How Do Average Hours Worked Vary with Development? Cross-Country Evidence and Implications Alexander Bick, Arizona State University Nicola Fuchs-Sch¨ undeln, Goethe University Frankfurt, CFS and CEPR David Lagakos, UC San Diego and NBER

April 18, 2016

How do Average Hours Vary Across World Income Distribution?

• No clear conclusion thus far; limited by lack of cross-country data • This paper: answer using new data set

- Harmonize 81 countries of all income levels - Draw on nationally representative household surveys - Challenge: surveys not already standardized - Large efforts to maximize international comparability

How do Average Hours Vary Across World Income Distribution?

• No clear conclusion thus far; limited by lack of cross-country data • This paper: answer using new data set

- Harmonize 81 countries of all income levels - Draw on nationally representative household surveys - Challenge: surveys not already standardized - Large efforts to maximize international comparability

Main Empirical Findings

• Average hours worked per adult are higher in poor countries

• True for both sexes, by broad age group, education and sector

• Magnitudes substantial: 29 hours/week in poorest countries,

compared to 19 hours per week in richest

• Extensive and intensive margins both at play; extensive more for

poorest vs middle income, intensive more for middle vs rich

Relevant for Development Accounting and Welfare

• Relevant for “development accounting” & theories of development

- Cross-country differences in output/hour larger than output/worker - Evidence against theories of income differences based on work effort / work ethic (e.g. Landes, 1999; Leamer, 1999) • Relevant for “welfare” differences across countries

- Example: Comparing North Americans and Africans - Penn World Tables: c roughly ∼ 5% as high for Africans - We show h ∼ 50 % higher too; welfare differences larger than suggested by c differences alone

Relevant for Development Accounting and Welfare

• Relevant for “development accounting” & theories of development

- Cross-country differences in output/hour larger than output/worker - Evidence against theories of income differences based on work effort / work ethic (e.g. Landes, 1999; Leamer, 1999) • Relevant for “welfare” differences across countries

- Example: Comparing North Americans and Africans - Penn World Tables: c roughly ∼ 5% as high for Africans - We show h ∼ 50 % higher too; welfare differences larger than suggested by c differences alone

This Talk

1

Measuring average hours worked across countries

2

Empirical findings

3

Implications for development accounting

4

Model + implications for welfare

Measuring Hours Worked

Constructing Our Data Set • Use surveys from 2005 or closest available year

• Use only nationally representative surveys of households

the European Union Labor Force Surveys (27), IPUMS (7), other individual surveys (47)

• Challenge: surveys not standardized; required large efforts to

harmonize

• Full data set: 81 countries; focus on 43 “core countries” with most

comparable data

Core Countries We define core countries as those that meet the following criteria 1

Survey covers whole calendar year, 5,000+ individuals

2

Actual hours worked (not usual) at all jobs (not just primary job)

3

In the last week, or recent reference week

4

Producing output counted in NIPA (not e.g. home child care)

Measuring Hours Worked

• Adult ≡ age 16+ • Employed ≡ working in prior week or self reports having regular

employment relationship • Three main measures of hours worked 1

Average hours per adult (unconditional)

2

Employment rate

3

Average hours per worker (conditional)

Empirical Findings

Average Weekly Hours per Adult 50 45 KHM

40 Hours per Week

35

TZA

LAOVNM

PER

30 GHA

25

PAK

UGA RWA

MNG IDN

COL USA

BWA

LVA EST CYP CZE PRT CHE SVN GRC GBR AUT NOR LTUSVK DNK POL HUN SWE FIN DEU ESP NLD BGR FRA ITA BEL

TUR MUS ROM

20 15

IRQ

10 5 0 6.5

7

7.5

8

8.5 9 9.5 ln(GDP per Capita)

10

10.5

11

Income Group Average

Males

Females

Average Hours per Prime (Aged 25-55) 50 45

KHM

40

PER

LAO GHA

35 Hours per Week

VNM

TZA

MNG

UGA

30

COL

IDN PAK

RWA

25 20

LVA USA CZE SVN BWA LTUEST CYP PRT GRC ROM SVK AUT CHE POLHUN MUS DNK GBR FIN BGR DEU TUR SWE FRA NOR ESP ITABEL NLD

IRQ

15 10 5 0 6

6.5

7

7.5

8 8.5 9 ln(GDP per Capita) Income Group Average

9.5

10

10.5

11

Average Hours per Old (Aged 55+) 50 45 40 KHM

Hours per Week

35 30

BWA

TZA

25

PER

GHA LAO

20

RWA UGA

15

PAK VNM

IDN COL

MNG

10

IRQ

5

NOR USA CYP EST PRT CHE MUS SWE LVA DNK ROM CZE GBR TUR LTU GRCFIN NLD DEU SVK HUN SVNESP BGR POL FRA AUT ITA BEL

0 6

6.5

7

7.5

8 8.5 9 ln(GDP per Capita) Income Group Average

9.5

10

10.5

11

Average Hours per Adult: Differences in Means

Age Group All Young Prime Old

Country Income Group Low-High Low-Middle Middle-High 10.2∗∗∗ 7.3∗∗∗ 2.9∗∗ 9.4∗∗∗ 7.5∗∗∗ 1.9∗ ∗∗∗ ∗∗ 7.7 6.7 1.0 ∗∗∗ ∗∗ 13.3 8.2 5.1∗∗∗

Average Weekly Hours Per Adult: Broader Sets of Countries

Core Countries Core + Partial-Year All Countries

Country Income Group Low-High Low-Middle Middle-High 10.2∗∗∗ 7.3∗∗∗ 2.9∗∗ ∗∗∗ ∗∗ 6.0 4.0 2.0∗∗ 5.8∗∗∗ 3.5∗∗ 2.3∗∗

Comparison to US Time-Series (Ramey & Francis, 2009) 50 45

Hours per Week

40 35 30 25 20 15 10 5 0 6

7

8 9 ln(GDP per Capita) 2005 Core Countries

10

US Time−Series

11

Account for Findings by Disaggregating Further?

• Are aggregate hours differences due to composition differences, by

e.g. education or sector? • We look at hours per adult by: less than secondary, secondary, more

than secondary • Also hours per worker at those employed in agriculture, services,

manufacturing

Account for Findings by Disaggregating Further?

• Are aggregate hours differences due to composition differences, by

e.g. education or sector? • We look at hours per adult by: less than secondary, secondary, more

than secondary • Also hours per worker at those employed in agriculture, services,

manufacturing

Account for Findings by Disaggregating Further?

• Are aggregate hours differences due to composition differences, by

e.g. education or sector? • We look at hours per adult by: less than secondary, secondary, more

than secondary • Also hours per worker at those employed in agriculture, services,

manufacturing

Differences in Average Hours by Education

Average Hours by Age and Country Income Education All All (Ages 25+, Non-missing Educ.) Ages 25+ Less than Secondary Secondary Completed More than Secondary

Country Income Low Middle 29.3 22.0 33.9 25.3 32.6 38.1 39.5

20.9 29.6 30.9

Group High 19.1 21.0 11.9 23.6 26.9

Differences in Average Hours by Education

Education All All (Ages 25+, Non-miss Educ.) Ages 25-55 Less than Secondary Secondary Completed More than Secondary

Country Income Group Low-High Low-Middle Middle-High 10.2∗∗∗ 7.3∗∗∗ 2.9∗∗ 12.9∗∗∗ 8.6∗∗ 4.3∗∗∗ 13.3∗∗∗ 10.5∗∗∗ 10.4∗∗∗

9.2∗∗∗ 7.4∗∗∗ 7.6∗∗

4.1∗∗ 3.1∗ 2.8∗

Differences in Hours per Worker by Sector

All All (Non-missing Sec.) Agriculture Manufacturing Services

Country Income Group Low-High Low-Middle Middle-High -1.4 6.6∗∗∗ 5.2∗∗∗ 5.2∗∗∗ -0.9 6.1∗∗∗ -2.6 0.1 -2.7 8.1∗∗∗ 1.9 6.2∗∗∗ 13.5∗∗∗ 5.1∗∗ 8.4∗∗∗

Hours per Worker in Agriculture

50 45

COL

TZA KHM

40 LAO GHA

Hours per Week

35

PAK

MNG

IRQ ROM

ESP

LTU

PER

30

GBR EST DEU HUN CZESVN SVK BEL GRC FIN ITA SWE CYP DNK POL

USA

LVA

VNM

IDN

AUT FRA

BWA

MUS

NOR NLD

PRT

BGR RWA

25

UGA

20 15 10 5 0 6.5

7

7.5

8

8.5 9 ln(GDP per Capita)

9.5

10

10.5

11

Hours per Worker in Manufacturing

KHM

50 45

GHA

RWA TZA

40

PAK VNM

MNG

LAO

COL PER

IDN IRQ

UGA

BWA ROM MUS BGR

Hours per Week

35 30

GRC LVAPOL USA EST HUN CZE LTU SVK PRTSVN CYP GBR DEUAUT ESP ITA FIN BEL FRA DNK NOR SWE NLD

25 20 15 10 5 0 6.5

7

7.5

8

8.5 9 ln(GDP per Capita)

9.5

10

10.5

11

Hours per Worker in Services

RWA

50

KHM

UGA TZA

45

PAK GHA LAO VNM

BWA

PER ROM

40

IRQ

35 Hours per Week

COL

IDN MNG

MUS BGR

30 25

LVA GRC POLSVK HUN CZE USA EST PRT LTU CYP SVN ITA AUT DEU ESP FRA GBR FIN BEL DNK SWE NOR NLD

20 15 10 5 0 6.5

7

7.5

8

8.5 9 ln(GDP per Capita)

9.5

10

10.5

11

Account for Findings by Extensive-Intensive Margin?

• Higher employment rates in poor countries?

• Greater hours worked per worker in poor countries?

• We’ll look at the aggregates (males and females separately in paper)

Employment Rates 100 90 UGA RWA TZA

Employment Rate (in %)

80

KHM LAO VNM

PER

70 GHA

IDN MNG

60 50

PAK

NOR CHE USA DNK NLD GBR CYP SWE PRT COL AUT SVN FIN CZE MUS BWALVA LTUEST ESP DEU FRA ROM SVK BEL GRC ITA TUR POLHUN BGR

40 IRQ

30 20 10 0 6

6.5

7

7.5

8 8.5 9 ln(GDP per Capita) Income Group Average

9.5

10

10.5

11

Average Weekly Hours Per Worker 50 KHM PAK

45

TZA

40 Hours per Week

35 30

COL

MNG GHAVNM IDN IRQ LAO

PER

BWA TUR

ROM MUS BGR

RWA UGA

LVA GRC POL SVK USA EST HUNCZE LTU CYP PRT SVN AUT ITA DEU ESP CHE GBR FIN FRA BEL DNK SWE NOR NLD

25 20 15 10 5 0 6

6.5

7

7.5

8 8.5 9 ln(GDP per Capita) Income Group Average

9.5

10

10.5

11

Implications for Development Accounting

Development Accounting

• Accounting for differences in GDP per worker across countries

• Caselli (2005); Klenow and Rodriguez Clare (1997); Hall and Jones

(1999); Hsieh and Klenow (2010)

• Every study has ignored differences in average hours per worker

Development Accounting

Low GDP per Adult GDP per Worker GDP per Hour

7.7 6.2 5.2

Country Income Group Middle High 30.5 33.3 27.1

100.0 100.0 100.0

High/Low 12.9 16.1 19.2

⇒ Hours don’t help account for income differences; make puzzle worse

⇒ Evidence against theories based on higher labor input in richer countries

Implications for Welfare

Quantifying Welfare Differences • Welfare metrics

(Jones and Klenow, 2015)

,→ Consumption equivalent variation of flow utility over cons. and leisure ⇒ We need to take a stand on preferences • Standard Neo-Classical Growth Model

(Prescott, 2004)

1

Add subsistence consumption

2

Calibrated version predicts cross-country hours per adult reasonably well

(Ohanian, Raffo and Rogerson, 2008)

* Benchmark exercise abstracts from taxes & government consumption 3

Use calibrated preferences for welfare analysis

Standard Neo-Classical Growth Model • Flow utility

u(c, h) = ln(c − c¯) − αv (h) (1) Marginal rate of substitution b/w leisure & cons. = the price ratio αv 0 (h) =w 1/(c − c¯)

(2) Profit-maximization: wage = marginal product of labor w = (1 − θ)Ak θ h−θ = (1 − θ)y /h

(1) & (2): hv 0 (h) =

(1−θ)

( yc − yc¯ )α

Calibration hv 0 (h) = 

1

2

3

(1 − θ) (1 − θ)  ⇔ α=   c¯ c c¯ 0 −y α − y y hv (h)

c y

Given average of yc , and yc¯ in high-income countries, set α to match avg. hours per adult in high-income countries Given α, yc , and yc¯ in each country, predict hours per adult in each country Specification v (h) (a) −ln(1 − h) 1 h1+1/φ , φ ∈ {1, 2, ∞} (b) 1+1/φ

θ



c, y

0.3224

$1 per day

PWT

Predictions

Data Model Log φ=∞ φ=2 φ=1

Mean Hours

¯ low inc. h ¯ high inc. h

¯ middle inc. h ¯ high inc. h

21.8

1.53

1.15

21.0 21.9 20.7 20.3

1.35 1.53 1.31 1.22

1.09 1.15 1.08 1.06

• Frisch φ = ∞ gives best fit of the slope

• The higher the labor supply elasticity, the better the fit of the slope

Predictions for Frisch φ = ∞ 50

Hours per Week

40

30

20

10

0 6.5

7

7.5

8

8.5 9 9.5 ln(GDP per Capita) Data

10

10.5

11

Model Inputs

Welfare Analysis • Consumption equivalent variation

(Jones & Klenow, 2015)

Details

- Welfare of country i is λi s.t. u(ci , hi ) = u(λi · cˆHI , hˆHI ) - Use empirical ci , hi and calibrated parameters to pin down λi

Welfare Analysis • Consumption equivalent variation

(Jones & Klenow, 2015)

Details

- Welfare of country i is λi s.t. u(ci , hi ) = u(λi · cˆHI , hˆHI ) - Use empirical ci , hi and calibrated parameters to pin down λi

Low

Country Income Group Middle High

High/Low

Consumption

6.4

26.3

100

15.7

+ Hours Per Adult Log φ=∞ φ=2 φ=1

4.5 4.6 3.4 2.6

23.8 23.9 22.2 21.7

100 100 100 100

22.1 21.7 29.7 38.4

Average Hours per Week on Home Production Country Income Group

Cooking Cleaning Childcare Shopping Collecting Water Total Hours

Low

Middle

High

8.9

8.1

6.1

(5)

(6)

(9)

6.0

7.1

5.7

(5)

(6)

(9)

6.0

6.4

2.6

(7)

(6)

(9)

2.0

2.2

3.7

(5)

(6)

(9)

3.5

2.0

0.0

(8)

(2)

(0)

26.4

25.8

18.1

Conclusions

• Adults work 50% more hours on average in poorest countries

• Largely consistent with model of subsistence consumption needs

(though still trying to reconcile within-country patterns)

• Welfare differences across countries larger than suggested by GDP

• Individuals in low-income countries are “leisure poor” in addition to

being “consumption poor”

Extra Slides

Average Weekly Hours per Adult Males 50 45

KHM

40

PAK

Hours per Week

35

PER COL

LAOVNM TZA

30

GHA

IRQ

UGA RWA

25

IDN MNG

20

TUR USA BWA MUS CYP CZEGRC CHE LVA AUT PRT NOR EST SVN GBR SVK ROM DNK NLD ESP LTU DEU POLHUN ITASWE FIN FRA BEL BGR

15 10 5 0 6

6.5

7

7.5

8 8.5 9 ln(GDP per Capita)

9.5

10

10.5

11

Income Group Average

Return

Average Weekly Hours per Adult Females 50 45 40 TZA

Hours per Week

35

KHM LAOVNM

30 25

PER

GHA

MNG

UGA RWA

20

IDN

15 10

BWA USA LVA ESTPRT COL ROM CYP SVN NOR LTUSVK CZE DNK FIN CHE BGR POLHUN SWE AUT GBR GRCFRA MUS DEU ESP NLD BEL ITA TUR

PAK

5 IRQ

0 6

6.5

7

7.5

8 8.5 9 ln(GDP per Capita)

9.5

10

10.5

11

Income Group Average

Return

Welfare Analysis for Frisch φ = ∞

1.4

Ratio of Welfare to Consumption

BGR

1.2

POL LTU HUN

ROM UGA

1

RWA

TUR

IRQ

MUS

GHA PAK

LVA

FRA ITA GBR BEL DEU ESP GRC SWE

SVK PRT EST CYP SVN CZE

.8

TZA

IDN

NLD FIN AUT DNK CHE USA

COL NOR

LAO MNG KHM VNM

.6

PER

BWA

.4 6

6.5

7

7.5

8 8.5 9 ln(GDP per Capita)

9.5

10

10.5

11

Average Hours Per Adult by Education

Education All All (Ages 25+, Non-missing Educ.) Ages 25+ Less than Secondary Secondary Completed More than Secondary

Country Income Low Middle 29.3 22.0 33.9 25.3 32.6 38.1 39.5

20.9 29.6 30.9

Group High 19.1 21.0 11.9 23.6 26.9

Average Hours Per Worker by Sector

Sector All All (Non-missing Sec.) Agriculture Manufacturing Services

Country Income Low Middle 40.2 41.6 40.3 41.2 36.8 36.7 44.8 42.9 47.8 42.7

Group High 35.0 35.1 39.4 36.7 34.3

How Do Average Hours Worked Vary with ...

Apr 18, 2016 - Main Empirical Findings. • Average hours worked per adult are higher in poor countries. • True for both sexes, by broad age group, education ...

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