An Introduction to R for Economic Data Analysis
Title Page
Preface
About the Examples and Datasets
Downloading the Data
1
Installing R on Your Computer
1.1
Understanding R and RStudio
1.2
Installing R
1.2.1
Windows
1.2.2
macOS
1.2.3
Linux
1.3
Installing RStudio
1.4
Launching RStudio
1.5
A Tour of RStudio
1.5.1
The Console (Bottom Left)
1.5.2
The Source Editor (Top Left)
1.5.3
The Environment Panel (Top Right)
1.5.4
The Files/Plots/Help Panel (Bottom Right)
1.6
Verifying Your Installation
1.7
Keeping R Updated
1.8
Exercises
2
R Objects
2.1
What is an Object?
2.2
Scalars
2.2.1
Numeric
2.2.2
Character
2.2.3
Logical
2.3
Vectors
2.3.1
Creating Vectors
2.3.2
Sequences
2.3.3
Accessing Vector Elements
2.3.4
Vector Operations
2.3.5
Naming Vector Elements
2.4
Lists
2.4.1
Creating Lists
2.4.2
Accessing List Elements
2.5
Data Frames
2.5.1
Creating Data Frames
2.5.2
Examining Data Frames
2.5.3
Accessing Data Frame Elements
2.5.4
Adding and Modifying Columns
2.6
Managing Objects
2.6.1
Viewing Objects
2.6.2
Removing Objects
2.6.3
Checking Object Properties
2.7
Combining Objects
2.7.1
Combining Vectors
2.7.2
Combining Data Frames
2.8
Exercises
3
Libraries and Functions
3.1
Functions
3.1.1
Base R Functions
3.1.2
Getting Help
3.2
Installing Packages
3.3
Loading Packages
3.4
Calling Functions from Packages
3.4.1
After Loading
3.4.2
Without Loading
3.4.3
Function Conflicts
3.5
Packages Used in This Book
3.6
Exercises
4
Importing Data
4.1
Folders and File Paths
4.1.1
Setting Up a Project Folder
4.1.2
The Working Directory
4.1.3
Absolute vs Relative Paths
4.1.4
Tips for File Paths
4.2
Importing CSV Files
4.3
Importing Excel Files
4.4
Importing Text Files
4.5
Importing Stata Files
4.6
Importing from FRED
4.6.1
Getting a FRED API Key
4.6.2
Using the Helper Function
4.6.3
Common FRED Series
4.6.4
Downloading Multiple Series
4.7
Importing from the Census Bureau
4.7.1
Getting a Census API Key
4.7.2
Using tidycensus
4.7.3
Finding Census Variables
4.8
Importing from IPUMS
4.8.1
Creating an IPUMS Extract
4.8.2
Using ipumsr
4.8.3
IPUMS Data Collections
4.9
Importing from the World Bank
4.9.1
Using WDI
4.9.2
Finding World Bank Indicators
4.9.3
Common World Bank Indicators
4.10
Checking Your Import
4.11
Exercises
5
Data Wrangling
5.1
The Tidyverse and the Pipe
5.2
Core dplyr Verbs
5.2.1
select() — Choose Columns
5.2.2
filter() — Choose Rows
5.2.3
mutate() — Create or Modify Columns
5.2.4
arrange() — Sort Rows
5.3
Summarizing and Grouping
5.4
Combining Operations
5.5
Reshaping Data
5.6
Joining Data
5.7
Handling Missing Values
5.8
Example: Analyzing Cafe Sales Trends
5.9
Example: State-Level Economic Analysis
5.10
Exercises
6
Data Visualization
6.1
The Grammar of Graphics
6.2
Scatter Plots
6.2.1
Basic Scatter Plot
6.2.2
Adding Color
6.2.3
Adjusting Point Size and Transparency
6.2.4
Adding a Trend Line
6.2.5
Labeled Points
6.3
Line Plots
6.3.1
Basic Line Plot
6.3.2
Customizing Lines
6.3.3
Multiple Lines
6.3.4
Area Plots
6.4
Bar Charts
6.4.1
Basic Bar Chart
6.4.2
Reordering Bars
6.4.3
Horizontal Bars
6.4.4
Colored Bars
6.4.5
Grouped Bar Charts
6.5
Histograms and Density Plots
6.5.1
Histograms
6.5.2
Density Plots
6.5.3
Combining Histogram and Density
6.6
Box Plots
6.7
Faceting
6.7.1
facet_wrap()
6.7.2
facet_grid()
6.8
Customizing Plots
6.8.1
Titles and Labels
6.8.2
Axis Formatting
6.8.3
Color Scales
6.8.4
Themes
6.9
Combining Multiple Plots
6.10
Saving Plots
6.11
Example: Economic Dashboard
6.12
Example: State-Level Comparisons
6.13
Example: Wage Distributions from PUMS
6.14
Example: Cafe Sales Analysis
6.15
Exercises
7
Summary Statistics and Tables
7.1
Summary Statistics in Base R
7.1.1
Measures of Central Tendency
7.1.2
Measures of Spread
7.1.3
Other Useful Functions
7.1.4
The summary() Function
7.2
Summary Statistics with dplyr
7.2.1
Basic Summaries
7.2.2
Grouped Summaries
7.2.3
The across() Function
7.3
Correlation
7.4
Creating Basic Tables with knitr
7.5
Publication-Quality Tables with kableExtra
7.5.1
Basic Styling
7.5.2
Adding Headers and Formatting
7.5.3
Conditional Formatting
7.5.4
Footnotes and Notes
7.6
The gt Package
7.6.1
Basic gt Table
7.6.2
Formatting Columns
7.6.3
Adding Color and Style
7.6.4
Source Notes and Footnotes
7.7
Descriptive Statistics Tables
7.8
Correlation Tables
7.9
Exporting Tables
7.9.1
Saving to Files
7.9.2
Exporting to CSV
7.10
Example: Economic Report Table
7.11
Example: Comparison Table
7.12
Example: State Comparison Tables
7.13
Example: Demographic Tables from PUMS
7.14
Example: Business Analytics Tables
7.15
Exercises
7.15.1
Macro Data Exercises
7.15.2
State Data Exercises
7.15.3
PUMS Data Exercises
7.15.4
Cafe Data Exercises
7.15.5
Advanced Exercises
8
Regression Analysis
8.1
Linear Regression with lm()
8.1.1
Simple Linear Regression
8.1.2
Extracting Model Components
8.1.3
Visualizing the Regression Line
8.2
Multiple Linear Regression
8.2.1
Formula Syntax
8.2.2
Example: The Mincer Wage Equation
8.2.3
Categorical Variables (Factor Variables)
8.3
Diagnostic Plots
8.3.1
Creating Custom Diagnostic Plots
8.4
Robust Standard Errors
8.5
Binary Response Models: Logit and Probit
8.5.1
The glm() Function
8.5.2
Probit Model
8.5.3
Interpreting Coefficients
8.5.4
Marginal Effects
8.5.5
Predicted Probabilities
8.5.6
Visualizing Predicted Probabilities
8.5.7
Model Fit for Binary Models
8.6
Count Data Models: Poisson Regression
8.6.1
Preparing Count Data
8.6.2
Fitting a Poisson Model
8.6.3
Interpreting Poisson Coefficients
8.6.4
Predicted Counts
8.6.5
Overdispersion
8.6.6
Negative Binomial Regression
8.7
Comparing Models
8.7.1
Nested Model Comparison with Likelihood Ratio Tests
8.7.2
Information Criteria
8.8
Presenting Regression Results
8.8.1
Creating Regression Tables
8.8.2
Publication-Quality Tables with gt
8.8.3
Comparing Multiple Models
8.9
Example: Phillips Curve Estimation
8.10
Example: Wage Determinants with PUMS
8.11
Example: State Poverty Analysis
8.12
Exercises
8.12.1
Linear Regression
8.12.2
Binary Response Models
8.12.3
Count Data Models
8.12.4
Model Comparison and Diagnostics
8.12.5
Advanced
Published with bookdown
An Introduction to R for Economic Data Analysis
An Introduction to R for Economic Data Analysis
Calvin A. Ackley, Ph.D.
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