15] Johansen, S., Identifying restrictions of linear equations: with applications to simultaneous equations and cointegration, Journal of Econometrics, 69, 111-132 (1995) · Zbl 0832.62100
[16] Johansen, S., 1996. Likelihood-based inference in cointegrated Vector Auto-Regressive models. Oxford University Press (revised second printing), Oxford.; Johansen, S., 1996. Likelihood-based inference in cointegrated Vector Auto-Regressive models. Oxford University Press (revised second printing), Oxford.
[17] Johansen, S.; Swensen, A. R., Testing exact rational expectations in cointegrated vector autoregressive models, Journal of Econometrics, 93, 73-91 (1999) · Zbl 0951.62094
[18] Kennan, J., The estimation of partial adjustment models with rational expectations, Econometrica, 47, 1441-1455 (1979) · Zbl 0414.90036
[19] Kozicki, S.; Tinsley, P. A., Vector rational error correction, Journal of Economic Dynamics and Control, 23, 1299-1327 (1999) · Zbl 1016.91080
[20] Lütkepohl, H., Introduction to Multiple Time Series Analysis (1993), Springer: Springer New York · Zbl 0835.62075
[21] Nickell, S. J., An investigation of the determinants of manufacturing employment in the UK, Review of Economic Studies, 51, 529-557 (1984)
[22] Pesaran, M. H., Costly adjustment under rational expectations: a generalization, Review of Economics and Statistics, 73, 353-358 (1991)
[23] Pesaran, M. H.; Shin, Y., Long run structural modelling, Econometrics Reviews, 21, 49-87 (2002) · Zbl 1104.91061
[24] Price, S., Forward looking price setting in UK manufacturing, The Economic Journal, 102, 497-505 (1992)
[25] Sargent, T. J., A note on the maximum likelihood estimation of the rational expectations model of the term structure, Journal of Monetary Economics, 5, 133-143 (1979)
[26] Timmermann, A., Present value models with feedback: solution, stability, bubbles and some empirical evidence, Journal of Economic Dynamics and Control, 18, 1093-1119 (1994) · Zbl 0814.90010
[27] Tinsley, P. A., Rational error correction, Computational Economics, 19, 197-225 (2002) · Zbl 1005.91030
[28] Weissenberger, E., An intertemporal system of dynamic consumer demand functions, European Economic Review, 30, 859-891 (1986)
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