Time Series Modeling Using Stata
The main purpose of this course is to help participants understand key concepts in time series econometrics through hands-on application in stata. Basic concepts and models will be taught in simplest language for economists and junior researchers in economics to equip them with basic tools required to conduct empirical researches. Statistical tests and models, including model estimation, model selection, hypothesis testing and interpretation will be presented in a step-by-step manner, and participants will learn how each statistical procedure is implemented in stata commands.
*  Participants will understand the key concepts in time series and how they are implemented in stata; *  Understand structure of economic data and methods for data management in stata; *  learn model estimation, model selection and hypothesis testing and interpretation; *  Acquire knowledge on univariate, bivariate and multivariate time series models, focusing on some topics such as ordinary least squares with stationary time series (OLS), vector autoregressive models (VAR), error correction (ECM) models, cointegration techniques, fully modified OLS (FMOLS), dynamic OLS (DOLS) and canonical cointegrating regression (CCR); *  Participants will be able to learn non-linear time series modelling such as regime switching models, threshold autoregressive models and non-linear autoregressive distributed lag (ARDL) models.
✓  This course targets junior to mid- level economists and economic statisticians from government institutions, ✓  research organizations whose main responsibility is economic modeling, ✓  analysis and research.
✓  Some basics of STATA ✓  Knowledge of Statistics and Econometrics