
The authors critically examine the Lucas tree model (LT-model) in asset pricing theory extended to include heterogeneous agents and multiple goods. Dividend streams of the trees are specified in terms of a particular good; different trees pay out indifferent goods. Equilibrium implications of the LT-model are weighted against those of the benchmark real assets model (RA-model) in financial equilibrium theory. As a conclusion, the LT-model has certain embedded structure that makes it significantly different from the RA-model, and the goal of the paper is to highlight this structure and the implications it may lead to. In particular, specializing households' preferences to be additively separable (over time) as well log-linear, the authors show that for a large set of initial endowments, the LT-model, even with potentially complete financial markets, admits a peculiar financial equilibrium in which all stocks but one are redundant. Also it is investigated why the LT-model is so much at variance with RA-model, and new results are uncovered on uniqueness of financial equilibria. Portfolio constraints possible in LT-models but not in RA-model are discussed.
Lucas tree model, Lucas Tree Model, Portfolio Constraints, Nonuniqueness of Equilibria, Peculiar Financial Equilibrium, Equilibrium Theory,, Lucas Tree Model, Equilibrium Theory, Peculiar Financial Equilibrium, Nonuniqueness of Equilibria, Portfolio Constraints,, equilibrium theory, portfolio constraints, peculiar financial equilibrium, Finance etc., non-uniqueness of equilibria
Lucas tree model, Lucas Tree Model, Portfolio Constraints, Nonuniqueness of Equilibria, Peculiar Financial Equilibrium, Equilibrium Theory,, Lucas Tree Model, Equilibrium Theory, Peculiar Financial Equilibrium, Nonuniqueness of Equilibria, Portfolio Constraints,, equilibrium theory, portfolio constraints, peculiar financial equilibrium, Finance etc., non-uniqueness of equilibria
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 33 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
