Solving infinite horizon growth models with an environmental sector

David Kelly, Charles D. Kolstad

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

This paper concerns computational models in environmental economics and policy, particularly so-called integrated assessment models. For the most part, such models are simply extensions of standard neoclassical growth models, extended by including the environment and pollution generation. We review the structure of integrated assessment models, distinguishing between finite horizon and infinite horizon models, both deterministic and stochastic. We present a new solution algorithm for infinite horizon integrated assessment models, relying on a neural net approximation of the value function within an iterative version of the Bellman equation.

Original languageEnglish (US)
Pages (from-to)217-231
Number of pages15
JournalComputational Economics
Volume18
Issue number2
DOIs
StatePublished - Oct 1 2001

Fingerprint

Infinite horizon
Growth model
Integrated assessment model
Pollution
Neural networks
Economics
Computational model
Neural nets
Approximation
Value function
Finite horizon
Bellman equation
Neoclassical growth model
Environmental policy
Environmental economics

Keywords

  • Climate change
  • Dynamic programming
  • Integrated assessment
  • Neural networks
  • Numerical solution methods

ASJC Scopus subject areas

  • Economics, Econometrics and Finance (miscellaneous)
  • Computer Science Applications

Cite this

Solving infinite horizon growth models with an environmental sector. / Kelly, David; Kolstad, Charles D.

In: Computational Economics, Vol. 18, No. 2, 01.10.2001, p. 217-231.

Research output: Contribution to journalArticle

Kelly, David ; Kolstad, Charles D. / Solving infinite horizon growth models with an environmental sector. In: Computational Economics. 2001 ; Vol. 18, No. 2. pp. 217-231.
@article{60d0822e0a624cd99aaa79b59a30fe2b,
title = "Solving infinite horizon growth models with an environmental sector",
abstract = "This paper concerns computational models in environmental economics and policy, particularly so-called integrated assessment models. For the most part, such models are simply extensions of standard neoclassical growth models, extended by including the environment and pollution generation. We review the structure of integrated assessment models, distinguishing between finite horizon and infinite horizon models, both deterministic and stochastic. We present a new solution algorithm for infinite horizon integrated assessment models, relying on a neural net approximation of the value function within an iterative version of the Bellman equation.",
keywords = "Climate change, Dynamic programming, Integrated assessment, Neural networks, Numerical solution methods",
author = "David Kelly and Kolstad, {Charles D.}",
year = "2001",
month = "10",
day = "1",
doi = "10.1023/A:1021018417052",
language = "English (US)",
volume = "18",
pages = "217--231",
journal = "Computer Science in Economics and Management",
issn = "0921-2736",
publisher = "Springer Netherlands",
number = "2",

}

TY - JOUR

T1 - Solving infinite horizon growth models with an environmental sector

AU - Kelly, David

AU - Kolstad, Charles D.

PY - 2001/10/1

Y1 - 2001/10/1

N2 - This paper concerns computational models in environmental economics and policy, particularly so-called integrated assessment models. For the most part, such models are simply extensions of standard neoclassical growth models, extended by including the environment and pollution generation. We review the structure of integrated assessment models, distinguishing between finite horizon and infinite horizon models, both deterministic and stochastic. We present a new solution algorithm for infinite horizon integrated assessment models, relying on a neural net approximation of the value function within an iterative version of the Bellman equation.

AB - This paper concerns computational models in environmental economics and policy, particularly so-called integrated assessment models. For the most part, such models are simply extensions of standard neoclassical growth models, extended by including the environment and pollution generation. We review the structure of integrated assessment models, distinguishing between finite horizon and infinite horizon models, both deterministic and stochastic. We present a new solution algorithm for infinite horizon integrated assessment models, relying on a neural net approximation of the value function within an iterative version of the Bellman equation.

KW - Climate change

KW - Dynamic programming

KW - Integrated assessment

KW - Neural networks

KW - Numerical solution methods

UR - http://www.scopus.com/inward/record.url?scp=0035493948&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0035493948&partnerID=8YFLogxK

U2 - 10.1023/A:1021018417052

DO - 10.1023/A:1021018417052

M3 - Article

VL - 18

SP - 217

EP - 231

JO - Computer Science in Economics and Management

JF - Computer Science in Economics and Management

SN - 0921-2736

IS - 2

ER -