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Archive of posts filed under the Economics category.

Taking the bus

Bert Gunter writes: This article on bus ridership is right up your alley [it’s a news article with interactive graphics and lots of social science content]. The problem is that they’re graphing the wrong statistic. Raw ridership is of course sensitive to total population. So they should have been graphing is rates per person, not […]

Election forecasts: The math, the goals, and the incentives (my talk this Friday afternoon at Cornell University)

At the Colloquium for the Center for Applied Mathematics, Fri 18 Sep 3:30pm: Election forecasts: The math, the goals, and the incentives Election forecasting has increased in popularity and sophistication over the past few decades and has moved from being a hobby of some political scientists and economists to a major effort in the news […]

Coronavirus disparities in Palestine and in Michigan

I wanted to share two articles that were sent to me recently, one focusing on data collection and one focusing on data analysis. On the International Statistical Institute blog, Ola Awad writes: The Palestinian economy is micro — with the majority of establishments employing less than 10 workers, and the informal sector making up about […]

2 econ Nobel prizes, 1 error

This came up before on the blog but it’s always worth remembering. From Larry White, quoted by Don Boudreaux: As late as the 1989 edition [of his textbook, Paul Samuelson] and coauthor William Nordhaus wrote: “The Soviet economy is proof that, contrary to what many skeptics had earlier believed, a socialist command economy can function […]

Information, incentives, and goals in election forecasts

Jessica Hullman, Christopher Wlezien, and I write: Presidential elections can be forecast using information from political and economic conditions, polls, and a statistical model of changes in public opinion over time. We discuss challenges in understanding, communicating, and evaluating election predictions, using as examples the Economist and Fivethirtyeight forecasts of the 2020 election. Here are […]

Who are you gonna believe, me or your lying eyes?

This post is by Phil Price, not Andrew. A commenter on an earlier post quoted Terence Kealey, who said this in an interview in Scientific American in 2003: “But the really fascinating example is the States, because it’s so stunningly abrupt. Until 1940 it was American government policy not to fund science. Then, bang, the […]

Econ grad student asks, “why is the government paying us money, instead of just firing us all?”

Someone who wishes anonymity writes: I am a graduate student at the Department of Economics at a European university. Throughout the last several years, I have been working as RA (and sometimes co-author) together with multiple different professors and senior researchers, mainly within economics, and predominantly analysing very large datasets. I have 3 questions related […]

Rethinking Rob Kass’ recent talk on science in a less statistics-centric way.

Reflection on a recent post on a talk by Rob Kass’ has lead me to write this post. I liked the talk very much and found it informative. Perhaps especially for it’s call to clearly distinguish abstract models from brute force reality. I believe that is a very important point that has often been lost […]

Do we trust this regression?

Kevin Lewis points us to this article, “Do US TRAP Laws Trap Women Into Bad Jobs?”, which begins: This study explores the impact of women’s access to reproductive healthcare on labor market opportunities in the US. Previous research finds that access to the contraception pill delayed age at first birth and increased access to a […]

Decision-making under uncertainty: heuristics vs models

This post is by Phil Price, not Andrew. Sometimes it’s worth creating a complicated statistical model that can help you make a decision; other times it isn’t. As computer power has improved and modeling capabilities have increased, more and more decisions shift into the category in which it’s worth making a complicated model, but often […]

Heckman Curve Update Update

tl;dr: “The policy conclusion we draw from our analysis is that age is not a short cut for identifying where governments should, or should not, invest. There are many well‐studied interventions for children that are worthy candidates for public funding based on efficiency considerations. However, the same is also true of many interventions targeting youth […]

This is your chance to comment on the U.S. government’s review of evidence on the effectiveness of home visiting. Comments are due by 1 Sept.

Emily Sama-Miller writes: The federally sponsored Home Visiting Evidence of Effectiveness (HomVEE) systematic evidence review is seeking public comment on proposed updates to its standards and procedures. HomVEE reviews research literature on home visiting for families with pregnant women and children from birth to kindergarten entry, and its results are used to inform federal funding […]

The importance of descriptive social science and its relation to causal inference and substantive theories

Here’s the abstract to a recent paper, Escaping Malthus: Economic Growth and Fertility Change in the Developing World, by Shoumitro Chatterjee and Tom Vogl: Following mid-twentieth century predictions of Malthusian catastrophe, fertility in the developing world more than halved, while living standards more than doubled. We analyze how fertility change related to economic growth during […]

Conflicting public attitudes on redistribution

Sociologist David Weakliem wrote recently: A Quinnipiac poll from April 2019: “Do you support or oppose raising the tax rate to 70% on an individual’s income that is over $10 million dollars?” 36% support, 59% oppose A CNN poll from February 2019: “Would you favor or oppose raising the personal income tax rate for those […]

“To Change the World, Behavioral Intervention Research Will Need to Get Serious About Heterogeneity”

Beth Tipton, Chris Bryan, and David Yeager write: The increasing influence of behavioral science in policy has been a hallmark of the past decade, but so has a crisis of confidence in the replicability of behavioral science findings. In this essay, we describe a nascent paradigm shift in behavioral intervention research—a heterogeneity revolution—that we believe […]

Adjusting for Type M error

Erik Drysdale discusses and gives some formulas, demonstrating on an example that will be familiar to regular readers of this blog.

No, I don’t believe that claim based on regression discontinuity analysis that . . .

tl;dr. See point 4 below. Despite the p-less-than-0.05 statistical significance of the discontinuity in the above graph, no, I do not believe that losing a close election causes U.S. governors to die 5-10 years longer, as was claimed in this recently published article. Or, to put it another way: Despite the p-less-than-0.05 statistical significance of […]

This one quick trick will allow you to become a star forecaster

Jonathan Falk points us to this wonderful post by Dario Perkins. It’s all worth a read, but, following Falk, I want to emphasize this beautiful piece of advice, which is #5 on their list of 10 items: How to get attention: If you want to get famous for making big non-consensus calls, without the danger […]

Do we really believe the Democrats have an 88% chance of winning the presidential election?

OK, enough about coronavirus. Time to talk about the election. Dhruv Madeka starts things off with this email: Someone just forwarded me your election model (with Elliott Morris and Merlin Heidemanns) for the Economist. I noticed Biden was already at 84%. I wrote a few years ago about how the time to election factors a […]

Vaccine development as a decision problem

This post by Alex Tabarrok hits all the right notes: At current rates, the US economy is losing about $40 billion a week. Thus, if $20 billion could advance a vaccine by just one week that would be a good deal. . . . It might seem expensive to invest in capacity for a vaccine […]