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Measuring Wealth Effects Using U.S. State Data Xia Zhou Christopher Carroll

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Measuring Wealth Effects Using U.S. State Data Xia Zhou Christopher Carroll
Measuring Wealth Effects Using U.S. State Data
Xia Zhou1
Christopher Carroll2
1 Fannie
2 Johns
Mae
Hopkins University
March 18, 2011
X.Zhou, C.Carroll (FNMA, JHU)
Measuring wealth effects using regional data
March 18, 2011
1 / 16
motivation
Motivation
Q: What is the relation between movements in wealth and subsequent
movements in spending?
Problem: Not clear this can be answered using aggregate data:
Not enough aggregate data.
Too many other things move along with wealth and consumption.
Contribution of this paper:
Construct state-level data on consumption and wealth.
Examine wealth effects using these data.
X.Zhou, C.Carroll (FNMA, JHU)
Measuring wealth effects using regional data
March 18, 2011
2 / 16
motivation
Further motivation: Distinguish housing vs. financial
wealth effects
Financial and housing wealth effects could be different:
Changes in one type of wealth might be viewed as more permanent
than the other.
Tax treatment of capital gains on the two types of wealth may be
different.
Stockholders might behave differently from homeowners.
Current literature finds mixed results, varying with data employed.
X.Zhou, C.Carroll (FNMA, JHU)
Measuring wealth effects using regional data
March 18, 2011
3 / 16
motivation
Data
Previous literature has used aggregate and household-level data
Aggregate data: aggregation problems, simultaneity problems.
household-level data: poor measurement of important variables.
Advantages of regional data
All states share the same monetary and federal system.
Because of heterogeneity across states, regional data should have less
simultaneity problems than aggregate data.
X.Zhou, C.Carroll (FNMA, JHU)
Measuring wealth effects using regional data
March 18, 2011
4 / 16
motivation
Data
Previous literature has used aggregate and household-level data
Aggregate data: aggregation problems, simultaneity problems.
household-level data: poor measurement of important variables.
Advantages of regional data
All states share the same monetary and federal system.
Because of heterogeneity across states, regional data should have less
simultaneity problems than aggregate data.
Contribution: Construct the regional data needed to conduct the wealth
effect study.
X.Zhou, C.Carroll (FNMA, JHU)
Measuring wealth effects using regional data
March 18, 2011
4 / 16
motivation
Some regional data exists, but has issues
The state-level financial wealth data used in Case, Quigley and Shiller
(2002): 1982:1-1999:4
Mutual funds data is only
available for 5 nonconsecutive
years ⇒ assume constant asset
distribution across states for
years without real data; lose
regional variations.
X.Zhou, C.Carroll (FNMA, JHU)
Proportion of mutual funds of
total stock market wealth
0.3
Share of mutual funds out of total stock wealth
There is no state-level financial
assets data ⇒ use mutual
funds data; assume constant
proportion of mutual funds out
of financial assets.
0.2
0.1
0.0
1975q1
1983q1
1991q1
1999q1
2006q1
Date
Source: FFA
Measuring wealth effects using regional data
March 18, 2011
5 / 16
motivation
Limitations with currently available state-level
consumption data
No state-level consumption data exists.
X.Zhou, C.Carroll (FNMA, JHU)
Measuring wealth effects using regional data
March 18, 2011
6 / 16
motivation
Limitations with currently available state-level
consumption data
No state-level consumption data exists.
I
Solution: use state-level retail sales data.
X.Zhou, C.Carroll (FNMA, JHU)
Measuring wealth effects using regional data
March 18, 2011
6 / 16
motivation
Limitations with currently available state-level
consumption data
No state-level consumption data exists.
I
Solution: use state-level retail sales data.
Several sets of retail sales measures are available for U.S. states.
X.Zhou, C.Carroll (FNMA, JHU)
Measuring wealth effects using regional data
March 18, 2011
6 / 16
motivation
Limitations with currently available state-level
consumption data
No state-level consumption data exists.
I
Solution: use state-level retail sales data.
Several sets of retail sales measures are available for U.S. states.
I
No systematic research comparing their quality.
Description of existing state-level consumption data
C HS
C SMM
C CQS
C GHO
C ZHOU
Data sources
Monthly Retail Trade Survey
Sales & Marketing Management
Regional Financial Associates
State Government Sales Tax Collections
C GHO + taxable retail sales
gross retail sales
X.Zhou, C.Carroll (FNMA, JHU)
Works using data
Hess and Shin (1998)
Del Negro (1998)
Asdrubali, Sorensen, and Yosha (1996)
Del Negro (1998)
Luengo-Prado and Sorensen (2006)
Case, Quigley and Shiller (2002)
Garrett, Hernandez-Murillo,
and Owyang (2004)
Ravina (2005)
Zhou (2010)
Measuring wealth effects using regional data
Time range
1978M1-1996M12
States
19
1963-1998
& 2000-present
51
1977Q3-2006Q4
51
1970Q1-present
45
1970Q1-present
45
March 18, 2011
6 / 16
Contributions of this study
Contributions of this study
Creates a new panel dataset for the financial wealth of U.S. states,
which I argue is a reliable measure of financial wealth growth at the
state level.
X.Zhou, C.Carroll (FNMA, JHU)
Measuring wealth effects using regional data
March 18, 2011
7 / 16
Contributions of this study
Contributions of this study
Creates a new panel dataset for the financial wealth of U.S. states,
which I argue is a reliable measure of financial wealth growth at the
state level.
Constructs a state-level measure of consumption that improves
significantly on existing data sources.
X.Zhou, C.Carroll (FNMA, JHU)
Measuring wealth effects using regional data
March 18, 2011
7 / 16
Contributions of this study
Contributions of this study
Creates a new panel dataset for the financial wealth of U.S. states,
which I argue is a reliable measure of financial wealth growth at the
state level.
Constructs a state-level measure of consumption that improves
significantly on existing data sources.
Estimates stock and housing wealth effects using these data.
I
I
Large but sluggish housing wealth effect (consistent with the existing
literature).
No evidence of significant stock wealth effects (current literature shows
if stock wealth effect exists, it shows much faster than housing wealth
effect; but could just be simultaneity).
X.Zhou, C.Carroll (FNMA, JHU)
Measuring wealth effects using regional data
March 18, 2011
7 / 16
Contributions of this study
Quality of the new financial wealth data
Data source: a private company has all data for each and every
individual account from more than 85 financial institutions.
I
Among them, there are 15 of the top 20 banks, and all the top 15
annuity issuers.
There are tens of millions of records for each time period.
I
Covers about 40% of total U.S. financial assets.
X.Zhou, C.Carroll (FNMA, JHU)
Measuring wealth effects using regional data
March 18, 2011
8 / 16
Contributions of this study
Quality of the new financial wealth data
The new financial wealth data at the aggregate level
Stock wealth growth rate
0.10
0.00
−0.10
−0.20
2001h1
2002h1
2003h1
2004h1
2005h1
2006h1
Date
FFA
X.Zhou, C.Carroll (FNMA, JHU)
IXI
Measuring wealth effects using regional data
March 18, 2011
9 / 16
Contributions of this study
Quality of the new financial wealth data
The new financial wealth data at the state level
0.10
Idiosyncratic stock wealth growth rate
Stock wealth growth rate
0.2
0.1
0.0
−0.1
0.05
0.00
−0.05
−0.10
−0.2
2001h1
2001h1
2002h1
2003h1
2004h1
2002h1
2003h1
2004h1
2005h1
Date
2005h1
Date
Arizona
Arizona
Florida
Florida
Other states
Note: Idisyncratic growth is defined as the difference in growth rates between AZ and FL, and other states
X.Zhou, C.Carroll (FNMA, JHU)
Measuring wealth effects using regional data
March 18, 2011
10 / 16
Contributions of this study
Quality of the new consumption data
It improves C GHO by incorporating gross retail sales or taxable retail
sales published by state tax agencies.
The construction of its growth rate is transparent and does not
involve any assumed models.
At the aggregate level
At the state level: Virginia
0.10
Real per capita retail sales growth
Real per capita aggregate retail sales growth
0.10
0.05
0.00
−0.05
0.05
0.00
−0.05
−0.10
−0.10
1970
1975
1980
1985
1990
1995
2000
Year
Growth of sum(c_ZHOUG)
Growth of sum(c_GHO)
Growth of sum(c_SMM)
X.Zhou, C.Carroll (FNMA, JHU)
2005
−0.15
1978
Growth of U.S. retail sales
Measuring wealth effects using regional data
1983
1988
1993
1998
Year
HS
Zhou
GHO
March 18, 2011
SMM
11 / 16
Contributions of this study
The wealth effect estimation
Three sets of consumption data were used
“Best Data”: gross retail sales or taxable retail sales published by
state tax agencies only.
“All Data”: “Best Data” plus C GHO .
“Good Data”: “All Data” with outliers taken care of.
Estimation equation is
f
h
+ ∆ε̃t ,
∆c̃i,t = αt + β1 ∆ỹi,t−2 + β2 ∆w̃i,t−2
+ β3 ∆w̃i,t−2
Ci,t −Ci,t−1
, ∆ỹi,t
Yi,0
h −W h
Wi,t
i,t−1
f
, and ∆w̃i,t
Yi,0
where ∆c̃i,t =
=
h =
∆w̃i,t
=
X.Zhou, C.Carroll (FNMA, JHU)
Yi,t −Yi,t−1
,
Yi,0
f −W f
(Wi,t
i,t−1 )
.
Yi,0
Measuring wealth effects using regional data
March 18, 2011
12 / 16
Contributions of this study
The wealth effect estimation
Impact on consumption of a one dollar change in housing wealth that
took place two years prior: about 5 cents.
The stock wealth effect: insignificant and economically small.
Large standard errors indicate statistically insignificant differences
between housing and stock wealth effects.
Regression results
Best Data
0.578
(0.533)
All Data
0.962∗∗
(0.382)
Good Data
0.775∗∗∗
(0.297)
f
∆wi,t−2
-.028
(0.033)
-.002
(0.031)
0.002
(0.022)
h
∆wi,t−2
0.046
(0.041)
2.478
(Accepted)
24
0.206
-.004
0.051∗
(0.026)
2.37
(Accepted)
90
0.051
0.06
0.042∗∗
(0.019)
2.466
(Accepted)
90
0.116
0.11
∆yi,t−2
β2 = β3
OBS
R̄ 2
Partial R̄ 2
X.Zhou, C.Carroll (FNMA, JHU)
Measuring wealth effects using regional data
March 18, 2011
13 / 16
Post 2005
Housing wealth and consumption during the recession
Q: What fraction of the consumption declines after 2006 can be associated with
the concurrent housing wealth changes.
Actual vs. predicted consumption growth: 6 states with the highest/lowest housing wealth
growth
1.1
Pred−−Top
1.05
1
Pred−−Bot
.95
Actl−−Bot
Actl−−Top
.9
2000
2002
2004
2006
2008
2010
year
avg cumu. consumption g. of 6 states /w highest housing wealth g. btw 01−06
avg cumu. consumption g. of 6 states /w lowest housing wealth g. btw 01−06
predicted consumption growth from regressing on labor income and housing wealth
predicted consumption growth from regressing on labor income and housing wealth
Note: JHU)
Indexed to 2000h1
X.Zhou, C.Carroll (FNMA,
Measuring wealth effects using regional data
March 18, 2011
14 / 16
Post 2005
For the top 6 states, almost 50 percent of the consumption drop in 2007 can
be associated with the housing wealth decline in the same year.
This possible association, however, declines over time to 23 percent in 2008,
and finally about 11 percent in 2009.
There is no evidence for strong association between consumption change
and housing wealth change for states with bottom housing wealth growth.
Top States
Bot States
Year
Index of
actl. c
Index of
pred. c
2006
2007
2008
2009
2006
2007
2008
2009
1.0940
1.0912
1.0188
0.9204
0.9841
0.9859
0.9859
0.9373
1.0940
1.0927
1.0760
1.0643
0.9841
0.9824
0.9784
0.9763
X.Zhou, C.Carroll (FNMA, JHU)
actl. ∆ci,t
pred. ∆ci,t
%∆ci,t associated
h
with ∆wi,t
−0.26%
−6.64%
−9.65%
−0.12%
−1.53%
−1.08%
47.43%
23.04%
11.23%
0.19%
−0.01%
−4.92%
−0.17%
−0.41%
−0.22%
−92.34%
4856.95%
4.43%
Measuring wealth effects using regional data
March 18, 2011
15 / 16
Post 2005
Conclusion
Contributions:
Creates a new panel dataset for the financial wealth of U.S. states.
Constructs a state-level measure of consumption.
Estimates stock and housing wealth effects using these data; help us
understand consumption changes during the recession.
X.Zhou, C.Carroll (FNMA, JHU)
Measuring wealth effects using regional data
March 18, 2011
16 / 16
Post 2005
Conclusion
Contributions:
Creates a new panel dataset for the financial wealth of U.S. states.
Constructs a state-level measure of consumption.
Estimates stock and housing wealth effects using these data; help us
understand consumption changes during the recession.
THANK YOU!
X.Zhou, C.Carroll (FNMA, JHU)
Measuring wealth effects using regional data
March 18, 2011
16 / 16
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