The blog of Michael Wiebe

I’m continuing my blog over at Substack: https://blog.michaelwiebe.com/.

In Broken City, landscape architect Patrick Condon presents a diagnosis of the housing crisis.

In The Great Housing Hijack, Cameron Murray sets up a framework with five equilibria (asset price, rental, spatial, density, and absorption rate), which he applies to various policy issues.

When we upzone land from single-family zoning to apartment zoning, we change the allocation of a city’s fixed stock of land.

What caused the housing crisis?

In the last post I used continuous quantities of housing: people could buy, say, 1.26 homes.

When we build new apartments, the people moving in vacate their old apartments; this reduces competition for old housing, making it more affordable.

There are a handful of papers applying the ‘disease burden’ method to study the long-term effects of the measles vaccine.

Moretti (2021) is about agglomeration effects in innovation: do inventors patent more when they’re around other inventors?

A year ago, I wrote a short post looking at the data in Cook (2014) (sci-hub) (replication files) on the effect of racial violence on African American patents over 1870-1940.

Summary In this post I replicate the paper “Is Legal Pot Crippling Mexican Drug Trafficking Organisations?

One of the main tools I use for replication is regression weights.

One explanation for China’s rapid economic growth is meritocratic promotion, where politicians with higher GDP growth are rewarded with promotion.

China has had double-digit economic growth for nearly three decades.

How robust are false positives to dropping 1% of your sample?

I’ve seen a few papers that use randomization inference as a robustness check.

Economists want to show that our results are robust, like in Table 1 below: Column 1 contains the baseline model, with no covariates, and Column 2 controls for \(z\).

PSA: if you read a paper claiming p<0.01, you shouldn’t automatically take that p-value literally.