Data Analysis for Economic Research
July 26, 2023
Preface
Introduction
This book is your guide to preparing for a career in Economics and Finance. These fields need you to be great at understanding and explaining data. This book will help you improve your data science and analytics skills, and use them to answer questions about business cycles, economic growth, and financial markets.
A significant part of this book is about teaching you how to program in R, a popular language used for data analysis and graphics. You’ll also learn how to use complementary software like RStudio, R Markdown, and LaTeX to craft professional reports that showcase your data analyses.
But it’s not all about coding. We’ll also explore economic indicators to help you understand business cycles and regional differences in economic performance. You’ll learn about traditional measures like GDP growth, inflation, money supply, and interest rates. We also touch on newer, survey- and text-based indicators, such as consumer confidence indices and news-based indicators of economic uncertainty, which come from language analysis of newspapers, social media, or Google searches.
The book is divided into three modules:
- Module I: Introduction to R for Economic Research
- Module II: Traditional Economic Indicators
- Module III: Survey- and Text-Based Economic Indicators
Each module builds on the previous one, providing you with a coherent learning journey.
By the time you finish this book, you’ll be ready to analyze a wide range of economic and financial data. Your learning progress will be assessed based on the completion of DataCamp courses and the production of three data reports, one for each module.
References
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