Makromodeller

Makromodeller, or macro models, are simplified representations of an economy used to analyze aggregate phenomena and inform policy. They aim to describe relationships among systemic variables such as output, inflation, unemployment, interest rates, and external balances, and to predict responses to shocks or policy changes.

Major families include dynamic stochastic general equilibrium (DSGE) models, vector autoregressions (VARs), and agent-based macro models. DSGE models are theory-driven and specify optimizing behavior by households and firms, price and wage rigidities, and monetary or fiscal policy rules. VARs are data-driven and capture interdependencies without strong structural assumptions. Agent-based models relax representative-agent assumptions and can incorporate heterogeneity and complex interactions.

Models are either calibrated or estimated from data. Calibration assigns plausible values and uses the model to simulate; estimation uses statistical methods such as maximum likelihood or Bayesian techniques to fit the model to observed data. Common applications include forecasting, scenario analysis, and policy evaluation, including the effects of quantitative easing or fiscal stimulus.

History and usage sections note that macromodels emerged from econometrics in the 20th century, with real business cycle (RBC) and later DSGE models gaining prominence in the 1980s–2000s. Notable examples include Smets and Wouters (2007) a widely cited US DSGE model, and VAR-based policy-analysis frameworks used by central banks. Limitations include model risk, reliance on strong assumptions such as rational expectations and market clearing, and difficulties in capturing financial frictions and international spillovers.