Computation of Equilibria in OLG Models with Many Heterogeneous Households

Joint Program Reprint • Journal Article
Computation of Equilibria in OLG Models with Many Heterogeneous Households
Rausch, S., and T. Rutherford (2010)
Computational Economics, 36(2): 171-189

Reprint 2010-15 [Read Full Article]

Abstract/Summary:

This paper develops a decomposition algorithm by which a market economy with many households may be solved through the computation of equilibria for a sequence of representative agent economies. The paper examines local and global convergence properties of the sequential recalibration (SR) algorithm. The SR algorithm is then demonstrated to efficiently solve Auerbach–Kotlikoff OLG models with a large number of heterogeneous households. We approximate equilibria in OLG models by solving a sequence of related Ramsey optimal growth problems. This approach can provide improvements in both efficiency and robustness as compared with integrated complementarity-based solution methods.

© 2010 Springer

Citation:

Rausch, S., and T. Rutherford (2010): Computation of Equilibria in OLG Models with Many Heterogeneous Households. Computational Economics, 36(2): 171-189 (http://dx.doi.org/10.1007/s10614-010-9229-8)
  • Joint Program Reprint
  • Journal Article
Computation of Equilibria in OLG Models with Many Heterogeneous Households

Rausch, S., and T. Rutherford

2010-15
36(2): 171-189

Abstract/Summary: 

This paper develops a decomposition algorithm by which a market economy with many households may be solved through the computation of equilibria for a sequence of representative agent economies. The paper examines local and global convergence properties of the sequential recalibration (SR) algorithm. The SR algorithm is then demonstrated to efficiently solve Auerbach–Kotlikoff OLG models with a large number of heterogeneous households. We approximate equilibria in OLG models by solving a sequence of related Ramsey optimal growth problems. This approach can provide improvements in both efficiency and robustness as compared with integrated complementarity-based solution methods.

© 2010 Springer