This course provides an overview of tools used for forecasting and focuses on key concepts, structures and processes, and issues in time series forecasting.
At the end of the course, participants should be able to:
- Understand the basic considerations to successful forecasting;
- Implement quantitative techniques to characterize time series properties, graphically and statistically using R; and
- Write a short note detailing the development of a simple forecasting model.
Requirement: Laptop, with installed R software (Download here.)
Registration fee: PhP 5,000 (inclusive of meals, kit, and certificate)
To register, click here.
About the trainor
Lawrence Dacuycuy, Ph.D. is a Full Professor at the School of Economics, De La Salle University. He was the Dean of the School from 2013 to 2015 and currently, sits as a member of the Commission on Higher Education’s Technical Committee for Economics. He is also the Vice President of the Philippine Economic Society. He finished his BS Economics in 1998 at the School of Economics, University of the Philippines and two years thereafter, he received his Master of Science in Economics degree from the same university. He obtained his doctorate in economics from Kyoto University in 2006.
His research focuses on applied nonparametric and semiparametric econometrics, theoretical migration, labour economics, and macroeconomic modelling. In 2009, he was one of the recipients of the National Academy of Science and Technology’s (NAST) Outstanding Young Scientist (OYS) award. In 2012, he was a recipient of the NAST Outstanding Scientific Paper Award for his research on wage functional analysis. His current research focuses on fiscal policy and related issues using Dynamic Stochastic General Equilibrium (DSGE) models.