Thank you for putting this starter pack together! Would be great to be added: @alejandroecon.bsky.social Thanks!

Thank you for putting this starter pack together! Would be great to be added: @alejandroecon.bsky.social Thanks!

Understanding the time-dependent dynamics of migration shocks is crucial for designing policies that balance local and national goals. Read more about my findings here:

alejandro-pt.github.io/papers/parra...

I estimate the model parameters using impulse response matching, aligning the model's simulated responses with the empirical evidence from the first part of my paper.

To capture the aggregate effects, I develop a dynamic spatial model. This continuous time framework incorporates forward-looking households, mobility frictions, and productivity spillovers to track how migration shocks ripple through the economy.

↘️ At the aggregate level, deporting 1% of the population reduces long-run output per worker by 1%.

So, while initially achieving short-term goals like reducing congestion, these policies can have persistent unintended consequences, taking decades to fully materialize.

I use a panel vector-autoregression with a shift-share instrument based on lagged birth rates to capture these time-dependent effects. This ensures robust estimates of migration's causal impacts at the local level.

As migrants move into newly de-congested regions, local economies respond.

↗️ At the commuting zone level, I find that a 1% rise of migration inflows increases wages and output per worker by 0.15%-0.25% and housing prices by 1%—peaking 4 years after the shock.

But migration is dynamic and responds to such policies. My JMP shows these policies can have unintended effects: as regions become less congested, they attract new migration flows, potentially reversing short-term gains.

In the U.S., debates around deportation and worker relocation often focus on reducing congestion or lowering housing prices.

www.cnn.com/2024/11/19/economy/new-home-undocumented-immigrants-trump/index.html