Camilo's research focuses on the development of 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 (Rigby and Stasinopoulos, 2005) to models with latent variables (Bartholomew et. al., 2011). The proposed framework allows for more flexible functional forms on the measurement equations not only for the mean, but also for higher order moments. The estimation is done through a novel and computationally efficient penalised method. Moreover, Camilo is also interested in applied statistical modelling, computational statistics, and causal inference.

Camilo holds a PhD and MSc in Statistics, a Graduate Diploma in Statistics, and a BA in Economics, all from the Universidad Nacional de Colombia (UNAL). Prior to joining LSE, he worked as a Senior Economist for the Central Bank of Colombia, with extensive experience and research outputs on macroeconomic analysis and time series forecasting.