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Graphics for Macroeconomics

Graphics for Macroeconomics. Principles. Graphing is done best when it clearly communicates ideas about data Focus on the main point while preventing distractions. Volatility. Volatility makes it hard to see trends Example from coin data. Scatter plots.

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Graphics for Macroeconomics

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  1. Graphics for Macroeconomics

  2. Principles • Graphing is done best when it clearly communicates ideas about data • Focus on the main point while preventing distractions

  3. Volatility • Volatility makes it hard to see trends • Example from coin data

  4. Scatter plots • Scatter plots help you see the relationship between variables • Time series plots vs. scatter plots

  5. Time-series plot

  6. Scatter Plot

  7. Time-series plots on same scale

  8. Scatter plot

  9. Elements of Graphical Style • Know your audience & know your goals • Show the data and appeal to the viewer • Minimize non-data ink • Avoid chart junk • Revise and edit, again and again

  10. Non-data ink Note that after 1990, the pattern of velocity and opportunity cost changed significantly, with a couple of years of transition and a new pattern to the slope. The new intercept was much higher than the old one and thus the relationship changed so that it was much more difficult to use the model for forecasting.

  11. Chartjunk

  12. Chartjunk • Don’t use 3 dimensions for a 2-dimensional object • Don’t add decorations, cartoons, etc. that do not tell your story Hi, I’m irrelevant!

  13. Make graphs tell your story • The golden ratio of height to width is 0.618 • Use scale to show variations in a variable

  14. Velocity is very stable

  15. Or is it unstable?

  16. Use colors to split data

  17. Beware of Outliers • Measurement outliers • Data errors • Innovation outliers • A shock or innovation

  18. Adding recession bars • See instruction sheet; useful to keep around

  19. Graphs as diagnostics for regressions • Plot actual and fitted values; residuals over time • Plot residuals squared or absolute values of residuals over time (solutions: interactive data analysis) • Do a scatter plot of residual vs. explanatory variable

  20. Example: consumption & income • We can save residuals and do plots of residuals themselves, actual & predicted, residuals vs. explanatory variables • Later, using saved residuals, we can plot squares and absolute values • Note that non-random residuals suggests that a non-linear model may be better

  21. Plotting from FRED • FRED graphs are nice

  22. Plotting from FRED • Sometimes you need to make your own graphs • Download FRED data to make graph • What’s wrong with this graph?

  23. Critique this graph • No title • Bad dates • Trailing zeroes on y axis • Legend takes up too much space

  24. Time-Series Graphs • Choose a scale to make the graph informative • Especially levels vs. growth rates • Which is best depends on purpose • Sometimes best to show level for long-term issues • Other times best to show growth rate for cyclical issues

  25. Nominal or Real? • Nominal variables of economic activity should never be plotted • You don’t know what is real activity and what is caused by higher prices • Only plot nominal variables for which it makes sense to do so: money supply, price level • Example: plot real GDP, not nominal GDP • Example: plot ratios of nominal variables, such as government debt/GDP

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