Erik Öberg

In making this course, I've borrowed a lot of material from other teachers. Thanks to all of you who makes your teaching material publicly available!

I also have quite a few exam questions and problem sets to share to anyone who wants to teach similar material. Just email me if you want them.

The course covers business-cycle frameworks (RBC and NK), Frictional Labor Markets (McCall, Burdett-Mortensen, DMP) and consumption-savings dynamics with incomplete asset markets (both partial and general equilibrium).

GitHub - erikoberg/teaching_material Contribute to erikoberg/teaching_material development by creating an account on GitHub.

For several years, I've been teaching Ph.D. Macroeconomics II in the first-year Ph.D. course sequence here in Uppsala. I've uploaded all lecture notes in the attached link, in case this is to the interest of someone else.

github.com/erikoberg/te...

Fair one-slide summary of literature leading up to 3-equation New-Keynesian model?

Skriver i senaste @ekonomiskdebatt.bsky.social om "Nationalekonomi som ingenjörsvetenskap? Ett förslag till ett nytt utbildningsprogram". Samlar upp en del tankar och diskussioner som förts med kollegor och här på sociala medier.

nationalekonomi.se/artikel/nati...

Does anybody know if there exist an updated version of these graphs from Acemoglu (JEL 2002) somewhere?

I'm preparing lectures on search models and wage dispersion, in which I use these graphs to introduce the concept of residual wage dispersion, but they are a bit outdated.

This is very helpful - thx a lot!

Yes, numerous measurement issues. I was thinking about how to start exploring this. I learnt today that there were some nice efforts in the 90's to clean "Solow residuals" from labor utilization (exploiting some optimality conditions and firm data on other firm inputs). E.g. Basu-Kimball (1997)

Econ Question: How much of fluctuations in TFP can be accounted for by fluctuations in worker effort? Like in booms, firms use the hours worked available to them more efficiently. Is there any attempt out there to answer this of related questions?

She has several other interesting papers and projects too, e.g., about in-house hiring vs staffing agencies, misallocation across firms and wealth inequality. See her webpage for more.

sites.google.com/view/agnetab...

Very happy to share that @agnetaberge.bsky.social will join
Uppsala as a post-doc in the fall! Agneta is macroeconomist coming out of IIES with a focus on labor markets and wage setting. In her JMP, she develops a theory of two-tier collective wage bargaining.

drive.google.com/file/d/1x-tV...

Table heading missing. The table shows fiscal multipliers and fiscal cost normalized with the counterpart numbers from a pure government spending shock.

Two closely related papers are Wolf (2024) and Ferriere-Navarro (2024). Be sure to check them out.

economics.mit.edu/sites/defaul...

axelleferriere.github.io/files/FN_IMF...

We also identify some key parameters/moments that do make a difference for these conclusions. One of them is the marginal propensity to consume out of profit income, for which we need more evidence. In our view, these findings paint an agenda for future research.

Importantly, these conclusions are insensitive to changes to a big part of the model parameter space, as per the reasoning above. For details about this, see the paper.

This feature gives a double dividend: saving a job is cheap relative to creating to new one. Moreover, saving a job avoids vacancy-depletion effects (as in Coles-Kelishomi (2018)), and reduces the unemployment risk that households face a lot.

Retention subsidies are effective relative to other firm transfers b/c the data supports fairly elastic separations, and relatively inelastic vacancy creation.

UI duration extensions are effective relative to other household transfers b/c the data supports limited insurance with respect to long-term unemployment. At the margin, we can stimulate household consumption a lot by insuring them against this.

Untargeted transfers to households are, in general, quite ineffective, whereas targeted transfers to the unemployed, like UI duration extensions, and job-saving retention subsidies give a lot of bang for the buck.

We find that fiscal multipliers vary greatly across different common policy interventions, from 0.3 to 1.6. You cannot compare stimulus packages by just counting dollars spent, you must look under the hood at the actual design!

Quantitatively, we use a state-of-the-art calibration of the model, building on our previous work and that of Rohan Kekre.

www.dropbox.com/scl/fi/wf5fw...

sites.google.com/site/rohanke...

Intermezzo: Special thanks to @aauclert.bsky.social-Bardoczy-Rognlie-@ludwigstraub.bsky.social and Boppart-Krusell-Mitman for teaching us to think about models in sequence space.

We exploit these properties to investigate which parameters (and features of the model) are important for determining the relative effectiveness of a variety of different stimulus designs.

A direct implication is that for comparing the fiscal multipliers of two different policies that achieve the same output effect, in many cases we don’t need to know all the parameters of the model, but only the parameters relating to the policy-specific direct effect.

This means that a solution to any policy shock can be written as the product of a policy-specific direct effect, and a policy-invariant GE effect, where the latter is a geometric sum of repeated cycles through these three blocks.

An HA block determines the asset market equilibrium given the labor market equilibrium, an NK block determines the goods market equilibrium given the asset market equilibrium, and a SAM block determines the labor market equilibrium given the goods market equilibrium.

This is because a first-order approximation of the equilibrium in sequence space takes the form of a Directed Cycle Graph.

A key insight of our paper is that despite the model richness and its infinite-dimensional state space, we can nevertheless go quite far in characterizing this model analytically, especially when comparing the effect of different policy shocks.

Due to its richness, with realistic heterogeneity and frictions in several markets, the model is suitable for quantitatively comparing the effect of different policy designs. At the same time, the richness makes the comparison challenging.