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Nick Bloom Micro-heterogeneity & Macro, partial equilibriumPowerPoint Presentation

Nick Bloom Micro-heterogeneity & Macro, partial equilibrium

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Nick Bloom Micro-heterogeneity & Macro, partial equilibrium

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Nick Bloom Micro-heterogeneity & Macro, partial equilibrium

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Do micro distributions matter for macro outcomes

- Probably the greatest unanswered question in macro is how to get a tractable micro-to-macro model.
- Macro is right now caught between:
- Non-structural macro models that work empirically (VARs)
- Structural single-agent models that – if tractable - are not great empirically

- The challenge is to come up with something that:
- Has theoretical micro foundations
- Is simple enough to understand (at least in intuition)
- Empirically fits the micro and macro data

The first micro-macro investment and employment models were partial equilibrium

- Early studies looked at partial equilibrium models, showing:
- These induce dynamics across time, i.e.
- Consumption (Bertola and Caballero, 1990, NBER MA)
- Investment (Bertola and Caballero, 1994, RESTUD)

- These induce time varying marginal responsiveness to stimulus as we shall see now….

Ricardo Caballero, Eduardo Engel and John Haltiwanger (1995)

“Plant-level adjustment and aggregate investment dynamics”

Brookings Papers on Economic Activity

Overview

- Runs a micro-macro estimate of investment behavior
- The fundamental idea was to:
- Use establishment-level investment data from the LRD
- Build a micro-level investment hazard
- Build a micro cross-sectional distribution
- Combine these to describe macro outcomes over time

- An important paper:
- First to do micro to macro investment with large samples
- Well executed (take data seriously, think carefully about empirics…)
- Well written

Many cites - the rewards for being first and clear…

I

Combining micro hazards and distributions to describe macro investment

Mandated (desired) investment

Year

(1)

Aggregate investment

Adjustment hazard

Distribution of plants

This is what the hazard (left) and distribution (right peaked plot) look like on average

An impressive empirical (especially for 1995)

They argue that these non-convexities and cross-sectional variations matter

They approximate the adjustment function with a polynomial

This polynomial and changing moments of the distribution generates variation in responsiveness

Message is micro-distributions matter

- Good paper – how could you build on this:
- Theory/Simulation – Take a General equilibrium approach, as helpful for persuading cross-spectrum of all macro types
- Modeling – could add in labor market rigidities
- Identification – ideally would have some great natural experiment during this period (changing 1st, 2nd, 3rd… moments), but nothing obvious in US, maybe other countries?

Ricardo Caballero, Eduardo Engel and John Haltiwanger (1997)

“Aggregate Employment Dynamics: Building from Microeconomic Evidence”

American Economic Review

Overview

- Paper also estimates the effect of micro-to-macro effects on aggregate employment dynamics
- Contribution is:
- Extended investment idea to employment
- Used a nice measure of desired employment – hours
- Use a more structural framework and provided other results

- Good paper, although I personally prefer their Brookings paper which was simpler but with the same excellent intuition

Well cited (but a bit less than their Brookings paper

I

Again combine micro hazards and distributions to describe macro outcomes (employment)

Mandated (desired) employment growth

Year

Aggregate employment change

Adjustment hazard

Distribution of plants

Again find the adjustment rate increasing in the desired change (so implying employment “jumps”)

And show a time varying response of employment dynamics to aggregate shocks

Message is micro-distributions matter

- Good paper – how could you build on this – very similar to earlier:
- Theory/Simulation – Take a General equilibrium approach, as helpful for persuading cross-spectrum of all macro types
- Modeling – combine labor and capital
- Identification – ideally would have some great natural experiment during this period (changing 1st or 2nd moment), but nothing obvious in US, maybe other countries?

Ricardo Caballero and Eduardo Engel (1999)

“Explaining Investment Dynamics in US Manufacturing: A Generalized (S,s) Approach”

Econometrica

Overview

- Paper also estimates the effect of micro-to-macro effects on industry and aggregate investment dynamics
- Contribution is:
- Explicit micro-macro empirical structure (no approximations)
- Uses aggregate industry data to estimate (good because easily available – so new technique)
- Provides some new technical ideas

- Great paper (critical reading for my PhD), although very tough to read as it is highly technical

Well cited, with impact more important than this suggests as these readers will be well trained…

Similar set up to last papers except one neat trick is to assume adjustment costs are stochastic

Assume adjustment costs drawn from an i.i.d. Gamma distribution

Adjust(above the line)

Adjustment cost draw

Do not adjust(below the line)

Log(Actual/Optimal) capital stock (i..e. log(K/K*))

Again combine micro hazards and distributions to describe industry and macro investment

Log (actual/desired) capital

Year

Aggregate (or Industry) investment rate

Adjustment hazard

Distribution of plants

The structural approach allows them to estimate deep adjustment cost parameters

Also show time varying responsiveness, and show a structural mode outperforms simple AR(2) model

Message is can generate structural micro-macro model in a fully structural way with good empirical fit

- Good paper – how could you build on this – very similar to earlier:
- Implications – Impressive modelling, now want to find some experiment/shock to push this further (like time varying uncertainty….)
- Modeling – again combine labor and capital, or in fact R&D, ICT or any other factor, GE or some other worthwhile extension
- Identification – ideally would have some great natural experiment during this period (changing 1st or 2nd moment), but nothing obvious in US, maybe other countries?

Russell Cooper, John Haltiwanger and Laura Power (1999)

“Machine replacment and the business cycle: Lumps and bumps”

American Economic Review

Overview

This paper also estimates the effects of micro-macro aggregation on investment…you can tell this was popular in the late 1990s

There are two interesting additional results in this paper:

Investment “spikes” explain a large fraction of investment variation

Aggregate investment rate (total)

Aggregate investment rate accounted for by spikes (>20%)

Percentage of plants with an investment spike

Accounting for micro rigidities matters most around turning points

Aggregate investment (solid line)

Investment holding cross-section constant (dotted line)

Investment holding hazard fixed (long dashed)