Multicollinearity and financial constraint in investment decisions: a Bayesian generalized ridge regression
This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student <italic>t</italic> distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.
Year of publication: |
2011
|
---|---|
Authors: | Kalatzis, Aquiles E.G. ; Bassetto, Camila F. ; Azzoni, Carlos R. |
Published in: |
Journal of Applied Statistics. - Taylor & Francis Journals, ISSN 0266-4763. - Vol. 38.2011, 2, p. 287-299
|
Publisher: |
Taylor & Francis Journals |
Saved in:
Online Resource
Saved in favorites
Similar items by person
-
Financial distress, financial constraint and investment decision: Evidence from Brazil
Bassetto, Camila F., (2011)
-
Financial distress, financial constraint and investment decision: Evidence from Brazil
Bassetto, Camila F., (2011)
-
Financial distress, financial constraint and investment decision: Evidence from Brazil
Bassetto, Camila F., (2011)
- More ...