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Missing Growth from Creative Destruction

Philippe Aghion (College de France & LSE) Antonin Bergeaud (LSE)Timo Boppart (IIES) Pete Klenow (Stanford) Huiyu Li (FRB SF)

January 2017

Aghion, Bergeaud, Boppart, Klenow and Li Missing Growth from Creative Destruction January 2017 1 / 37

Introduction

Introduction

Products that are newly introduced and cease to exist, constitute amain challenge to estimate time variations in Price Index (PPI, CPI)−→ about 40% of items in the PPI and 30% in the CPI exit in atypical year

Standard procedure is to resort to imputation, i.e. to use pricechanges of surviving products to infer the overall price change

In this paper:−→ we argue that imputation leads to an underestimation of theproductivity gains from innovation−→we quantify the resulting missing growth for the overall USeconomy over the past three decades


Introduction

Basic model

Time is discrete and in each period the economy is populated by massL of identical one-period lived individuals who consume a final good.

Final good production:

Y =

(∫ N

0[qωyω]

σ−1σ dω

) σσ−1

,

where yω and qω are the quantity and quality of intermediate inputω, N denotes the number of intermediate varieties currently available,and σ > 0 denotes the elasticity of substitution between intermediateinputs.


Introduction

Innovation (1)

Creative destruction by new entrant (d) :−→ arrival rate λd ∈ [0, 1) in any sector ω, step size

γd = qω,t+1/qω,t .

Own improvement by incumbent (i) :−→ arrival rate λi ∈ [0, 1) in any sector ω, step size

γi = qω,t+1/qω,t .


Introduction

Innovation (2)

New varieties (n)−→ at rate λn

−→ new varieties may come at an above average quality by factor γn

Product VS process innovation


Introduction

Source of missing growth

True real output growth:

Yt+1

Yt=

Mt+1

Mt.Pt

Pt+1,

where M = YP is aggregate nominal output (or aggregateexpenditure on the final good), and P denotes the aggregate priceindex

Measured real output growth:

Yt+1

Yt=

Mt+1

Mt.Pt

Pt+1


Introduction

Missing Growth

Thus missing growth is entirely due to overstated (quality-adjusted)inflation:

MGt+1 = ln(Yt+1

Yt)− ln(

Yt+1

Yt) = ln(

Pt+1

Pt)− ln(

Pt+1

Pt)

Our assumption is that the Statistical Agency imputes inflation ratefrom disappearing products based on inflation rate of survivingproducts. CPI and PPI

We obtain:

MG =1

σ− 1log

(1 +

λd

[γσ−1d − 1− λi

(γσ−1i − 1

)]+ λnγσ−1

n

1 + λi

(γσ−1i − 1

) ).


Quantification Market Share Approach

Estimating missing growth using market shares

Here we estimate missing growth using the market shares of entrantplants/establishments, of incumbent plants that stay in the market,and of exiters




Let sIt−1,t denote the aggregate market share in period t of the set ofplants operating in both periods t and t − 1 (we refer to those firmsas continuers from date t − 1).

Let sIt−1,t−1denote the aggregate market share in period t − 1 of thesame continuers.




Missing growth can be expressed as:

MGt = − ln

(Pt

Pt−1

)+ ln

(Pt

Pt−1

)=

1

σ− 1ln

(sIt−1,t−1

sIt−1,t

)(1)




Thus true growth will exceed measured growth whenever the marketshare of continuing incumbents shrinks over time.

Intuitively : the difference between true growth and measured growthis equal to the difference between true growth and incumbent averageproductivity growth...

....and the market share of incumbents shrinks whenever the averageproductivity of continuing incumbents grows more slowly thanaverage productivity of the economy.




We do the analysis at the plant level and use the LongitudinalBusiness Database (LBD) which covers all plants with at least 1employee from 1976-2013.

We focus on period 1983-2013.

We then infer sIt−1,t−1 and sIt−1,t from the LBD information onemployment or payroll as measures of relative market shares.



Missing Growth implied by Survivors Market Shares

% points per year

Missing Measured “True”

1983–2013 0.56 1.93 2.49

1983–1995 0.60 2.01 2.61

1996–2005 0.41 2.65 3.06

2006–2013 0.69 0.90 1.59

Employment vs Payroll Plant vs Firms Choice of k


Quantification Indirect Inference

Indirect inference (1)

Rely on algorithm in Garcia-Macia, Klenow and Hsieh (2016) (GHK)

GHK uses data from the LBD for two time periods: 1976-1986 and2003-2013.−→ Over those two time intervals, they compute average (measured)TFP growth, exit rate of firms by age, employment, employment byage, job destruction and creation. . . to infer arrival rates and step sizeof innovations




We run GHK codes for different initial values of aggregate totalproductivity growth gu.

For each gu we derive the corresponding (λ’s, γ’ s)u by running theGHK algorithm, which in turn yields a value Gu for measured growth.

We stop at u∗ such that the corresponding computed value ofmeasured growth gu∗ is equal to the actual measured TFP growth rate

Missing growth is then taken to be equal to

MG = gu∗ − gu∗ .




Key advantages−→ need not assume that CD and NV only come from new plants−→ need not assume a constant number of products per plant



Result from indirect inference

σ = 4 1 plant = 1 variety (market share)

1976-1986 0.91 0.46∗

from CD 0.85

2003-2013 1.29 0.68

from CD 1.19

∗ average over 1983-1986.Akcigit Kerr (2010)



Conclusion

In this paper we developed a Schumpeterian growth model whichsuggested two ways of assessing the magnitude of missing growthfrom imputation.



Conclusion

The first approach is simple and intuitive and already suggests thatMG is large ( ˜ 0.6 ppt per year on average)−→ but it relies on simplifying restrictions and in particular itabstracts from CD by incumbents

The second approach does not rely on such restrictions, and−→ allows for CD by incumbents, thereby yielding higher MG ( ˜ 1.1ppt per year on average)−→ it allows us to decompose MG into its different sources, and wefind that most of it comes from CD



Conclusion

Some implications1 Ideas may no get as hard to find as official statistics suggest.2 US FED may wish to raise its inflation target to achieve price stability.



Result from Akcigit Kerr (2010)

Back



Declining Dynamism

1 Establishments vs. firms

2 Net entry vs. gross entry

3 5-year lag vs. year entered



Declining Dynamism



Manufacturing

All Mfg. Non-Mfg.

1983–2013 0.56 0.03 0.67

1983–1995 0.60 0.23 0.71

1996–2005 0.41 -0.13 0.51

2006–2013 0.69 -0.07 0.79



Product versus Process innovation

If process innovation:

Unit prices fall with innovation

Might be easy to measure growth from CD

Data: elasticity of unit prices wrt revenue ≈ 0.

e.g. Hottman, Redding and Weinstein (2015)

Consistent with product innovation.Back



Rate of imputation on CD

CPI: 97.4%

PPI:

If no price report from a participating company has been received in aparticular month, the change in the price of the associated item will, ingeneral, be estimated by averaging the price changes for the other itemswithin the same cell (i.e., for the same kind of products) for which pricereports have been received.

Back



Methods to deal with missing prices in the CPI (1)

When the BLS cannot track a same item over time (see GeneralAccounting Office (GAO) Report, 1999))

No adjustment when new item and old item are deemed comparable

Otherwise

Direct quality adjustmentClass-mean imputationLinking imputation




Class-mean imputation is based on the rate of price changesexperienced by other substitutions (those that the commodity analysthad considered comparable or had directly adjusted)

Linking method is based on the rate of price changes of all products(mostly surviving)




GAO report (1999)

58% of substitutions were deemed comparable (these prices enter theCPI without adjustment)

The adjustments to non-comparable substitute price broke down as:

31.1% direct quality adjustments33.4% class-mean imputation35.5% linking imputation




We make three assumptions:

1 Comparable substitutions do not involve any innovation.

2 The direct adjustments occur only with some of the incumbentimprovements to their own products (OI).

3 CD results in imputation by class-mean or linking in the proportionsabove.

Under these assumptions, CD was treated with the equivalent ofall-items-in-a-category imputation effectively 97.4% of the time in 1997.



Evidence for imputation in other countries’ PPI

Evidence from Eurostat’s Handbook on industrial producer price indices(PPI)



Alternative measurements (1)

Employment Payroll

1989–2013 0.60 0.69

1989–1995 0.77 0.97

1996–2005 0.41 0.38

2006–2013 0.69 0.83

Back



Revenue vs. Employment (1)

CMF (Census of Manufacturing Firms) is every five years so we onlyknow the *cumulative* market share growth of incumbent plants thatsurvive for at least 5 years

For these survivors, market share by revenue grew less fast thanmarket share by employment−→ hence MG is higher under revenue share than under employmentshare

CMF and LBD yield similar MG when using employment share

Back



Revenue vs. Employment (2)

Evidence using French firms

Back




New NewPlants Firms

1983–2013 0.56 0.08

1983–1995 0.60 0.29

1996–2005 0.41 -0.03

2006–2013 0.69 -0.14

Back




5 year old 3 year old 0 year oldplants plants plants

1983–2013 0.56 0.47 0.20

1983–1995 0.60 0.54 0.28

1996–2005 0.41 0.38 0.20

2006–2013 0.69 0.46 0.07

Back



Motivation for using k=5

Back


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