Over on Twitter Bill McBride points out a note on house prices from Goldman “The supply-demand picture that has been the basis for our call for a multi-year boom in home prices remains intact. … Our model now projects that home prices will grow a further 16% by the end of 2022.” Goldman: "The supply-demand picture that has been the basis for our call for a multi-year boom in home prices remains intact.
I recently gave a talk on housing markets, beginning with some observations and asking a few pressing questions. U.S. house prices are increasing at about a 20 percentage point annual rate in recent months, the highest rate of growth ever recorded. The level of real (inflation-adjusted) house prices is the highest in 131 years of house price data stretching back to 1890. What does this mean for the housing market?
I continue to experiment with ggfx. This week I made some charts showing U.S. housing starts. This chart emphasizes the fact that while housing starts have been increasing over the past decade, the absolute level of starts is only moderate when compared to pre-Great Recession (2008-2009) data. I like to use the ggfx::with_outer_glow functions to create a hazy glow around the density plot. Here is the R code for that chart.
Yesterday I gave a virtual talk at JSM 2021 on Visualizing Economic and Financial Market Trends in Volatile Times. Here is a summary of my remarks. The COVID-19 pandemic and associated economic slowdown has led to unprecedented volatility in many economic and financial time series. With swings well outside of historical ranges, many forecasting models break down. Data visualization techniques are a powerful tool to help the analyst understand evolving economic and financial market trends.
I want to share with you a fun rose chart. No not the Nightingale chart (see Jeff Shaffer). Rather we’re talking about a cool generative chart, that fit in a tweet from @aschinchon [https://twitter.com/aschinchon] : #rose library(tidyverse) seq(-3,3,by=.01) %>% expand.grid(x=., y=.) %>% ggplot(aes(x=(1-x-sin(y^2)), y=(1+y-cos(x^2)))) + geom_point(alpha=.05, shape=20, size=0)+ theme_void()+ coord_polar()#rtistry #rstats #Maths #generativeart pic.twitter.com/vAVeQU0K2o — Antonio Sánchez Chinchón (@aschinchon) June 16, 2021 I was inspired to use ggfx to add some features.
This morning the U.S. Bureau of Labor Statistics reported record high job openings in the JOLTS data. Using the code in this post I tweeted out this chart showing job openings are at a record high in the US. chart link With so many job openings you might be curious to ask whether or not the recession that started last year is well and truly over. Many indicators certainly seem to say say.
Recently I’ve been doing some experiments with the new R package ggfx. Earlier this month I shared an example, using ggfx for good. Since then, new features have been added to ggfx and I’ve found new applications for them. In this post, we’ll take some standard charts and watch them glow up as we add new features from ggfx. Having our charts glow up might not be the best idea, Bob Rudis suggests we’re converging on Excel level graphs.
I have been recently messing around with the new ggfx package. using #rstats ggfx::with_bloom and ggridges::geom_density left with ggfx, right without pic.twitter.com/L8yknjAJVw — 📈 Len Kiefer 📊 (@lenkiefer) March 4, 2021 Most of my applications (see below for a gallery) have maybe not been applying good dataviz guidelines. But I think I have found a good example. We can use the ggfx::with_blend function to layer a recession indicator with a time series and color code the lines.
Yesterday I gave a virtual lecture on data visualization at GMU. Here I’m posting the slides I used for that talk and including my discussion notes for the portion of the talk where I discussed guidelines for data visualization. At the beginning of the talk I spoke a bit about data visualization guidelines. I framed this part of my talk around Jon Schwabish’s five guidelines from his new book Better Data Visualizations see (on Amazon) and here for a blog summary.
Last week the U.S. Commerce Department reported the advance estimate for annual economic growth for 2020. For the full year, US gross domestic product contracted 3.5 percentage points, the largest annual decline since the 11.6 percentage point contraction in 1946. The similarities pretty much end there. In 1946 the US economy was demobilizing after finishing the fight against fascism. Factories were shuttered that had been producing munitions, fighter planes, tanks and liberty ships, while the G.