Halbert White, often known as Hal White, was an influential econometrician and professor, primarily known for his work in the field of economics and statistics. Born on November 19, 1950, he made a significant impact through his research on econometric methodology, particularly in the areas of model specification, estimation, and inference.
One of Halbert White’s most notable contributions is the robust standard errors technique, commonly known as White standard errors, which he introduced in a seminal paper published in 1980. This technique is crucial for dealing with heteroscedasticity in regression analysis. Heteroscedasticity occurs when the variability of a variable is unequal across the range of values of a second variable that predicts it. His method adjusts the standard errors of regression coefficients to account for the inconsistency, thus providing more reliable inference.
Throughout his career, White contributed to numerous other areas of econometrics, including the study of neural networks and their application to economic data. He held an academic position at the University of California, San Diego, where he worked until his passing in 2012. His profound influence extends through his work, which continues to be essential in econometric analysis, aiding both theoretical understanding and practical applications in economic research.