FCSM Session J-4: 

The Importance of 

Private Sector Data to 

Federal Statistics

Fiona Greig, Global Head of Investor Research and Policy, Vanguard

October 2023
The pros and cons of private sector data

 Timeliness – comes out faster or 

offers more of a leading indicator

 Granularity – distributional or 

demographic

 Statistical precision, given large 

sample sizes

 New measures – e.g. Times Square 

theatre ticket sales as an indication of 

willingness to risk COVID.

 Unpredictable and unpublished 

release schedules

 Micro data not available

 Not nationally representative

 Opaque data generation processes –

hard to combine with other sources

2
Vanguard is using retirement plan enrollments to provide an 

early and demographic look into hiring trends

Notes: The “hires rate” refers to new hires as a share of existing employees. The Vanguard hires rate is calculated at the firm level and is based on new enrollments in 401(k) retirement plans administered by Vanguard divided by the number of all active 401(k) plan 

participants in a given month. New hires are recorded based on their hire date rather than their retirement plan enrollment date. The last 12 months of the Vanguard hires series is adjusted upward to account for an empirically observed lag in 401(k) enrollment times for new 

hires. The series is seasonally adjusted using the X-13 ARIMA method. The dataset represents a balanced sample of firms that offer retirement plans across all sectors of the economy and of all sizes, which Vanguard has administered since January 2003. The gray bars 

indicate economic recessions.

Sources: Vanguard., The Bureau of Labor Statistics 3

 Timeliness – published before JOLTS

 Statistical precision – JOLTS has one of 

the lowest survey response rates

 Granularity – gender cuts forthcoming

 Not nationally representative. 1/3 working 

age families have no retirement plan; 

balanced panel of clients; heavily weights 

manufacturing firms.
Vanguard investor pulse: Anxiety and cash needs on the rise

November 22, 2022

White House, Treasury, and 

Federal Reserve 

Board feedback:

• ‘We are interested in timely 

indicators of economic 

hardship to understand the 

welfare impacts of inflation. 

What are the reasons for 

withdrawals and the amounts?’

• ‘Who is using the liquidity to 

support consumption? Can 

you segment this 

by income, age, and 

geography?’

4

Source: Vanguard.
Cracking the (difficult) private sector incentive problem 

Firms have many reasons NOT to share their data

• Privacy – we don’t share our data

• Contractual limitations – our clients won’t allow us 

to share our data

• Monetized data – we normally charge for this data

• Topic mis-alignment – this topic isn’t of interest to 

our business lines

• Effort – this takes time and we have limited 

resources

• Ongoing commitment – this isn’t a priority for our 

new boss

Can you give them more reasons TO share their data? 

Competitive insights: How can we win more business?

• What is our market share?

• Which segments of the market are we (under)serving?

• Where are our clients coming from and going to? 

Client insights: How can we serve our clients better? 

• What share of wallet do we have for our clients?

• What does the rest of the client’s income, spending, 

assets and liabilities look like? 

Recognition: How do we advance our brand?

• Can we be known for unique data and insights?

• Can we get credit for contributing data for good?

Learning: How do we increase our data acumen?

• Can we be on the cutting edge of responsible data use?

• Can we be early adopters of “world-class” deidentification and privacy standards and practices?

• Are there novel datasets we can gain access to?

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