F Temporal Patterns in Economics

This module delves into key temporal patterns observed in Economics and Finance, emphasizing the understanding of economic trends, business cycles, and seasonal variations. Economic trends capture long-term shifts, such as sustained economic growth, declining poverty rates observed in many countries over past centuries, the aging demographic in developed nations, and the steady inflation leading to rising prices over time. Business cycles depict regular, non-seasonal variations in economic activity around these trends, often characterized by expansion (or boom) phases and contraction (or recession) phases. Seasonal patterns, on the other hand, reflect predictable annual variations influenced by factors like holidays, weather, and cyclical employment shifts. This module shows how to differentiate, visualize, and interpret these temporal patterns.

F.1 Overview

Outlined below is the chapter contained in this module:

  • Chapter 16: “Temporal Patterns” provides an insight into time series data’s features and characteristics from a macroeconomic lens, examining trends, business cycles, and seasonality.

Additionally, the following DataCamp course supplements the chapter mentioned above:

  • Manipulating Time Series Data in R: This course covers the foundations of time series analysis, including summary statistics, trend interpretation, window functions, and methods for imputing missing data.
  • Importing and Managing Financial Data in R: This course teaches how to import financial and economic time series data into R from local files and internet sources, addressing the challenges of merging data from various origins.

The module culminates in the creation of a data report:

F.2 Learning Objectives

By the end of this module, you should be able to:

  1. Define and differentiate between economic trends, business cycles, and seasonal patterns.
  2. Understand and explain the macroeconomic implications of each temporal pattern.
  3. Use the ggplot2 package in R to visualize time series data effectively.
  4. Analyze and interpret variations in economic data over time.
  5. Synthesize knowledge from both textual resources and practical applications to draft comprehensive reports on temporal patterns in macroeconomics.

F.3 Learning Activities & Assessments

Throughout this module, you’ll engage in the following activities:

  • Textbook Engagement: Read the textbook chapter 16 and reproduce the content provided. Input the code from the chapters into RStudio and verify that your results match the chapter outputs.

  • DataCamp Training: Work through the Manipulating Time Series Data in R and Importing and Managing Financial Data in R courses on DataCamp. While progressing through the course, keep an R script handy and apply the learned functions to any of the datasets introduced in this module. This preserves the new functions of the course and potentially offers new insights from the chosen dataset.

  • Data Report Creation: To consolidate your learning, craft a Data Report on Temporal Patterns using R Markdown. Your report should clearly display data, provide meaningful analyses, and embody the module’s content.

Your assessment will be based on:

  • DataCamp Course Completion: Finish the designated DataCamp courses for this module. Your grade is based on course completion; thus, you receive full credit by completing all chapters and obtaining a minimum of 75% XPs (experience points) by the deadline. Hence, while the Take Hint and Show Answer options reduce your XPs, they won’t affect your module grade if you stay above the 75% threshold.

  • Data Report Evaluation: The quality of the data report is central to module assessment. It should be professional, suitable for clients, and reflect the module’s content. Ensure you adhere to the data report instructions.

For further guidance on maximizing your textbook and DataCamp experience, consult the Textbook Engagement and Learn R with DataCamp sections. For specifications on the data report’s format and content, consult the Data Report Instructions and the subsequent section below.

F.4 Data Report on Temporal Patterns

Choose at least two economic indicators highlighted in this module and conduct a trend analysis, seasonal assessment, and business cycle analysis.

As preparation for this assignment, please work through the module chapters and DataCamp courses listed under the overview section above. Ensure your report adheres to the guidelines detailed in Data Report Instructions, which dictates the creation of two versions: official and internal. Upon completion, submit both versions on Blackboard.