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Camilo's research focuses on developing a general unified statistical framework for estimating and testing linear and non-linear latent variable models. In particular, he extends the Generalised Additive Models for Location, Shape, and Scale (GAMLSS) framework to accommodate latent variables. His proposed framework allows for flexible functional forms in measurement equations, enabling estimation of mean and higher-order moments through a novel computationally efficient penalised method. Furthermore, Camilo's interests encompass applied statistical modeling, computational statistics, and causal inference. He holds a PhD from the London School of Economics, an MSc in Statistics, a Graduate Diploma in Statistics, and a BA in Economics from the National University of Colombia. Prior to joining LSE, he worked as a Senior Economist at the Central Bank of Colombia, gaining extensive experience in macroeconomic analysis and time series forecasting.
Central Bank Colombia • Colombia
Worked extensively on research outputs, macroeconomic analysis, and time series forecasting.
Department of Economics