Technology Shocks and Hours Revisited:
A Supply-Side Interpretation
Hikaru Saijo
University of California, Santa Cruz

Dec 26 2014, End of Year Tokyo Conference, CIGS

Introduction• Two views of business cycle: RBC and New Keynesian.
• Gali (1999)’s empirical finding: Positive technology shock

reduces aggregate hours. −→ Evidence in favor of NK.
• This paper: When household heterogeneity taken into

account, evidence in favor of RBC.

Introduction• Intertemporal substitution of labor supply central to modernbusiness cycle theories.
- Households’ ability to transfer wealth across periods critical.
• More than half of the U.S. households do not participate in

the asset market.
• Suggests theory overstates the intertemporal substitution

effect.
• Verifies this hypothesis using micro data.

CEX Data• Consumer Expenditure Survey (CEX) collected by BLS.
• Interview survey since 1980.
• Sample size ≈ 5,000 households.

CEX Data• Financial information collected: Amounts in
1 “Checking accounts, brokerage accounts and other similaraccounts”
2 “Savings accounts at banks, savings and loans, credit unions,etc”
3 “Stocks, bonds, mutual funds and other such securities”
4 “U.S. savings bonds”• Refer to households with positive responses to “Stocks, bonds,mutual funds and other such securities” as asset holders.
• According to this definition, 85% of households are assetholders.
• Later check alternative definitions.

Technology Shock• Measure technology shocks using the “purified” Solow

residuals constructed in Basu, Fernald, and Kimball (2006).
• Control for non-technological effects in measured TFP such asutilization, nonconstant returns, and imperfect competition.

All Households

TechnologyHours6Percentage growth420−2−4Corr(∆ Ht, ∆ Zt) = 0.00
−61982

1984

1986

1988

1990

1992

1994

1996

Non-Asset Holders

Technology
Hours

6Percentage growth420−2−4Corr(∆ Ht, ∆ Zt) = −0.18
−6
1982

1984

1986

1988

1990

1992

1994

1996

Asset Holders

Technology
Hours

6Percentage growth420−2−4Corr(∆ Ht, ∆ Zt) = 0.47
−61982

1984

1986

1988

1990

1992

1994

1996

Measuring Impulse Responses• Run a regression on current and lagged technology:∆Ht = a +4X

cj ∆Zt−j + etj=0• Obtain impulse responses in levels by cumulating coefficientson the technology growth (the cj ’s).

Aggregate Impulse Response: BLS vs. CEX Data

Percent

BLSCEX

332.5

2.5

22

1.5

1.5

11

0.5

0.5

00

−0.5

−0.5

−1

−1

−1.5

0

12
Years

34

−1.5

0

12
Years

34

Household-Level Impulse Response

Percent

Asset holders

Non−asset holders

2.5

2.5

22

1.5

1.5

11

0.5

0.5

0

0

−0.5

−0.5

−1

−1

−1.5

−1.5

−2−2−2.5

0

12
Years

34

−2.5012Years

34

Household-Level Impulse Response• When technology improves,• Asset holders increase hours.
• Non-asset holders reduce hours.

• Within asset holders, the hours increase is larger forhouseholds with larger asset holdings.
• Results robust to
X Including lagged dependent variables.
X Controlling for other macro shocks.

Household-Level Impulse Response• Results mixed if other definitions are used to split households.
• Savings accounts.
• U.S. savings bonds.

IRF

IRFInterpretation• Return on these assets less correlated with technology.
• People hold these assets mainly for precautionary reasons /long-term savings (e.g., retirements).
• Liquidity constraints unlikely to explain the finding. (Detailsin paper)Structural Estimation• Estimate a DSGE model using the impulse response to atechnology shock.
• Full asset market participation model estimated withaggregate IRF only −→ Substantial nominal rigidities.
• Limited asset market participation model estimated withaggregate and household IRF −→ Flexible prices and wages.

Model• DSGE model with limited asset market participation.
• (1 − χ) fraction of households participate in the stock andbond market and the remaining χ fraction do not.
• When χ = 0, standard model.

Model• Asset holders:maxa aaE0a{Ct ,Ht ,St ,Bt }

∞
Xt=0



(Hta )1+η
a
β t ln(Cta − bCt−1)−,1+η

subject toaa
Pt Cta +PtE Sta +Bta ≤ Wt Hta +(DtE +PtE )St−1+Rt−1 Bt−1+Tta .

• Non-asset holders:max E0{Ctn ,Htn }

∞
Xβt



(Htn )1+η
nln(Ctn − bCt−1)−t=0

subject to
Pt Ctn ≤ Wt Htn + Ttn .

1+η,Model1

Intermediate goods firms
X Monopolistically competitive, maximize dividends.
X Price adjustment cost, investment adjustment cost, variablecapital utilization.
X Technology shock: ln zt = z̄ + ln zt−1 + t .

2

Final goods firms
X Perfectly competitive, produce final goods by combining
intermediate goods.

3

Wage setting
X Households sell differentiated labor service to “labor packer”.
X Wage adjustment cost.

4

Central bank
X Taylor-type rule responding to inflation and output growth.

Estimation• Some parameters are pre-fixed. The participation rate is set to15% (source: CEX).
• Minimum distance method: Match the model IRF with thedata.
• Variables used: IRF ofOutput, consumption, investment, hours (all households),
hours (asset holders), hours (non-asset holders), real wage,inflation, FF rate, utilization rate.

Estimation
δ2 /δ1ηbκ
ϕφP

Description
Utilization curvature
Inverse Frisch elasticity
Consumption habit
Investment adj. cost
Elasticity of labor b/w
asset and non-asset holders
Price adj. cost

φWWage adj. cost

ρRTaylor rule smoothing

Baseline

Full participation

0.00

0.00(0.000)(0.007)

0.03

0.00

(0.002)(0.001)0.83

0.84(0.003)(0.028)

0.00

0.00

(0.005)(0.013)8.44–(0.003)

0.04

33.74

(0.002)(0.013)0.00

200.00(0.002)

0.07

0.90

(0.002)

φπ
φY
100σz

Taylor rule inflation
Taylor rule output
Technology shock

1.00

2.38

(0.000)(0.008)

0.88

1.10

(0.002)(0.016)

0.55

0.54

(0.072)(0.036)

Estimation
δ2 /δ1ηbκ
ϕφP

Description
Utilization curvature
Inverse Frisch elasticity
Consumption habit
Investment adj. cost
Elasticity of labor b/w
asset and non-asset holders
Price adj. cost

φW

Wage adj. cost

ρR

Taylor rule smoothing

Baseline

Full participation

0.00

0.00

(0.000)(0.007)

0.03

0.00

(0.002)(0.001)

0.83

0.84

(0.003)(0.028)

0.00

0.00

(0.005)(0.013)8.44–(0.003)

0.04

33.74

(0.002)(0.013)0.00

200.00(0.002)

0.07

0.90

(0.002)

φπ
φY
100σz

Taylor rule inflation
Taylor rule output
Technology shock

1.00

2.38

(0.000)(0.008)0.88

1.10(0.002)(0.016)0.55

0.54(0.072)(0.036)

Impulse Response, Baseline Model

Percent

Asset holders

Non−asset holders

2.5

2.5

22

1.5

1.5

11

0.5

0.5

0

0

−0.5

−0.5

−1

−1

−1.5

−1.5

−2−2

−2.5

0

Other variables

12Years

3

4

−2.5

0

12
Years

34

Intuition• Positive technology shock −→ Higher wages and return on

investment.

Intuition• Positive technology shock −→ Higher wages and return on

investment.
• Asset holders increase hours to reap the benefit of the higher

return.

Intuition• Positive technology shock −→ Higher wages and return oninvestment.
• Asset holders increase hours to reap the benefit of the higher

return.
• Non-asset holders reduce hours because of the income effect.

Intuition• Positive technology shock −→ Higher wages and return oninvestment.
• Asset holders increase hours to reap the benefit of the higher

return.
• Non-asset holders reduce hours because of the income effect.
• Most households non-asset holders −→ In the aggregate,hours fall.

Impulse Response, Increasing Price and Wage Stickiness

Percent

Asset holders

Non−asset holders

2.5

2.5

22

1.5

1.5

11

0.5

0.5

00−0.5−0.5−1−1−1.5−1.5−2−2−2.5

0

12
Years

34−2.50

12
Years

34

Intuition• Positive technology shock −→ Higher markups in the shortrun.

Intuition• Positive technology shock −→ Higher markups in the shortrun.
• Lower wages and return on investment.

Intuition• Positive technology shock −→ Higher markups in the shortrun.
• Lower wages and return on investment.
• Asset holders reduce hours.

Conclusion• Exploit cross-sectional heterogeneity at the household level.
• Finding: Negative response of aggregate hours to technology

shocks driven by the income effect.
• RBC with limited asset market participation consistent withdata.
• New Keynesian model inconsistent with micro evidence.

Backup slides

Household-Level Impulse Response

Percent

Savers
43

3

2

2

1

1

0

0

−1

−1−2−2−3−3−4−4−5−5−6

ReturnNon−savers

40

12Years

34−6012Years

34

Household-Level Impulse Response

Percent

Saving bond holders
3221100−1−1−2−2−3−3−4−4−5ReturnNon−saving bond holders

3012Years

34−5012Years

34

Impulse Response, Baseline ModelOutput

Consumption

3322

1

100−1−1024

Investment242

100−20Real wage

24Inflation

2Hours (all households)

6−4−1024

Nominal interest rate
104

Utilization

402

1−1−1

0.5

Return211.5000−2024−202

4−302

4−2024