Bias-Corrected-Meta-Regression-Using-Robust-Variance-Estimation

This repository contains R code for conducting bias-corrected meta-regression analyses, specifically designed to estimate price and income elasticities. The code implements robust variance estimation techniques to ensure accurate standard errors and confidence intervals, even in the presence of heteroscedasticity or other violations of standard regression assumptions. Key Features: • Bias correction for meta-regression coefficients. • Robust variance estimation methods, including Huber-White sandwich estimator and clustered standard errors. • Calculation of price and income elasticities with corrected bias. • Comprehensive examples and usage instructions. This repository is intended for researchers and analysts performing meta-regression analysis who require reliable estimates despite potential model misspecifications. It is particularly useful in economic studies where price and income elasticities are key parameters of interest.