econometrics

OLS regression estimates linear relationships in economic data, returning coefficients, standard errors, p-values, and model diagnostics to interpret the significance and direction of variables.

Panel data methods with fixed and random effects control for unobserved heterogeneity by leveraging multiple dimensions, producing consistent coefficient estimates across cross-sectional and time-series observations.

Instrumental Variables and 2SLS address endogeneity by using instruments to isolate exogenous variation, yielding consistent coefficient estimates and standard errors for causal inference.

Vector Autoregression models dynamic interactions in time-series data by capturing joint dependencies across variables, producing coefficient estimates and diagnostics for forecasting key economic indicators.

Difference-in-Differences evaluates causal effects by comparing pre- and post-treatment dynamics across groups, producing estimated treatment coefficients and standard errors for policy or intervention analysis.

Model diagnostics include heteroskedasticity, autocorrelation, and multicollinearity tests that evaluate OLS assumptions, returning test statistics and p-values to validate regression results.