Watch Modelling Error Video Tutorials & Courses

What happens when the key variables in your analysis can't be perfectly observed? This video kicks off a new mini-series on measurement error and factor models, which is a useful way to handle imperfectly measured variables like cognitive ability, personality traits, and health status in structural economic models. In this intro, we'll map out the series ahead: - The classical measurement error problem and its econometric consequences - Principal Components Analysis (PCA) and Factor Analysis as dimensionality-reduction tools - Factor models: identification, estimation, and connections to methods covered earlier in the channel - Recent applications in labor economics and education economics Tyler Ransom is an Associate Professor of Economics at the University of Oklahoma. Subscribe for more videos on data science, econometrics, and research methods! #measurementerror #factormodels #econometrics #structuraleconometrics #latentvariables #principalcomponentsanalysis #PCA #factoranalysis #attenuationbias #omittedvariablebias #proxyvariables #laboreconomics #educationeconomics #unobservedheterogeneity #discretechoice #structuraleconguy #graduateeconometrics #appliedeconometrics #causalinference #dimensionalityreduction Key Highlights & Overview: Mastering <strong>Modelling Error</strong> is essential for modern technical workflows and software skills. Explore curated video courses, expert walkthroughs, and detailed lesson notes today on <strong>TutorTube</strong>.