macroeconometrics
Macroeconometrics is the quantitative study of macroeconomic phenomena using statistical methods to test theories, estimate relationships and forecast macroeconomic variables. It sits at the intersection of econometrics and macroeconomics, employing time-series data and, increasingly, Bayesian techniques to analyze issues such as output, inflation, employment, and policy effects.
Core models include vector autoregressions (VARs) which capture dynamic interdependencies among multiple macro indicators. Structural VARs
Other approaches include cointegration and error-correction models to study long-run relationships among non-stationary series; ARDL models;
Key data issues include non-stationarity, structural breaks, measurement error, and data revisions. Estimation challenges involve endogeneity,
Applications range from evaluating monetary and fiscal policy, studying business cycles, understanding unemployment dynamics, to forecasting
Historically, macroeconometrics evolved from reduced-form time-series methods to SVAR and cointegration in the 1980s and 1990s,