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The Effect of Dividends
on Consumption
MICROSOFT’S $32 BILLION CASH dividend of December 2004 was the largest
corporate payout ever. Classical models of finance and consumption-saving
decisions predict that this dividend will have little effect on the consumption
of Microsoft investors. Under the assumptions of Merton Miller and Franco
Modigliani, for example, investors can always reinvest unwanted dividends,
or sell shares to create homemade dividends, and thereby insulate their
preferred consumption stream from corporate dividend policies. 1 Thus, in
traditional models, the division of stock returns into dividends and capital
gains is a financial decision of the firm that has no “real” consequence for
investor consumption patterns.
Yet there are a number of reasons to think that dividend policy, and
dividends more generally, may indeed affect consumption. Most obviously,
the popular advice to “consume income, not principal” suggests a potentially
widespread mental accounting practice in which investors do not view
dividends and capital gains as fungible, as in the homemade dividends
story and traditional theories of consumption, but rather place them into
M A L C O L M B A K E R
Harvard University
S T E F A N N A G E L
Stanford University
J E F F R E Y W U R G L E R
New York University
We thank Yakov Amihud, John Campbell, Alok Kumar, Erik Hurst, Martin Lettau, James Poterba, Enrichetta Ravina, Hersh Shefrin, Joel Slemrod, Nicholas Souleles, and seminar participants at the American Finance Association 2007 Meetings in Chicago and at Babson College, the University of British Columbia, the Brookings Institution, the University of Colorado, HEC, INSEAD, Imperial College (University of London), the National Bureau of Economic Research Working Group on Behavioral Finance, the New York University Stern School of Business, the Stanford Graduate School of Business, and the University of Southern California for helpful comments. We thank Terrance Odean for providing data. Malcolm Baker gratefully acknowledges financial support from the Division of Research of the Harvard Business School.
- Miller and Modigliani (1961).
different mental accounts from which they have different propensities to
consume. 2 This behavior is also consistent with a belief that dividends,
unlike capital gains, represent permanent income. Less exotic but equally
realistic frictions, such as transaction costs (of making homemade dividends)
and taxes, can also lead an investor to favor consuming dividends before
capital appreciation.
Although the dividends-consumption link is a potentially fundamen-
tal one between corporate finance and the real economy, little empirical
research has pursued the issue. The reason is probably that the most easily
available data on consumption and dividends are aggregate time-series data,
which have several limitations. Among other challenges, such data require
one to identify the effect of a smooth aggregate dividend series using a small
number of data points; they combine investors and noninvestors; and they
face an essentially prohibitive endogeneity problem: omitted variables such
as business conditions will jointly affect consumption, dividends, and cap-
ital appreciation, making it difficult to establish the causality behind any
observed correlations.
This paper studies the effect of dividends on investor consumption using
two micro data sets that reveal and exploit powerful cross-sectional variation
in dividend receipts and capital gains. The first is the Consumer Expenditure
Survey (CEX), which is a repeated cross section with data on expenditure
measures and self-reported dividend income and capital gains (or losses).
Our CEX sample includes several hundred households per year between
1988 and 2001. The second data set includes the trading records of tens of
thousands of households with accounts at a large discount brokerage from
1991 through 1996.^3 Although these portfolio data do not contain an explicit
expenditure measure, they complement the CEX by allowing us to accu-
rately measure net withdrawals from the portfolio, a novel dependent vari-
able in its own right and a precursor to expenditure. The data set also allows
us to measure the withdrawal rates of different types of dividend income,
including ordinary, special, and mutual fund dividends, which allows for
finer comparisons.
We start with an analysis of the CEX data. Our most basic approach
is to regress consumption on realized dividend income, controlling for
232 Brookings Papers on Economic Activity, 1:
- Mental accounting behavior of this sort is discussed in detail in Thaler and Shefrin (1981), Shefrin and Statman (1984), and Shefrin and Thaler (1988).
- This data set was introduced by Barber and Odean (2000).
Although our findings are surely driven by a combination of factors,
mental accounting seems among the most compelling. The notion that
many investors do not view dividends and capital gains as fungible seems
especially plausible in light of the popular adage to “consume income, not
principal.” Mental accounting offers a natural explanation for both our main
findings and certain finer results. For example, ordinary dividends are more
likely to be mentally accounted for as current income than are large spe-
cial dividends. Hence, the mental accounting framework predicts a higher
propensity to consume from ordinary dividends than from large special
dividends. This is what we find in net withdrawals (where we can measure
different types of dividends). Tax and transaction cost explanations, on
the other hand, do not predict this pattern.
This paper builds on earlier work that uses aggregate data.^4 Some papers
have viewed the equality of the propensity to consume from dividends and
corporate retained earnings, not capital appreciation, as the null hypothesis
of interest and found weak evidence that corporate saving affects consump-
tion. Other papers find little evidence that capital gains and losses have an
effect on aggregate consumption. 5
Our results also relate to evidence, consistent with the existing literature
on the consumption response to windfalls, that consumers have a relatively
high propensity to consume moderately sized cash windfalls.^6 It appears that
ordinary dividends are treated like moderate-size windfalls. However, our
analysis differs from the existing literature in that we focus on the relative
propensity to consume two forms of income, dividends and capital gains,
234 Brookings Papers on Economic Activity, 1:
- See Feldstein (1973), Feldstein and Fane (1973), Peek (1983), Summers and Carroll (1987), Poterba (1987), and Poterba (2000).
- To our knowledge, the only paper to use micro data in this context is a contempora- neous paper by Rantapuska (2005). He analyzes Finnish investor registry data and finds that there is little reinvestment within two weeks after receipts of dividends or tender offer proceeds. His results are broadly consistent with and complementary to ours, but there are some important differences. In particular, the CEX data allow us to look at actual consump- tion, not just reinvestment. Moreover, reinvestment may occur over horizons much longer than two weeks, an issue that our brokerage account data allow us to investigate. Finally, automatic reinvestment plans are absent in Finland but common in the United States, so the effect of dividends on consumption and reinvestment could be quite different in any case.
- For instance, Souleles (1999) finds that consumption responds to federal income tax refunds whether or not the household faces borrowing constraints, and Souleles (2002) documents that consumption responds to preannounced tax cuts. Related studies in this vein include Bodkin (1959), Kreinin (1961), Wilcox (1989), Parker (1999a), Stephens (2003), and Johnson, Parker, and Souleles (2006).
holding their sum, total return, constant. More broadly, this study falls into
a growing literature on “household finance.” 7
At the end of the paper, we briefly consider what our estimates imply
for the response of aggregate consumption to the May 2003 dividend tax
cuts. Alternative scenarios suggest a consumption stimulus in the range of
$8.3 billion to $49.9 billion, which is not insubstantial in relation to a stan-
dard deviation of total personal consumption expenditure of $66 billion
over the preceding five years.
Evidence from the Consumer Expenditure Survey
Our first data set is drawn from the Consumer Expenditure Survey,
obtained from the Inter-University Consortium for Political and Social
Research at the University of Michigan. The strength of the CEX is its
detailed data on household consumption and demographics. Its compara-
tive weakness, for our purpose, is that dividends and portfolio returns are
self-reported and thus likely to be noisy. After introducing the data and
definitions, we describe our empirical methodology and then present regres-
sion estimates of the effects of dividends on consumption.
Data and Definitions
The CEX has been conducted annually by the Bureau of Labor Statistics
since 1980. 8 It is a short panel based on a stratified random sample of the
U.S. population. Selected households are interviewed quarterly for five
quarters and are then replaced by new households. As we discuss more fully
below, the information on financial asset holdings and changes in these
holdings over the preceding twelve months is collected in the fifth interview;
data on dividends, interest received, other income variables, and demo-
graphics are collected in the second and fifth interviews and cover the
twelve months before the interview date. We extract most of the variables
from the CEX family files, but the data on housing and credit are from the
detailed expenditure files.
Malcolm Baker, Stefan Nagel, and Jeffrey Wurgler 235
- See Campbell (2006).
- We use the average estimates in the interview survey of the CEX, not the more detailed records from the diary survey.
gains or losses component. To compute the latter, G, we need to make an
assumption regarding the timing of investment. We assume that half the
reported investment was made at the beginning of the period and half at
the end.
We employ a few filters to screen out unusual observations. We require
that there be only one consumer unit (family) in the household and that
the marital status of the respondent and the size of the family remain the
same from the second to the fifth interview. We delete observations where
any wealth component or income is topcoded. 11 We require that lagged
financial wealth be positive and that a nonzero fraction of this wealth be
invested in stocks or mutual funds. This last screen is the most significant:
most (roughly 80 percent) of the households in the sample do not participate
in the stock market. We use the consumer price index (CPI) to deflate all
variables to December 2001 dollars.
Summary Statistics
Table 1 presents summary statistics for the CEX data. After applying the
filters, we have 3,106 household-year observations. In this sample, mean
nondurables consumption, reported in the top panel, is $15,042, and the
median is slightly lower. Total expenditure, including durables, is three to
four times as large. The next two panels report wealth and income measures.
Financial wealth is typically around a third of total wealth. Total income,
which includes dividends but not capital gains, has a mean of $56,566 and
again a slightly lower median. Comparing the first and third panels, one sees
that, on average, total income is slightly higher than total expenditure.
For the households in our sample that hold some stock, average interest
income is $1,264 and average dividends total $935.
As one would expect, the mean capital gain of $363 is relatively small
compared with total income, and its average share in total income is roughly
the same as the average share of interest income. Capital gains, however, do
show significant variation across households. Note that the extreme values
Malcolm Baker, Stefan Nagel, and Jeffrey Wurgler 237
- To preserve the anonymity of respondents, the CEX administrators reset observations above certain thresholds on wealth, income, and some other variables to a cutoff threshold value. Before 1995 the topcoding level was $100,000 for many items in the survey. However, since the topcoding threshold applies to single items, the total value of variables such as income after tax, for example, which is calculated as the sum of many single items, can be much larger than $100,000. After 1995, the topcoding thresholds were raised.
Table 1. Annual Summary Statistics for the Sample Drawn from the Consumer Expenditure Survey, 1988–
a
Dollars except where stated otherwise
No. of
Percentile
Variable
observations
Mean
50th
5th
95th
Minimum
Maximum
Consumption Nondurables
b^
Total
Wealth
c
Financial
Total
d^
Income Total (
Yt
c) (^)
Interest (
I^ t^
)^
Dividends (D
)^ t^
Other
Capital gains (
G
) t f^
240 Brookings Papers on Economic Activity, 1:
are from wealthy households with a large amount of financial wealth. What
the table does not show is that capital gains also vary widely across time:
virtually all of the largest negative observations, including the minimum
of −$301,407, originate from 2001, where the measurement period includes
the crash in technology stock prices during 2000 and 2001.
The fourth panel shows that, on average, interest and dividends account
for 4 percent and 2 percent of total income, respectively. The distribution
is skewed, with a median household dividend income of zero. It is likely
that some of the zero-dividend observations in the CEX result from
underreporting of dividends by the interviewees. To ensure that our re-
sults are not driven by the zero-dividend observations, we include a zero-
dividend dummy variable in our regressions.
Empirical Methodology
The null hypothesis of interest is that capital gains and dividends are
fungible, which means that households should react similarly to a change
in wealth whether it comes in the form of a capital gain or in the form of a
dividend. In other words, only the total return should matter, not the split
of that return into dividends and capital gains or losses.
To test this hypothesis, we run ordinary least squares regressions with
specifications alternatively in levels, first differences, and log differences.
We describe and motivate these in turn. Our basic levels specification is
as follows:
where C it is household i ’s consumption in period t (in this specification,
consumption is summed over the four quarters preceding the fifth interview);
Z it is a vector of household characteristics; F it is a vector of financial vari-
ables that includes income, lagged wealth, and interactions with Z it ; R it is
the total dollar return on stocks including dividends; and D it is total dollar
dividend income. In equation 1 the total stock return is already accounted
for with Rit , and therefore d = 0 under the null. However, if for some reason
a household has a higher propensity to consume from dividends than from
capital gains, we expect d > 0.
The levels specification can be interpreted as an approximation to the
consumption rule used by households. Different consumption models map
income, wealth, and other household characteristics onto consumption in
( ) 1 C it = a 0 + a 1 ′ Z it + a 2 ′ F it + gR it + dD it + uit ,
different ways. 12 We are agnostic as to which consumption model is most
accurate. Our goal is simply to distinguish between models in which capital
gains and dividends are fungible and those in which the effect of dividends
diverges from that of capital gains. We approximate the consumption rule
with a range of variables that may be relevant for consumption decisions,
allowing them to enter linearly, quadratically, and through interactions
to approximate the nonlinear consumption function. 13 In the end the lev-
els specification boils down to asking whether two consumers in the
same financial situation, with similar income, similar household charac-
teristics, and similar total return on financial assets, but different compo-
sitions of total returns across dividends and capital gains, have different
consumption.
Household characteristics in Z it include the education of the household
head (dummies for high school and college graduation), the age of the
household head, age of household head squared, family size, family size
squared, and a set of year-month fixed effects to absorb seasonal varia-
tion in consumption as well as variation in macroeconomic factors. 14
Financial variables in F it include variables that proxy for future income
and for current cash on hand, including income after tax (excluding div-
idends), 15 lagged total wealth, lagged financial wealth, the percentage of
financial wealth invested in stocks, and the squares of all these variables.
We also allow for interactions of age and family size with income,
lagged wealth, and lagged financial wealth.
In interpreting an estimate that d > 0, the key question is whether this
set of controls is sufficient or whether some omitted variable could be pos-
itively correlated with dividends, thus biasing upward the estimate of d.
Although all of these controls should do a reasonable job of approximating
households’ consumption rule, it is difficult to fully rule out the possibility
- Under the basic form of the permanent income hypothesis, permanent income deter- mines consumption, and so the right-hand-side variables in equation 1 matter to the extent that they are correlated with permanent income. In models of buffer-stock saving with impatience, such as those of Deaton (1991) and Carroll (1997), consumption depends on cash on hand (liquid wealth plus current income) relative to its target level.
- This approach follows Hayashi (1985), Carroll (1994), and Parker (1999b).
- The quarterly interviews are conducted for overlapping ends of quarters, and so we need year-month fixed effects, not simply year-quarter fixed effects.
- The income variable does not include capital gains (realized or unrealized), so we only need to subtract dividends. In specifications where dividends plus interest is the explana- tory variable, we subtract dividends and interest.
Malcolm Baker, Stefan Nagel, and Jeffrey Wurgler 241
fifth and the second interview. As mentioned above, dividends and income
in the CEX are measured over overlapping twelve-month periods leading
up to the second and fifth interviews. We define Δ D it and Δ( Y it − D it ) as the
difference in the reported values. Because of the imperfect matching of mea-
surement periods between Δ Cit and Δ Dit , the d estimate is likely to be biased
toward zero. (The same is true for b 2 .) Inferences about the magnitude of
d will thus be difficult, but a significant positive coefficient will still be
meaningful, as the null is still d = 0. As before, Z it is a vector of household
characteristics and time dummies. In some specifications we also include
the level of second-quarter consumption as an explanatory variable, because
it may pick up some noise that is introduced through the measurement-
period mismatch between Δ C it and the income variables.
Finally, to check whether the results are robust to functional form, we
also try a third set of specifications with the change in the logarithm of
consumption as the dependent variable. There we use an indicator vari-
able for the sign of dividend growth as our key explanatory variable, because
we lack a clear prediction about how consumption growth would be affected
quantitatively by dividend growth. For example, a 10 percent increase
in dividends would presumably have a different effect on the percentage
growth in consumption when dividends are a small proportion of total
income than when they are a large proportion. By using an indicator vari-
able, we simply estimate the average difference in consumption growth
between households with dividend increases and those with dividend
decreases. 18
Effects of Dividends on Household Consumption
Table 2 reports estimates of equation 1. Specifications in the first four
columns use nondurables consumption as the dependent variable, and the
rest use total expenditure. Independent variables in the first specification
include total returns, dividends, and a dummy for zero dividends, plus a
large number of controls. We find little economic impact of total returns
on consumption, and no statistically significant relationship. But divi-
dends are positively related to the level of consumption, and the effect is
statistically significant. A one-dollar difference between households in
- See Johnson, Parker, and Souleles (2006) for a similar dummy variable approach to analyze the effect of tax rebates on log consumption.
Malcolm Baker, Stefan Nagel, and Jeffrey Wurgler 243
Table 2. Regressions of Consumption on Dividends, Total Returns, and Other Sources of Income Using Consumer ExpenditureSurvey Data in Levels
a
Dependent variable
Nondurables expenditure
b^
Total expenditure
Independent variable
Total return on stocks (
R
= t^
G
D
)^ t
Dividends (
D
) t
Dividends lagged one period (
D
t −
Dummy variable equaling 1 if
D
= t^
D
t −^1
Total return (
R
= t^
G
D
I
)^ t
Dividends and interest (
D
I
)^ t
Dividends and interest lagged one period (
D
t −
I
t −
Dummy variable equaling 1 if
D
I
= t^
D
t −^1
I
t −^1
No. of observations
R
2
Source: Authors’ regressions using Consumer Expenditure Survey data.a. Consumption, total returns, dividends, and interest income are for the four quarters from the household’s second to its fifth interview. Lagged variables cover the four quarters ending with the second interview. All regressions include year-month fixed effects, household controls (family size, high school education of respondent, college education of respondent, age of respondent), income andwealth controls (income, lagged income, financial wealth, total wealth, and percent of financial wealth in stocks, with all wealth variables for the period ending four quarters before the fifth interview),and variables interacting household controls with other household controls (high school education
× age, college education
×^
age, family size
× age, age squared, family size squared) and with income
and wealth variables (financial wealth
×^
age, income
× family size, total wealth
×^
family size, income squared, total wealth squared, financial wealth squared, and percentage of financial wealth in stocks
squared). Numbers in parentheses are heteroskedasticity-robust standard errors. All variables in dollars are deflated by the consumer price index.
b. Defined as in table 1.
The last four specifications in table 2 use total expenditure as the depen-
dent variable. The estimated coefficients on D t and D t + I t are roughly four
to five times those in the regressions with nondurables consumption on
the left-hand side. As total expenditure is proportionally higher than non-
durables consumption, on average these results suggest that dividend income
is not used exclusively for nondurables consumption but rather boosts
expenditure of all types. In all other respects, the results in these specifi-
cations are similar to those for nondurables.
It is interesting that no evidence emerges of a significant effect of cap-
ital gains; indeed, all the point estimates on total returns are negative. Of
course, a low (but positive) propensity to consume capital gains would
not have been surprising. Under the permanent income hypothesis, for
instance, forward-looking consumers spread the consumption from an
unexpected increase in wealth over their lifetime, so that the coefficient
on total returns is predicted to be on the order of the real interest rate. From
this perspective, what is striking about the results in table 2 is the far
higher consumption from the return component that we label “dividends.”
The very large effects of dividends on total expenditure, in particular,
strongly suggest that individuals consume dividends disproportionately
in the period in which they are received.
Table 3 reports estimates of equation 2. The first specification includes
total returns, the change in dividends, and other controls, including a
dummy for zero dividends over the preceding and current twelve-month
periods and, in some specifications, lagged consumption. Since we are
regressing the change in quarterly consumption (from the second to the
fifth interview) on changes in dividends measured over twelve-month
periods (preceding the second and fifth interviews), one would expect
the coefficient estimates on Δ D t to be about one quarter of those on D t in
the levels specifications.
The results indicate that multiplying the coefficient estimates on Δ D t
by four does yield numbers that are at least of the same order of magni-
tude as the estimates in table 2, although somewhat lower, in particular
for the nondurables specifications. The moderate decrease is consistent
with some ex ante effect in the levels estimates, but it could also reflect
the noise introduced through the imperfect matching of dividends and
consumption measurement periods. Consistent with the latter possibility,
controlling for lagged consumption, which should absorb some of the
noise, raises the magnitude of the coefficient on dividend changes. But
246 Brookings Papers on Economic Activity, 1:
Table 3. Regressions of Consumption on Dividends, Total Returns, and Other Sources of Income Using Consumer ExpenditureSurvey Data in First Differences
a
Dependent variable
Change in nondurables expenditure
b^
Change in total expenditure
Independent variable
Total return on stocks (
R
= t^
G
D
c ) (^) t
Change in dividends (
D
d ) (^) t
Dummy variable
1 when
D
= t^
D
t −^1
Change in income less dividends (
[ Y
− t^
D
]) t
d^
Total return (
R
= t^
G
D
I
)^ t
Change in dividends plus change in interest
D
I^ ) t
d^
Dummy variable
1 when
D
I
= t^
D
t −
I
t −
Change in income less dividends and interest
[ Y
− t^
D
− t^
I
]) t^
d^
Consumption lagged one period (
C
t −^1
)^
No. of observations
R
2
Source: Authors’ regressions using Consumer Expenditure Survey data.a. The dependent (consumption) variables are defined as the difference between quarterly consumption in the fifth (and last) interview and that in the second interview three quarters earlier. All regressions include year-month fixed effects and household controls (family size and high school education, college education, and age of respondent) and the following interactions: high school education
×^
age, college
education
× age, family size
×^
age, age squared, and family size squared. Numbers in parentheses are heteroskedasticity-robust standard errors. All variables in dollars are deflated by the consumer price index.
b. Consumer nondurables expenditure is defined as in table 1.c. Total returns are measured over the four quarters before a household’s fifth interview.d. Difference between annual income items reported at the fifth interview and the second interview three quarters earlier. This variable is only an approximation of the first difference because income is measured after tax whereas dividends are measured before tax.
Table 4. Regressions of Consumption on Dividends, Total Returns, and Other Sources of Income Using Consumer ExpenditureSurvey Data in Log Differences
a
Dependent variable
Change in nondurables expenditure
b^
Change in total expenditure
Independent variable
Log (
[
G
D
]/ t
FW
t −^1
c) (^)
Dummy variable
1 when
D
0 t^
Dummy variable
1 when
D
= t^
D
t −^1
Change in log of income less dividends
log[
Y^ t
D
]) t
d^
Log (
[
G
D
I
]/ t^
FW
t −^1
)^
Dummy variable
1 when
D
I τ
Dummy variable
1 when
D
I
= t^
D
t −
I
t −
Change in log of income less dividends and interest
log[
Y^ t
D
− t^
I
]) t
d^
Log of consumption lagged one period (
C
t −
No. of observations
R
2
Source: Authors’ regressions using Consumer Expenditure Survey data.a. The dependent (consumption) variables are defined as the difference between the logarithm of quarterly consumption in the fifth (and last) interview and that in the second interview three quarters earlier. All regressions include year-month fixed effects, household controls (family size and high school education, college education, and age of respondent), and the following interactions: high schooleducation
× age, college education
× age, family size
×^
age, age squared, and family size squared. Numbers on parentheses are heteroskedasticity-robust standard errors. All variables in dollars are deflated
by the consumer price index.
b. Consumer nondurables expenditure is defined as in table 1.c. Total returns (
G^ +^ D ) are measured over the four quarters prior to a household’s fifth interview.
FW
is financial wealth, defined as in table 1, note d.
d. Difference between annual income items reported at the fifth interview and the second interview three quarters earlier.
250 Brookings Papers on Economic Activity, 1:
As an additional robustness check, we have also removed capital gains
outliers from the regression. In a survey like the CEX, which is based on
self-reported information, the capital gains data are likely to have substan-
tial measurement error. We want to ensure that the absence of a capital
gains effect on consumption is not caused by a few large and potentially
erroneous outliers. Winsorizing capital gains at their 5th and 95th per-
centiles, however, results in quantitatively similar estimates.^20 Perhaps more
important, winsorizing the capital gains data leaves the coefficients on
dividends virtually unaffected. Overall, it seems that the results are not
unduly influenced by outliers.
In summary, the best available U.S. micro data on consumption suggest
that controlling for total returns, dividends have a significant effect on
consumption. The relationship is generally robust across specifications in
levels, simple differences, and log differences.
Evidence from Household Portfolios
As already mentioned, a concern with the self-reported CEX data is that
dividends and capital gains are likely to be measured with substantial error.
It is not clear to what extent measurement error influences the foregoing
results. Furthermore, the results would be made even more persuasive if
we could verify the intermediate, mechanical step between receipt of div-
idends and consumption expenditure—that dividends are in fact withdrawn
from brokerage accounts, and at a higher rate than capital gains. Our second
micro data set, based on household portfolios, achieves these objectives and
thus complements the CEX data. Furthermore, it allows us to study net
withdrawals from investment portfolios, an interesting and novel dependent
variable in its own right. 21 Finally, the larger sample size and detail of the
portfolio data allow for certain robustness tests and sample splits that are
not possible in the CEX data.
- Winsorizing replaces all observations in the tails of the distribution (in this case the top and bottom 5 percent) with the observed values at the 5th and the 95th percentiles, respectively. In the base case nondurables regression (regression 2-1) in table 2, the coeffi- cient on the total return drops to −0.02 with a standard error of 0.02. In the base case total expenditure regression (regression 2-5) in table 2, the coefficient rises to 0.01 with a stan- dard error of 0.04.
- In a paper that is similar in spirit, Choi and others (2006) use shifts in savings into 401(k) plans to identify changes in consumption.
