I am not 100% convinced by this. The matchup between their painting-based economic index (it's the first component from a PCA analysis, the data for each painting being a vector of pixel-counts for colours in each of 108 bins based on HSV) and GDP growth is pretty dubious, and in places where the two vary together the painting-based metric frequently changes several years before the allegedly-corresponding change in GDP growth.
They have ad hoc explanations for the divergences and try to make lemonade out of the lemons by claiming that their index reveals "higher-frequency fluctuations that traditional series smooth over" but I am willing to bet that if they had had to predict the divergences before doing the calculations they wouldn't have been able to.
The argument is not that the color index is a perfect replica of GDP, but that it is an independent, higher-frequency proxy for economic activity that captures dimensions missed by traditional reconstructions.
The value of the index lies precisely where it converges with broad historical trends and where it diverges, suggesting new information. The observation that the color index frequently changes before GDP is a sign of its validity, not a weakness - e.g. shifting consumer demand/sentiment or supply chain shocks and a leading indicator of GDP
I'm 0% convinced. You can tell from a color palate whether some wallpaper was from the 70's or 80's, but that tells you nothing about the economic conditions and everything about what colors were in style.
As a photographer, I’ve noticed that no two photos of a given painting ever look the same. There is much variation due to lighting, color temperature, sensor capabilities, etc. Without controlling for these variables, it’s hard to see how comparisons can be made accurately.
I don't think basic color accuracy matters for this, it's more macro. In other words, two professionally taken images of a painting aren't going to make it look bright and colorful in one, and dark and somber in another.
Whether there's a slight green tint, or a certain blue doesn't pop quite as much, doesn't seem like it would affect the findings.
Not just that. A much larger confounding factor is that paintings change over time. If you've ever watching a painting restoration video, you'll discover that the way a painting looks today depends dramatically on its age, how it was stored, and what restorations have been applied to it and when. Varnish yellows over time. Before electricity, rooms were light by fire which deposits ash everywhere.
We develop a novel approach to measuring long-run economic growth by exploiting systematic variation in the use of color in European paintings. Drawing inspiration from the literature on nighttime lights as a proxy for income, we extract hue, saturation, and brightness from millions of pixels to construct annual indices for Great Britain, Holland, France, Italy, and Germany between 1600 and 1820. These indices track broad trends in existing GDP reconstructions while revealing higherfrequency fluctuations-such as those associated with wars, political instability, and climatic shocks-that traditional series smooth over. Our findings demonstrate that light, decomposed into color and brightness components, provides a credible and independent source of information on early modern economic activity.
Love it. I think time series views of these things on a site would be fun to watch or put on social media to spread this. Very cool. I appreciate the first citation. I’d vote film as the next medium of interest.
I don’t understand. The link opens to a web page, and the download link is clearly labeled as a PDF. Why the warning? And why warn about PDFs in general, have they been having zero day embedded malware lately or something?
This comment chain gave me a fun idea to lightly troll people. Just comment "Caution: <file format or file type>" on a thread with no further explanation and gaslight people into thinking there is some problem
I am not 100% convinced by this. The matchup between their painting-based economic index (it's the first component from a PCA analysis, the data for each painting being a vector of pixel-counts for colours in each of 108 bins based on HSV) and GDP growth is pretty dubious, and in places where the two vary together the painting-based metric frequently changes several years before the allegedly-corresponding change in GDP growth.
They have ad hoc explanations for the divergences and try to make lemonade out of the lemons by claiming that their index reveals "higher-frequency fluctuations that traditional series smooth over" but I am willing to bet that if they had had to predict the divergences before doing the calculations they wouldn't have been able to.
I think this is probably mostly pareidolia.
The argument is not that the color index is a perfect replica of GDP, but that it is an independent, higher-frequency proxy for economic activity that captures dimensions missed by traditional reconstructions.
The value of the index lies precisely where it converges with broad historical trends and where it diverges, suggesting new information. The observation that the color index frequently changes before GDP is a sign of its validity, not a weakness - e.g. shifting consumer demand/sentiment or supply chain shocks and a leading indicator of GDP
Also, color pigments might age differently.
Is the image we see today really what was initially drawn?
E.g. the famous night watch picture, which was larger and brighter.
I'm 0% convinced. You can tell from a color palate whether some wallpaper was from the 70's or 80's, but that tells you nothing about the economic conditions and everything about what colors were in style.
As a photographer, I’ve noticed that no two photos of a given painting ever look the same. There is much variation due to lighting, color temperature, sensor capabilities, etc. Without controlling for these variables, it’s hard to see how comparisons can be made accurately.
I don't think basic color accuracy matters for this, it's more macro. In other words, two professionally taken images of a painting aren't going to make it look bright and colorful in one, and dark and somber in another.
Whether there's a slight green tint, or a certain blue doesn't pop quite as much, doesn't seem like it would affect the findings.
I've seen exactly what you said isn't going to happen in two pro photos of an old (pre-1800s) painting.
One might have been altered to reduce the effect of centuries of oil-lamp soot, but it's still true.
Not just that. A much larger confounding factor is that paintings change over time. If you've ever watching a painting restoration video, you'll discover that the way a painting looks today depends dramatically on its age, how it was stored, and what restorations have been applied to it and when. Varnish yellows over time. Before electricity, rooms were light by fire which deposits ash everywhere.
We develop a novel approach to measuring long-run economic growth by exploiting systematic variation in the use of color in European paintings. Drawing inspiration from the literature on nighttime lights as a proxy for income, we extract hue, saturation, and brightness from millions of pixels to construct annual indices for Great Britain, Holland, France, Italy, and Germany between 1600 and 1820. These indices track broad trends in existing GDP reconstructions while revealing higherfrequency fluctuations-such as those associated with wars, political instability, and climatic shocks-that traditional series smooth over. Our findings demonstrate that light, decomposed into color and brightness components, provides a credible and independent source of information on early modern economic activity.
“Our findings [show] that light […] provides a credible and independent source of information on early modern economic activity.”
Wow!
they be like: dark is bad, light is good and popularity of each is changing over time
i mean, it's so natural, no? Yin Yang and stuff, like common sense type of things.
Love it. I think time series views of these things on a site would be fun to watch or put on social media to spread this. Very cool. I appreciate the first citation. I’d vote film as the next medium of interest.
Interesting idea.
Caution: PDF
I don’t understand. The link opens to a web page, and the download link is clearly labeled as a PDF. Why the warning? And why warn about PDFs in general, have they been having zero day embedded malware lately or something?
This comment chain gave me a fun idea to lightly troll people. Just comment "Caution: <file format or file type>" on a thread with no further explanation and gaslight people into thinking there is some problem
Afterwards, you can run into a theater and yell “fire!”
Love it. I respect the first citation.
I would vote to pursue film as the next medium. I would be interested in the predictive potential of your model.
I am not certain this model will teach us a lot but it certainly gets one to think independently which is desperately needed to maintain our humanity.
Thank you for sharing and publishing.