English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

General equilibrium macroeconomic models are a core tool used by policymakersto understand a nation's economy. They represent the economy as a collection offorward-looking actors whose behaviours combine, possibly with stochasticeffects, to determine global variables (such as prices) in a dynamicequilibrium. However, standard semi-analytical techniques for solving thesemodels make it difficult to include the important effects of heterogeneouseconomic actors. The COVID-19 pandemic has further highlighted the importanceof heterogeneity, for example in age and sector of employment, in macroeconomicoutcomes and the need for models that can more easily incorporate it. We usetechniques from reinforcement learning to solve such models incorporatingheterogeneous agents in a way that is simple, extensible, and computationallyefficient. We demonstrate the method's accuracy and stability on a toy problemfor which there is a known analytical solution, its versatility by solving ageneral equilibrium problem that includes global stochasticity, and itsflexibility by solving a combined macroeconomic and epidemiological model toexplore the economic and health implications of a pandemic. The lattersuccessfully captures plausible economic behaviours induced by differentialhealth risks by age.

Solving Heterogeneous General Equilibrium Economic Models with Deep Reinforcement Learning