DSGE Models

What Are DSGE Models?

Dynamic stochastic general equilibrium (DSGE) models are macroeconomic models used for economic analysis and policymaking by central banks and government institutions. DSGE models analyze the interactions between economic variables over time, incorporating random shocks and the optimizing behavior of economic agents.

DSGE models evolved from models of actual business dynamics introduced by Kydland and Prescott and have become the predominant tool for macroeconomic analysis since their development in the 1980s. Central banks, the IMF, academic researchers, and other institutions use these models extensively for monetary and fiscal policy simulations as well as economic forecasting.

Characteristics of DSGE Models

DSGE models are named for these key characteristics:

  • Dynamic: DSGE models consider how current decisions impact future economic conditions, accounting for the expectations of economic agents​. For example, central banks use DSGE models to understand how today’s interest rate decisions will impact future inflation and economic growth.
  • Stochastic: They include random shocks, such as sudden changes in oil prices or financial crises, to capture economic fluctuations due to unforeseen events.
  • General: DSGE models analyze the economy as a whole, ensuring that all markets and sectors are interlinked and jointly determined​.
  • Equilibrium: They model the state where supply and demand balance across all markets, influenced by policy changes and external shocks​.

Applications of DSGE Models

DSGE models are used for estimating nonlinear macroeconomic models, applying Bayesian techniques, performing general equilibrium modeling, and other tasks. They are essential for conducting monetary policy analysis, performing fiscal policy simulations, and generating macroeconomic forecasting to aid decision-making processes. DSGE models are often used to create fan charts to visualize the range of possible future economic outcomes, a technique often used by central banks for communicating uncertainty.


See also: econometrics and economics, Monte Carlo simulation, analytical solution, time series regression, systemic risk, state-space models, Bayesian state-space models