This document discusses a study examining the impact of changes in disposable income and asset wealth on consumption. The author conducts an analysis of wealth effects on the consumption function using econometric techniques and data from 1964-2014 in the United States. The results show that financial wealth effects are statistically significant and have a relatively large impact on consumption, while housing wealth effects are often not significant. The author aims to build on previous related work and provide evidence that fluctuations in stock market and housing values can significantly affect consumer spending behavior in the short run.

1. Wealth Effects On The
Consumption Function
ECO460
Michael Keith Deane
November 1, 2014

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Table of Contents
Abstract………………………………………………………………………………………………………………………….3
I. Introduction...................................................………...........................…….........................................................4
II. Literature Review..............................................…............................................................................................6
III. Methodology and Strategies……............................……............................……............................................7
i. Ordinary Least Squares (OLS) and Instrumental Variables
IV. Data..........................................................................................................……............................…….....................9
i. (Dis) Aggregate Financial Wealth versus (Dis) Aggregate Housing Wealth…………11
V. Results..................................................................................................……............................…….....................12
i. Model Estimations………...………………………………......…………………………………..………...16
ii. Model Interpretations……………………………………………………………………….……………17
VI. Conclusion..........................................................................................……............................…….....................18
References………………………………………….......................................……............................…….....................19
Appendix-A…………………..………………..……….................................……............................…….....................20

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WEALTH EFFECTS ON THE CONSUMPTION FUNCTION
EVIDENCE COMPARES THE UNITED STATES TO THE EURO AREA
Michael K. Deane
Sykes College of Business
University of Tampa
Abstract
This paper estimates the impact of changes in disposable income and asset wealth on
consumption. A variety of econometric techniques and theories address the issue of whether
wealth effects significantly affect the consumption expenditure equation. The first empirical
literature was Friedman’s permanent income hypothesis (1957) and Modigliani and Ando’s
life-cycle hypothesis (1963). Both proposed that consumption had very minimal responsiveness
to wealth effects, suggesting that long-run aggregate consumption would follow a random
walk due to the homogeneity of income and wealth. Other empirical studies contradict these
hypotheses; showing that fluctuations in economic activity are often followed by adjustments
to consumer expenditures in response to financial stock market turmoil and severe drops in
housing values. The main goal of this work is to measure wealth effects in the form of stock
and real estate market fluctuations throughout the United States to show that consumption
expenditures are strongly responsive to these wealth effects. In this work, I aim at building
upon a related paper, Sousa (2009) to support that (i) financial wealth effects are relatively
large and statistically significant and (ii) housing wealth effects are quite often not significant.
Keywords: Consumption, wealth effects: housing wealth, financial wealth.

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I. INTRODUCTION
“Consumption is the sole end and purpose of all production; and the interest of the producer
ought to be attended to, only so far as it may be necessary for promoting that of the consumer.”
– Adam Smith
Consumption is a central element in most macroeconomic models because it accounts for
about 50% to 70% of GDP in most economies. Economist John Maynard Keynes developed the
consumption expenditure function in 1936, in his most famous book The General Theory of
Employment, Interest, and Money. The mathematical function became a core component of
macroeconomic theory for describing the relationship between real disposable income and
consumer spending. Keynes suggested that, “as income increases, consumption increases but not
by as much as the increase in income”. The Keynesian consumption function is a naïve model
because it only bases consumption on current income and ignores potential increases or
decreases in future income. Since its development, there has not ben many works focused on the
role of assets and asset prices in modeling the pattern of consumption expenditures.
To elaborate on Keynes’ theory and correct for some naïve assumptions, distinctions
between consumption out of permanent versus temporary income variables and wealth variables
such as stock market and real estate wealth were developed by Friedman’s permanent income
hypothesis (1957) and Modigliani and Ando’s life-cycle hypothesis (1963). These empirical
studies sought to quantify the effects of changes in wealth on consumption expenditures. Both
proposed that consumption had very minimal responsiveness of consumption to wealth effects,
suggesting that long-run aggregate consumption would follow a random walk due to the
homogeneity of income and wealth. Other developments such as Slacalek (2006) “provide

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evidence of substantial heterogeneity in the wealth effects across countries”. Aggregate
consumption shows coinciding with standard income and wealth variables there is indication of a
long-run positive relationship. This long-run equilibrium has empirical support such as DeJuan
(2003) indicating the marginal propensity to consume out of permanent income is equal to
1.0241. Recent advancements in empirical research, such as Sousa (2009) show that marginal
propensity to consume is strongly responsive to wealth effects on income, proving short-run
disequilibria between these variables with econometric modeling techniques.
Short-run financial wealth fluctuations indicate relatively large and statistically
significant adjustments to consumer expenditures. These short-run dynamics are explored with
an error correction model that identifies financial wealth effects on the consumer expenditure
equation with consumption-based reactions to stock market turmoil and severe drops in housing
values. The main goal of this paper is to measure wealth effects on consumption using chained
2005-adjusted dollars to estimate the impact of changes in average income and asset wealth
affect consumption throughout the United States using an income process calibrated to 1964-
2014 annualized U.S. data.
The paper is organized as follows. Section 2 provides the model and methodology.
Section 3 presents the data and empirical results. Section 4 concludes.

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II. LITERATURE REVIEW
The consumption function is a mathematical formula developed by economist John
Maynard Keynes to describe the relationship between real disposable income and consumer
spending. Keynes believed that changes in autonomous2 spending are dominated by unstable
exogenous fluctuations in planned investment spending known as animal spirits; which are
influenced by emotional waves of optimism and pessimism. Income is a deterministic variable in
exogenous spending. By looking intuitively at how the consumption function responds to
changes in financial wealth effects, namely stock market and real estate values. Though there are
no direct effects on real purchasing power; consumer expenditures show a trend to rise with
more optimistic points economic stability and fall when consumers feel compelled to take
precautionary saving measures that postpone consumption. Friedman’s permanent income
hypothesis (1957) assumed that individuals smooth consumption based on their permanent
income. Modigliani and Ando’s life-cycle hypothesis (1963) built on this research to show that
personal consumption expenditures were unresponsive to changes in transitory income because
income was consumed at a constant rate.
Recent advancements in research shows evidence of the contrary, such as Poterba (2000),
by pointing out, “evidence of small and transitory wealth effects”. This reveals that consumer
expenditures are responsive to wealth effects by either increasing resultant consumption
expenditures or increasing precautionary savings behavior (hence decreasing consumption
expenditures). A growing body of empirical evidence describes how transitory changes in wealth
variables affect aggregate consumption. The coinciding movement with standard income and
2 Autonomous variables are denoted by subscript 0 to the respective variable.

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wealth variables is clear evidence of the long-run equilibrium relationship. Short-run dynamics
explore short-run disequilibria with empirical support from error correction specification models.
The Marginal Propensity to Consume as an effect of wealth from stock market increases is found
to be statistically significant and noticeable, while the marginal propensity to consume as an
effect of housing wealth is typically lower in the euro area than in the U.S. is not statistically
significant and found to be relatively low in data from both countries.
Empirical support from Sousa (2009) shows the differences of these results between
countries. Findings by Skudelny (2008) show that in the euro area, the marginal propensity to
consume out of financial wealth ranges between “1.3 to 3.5 cents per euro”. Sousa’s estimates of
marginal propensity to consume out of financial wealth range from 0.7 to 1.9 cents per euro.
These findings support the statistical significance for the responsiveness of consumption to
financial wealth, further pointing out that “a 10% increase in financial wealth leads to an increase
of between 0.6 and 1.5% in consumption”. Using quarterly U.S. data from 1980:1 to 2007:4 to
compare the findings from the euro area Sousa (2009) shows similar results. In particular, “the
estimates of the marginal propensity to consume out of wealth range between four and seven
cents of increase in consumer spending from a dollar increase in aggregate wealth”.
III.METHODOLOGY STRATEGIES
To test the hypothesis, the generalized least squares model specification is first used. Changes in
inflation-adjusted consumption are regressed against changes in inflation-adjusted income and
logged. To quantify the wealth effects on consumption financial wealth per capita is measured by

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the simple moving averages of the S&P 500 index closing values. Real estate wealth per capita is
represented by historical real estate values of the Case Schiller real estate index.
Consumption expenditure is expressed as:
C = C0 + mpc (Y-T) – cr
Autonomous consumption variables that are independent from the model such as disposable
income relate to consumer optimism about future income. These effects can increase and
decrease spending expenditures. Keynes called the relationship between disposable income YD
and consumption expenditure C the consumption function and expressed it as:
C = C0 + mpc * YD or C = C0 + mpc * (Y-T).
To further understand the impact of wealth effects on consumption expenditures, the
econometric model for the consumption function seeks to quantify the differences in these
wealth effects. The model looks to clarify the trend relationship by looking the variables and
looking into per capita terms using a consumption function and logging the variables to test for
the validity of the permanent income hypothesis, as specified in the following equation:
where
μ = Constant and εt is the error term.
Log Ct = logged consumption
Wt = Asset wealth
Yt = Disposable income from a budget constraint, the parameters βw and βy, respectively,
capture the long-run elasticity of marginal propensity to consume or save with respect to
fluctuations in income as a result of financial and/or housing market gains and losses

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IV. DATA
*Using most recent data tables from the Economic Report of the President.
*Methodology explanations are given below data outputs.
Although the variables do not appear to be highly skewed, the data in the model does not appear
normally distributed because the JB probs are less than 0.2.This may be the cause of some
extreme values influencing the data set or multicollinearity.

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As the theory predicted, consumption and income appear to have the strongest and are the closest
to exhibiting one for one movement and a test for correlation is important. This movement is
indicative of a major problem with multicollinearity due to Centered VIFs being far greater than
5. The nature of these variables makes multicollinearity difficult to avoid but the widened
confidence ellipses indicate that the model is explanatory.

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The scatter plot for marginal propensity to consume in response to income shows nearly one for
one positive and a linear relationship along the fitted regression.
The substantial evidence of heterogeneity in these variables provokes the need to look at the (dis)
aggregated wealth effects on consumption. Examining whether the variables exhibit a random
walk shows gives insight into marginal propensity to consume given fluctuations in the variables.

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The next portion uses the Augmented Dickey Fuller test to determine the existence of unit roots
and then goes on to analyze the existence of cointegration using the Engle and Granger
methodology to dis-aggregate consumption expenditures by which variables are most heavily
influential or following a random walk. The fluctuations in financial wealth correlate to
fluctuations in consumption but the real estate wealth seems trend without any relationship.
IV. RESULTS
Time series data is first to be checked for a unit root with the Augmented Dickey-Fuller unit
root test. The test determines the existence of unit roots at the 1% level in the series and
concludes that all series are first-order integrated.
Unit Roots:

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The unit roots with drifts are indicative of the partial correlation but shows that there is a strong
relationship between the income variables, but not between longer-lagged periods and the next
step is to look for cointegration.
Cointegration:
Cointegrating combinations are “equilibria”. So it is important to be able to discover and model
these relationships. The cointegration test reveals that these variables are highly correlated and
indications that although both variables and the error term are I(1) the model is not spurious.

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The outliers of the residual table graph appear to be influenced by periods of recessions and
expansions from U.S. economic business cycle fluctuations, to correct for these outliers making
the model skewed, an improved model would eliminate the outliers that exist most
predominantly in the consumption and real estate wealth variable.
The objective was to disaggregate the financial wealth effects to see the respective significances
of each. Looking into the distinctions from the short-run and long run wealth effects provides a
better understanding of the persistence of consumption growth. Recent research, such as
Peltonen (2008) makes the claim that housing wealth effects are substantially larger than for
stock market wealth, but the plots of the regressors indicate differently; where income steadily
rises and seems unresponsive to the periodic increases in real estate wealth. While earlier
theories suggested that marginal propensity to consume should remain constant regardless of
what asset categories are considered a growing body of evidence has argued differently such as,

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(Zeldes and Poterba 1989) who argued that stock market or housing wealth may have a different
impact on consumption. This may first be attributed to liquidity reasons and the expected
permanency of changes of these different asset groups. Due to the amount of influential
variables, there is no conclusive evidence. Research including Kohler and Dvornak (2003) finds
evidence of “substantial housing wealth effects”. These results are conflicting with earlier results
such as McFadden (1997) finding “a weak relation between individual savings rates and changes
in housing prices. Given the nature of the time series data I expected to find positive first-order
serial correlation. There is evidence of positive serial correlation because the previous periods
have errors with the same sign as current periods, which is shown in the Breusch-Godfrey Test.
Serial Correlation:

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Estimation Outputs with Ordinary Least Squares model specifications:
Model A
Model B

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Interpretations:
Model A
The coefficients indicate that the log of income is closely related to the log of consumption. A 1
one percentage point increase in income leads to a 0.71 percentage point increase in
consumption, corresponding to the claims made by Keynes; that when income increased,
consumption would too, but not by as much.
Model B
Incorporating the wealth effects shows the predicted results in terms of the statistical significance
the disaggregated effects on consumption. The elasticity of consumption with respect to
increases in net financial wealth is statistically significant and relatively large. A 10% increase in
financial wealth causes a 1.2% increase in consumption. The same 10% increase in housing
market values has a minimal influence on consumption with an increase of just .01%.

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VI. CONCLUSION
There are several econometric techniques to address the issue of wealth effects on consumption
and analysis typically focuses on the impacts of wealth effects on corresponding fluctuations of
consumption. John Maynard Keyes set the basis for the first school of thought; followers of
Keynesian ideas regard the self-correcting mechanism, which works through wage and price
adjustment, as very slow, wages and prices are sticky. Stagnant periods in consumption growth
pose complex challenges especially in the magnitude of downturns in asset markets. The long-
run response of consumption to wealth effects tends to be substantially larger than its short-run
effects. By disaggregating the wealth effects it can be seen the consumption is substantially more
responsive to financial wealth than real estate wealth. The volatility of consumption suggests that
consumption should be more heavily integrated with capital markets. Since consumer
expenditures are highly sensitive to changes in financial liabilities and mortgage loans,
consumption has exhibited tendencies of persistence during strong economic activity and
sluggish lags in expenditures typically propagate falls in economic activity. Downturns and
expansions in asset market crashes and booms are first exhibited in the responses of consumption
fluctuations in times of financial wealth growth or losses, whereas real estate values are
minimally influential on aggregate expenditures. The macroeconomic consequences of
consumption are of quintessential importance for the stability of an economy and its elasticity to
wealth effects should be used for optimizing economic activity.

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REFERENCES
[1] Fung, Michael K., and Arnold C. S. Cheng, “The Wealth Effects Of Housing and Stock
Markets on Consumption: Evidence from a Sample of Developed and Developing
countries”.
[2] Sousa, Ricardo, "Wealth Effects on Consumption Evidence from the Euro Area." European
Central Bank 1050 (May 2009): 4-18. Web. 23 Nov. 2014.
[3] Kishor, Kundan, "Does Consumption Respond More to Housing Wealth Than to Financial
Market Wealth? If So, Why?" The Journal of Real Estate Finance and Economics 35.4
(2007): 427-448. Web. 23 Nov. 2014.
[4] Jansen, Eilev, “Wealth Effects on consumption in financial crises: the case of Norway”
[5] Iacoviello, M.,“Housing Wealth and Consumption.” International Finance Discussion Paper
1027 (August 2011): 1-11. Web. 23 Nov. 2014.
[6] U.S. Bureau of Labor Statistics, Average annual income [CUUR0000SA0R], retrieved from
FRED, Federal Reserve Bank of St. Louis
[7] U.S. Bureau of Economic Analysis, Real personal consumption expenditures per capita,
financial wealth per capita, and real estate wealth per capita retrieved from FRED,
Federal Reserve Bank of St. Louis

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APPENDIX A.
Basis for life-cycle hypothesis and permanent income hypothesis