Econ Visualization Purpose This skill creates publication-quality figures for economics papers, using clean styling, consistent scales, and export-ready formats. When to Use Building figures for empirical results and descriptive analysis Standardizing chart style across a paper or presentation Exporting figures to PDF or PNG at journal quality Instructions Follow these steps to complete the task: Step 1: Understand the Context Before generating any code, ask the user: What is the dataset and key variables? What chart type is needed (line, bar, scatter, event study)? What output format and size are required? Step 2: Generate the Output Based on the context, generate code that: Uses a consistent theme for academic styling Labels axes and legends clearly Exports figures at high resolution Includes reproducible steps for data preparation Step 3: Verify and Explain After generating output: Explain how to regenerate or update the plot Suggest alternatives (log scales, faceting, smoothing) Note any data transformations used Example Prompts "Create an event study plot with confidence intervals" "Plot GDP per capita over time for three countries" "Build a scatter plot with fitted regression line" Example Output

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Publication-Quality Figure in R

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library ( tidyverse ) df <- read_csv ( "data.csv" ) ggplot ( df , aes ( x = year , y = gdp_per_capita , color = country ) ) + geom_line ( size = 1 ) + scale_y_continuous ( labels = scales :: comma ) + labs ( title = "GDP per Capita Over Time" , x = "Year" , y = "GDP per Capita (USD)" , color = "Country" ) + theme_minimal ( base_size = 12 ) + theme ( legend.position = "bottom" , panel.grid.minor = element_blank ( ) ) ggsave ( "figures/gdp_per_capita.pdf" , width = 7 , height = 4 , dpi = 300 ) Requirements Software R 4.0+ or Python 3.10+ Packages For R: ggplot2 , scales , dplyr For Python: matplotlib , seaborn (optional alternative) Best Practices Use vector formats (PDF, SVG) for publication Keep labels concise and readable Document data filters used in the figure Common Pitfalls Overcrowded plots without clear labeling Inconsistent scales across figures Exporting low-resolution images References ggplot2 documentation Tufte (2001) The Visual Display of Quantitative Information Changelog v1.0.0 Initial release