Should Dynamic Scoring Be Done with Heterogeneous Agent-Based Models? Challenging the Conventional Wisdom

47 Pages Posted: 21 Sep 2008

Date Written: September 19, 2008

Abstract

Traditionally, Dynamic Scoring calculations experiments are carried out using representative agent based macroeconomic models. Existing literature does not provide any objection to this approach. In this paper, I develop a heterogeneous agent model similar to the Saver-Spenders model of Mankiw (2000). But spenders in my model are merely credit constrained and not rule-of-thumb consumers. Both groups are intertemporal optimizers because of the existence of Internal Habit Persistence. Transition path of most of the macro and fiscal variables for various tax cuts under alternative financing scheme shows pattern which are significantly different and sometimes contrasting to the representative agent model. Dynamic scoring calculations reveal a downward bias of the representative agent model. Underestimation of the dynamic response could be as large as 45%. Finally, steady state results indicate smaller impact of contractionary policies on major fiscal variables such as net tax revenue and tax base. Over all, the paper argues that the need to use heterogeneous agent based model in dynamic fiscal calculations is not only desirable, but also essential.

Keywords: Savers-spenders model, rule-of thumb consumer, intertemporal optimizers, dynamic scoring, habit persistence, alternative financing, debt financing, fiscal policy

JEL Classification: E62, H2, H3, H6

Suggested Citation

Rahman, Muhammad, Should Dynamic Scoring Be Done with Heterogeneous Agent-Based Models? Challenging the Conventional Wisdom (September 19, 2008). CAEPR Working Paper No. 2008-023, Available at SSRN: https://ssrn.com/abstract=1270634 or http://dx.doi.org/10.2139/ssrn.1270634

Muhammad Rahman (Contact Author)

Indiana University ( email )

107 S Indiana Ave
100 South Woodlawn
Bloomington, IN 47405
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
120
Abstract Views
2,165
Rank
417,769
PlumX Metrics