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What the Cyclical Response of Advertising Reveals about Markups and - - PowerPoint PPT Presentation

What the Cyclical Response of Advertising Reveals about Markups and other Macroeconomic Wedges Robert E. Hall Hoover Institution and Department of Economics Stanford University Conference in Honor of James Hamilton Federal Reserve Bank of San


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What the Cyclical Response of Advertising Reveals about Markups and

  • ther Macroeconomic Wedges

Robert E. Hall Hoover Institution and Department of Economics Stanford University Conference in Honor of James Hamilton Federal Reserve Bank of San Francisco 19 September 2014 ·

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Theorem:

Let R be the ratio of advertising expenditure to the value of

  • utput. Let −ǫ be the residual elasticity of demand. Let m be

an exogenous multiplicative shift in the profit margin. Then the elasticity of R with respect to m is ǫ − 1, which is a really big number. ·

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Papers on variations in market power

◮ Bils (1987), Nekarda and Ramey (2010, 2011) ◮ Rotemberg and Woodford (1999) ◮ Bils and Kahn (2000) ◮ Chevalier and Scharfstein (1996) ◮ Edmond and Veldkamp (2009)

·

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Literature on advertising

◮ Dorfman and Steiner (1954) ◮ Bagwell, Handbook of IO (2007), 143 pages!

·

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Wedges

Profit-margin wedge m raises the markup of price over cost—for example, lowers residual elasticity of demand

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Wedges

Profit-margin wedge m raises the markup of price over cost—for example, lowers residual elasticity of demand Product-market wedge f raises the purchaser’s price relative to the seller’s price—for example, a sales tax ·

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Propositions

The elasticity of the advertising ratio R with respect to the profit-margin wedge m at the point f = m = 1 is ǫ − 1.

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Propositions

The elasticity of the advertising ratio R with respect to the profit-margin wedge m at the point f = m = 1 is ǫ − 1. The elasticity of the advertising ratio with respect to the product-market wedge f is −1.

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Propositions

The elasticity of the advertising ratio R with respect to the profit-margin wedge m at the point f = m = 1 is ǫ − 1. The elasticity of the advertising ratio with respect to the product-market wedge f is −1. The elasticity of the labor share λ with respect to the profit-margin wedge m is −1.

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Propositions

The elasticity of the advertising ratio R with respect to the profit-margin wedge m at the point f = m = 1 is ǫ − 1. The elasticity of the advertising ratio with respect to the product-market wedge f is −1. The elasticity of the labor share λ with respect to the profit-margin wedge m is −1. The elasticity of the labor share with respect to the product-market wedge f is −1. ·

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From these propositions,

log R = (ǫ − 1) log m − log f + µR

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From these propositions,

log R = (ǫ − 1) log m − log f + µR and log λ = − log m − log f + µλ, where µR and µλ are constant and slow-moving influences apart from m and f. ·

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Solving for log m and log f yields

log m = log R − log λ ǫ + µm

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Solving for log m and log f yields

log m = log R − log λ ǫ + µm and log f = − log λ − log R − log λ ǫ + µf Here µm and µf are constant and slow-moving influences derived in the obvious way from µR and µλ. ·

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Advertising is a capital stock

At = at + (1 − δ)At−1.

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Advertising is a capital stock

At = at + (1 − δ)At−1. κt = r + δ 1 + r vt. ·

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Advertising spending / private GDP

0.70 0.75 0.80 0.85 0.90 0.95 1.00 1.05 1.10 1.15 1.20 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

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Labor share

100 102 104 106 108 110 92 94 96 98 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

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Profit-margin wedge

‐0.08 ‐0.06 ‐0.04 ‐0.02 0.00 0.02 0.04 0.06 0.08 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

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Product-market wedge

‐0.08 ‐0.06 ‐0.04 ‐0.02 0.00 0.02 0.04 0.06 0.08 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

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Periodicity

Periodicity: number of years between one peak and and the next in a cyclical component

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Periodicity

Periodicity: number of years between one peak and and the next in a cyclical component Periodicity of a component at frequency ω is 2π/ω ·

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Filtering out higher periodcities

Baxter and King, 1999

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Filtering out higher periodcities

Baxter and King, 1999 Linear filter φ(L)

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Filtering out higher periodcities

Baxter and King, 1999 Linear filter φ(L) The time series ˆ xt = φ(L)xt, with adroit choice of φ(L), can emphasize business-cycle periodicities—ranging from once every two years to once every 5 years—and attenuate higher periodicities

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Filtering out higher periodcities

Baxter and King, 1999 Linear filter φ(L) The time series ˆ xt = φ(L)xt, with adroit choice of φ(L), can emphasize business-cycle periodicities—ranging from once every two years to once every 5 years—and attenuate higher periodicities Gain applied to a periodicity with frequency ω is |φ(eiω)| ·

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Gain functions for filters that emphasize cyclical movements

0.0 0.2 0.4 0.6 0.8 1.0 1.2 2 3 5 6 8 9 11 12 13 15 16 18 19

Normalized gain Periodicity, years First difference Two sided

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Calculated Filtered Time Series for the Profit-Margin Wedge

‐0.08 ‐0.06 ‐0.04 ‐0.02 0.00 0.02 0.04 0.06 0.08 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

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Calculated Filtered Time Series for the Product-Market Wedge

‐0.08 ‐0.06 ‐0.04 ‐0.02 0.00 0.02 0.04 0.06 0.08 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

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Regressions of the filtered markup wedge on the employment rate

Employment timing Filter Coefficient Standard error Years Upper-tail p- value for coefficient = -0.1 First difference 0.02 (0.05) 1951-2010 0.004 Symmetric 0.01 (0.04) 1952-2008 0.003 First difference 0.00 (0.05) 1952-2010 0.014 Symmetric 0.00 (0.04) 1953-2008 0.006 Contemporaneous Lagged one year

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Regressions of the filtered product-market wedge on the employment rate

Employment timing Filter Coefficient Standard error Years Upper-tail p- value for coefficient = 0 First difference

  • 0.09

(0.18) 1951-2010 0.298 Symmetric

  • 0.06

(0.17) 1952-2008 0.368 First difference

  • 0.84

(0.14) 1952-2010 0.000 Symmetric

  • 0.82

(0.14) 1953-2008 0.000 Contemporaneous Lagged one year

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Role of the two wedges in employment volatility

Lt = θ log mt + ρ log ft + xt

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Role of the two wedges in employment volatility

Lt = θ log mt + ρ log ft + xt Master wedge = mf

ǫ ǫ−1

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Role of the two wedges in employment volatility

Lt = θ log mt + ρ log ft + xt Master wedge = mf

ǫ ǫ−1

Reasonable to take θ = ρ

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Role of the two wedges in employment volatility

Lt = θ log mt + ρ log ft + xt Master wedge = mf

ǫ ǫ−1

Reasonable to take θ = ρ From Hall, JPE, 2009, I take θ = −1 as the main case, but examine the consequences of lower and higher values ·

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Contributions of Wedges to Employment Movements as Functions of the Parameter θ

‐1.0 ‐0.5 0.0 0.5 1.0 1.5 2.0 ‐0.5 ‐1 ‐1.5 ‐2

Fraction of covariance with employment rate Effect of wedge on employment rate, θ Contribution of product‐market wedge Contribution of profit‐ margin wedge Contribution of

  • ther influences on

employment

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Conclusions about the profit-margin wedge

The profit-margin wedge extracted from the advertising/GDP ratio R and the labor share λ has low volatility and no apparent cyclical movements

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Conclusions about the profit-margin wedge

The profit-margin wedge extracted from the advertising/GDP ratio R and the labor share λ has low volatility and no apparent cyclical movements The wedge is close to uncorrelated with both this year’s employment and last year’s

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Conclusions about the profit-margin wedge

The profit-margin wedge extracted from the advertising/GDP ratio R and the labor share λ has low volatility and no apparent cyclical movements The wedge is close to uncorrelated with both this year’s employment and last year’s The evidence against a countercyclical profit-margin mechanism for cyclical movements of employment seems strong ·

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Conclusions about the product-market wedge

The product-market wedge f is not correlated with current-year employment change, but is strongly correlated with previous-year employment change

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Conclusions about the product-market wedge

The product-market wedge f is not correlated with current-year employment change, but is strongly correlated with previous-year employment change The wedge’s adverse effect operates not in the year of a recessionary employment contraction, but rather in the following year

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Conclusions about the product-market wedge

The product-market wedge f is not correlated with current-year employment change, but is strongly correlated with previous-year employment change The wedge’s adverse effect operates not in the year of a recessionary employment contraction, but rather in the following year The product-market wedge is responsible for the fall in the advertising/GDP ratio R and for the decline in the labor share λ, in the aftermath of an employment contraction ·

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Other influences

◮ A Hicks-neutral productivity index, h ◮ A labor wedge or measurement error, fL ◮ A capital wedge or measurement error, fK ◮ An advertising wedge or measurement error, fA

·

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Model with other influences

R = κA pQ = α fA fQ m (m − 1)ǫ + 1 ǫ

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Model with other influences

R = κA pQ = α fA fQ m (m − 1)ǫ + 1 ǫ λ = W pQ = 1 fL fQ m γ ǫ − 1 ǫ ·

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Conclusions

◮ The Hicks-neutral productivity index h and the capital

wedge or measurement error fK affect neither the advertising/sales ratio R nor the labor share λ.

◮ The new wedge fA affects R with an elasticity of −1 and

the new wedge fL affects λ with an elasticity of −1; the margin wedge m remains the only wedge that has a high elasticity.

◮ The advertising wedge or measurement error, fA, lowers R

in the same way that fQ does.

◮ The labor wedge or measurement error, fL, lowers λ in the

same way that fQ does.

◮ Equal values of fA and fL have the same effect as fQ of the

same value. ·

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Role of the two wedges in employment volatility

Lt = −θ log mt − δ log ft + xt

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Role of the two wedges in employment volatility

Lt = −θ log mt − δ log ft + xt Prior: θ = δ = 1 ·

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Optimal price

max

p,A

p f − c

  • p−ǫ ¯

p ¯

ǫAα ¯

A −¯

α − κA

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Optimal price

max

p,A

p f − c

  • p−ǫ ¯

p ¯

ǫAα ¯

A −¯

α − κA

p∗ = ǫ ǫ − 1 f c ·

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Profit-margin shock

p = m p∗

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Profit-margin shock

p = m p∗ p = m f ǫ ǫ − 1 c ·

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Optimal advertising

α A Q p f − c

  • = κ

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Optimal advertising

α A Q p f − c

  • = κ

κA pQ = αp/f − c p

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Optimal advertising

α A Q p f − c

  • = κ

κA pQ = αp/f − c p R = κA pQ = α(m − 1)ǫ + 1 f m ǫ

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Optimal advertising

α A Q p f − c

  • = κ

κA pQ = αp/f − c p R = κA pQ = α(m − 1)ǫ + 1 f m ǫ With f = m = 1, R = α ǫ ·

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Labor share

λ = W pQ

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Labor share

λ = W pQ λ = γ c Q pQ = γ ǫ − 1 ǫ 1 f m ·

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Implications of Alternative Values of the Residual Elasticity of Demand, with θ = −1

θ β m θ β f θ β m θ β f θ β m θ β f

  • 0.05

0.12

  • 0.02

0.09

  • 0.01

0.08 (0.09) (0.18) (0.05) (0.18) (0.02) (0.18)

  • 0.02

0.07

  • 0.01

0.06 0.00 0.05 (0.08) (0.17) (0.04) (0.17) (0.02) (0.18)

  • 0.01

0.84 0.00 0.84 0.00 0.83 (0.09) (0.15) (0.05) (0.14) (0.02) (0.14) 0.00 0.82 0.00 0.82 0.00 0.82 (0.08) (0.14) (0.04) (0.14) (0.02) (0.14) Implied contributions of wedges to cyclical movements in the employment rate ε, residual elasticity of demand 3 6 12 Employment timing Filter Contempo- raneous First difference Symmetric Lagged one year First difference Symmetric 35

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Implications of Alternative Values of the Depreciation Rate

θ β m θ β f θ β m θ β f θ β m θ β f

  • 0.15

0.22

  • 0.02

0.09 0.11

  • 0.04

(0.07) (0.17) (0.05) (0.18) (0.04) (0.18)

  • 0.16

0.21

  • 0.01

0.06 0.14

  • 0.09

(0.06) (0.17) (0.04) (0.17) (0.03) (0.17) 0.14 0.69 0.00 0.84

  • 0.02

0.85 (0.07) (0.15) (0.05) (0.14) (0.04) (0.14) 0.17 0.65 0.00 0.82

  • 0.03

0.86 (0.06) (0.15) (0.04) (0.14) (0.04) (0.14) Employment timing Filter Implied contributions of wedges to cyclical movements in the employment rate δ , annual rate of depreciation 1 0.6 0.3 Contempo- raneous First difference Symmetric Lagged one year First difference Symmetric 36

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Covariance decomposition

V(Lt) = θ Cov(mt, Lt) + θ Cov(ft, Lt) + Cov(xt, Lt)

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Covariance decomposition

V(Lt) = θ Cov(mt, Lt) + θ Cov(ft, Lt) + Cov(xt, Lt) 1 = θ Cov(mt, Lt) V(Lt) + θ Cov(ft, Lt) V(Lt) + Cov(xt, Lt) V(Lt) .

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Covariance decomposition

V(Lt) = θ Cov(mt, Lt) + θ Cov(ft, Lt) + Cov(xt, Lt) 1 = θ Cov(mt, Lt) V(Lt) + θ Cov(ft, Lt) V(Lt) + Cov(xt, Lt) V(Lt) . 1 = θβm + θβf + βx ·

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