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Zi Yang Kang

@ziyangkang.bsky.social

370 followers 290 following 24 posts

Economist + assistant professor at the University of Toronto

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Zi Yang Kang @ziyangkang.bsky.social · Dec 3

1/ My co-author @mitchwatt.bsky.social is on the #EconJobMarket this year.

Mitch is an applied theorist interested in market design, IO, and public policy.

I happen to know his #JMP and its companion paper very well. 😇

🧵👇 with an overview of both papers.

#EconSky

Mitch's JMP: Optimal Redistribution Through Subsidies

Our other paper: Optimal In-Kind Redistribution

Reposted by Zi Yang Kang

Alex Teytelboym @t8el.bsky.social · Jul 29

The @nytimes.com says: "The Bull Market for Economists Is Over." www.nytimes.com/2025/07/28/b....

But Oxford Econ Dept & Nuffield College continue to offer their prestigious 3-year postdoc in economics! 👏 🎯

Deadline 🚨 30 September 🚨 to get offer by Xmas 🎄: economics.web.ox.ac.uk/nuffield-pos...

Nuffield Postdoctoral Research Fellowships

Deadline: Tuesday, 30 September 2025

economics.web.ox.ac.uk

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

@skyview.social unroll please 🙏

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

20/ Finally, perhaps the most important thing: Mitch is also a wonderful human being and colleague.

Hire him and find out for yourself! ☺️

Mitch's JMP: www.mitchellwatt.com/files/toppin....

Our other paper: www.mitchellwatt.com/files/OIKR.pdf.

www.mitchellwatt.com

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

19/ Outside of these two papers, Mitch has a ton of other work, including:

- a paper (R&R at ReStud) with Paul Milgrom
- an empirical(!) paper with @johnjhorton.bsky.social and @shoshievass.bsky.social
- his own papers

Check out his long CV here: www.mitchellwatt.com/files/Mitche....

www.mitchellwatt.com

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

18/ By solving these, we also derive other results in the papers, including:

- comparative statics with respect to redistributive weights
- results on how valuable *preventing* topping up is to the social planner
- extensions with budget constraints and equilibrium effects

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

17/ Summarizing these technical difficulties for my fellow nerds:

Mitch's JMP 👉 topping up allowed 👉 social planner's problem = convex program with FOSD constraints.

Our other paper 👉 topping up not allowed 👉 social planner's problem = convex program with SOSD constraints.

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

16/ The analysis is tricky because the outside option of each consumer depends on his demand type.

We overcome this by guessing Lagrangian multipliers and verifying that they are optimal.

It took us many guesses and sleepless nights, but now we can write them out:

Explicit expression for one of the Lagrangian multipliers.

Explicit expression for another of the Lagrangian multipliers.

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

15/ Also, this result concerns the social planner's *marginal* incentives to intervene, but it doesn't tell us what the *global* optimum is.

To do that, we develop mechanism design tools.

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

14/ Of course, this assumes that you want to redistribute to consumers with the lowest demand.

There are cases (think disability care) where you might want to redistribute to consumers with the highest demand.

Our result covers these cases too.

Sufficient statistics for when to intervene (Mitch's JMP).

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

13/ So, on the margin, the cash transfer effect dominates. This means that a sufficient statistic for when it's optimal to intervene is the *average* social value of a dollar to consumers.

Intervention is optimal if + only if this exceeds the shadow cost of that dollar!

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

12/ We use a first-order approach to bound these effects (quantity distortion vs cash transfer).

We show that an ε quantity of a free public option leads to:
- an O(ε^1.5) 👆 in consumer utility from quantity distortion
- an O(ε) 👆 in consumer utility from cash transfer

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

11/ Since you want to redistribute to low-demand consumers, this is the best targeting that you could hope for.

With linear subsidies, there would have been 👆 quantity distortion for *all* consumers.

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

10/ Why? When topping up is allowed (Mitch's JMP), having a tiny quantity of a free public option results in:

(1) 👆 quantity distortion for low-demand consumers
(2) 🚫 quantity distortion for high-demand consumers
(3) 💵 cash transfer (= price of public option) to all consumers

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

9/ So when is it optimal to intervene with nonlinear subsidies?

When you're trying to redistribute to consumers with lower demand: if + only if it’s optimal to intervene with a *free public option*.

Note that we would've gotten the wrong answer by focusing on linear subsidies!

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

8/ It turns out that whether consumers have the ability to top up or not drastically affects the analysis.

So, Mitch's JMP 👉 topping up is allowed.

Our other paper 👉 topping up is not allowed.

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

7/ And why do we have two papers rather than one? Because housing is different from health care!

You cannot top up your public housing unit by renting more space privately.

But you can top up your public health care with visits to private doctors/clinics.

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

6/ So what makes our take on them new?

(A) Motivated by instruments we see (e.g., free public option), we allow for *nonlinear* subsidies.

(B) Unlike much (most!) of mechanism design, outside options are *not* zero (everyone can always consume their laissez-faire allocations).

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

5/ Of course, we are far from the first to ask these questions.

There are many excellent papers (e.g., in public finance) that have examined them!

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

4/ In each of these two papers, we answer these questions by:

(1) Developing "sufficient statistics" that give necessary + sufficient conditions to intervene.

(2) Building new mechanism design tools to figure out optimal interventions, which we can cutely summarize like this.

Example of how optimal interventions can be summarized.

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

3/ But is this optimal? Specifically:

(1) *When* should governments intervene with these instruments?

(2) *How* should governments optimally design these instruments?

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

2/ Here's the gist: Governments often redistribute by intervening in markets such as housing and health care.

Common instruments for interventions include a baseline "public option" (think public housing/healthcare) and subsidy programs (like private subsidies).

Zi Yang Kang @ziyangkang.bsky.social · Dec 3

1/ My co-author @mitchwatt.bsky.social is on the #EconJobMarket this year.

Mitch is an applied theorist interested in market design, IO, and public policy.

I happen to know his #JMP and its companion paper very well. 😇

🧵👇 with an overview of both papers.

#EconSky

Mitch's JMP: Optimal Redistribution Through Subsidies

Our other paper: Optimal In-Kind Redistribution

Zi Yang Kang @ziyangkang.bsky.social · Dec 2

I think the bigger point is just that there are other reasons for intervention in markets than for the sake of economic efficiency (equity being an example here).

Reposted by Zi Yang Kang

Shosh Vasserman @shoshievass.bsky.social · Nov 7

The running list of IO job market candidates for 2024-2025 is live!

Fill this out to add your info: forms.gle/upCQ4Ez7sBTP...

Running list here: shoshanavasserman.com/io-jmc/

Reposted by Zi Yang Kang

Luca Rigotti @lucarigotti.bsky.social · Oct 3

Pitt's econ department has 3 junior faculty positions! One of them has a preference for a theorist.
Listings link: www.aeaweb.org/joe/listings...,

American Economic Association