Concepts, Methods and Techniques in
Political Science, Public Policy
and International Relations

TRACK: Time-Series Analysis
WEEK 1: 15 - 19 JANUARY 2024

Basics of Time-Series Analysis

Natália P. Moreira, Wesleyan University, USA

Teaching Assistant: Luiz Cantarelli

Course Description

Time series variables (e.g., presidential approval, public mood liberalism, GDP, inflation, education level) are extremely common in the social sciences. However, due to certain properties, these series cannot always be handled using standard regression approaches. This course serves as an introduction to the world of time series analysis. In this module, we will discuss the essentials of time series with a focus on preparing you for cross-sectional time series analysis.  We will explore the properties of time series (e.g., non-independence of observations, moving averages, unit-roots), and introduce strategies to test and model these data.

Dates - This course runs January 15-19, 2024.

During the first four days, the course will involve about three hours of lecture time with breaks, then lunch, then three to four hours of hands-on instruction in analysis that takes place in smaller groups using Stata. On the fifth day, students will present a specific project that applies the concepts introduced in the course.


  • The basics of TS data
  • A very quick overview of univariate ARIMA
  • Modeling Stationary Data
  • Modeling Non-Stationary Data
  • Autoregressive distributed lag (ADL) and error correction model (ECM) approaches
  • Cointegration and ECMs
  • Dynamic models and interpretation (DYNARDL)

what we will learn


A full-semester graduate-level course in multiple regression analysis.