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Working Under Pressure: Improving Labor Productivity through Financial Innovation Aletheia Donald, World Bank

Presented at RAND Behavioral Finance Forum 2019. Learn more at https://www.rand.org/education-and-labor/centers/befi/conference/2019.html

https://www.rand.org/education-and-labor/centers/befi/conference/2019.html

Job Loss Expectations, Durable Consumption and Household Finances

Evidence from Linked Survey Data

Yuri Pettinicchi (MEA Munich) Nathanael Vellekoop (University of Toronto)

RAND Behavioral Finance Forum 2019

October 3, 2019

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Research Questions

1. How predictive are job loss expectations of workers?

2. Do job loss expectations affect car acquisitions and savings?

"Do you think that there is any chance that you might lose your jobin the coming 12 months? You can indicate this in terms of apercentage. [0 − 100]"

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Motivation

1. Predictive power of expectations– Job loss: Stephens, RESTAT 2004; Hendren, AER 2017– Income: Dominitz and Manski, JASA 1997; Dominitz, JEctrics 2001

2. Mixed evidence on job loss expectations and consumption– Stephens, RESTAT 2004; Klemm, 2012

3. Some anticipation behavior of actual unemployed– Consumption: Gruber, AER 1997; Hendren, AER 2017; Benito, 2006– Small durables: Browning and Crossley, JEEA 2009– Financial assets: Basten, Fagereng and Telle, JMCB 2016

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Labor Market in The Netherlands

� 7 million workers employed (2010-2016).� Unemployment rate: 5-7%� Workers with flexible contract: 21-26%

– Difference in employment protection� Universal unemployment insurance

– Entitlement criteria: (i) no wrongful or own termination, available for work, (ii) search requirement (monitored + sanctions) and (iii) it depends on length of employment prior tospell

– Replacement rate is 70% of average earnings in the 12 months prior (and 75% for the first 2 months)

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Data

1 Survey– Two representative household panels for the Netherlands: DHS and LISS

(2008-2018)

2 Administrative (Statistics Netherlands)– Monthly payroll data for the universe of firms (public and private)– Monthly car acquisitions (universe of car registrations)– Annual household assets and liabilities: deposits, stocks + bonds, net

worth

1+2 Linking (2010-2016)– 85% gives consent to be linked– Anonymous identifiers

Job Loss Expectations: Over Time

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Job Loss Expectations: Distribution

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Labor Market Flows

TransitionNo change in 12 months (baseline)Any job loss

78.1%21.9% 100%

New job, same firm 3.8% 17%New job, new firm 6.7% 31%Unemployed 3.8% 17%Other job loss 7.6% 35%

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– Job loss defined as loss of contract– Unemployed defined as collecting unemployment benefits– Self-employment or retirement are excluded

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Results

1. How predictive are job loss expectations ofworkers?

2. Do job loss expectations affect car acquisitions?

3. Do job loss expectations affect savings?

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1. Predictive Power

Same Firm New FirmAny Job Loss New Job, New Job, Unemployed Other Job Loss

(1) (2) (3) (4) (5)

Job loss expectation [0-100] 0.89∗∗∗ 0.05 0.54∗∗∗ 1.46∗∗∗ 0.21∗∗∗(0.00) (0.10) (0.10) (0.10) (0.10)

Controls yes yes yes yes yesTime fixed effects yes yes yes yes yesMean dependent variable[%] 22.0 3.9 6.8 3.9 7.8N households 6,140 6,029 6,089 5,983 6,048N observations 19,628 19,163 19,461 19,003 19,217

2. Car Purchases – ValueBuy Car

(1)ln(value car)

(2)Buy Car

(3)ln(value car)

(4)

Job loss expectation [0-100]

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1.7(5.9)

-1.79∗

(1.04)Probability job loss [21-40] 4.7 0.36

(4.4) (0.82)Probability job loss [41-60] -2.8 -1.58∗∗

(4.4) (0.80)Probability job loss [61-80] -4.7 -2.56

(9.2) (1.70)Probability job loss [81-100] 11.4 0.19

(7.3) (1.39)Controls yes yes yes yesTime fixed effects yes yes yes yesMean dependent variable 10.5% 0.57 10.5% 0.57N households 6,047 6,051 6,047 6,051N observations 18,865 18,890 18,865 18,890

Higher job loss expectations are negatively correlated with car value of acquired car.

2. Car Purchases – Type of CarOld Car

(1)New Car

(2)Old Car

(3)New Car

(4)

Job loss expectation [0-100]

acquiring new cars.

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0.09(0.06)

-0.28∗∗

(0.11)Probability job loss [21-40] 0.07 -0.06

(0.04) (0.08)Probability job loss [41-60] 0.02 -0.25∗∗

(0.04) (0.09)Probability job loss [61-80] 0.01 -0.21

(0.09) (0.17)Probability job loss [81-100] 0.17∗∗ -0.14

(0.07) (0.14)Controls yes yes yes yesTime fixed effects yes yes yes yesMean dependent variable [%] 8.7 1.9 8.7 1.9N households 6,046 5,970 6,046 5,970N observations 18,858 18,268 18,858 18,268

Higher job loss expectations are negatively correlated with probability of

3. Savings and Wealth Holdings –Flows

Savings Stocks Financial Wealth Savings (1)(2) (3) (4)

Stocks (5)

Financial Wealth (6)

7.96∗∗∗

(2.91)

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-0.04(0.78)

6.76∗∗

(3.05)Job loss expectation [0-100]

Probability job loss [21-40]



109.9(223.0)497.6∗∗(204.6)567.6

(435.5)

-147.6∗∗

(67.6)-4.7

(54.2)126.7

(118.0)

-28.9(247.5)528.2∗∗(214.4)736.1∗(435.5)

Probability job loss [81-100] 581.3 -55.9 180.7(408.5) (103.2) (438.4)

Controls yes yes yes yes yes yesTime fixed effects yes yes yes yes yes yesMean dependent variable [Euro] 417.8 85.5 518.4 417.8 85.5 518.4N households 4,347N observations 13,033

Higher job loss expectations are positively correlated with savings flows.

3. Savings and Wealth Holdings – End of YearBalancesSavings

(1)Stocks Fin. Wealth Savings Stocks Fin. Wealth (2)

(3) (4) (5) (6)

0.048∗∗∗ (0.014)

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0.009(0.007)

0.056∗∗∗ (0.019)

Job loss expectation




2.38∗∗

(0.97)2.33∗∗

(1.00)1.87

(1.61)

-0.75∗

(0.40)-0.08(0.42)0.04

(0.70)

1.54(1.20)2.26∗(1.25)1.91

(2.01)Probability job loss [81-100] 3.83∗

∗

(1.82)

1.64∗

(0.99)5.27∗∗

(2.48)Controls yes yes yes yes yes yesTime fixed effects yes yes yes yes yes yesMean dependent variable [1,000 Euro] 20.46 4.25 25.50 20.46 4.25 25.50N households 4,347N observations 13,033

Low job loss expectations associated with some rebalancing of financial portfolios.

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Conclusions

1. Predictive power� Using linked administrative data we find that workers predict very well

transitions into unemployment and firm-to-firm transitions.� Suggests that workers adjust search effort and/or desired wages

2. Car acquisitions� Find that higher job loss expectations are related to smaller propensities to buy

cars, especially new cars3. Household finances

� Higher job loss expectations are related to larger inflows indeposits� Some evidence for rebalancing of financial portfolio into deposits

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Thank you for your time!

Any comments welcome at [email protected]

mailto:[email protected]

Linear predictions - unconditional

01 0

2 03 0

4 05 0

6 07 0

0 2 0 8 0 1 0 04 0 6 0j o b l o s s

A n y j o b l o s s

Figure: Any Job Loss

01 0

2 03 0

4 05 0

6 07 0

0 2 0 8 0 1 0 04 0 6 0j o b l o s s

U n e m p l o y e d

Figure: New Job, New Firm

01 0

2 03 0

4 05 0

6 07 0

0 2 0 8 0 1 0 04 0 6 0j o b l o s s

N e w j o b , n e w f i r m

Figure: Unemployed

01 0

2 03 0

4 05 0

6 07 0

0 2 0 8 0 1 0 04 0 6 0j o b l o s s

O t h e r j o b l o s s

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Figure: Other Job Loss

Plotted regression coefficients0

. 51

1. 5

0 2 0 4 0 6 0 8 0 1 0 0j o b l o s s

A n y j o b l o s s

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Figure: Any Job Loss

Plotted regression coefficients

−. 4−. 2

0. 2

. 4. 6

0 2 0 8 0 1 0 04 0 6 0j o b l o s s

N e w j o b , s a m e f i r m

Figure: Unemployed

0. 5

11. 5

2

0 2 0 8 0 1 0 04 0 6 0j o b l o s s

U n e m p l o y e d

Figure

0. 2

. 4. 6

. 8

0 2 0 8 0 1 0 04 0 6 0j o b l o s s

N e w j o b , n e w f i r m

Figure: New Job, New Firm

−.2

0 .

2 .4

.6

0 2 0 8 0 1 0 04 0 6 0j o b l o s s

O t h e r j o b l o s s

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Figure: Other Job Loss

AARP PUBLIC POLICY INSTITUTE | AARP.ORG/PPI | © 2018 AARP. ALL RIGHTS RESERVED

Jobs and Precautionary SavingsCatherine S. HarveySenior Policy AdvisorAARP Public Policy Institute

https://www.aarp.org/ppi/


Working Under Pressure: Improving Labor Productivity through Financial Innovation

Aletheia Donald

Jobs and Precautionary Savings



Summary and Contributions


• Do redistributive pressures in family/friend networks tax earnings and discourage people from working more?

• Do private locked savings accounts alleviate the “kin tax” and encourage productivity?

• Innovative application of commitment mechanism• Potential to disrupt a social norm

“And who will help me eat the bread?”



Implications

11/25/192Jobs and Precautionary Savings

• Social networks as financial support • Addressing universal barriers to saving

Creative Commons



Questions


• How much of the effect is due to having a formal account for the first time?

• What are the opportunities and limitations to scale?

Creative Commons



Job Loss Expectations, Durable Consumption and Household Finances: Evidence from Linked Survey Data

Nathanael Vellekoop




Summary and Contributions


• How do workers’ expectations of losing their job– Predict actual job loss and job transitions?– Affect savings and consumption behavior?

• Creative use of linked administrative datasets• Clear description of results and limitations• Timely and relevant

Getty Images



Implications


• Leading indicator of recession?• Redesigning unemployment insurance for a

changing labor market

Creative Commons



Questions


• What about trends in work? Shorter tenure, older workers, delayed retirement

• Are cars special?

WTOP


Understanding How Salient Information Affects Financial Decisions

Katherine Carman, BeFi Director

BEHAVIORAL FINANCE FORUM

Photo by mmphoto/Adobe Stock

Thank You

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Engage

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#BeFiForum

@RANDCorporation @AARPpolicy

Highlights of Day

• Mediating Investor Attention• Consumer Credit Behavior• Information and Advice• Innovations in Policy and Industry• Retirement Savings• Investor Behavior• Precautionary Savings

4

BeFi 2020Financial Security Over the Lifespan

Call for Papers

BEHAVIORAL FINANCE FORUM

Photo by Monkey Business/AdobeStock

Call for Papers

• We are releasing our call for papers early to encourage researchers, policymakers, and practitioners to think about new research and to develop partnerships now that may help to advance our understanding of financial behavior and allow for testing of new ideas that support financial security.

6

Possible Topics

• Encouraging precautionary savings to support emergency financial needs

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Possible Topics

• Encouraging precautionary savings to support emergency financial needs• Household financial decision making around critical life

events, such as caregiving, divorce, and late-career changes

8

Possible Topics

• Encouraging precautionary savings to support emergency financial needs• Household financial decision making around critical life

events, such as caregiving, divorce, and late-career changes• Effective mechanisms for households to balance liquidity with

long-term financial goals

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Possible Topics

• Analysis of underserved and/or understudied populations, such as older workers and immigrants

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Possible Topics

• Analysis of underserved and/or understudied populations, such as older workers and immigrants• Shifting from a savings mindset into a spenddown mindset in

retirement

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Possible Topics

• Analysis of underserved and/or understudied populations, such as older workers and immigrants• Shifting from a savings mindset into a spenddown mindset in

retirement• The impact of changes in behavior in one domain on other

financial choices

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