Examples of Micropayments Data

James McAndrewsFederal Reserve Bank of New York

2008 World Congress on National Accounts and Economic Performance Measures for Nations

May 13, 2008The views expressed in this paper are those of the authors and do not necessarily represent the views of the Federal Reserve

Bank of New York or of the Federal Reserve System.

Payment Data

Central banks are usually operators of the large-value payment system.

Many important economic policy questions are involved, related to efficiency, risk, and equity.

Payment Data

In recent years, central bank economists have begun collecting disaggregated data on payment activity.

• Summary reports.• Hypothesis tests.

Payment Data

In this presentation, I’ll show two examples of using micropayments data using the Federal Reserve’s large-value payment system, Fedwire.

Changes in the Timing Distribution of Fedwire Funds

Transfers, Armantier, Arnold, McAndrews (2008)

Payment TimingA large literature has examined the economics of payment timing: Theory: Angelini (1999, 2000)Bech and Garratt (2003)Kahn, McAndrews, Roberds (2003)Mills and Nesmith (2007)Bech (2007)Empirical workMcAndrews and Rajan (2000)Becher, Galbiati, and Tudela (2007)

1998

2006

0.00

0.25

0.50

0.75

1.00

Perc

ent o

f Dai

ly Va

lue

of P

aym

ents

21 22 23 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18Hour

Notes: Mean daily percent of total payment value settled in each minute. Values exclude payments related to CHIPS, CLS, DTC and P&I payment funding.Sources: Federal Reserve Bank of New York, Authors' calculations.

Fedwire Funds Value Time Distribution, 1998 and 2006

Five stylized changes in the Fedwire Funds value time distribution

1998 to 2006

1.The distribution of value settled became more concentrated and less variable.

2.The highest peak of activity is later.

3. Three distinct peaks, 16:30, 17:00, and the third (the sharpest) at 17:11.

4.The 1998 distribution exhibits regular clock effects which virtually disappear in 2002.

5.The 2006 distribution shows higher activity at 08:00 and 08:30, and the 08:00 peak is only present in 2006.

Evolution of the value time distribution

0.000.250.500.751.00

0.000.250.500.751.00

0.000.250.500.751.00

21 23 1 3 5 7 9 11 13 15 17 21 23 1 3 5 7 9 11 13 15 17 21 23 1 3 5 7 9 11 13 15 17

21 23 1 3 5 7 9 11 13 15 17 21 23 1 3 5 7 9 11 13 15 17 21 23 1 3 5 7 9 11 13 15 17

21 23 1 3 5 7 9 11 13 15 17 21 23 1 3 5 7 9 11 13 15 17 21 23 1 3 5 7 9 11 13 15 17

1998 1999 2000

2001 2002 2003

2004 2005 2006Perc

ent o

f Tot

al D

aily

Valu

e

HourNotes: Mean daily percent of total payment value settled in each minute. Values exclude payments related to CHIPS, CLS, DTC and P&I payment funding.Sources: Federal Reserve Bank of New York, Authors' calculations.

Fedwire Funds Value Time Distributions by Year

These shifts in the value time distribution are statistically significant

25 96

-8

-6

-4

-2

0

2

4

6

8

Min

utes

diff

eren

ce b

etwe

en 2

006

and

1998

0 20 40 60 80 100Percentile of Time of Value

Notes: Minutes subtracted/added to each percentile until a Mann-Whitney rank-sum test is insignificant at 5% level.Sources: Federal Reserve Bank of New York, Authors' calculations.

Mann-Whitney U Test on Percentiles of Value Time, 1998 to 2006

Estimation strategy:reduced form regressions, one OLS

regression per percentile

• Reduced-form equation characterizing equilibria of coordination game.

• 100 independent OLS regressions• 2220 observations: business days between

March 1998 and December 2006.• Same set of independent variables in each

regression.

Variables are grouped into 5 categories

1) Value and Volume.

2) Federal Reserve Policies and Operations.

3) Settlement System Activities.

4) Other Control Variables.

5) Calendar Effects.

0

.02

.04

.06

.08

-.1

-.05

0

0

.05

.1

-.05

0

.05

.1

.15

0

500

1000

1500

0

.05

.1

.15

12 13 14 15 16 17 18 12 13 14 15 16 17 18 12 13 14 15 16 17 18

12 13 14 15 16 17 18 12 13 14 15 16 17 18 12 13 14 15 16 17 18

0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100

0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100

1: Inter-bank payment value 2: Customer payment value 3: Federal funds deliveries

4: Federal funds returns 5: Payments >= $10 6: Number of Payments

Coef

ficie

nt a

nd 9

5% C

I

PercentileNotes: Independent OLS regressions with Newey-West standard errors (max lag = 10), for the 2nd-99th percentile of value time. The color of the point indicates the signficance of the coefficient, Red = 1%, Green = 5%, Dark Gray = insig. The upper x-axis is the mean 2006 time for selected percentiles. Obs = 2220 for each regression.

Value and VolumeRegressions of the Fedwire Funds Value Time Percentiles

The role of settlement institutions on Fedwire Funds payment timing

18 Jan 2000CHIPS moves closing

to 17:00

22 Jan 2001CHIPS Intraday Finality

15:00

15:30

16:00

16:30

17:00

17:30

18:00

18:30

19:00

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Coincident with:DTC and CHIPS CHIPSDTC Neither

Notes: 7 days settling after 19:00 were excluded. Values exclude payments related to CHIPS, CLS, DTC and P&I payment funding.Sources: Federal Reserve Bank of New York, Authors' calculations.

Time of Peak 10 Mintues of Fedwire Value

Discussion

Why should Fedwire value move with CHIPS timing?

Four hypotheses:• Liquidity cascade• Customer credit cascade• Resolution of uncertainty• Focal point

Economic significance:Factors influencing the 1998 – 2006

change in the 75th Percentile

We “subtract out” the time trend, and ask how much can different variables explain of the later settlement.

• Volume and value—40 percent

• Changes in CHIPS—30-20=10 percent

• Increase in concentration—40 percent

Conclusions

Our results tend to support that the provision of liquidity, settlement institution activity, volume and value transferred, and industry structure are all influential in explaining changes in the timing of payment on Fedwire.

Segmentation in the U.S. Money Market: Fed funds and Eurodollars McAndrews, in progress

Close-up of Eurodollar-Fed funds interest rate spread in recent period

Values traded in the market segments

Values traded in the market segments: close-up of recent period

Predicted spreads from an EGARCH estimation

2002-2004 8/2007 –4/2008

Payments data

The studies examined are examples of work that seeks to test hypotheses with appropriate microdata about a previously unexamined part of the financial system.

Protocols need to be established to share these data with researchers outside of central banks.