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Un autre coup d'œil au modèle linéaire fondé sur le coefficient q de Tobin: une analyse empirique des dépenses agrégées d'investissement en capital des entreprises quand il y a des dépenses de maintenance .
Author(s) -
Kalyvitis Sarantis
Publication year - 2006
Publication title -
canadian journal of economics/revue canadienne d'économique
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.773
H-Index - 69
eISSN - 1540-5982
pISSN - 0008-4085
DOI - 10.1111/j.1540-5982.2006.00390.x
Subject(s) - economics , depreciation (economics) , fixed investment , investment (military) , capital (architecture) , tobin's q , capital expenditure , econometrics , statistic , aggregate supply , fixed capital , stock (firearms) , aggregate (composite) , monetary economics , capital formation , microeconomics , aggregate demand , finance , financial capital , profit (economics) , mathematics , law , archaeology , engineering , political science , mechanical engineering , monetary policy , statistics , politics , materials science , composite material , history
The paper revisits the empirical investment literature, which has established that aggregate business fixed investment is not found to be related linearly to marginal or average Tobin's q . The theoretical background is extended here by developing a supply‐side model where the depreciation rate of private capital is determined endogenously. The firm can either invest in ‘new’ capital, which adds directly to the existing capital stock at the presence of convex adjustment costs, or extend the durability of installed capital through maintenance expenditure, which affects its depreciation rate. The model shows that Tobin's q is then a positively related sufficient statistic for both components of aggregate capital expenditures. This central implication is tested empirically using aggregate time‐series survey data from Canada on ‘new’ investment and maintenance expenditures covering the period 1956–93. The estimated relationships produce significant and plausible parameter estimates for the structural parameters of the q model.