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A behavioral model of nondurable consumption expenditure
A Behavioral Model of nondurable Consumption Expenditure
MARTIN MICHAEL TOLAR” University of Western Sydney
ABSTRACT:
This paper employs survey data in an attempt to produce a behavioral model of nondurable consumption expenditure. This model is then applied to Australian data for the period 1976(l) to 1994(2). Despite empirical difficulties associated with the attainment of some time series data, our results prove encouraging for the adoption of behavioral methodologies in the production of nondurable consumption functions, while casting doubts upon the currently accepted rational expectations permanent income model of nondurable consumption expenditure.
INTRODUCTION
In recent times the neoclassical concept of ration~ity has come to do~nat~ the manner in which economists model expectations formation and economic decision making. This study challenges this concept within the context of the nondurable consumption expenditure decision making process. Rational economic man was reintroduced into economic debate by Muth (1961), within the context of expectations formation. However, it was not until the works of Lucas (1972), Sargent (1973), Sargent and Wallace (1973a, 1973b, 1975) and Barre (1976) that rational expectations and the concept of rationality re-entered mainstream macroeconomic debate. By definition, rational expectations propounds that the expectations formed by economic agents are equivalent to those produced by the relevant economic model, and any errors that occur are of a random nature, resulting from unavailable information (see Mum, 1961). *Direct all correspondence to: Martin Michael Tolar. University of Western Sydney, Macarthur Faculty Business and Technology, P.O. Box 555, Campbelltown, NSW, Australia 2560: e-mail: [email protected]. Journal of S~i~~connmi~, Volume 26, No. 3, Pp. 291-302 Copyright 0 1997 by JAI Press, Inc. All rights of reproduction in any form reserved. ISSN: 10534357
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Following F~edman (1957) and Muth (1961), Hall (1978) produces a model of nondurable consumption expenditure that models individuals as forward looking rational economic beings that form nondurable consumption expenditure decisions on the basis of their permanent income.’ Despite this approach’s widespread acceptance, empirical examinations of the hypothesis have produced inconclusive results (see Flavin, 1981, 1985; Mankiw & Shapiro, 1985, MacDonald & Kearney, 1990; Milbourne & Otto, 1992 for a general overview), while on a theoretical level there exist a number of anomalies between the underlying assumptions of human behavior in Hall’s model and the economic actuality. This study attempts to rectify the theoretical shortcomings of Hall’s approach by employing a behavioral methodology in the development of an alternate model of nondurable consumption expenditure. It is envisaged that the employment of this methodology will produce a model that will capture both economic and noneconomic information that individuals consider to be important in deciding to expend upon nondurable goods and services that are currently not contained within the method proposed by Hall. We conclude that based upon this preliminary study, econometric models that employ behavioral methodologies in their development may at best improve their forecasting ability and at least improve their theoretical appeal as a consequence of the adoption of behavioral research techniques. The remainder of this study is set out as follows: Section 2 provides a review of the literature pertaining to the rational expectations permanent income hypothesis, and Section 3 presents an outline of the data and methodology employed in this paper. We present our results in Section 4 and then draw together our conclusions in Section 5. LITERATURE REVIEW Friedman’s (1957) Permanent Income Hypothesis (PIH) has been adopted by the neoclassical school as their model of optimizing behavior in the context of nondurable consumer expenditure decision making. The PIH follows Fisher’s (1930) model of intertemporal optimization and Modigliani’s (1949) Life Cycle Hypothesis. Initially the PIH was developed by Friedman as a forward looking model of consumption expenditure. However, as a consequence of empirical difficulties, the PIH was tested in and hence has come to be associated with the backward looking adaptive expectations hypothesis. Hall (1978) rectifies this occurrence by placing the PIH into a rational expectations framework, returning the PIH to its intended context, which can be represented as follows:
Cff1 = a+ l3c,+ u,, ,,
(1)
where C denotes nondurable consumption expenditure, a is the fixed coefficient, 13is a regression coefficient, and u is the random error coefficient.
Nondurable Cons~~ptjon
~xfendjture
293
Equation 1 is the result of economic agents forming nondurable expenditure decisions for the next period (t + 1) based upon the information available at time t. Thus Hall produces the testable null hypothesis that: Rational economic agents utilize all of the information available at time t in their planned nondurable consumption expenditure in period t + 1. Consequently, the only significant predictor of nondurable consumption expenditure in any given period is the previous periThus a regression equation that ods nondurable consumption expenditure. includes additional lagged parameters, other than a one period lagged value of nondurable consumption expenditure, will not improve the model’s predictability. Hall’s approach presents some diff%ulties, in that his exa~nation is a test of a joint hypothesis, that of the method in which consumers expend on nondurables and the manner in which they form their expectations about the future. The proposition that current consumption is an unbiased predictor of future consumption, thus consumption expenditure behaves as a random walk, appears to place more emphasis on the second of the joint hypotheses. Consequently, rejection of Hall’s methodology may not be a result of a rejection of the PIH, but rather the Rational Expectations Hypothesis (REH). As a consequence of Hall’s unification of the REH with the PIH (REPIH), a number of theoretical problems arise, most of which are inherited from the adoption of the REH. First, it is assumed that economic agents have a complete understanding of the workings of the economy and that information is perfect, in the sense that everybody has equal access to the same informational set. Hence Hall assumes that economic actors have the cognitive capability and information to calculate their permanent income, thus being in a position to balance current and future nondurable consumption expenditure accordingly. Such an assumption ignores the intellectual, informational, time and opportunity cost constraints placed upon an individual, in their attempt to calculate their permanent income and expend upon nondurables accordingly. Our second criticism of the assumption of rational economic agents stems from the Post-Keynesian school’s advocacy of an uncertain and unknowable future. Following Keynes (1921, 1936), the Post-Keynesian school dispute the REH, on the grounds of fundamental or incalculable uncertainty. As a consequence of an uncertain and unknowable future, it is impossible for individuals to form accurate predictions, while providing models to calculate predictions of these future economic occurrences proves to be just as difficult (see Colander & Guthrie, 1980). Keynes raises doubts as to the ability of economic actors to assign numerical probabilities to uncertain future events, hence placing them in a position that does not allow them to maximize their utility (see Rutherford, 1984). It is from this explanation of uncertainty that the Post-Keynesian school approaches its critique of the REH. The problem for Keynes and Post-Keynesian economists is not that long term predictions have low probabilities, but that “. . . there is no scientific basis on which to form any calculable probability whatever. We simply do not know” (Keynes,
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1937 p. 214). It is from the uncertain nature of the future and the associated lack of available knowledge, that Post-Keynesians attack the REH, that is, “. . . if rational action requires true or probable knowledge and true or probable knowledge eludes us, then so does rational action itself’ (Rutherford, 1984, p. 384). Finally, the theoretical framework in which Hall’s model of the REPIH has been developed is based upon the assumption “. . . that consumers face a known, constant, real interest rate” (Hall, 1978, p. 977). Such a proposition has two shortcomings. In the first instance, this supposition makes a strong cognitive assumption about the level of understanding possessed by economic agents in respect to not only economics, but more specifically interest rates and supposes that individuals are capable of making distinctions between economic variables in both nominal and real terms. Secondly real interest rates appear to be highly variable in the Australian experience over time, (see Figure 2). Although our approach is novel, it is not the first to utilize survey data in an examination of consumption expenditure. Pickering (198 1) and Earl (1986) develop behavioral models of durable consumption expenditure by employing expectations data. They conclude that as the time frame of a durable purchase is increased (in terms of repayments), then the level of a consumer’s confidence will be reduced2 and hence so will the likelihood of individuals committing themselves to the purchase. While Fissel and Jappelli (1990) Batchelor and Dua (1992), and Acemoglu and Scott (1994) explore the ability of panel data, consumer survey data and consumer sentiment indices to explain changes in nondurable consumption expenditure. They find that the explanatory ability of such data and the methodologies employed in past examinations call into question the REPIH.
l-_--l short
_-_--.
Figure 1.
Real Interest Rates (1958-l
992)
Long
Nondurable Consumption
295
Expenditure
DATA AND METHODOLOGY Data Our investigation ondary data.
involves the collection
and analysis of both primary and sec-
Primary Data
We employ the use of survey data which is obtained from the administration of a telephone questionnaire. Following Zikmund (1994), a sample size of 100 respondents was chosen using a systematic sampling technique. This questionn~re was employed to determine which variables are implant in the respondents nondurable expenditure decision. To achieve this, respondents were questioned on what pieces of economic information they considered when deciding to expend upon nondurables. Here respondents were presented with 13 alternatives, and space was allocated for other economic and noneconomic considerations. Secondary
Data
The secondary data employed in this analysis is obtained from the Australian Bureau of Statistics (ABS13 and the Reserve Bank of Australia (RBA).4 The data is quarterly, seasonally adjusted in real terms {base year 1989/90) and covers the period 1976(l) to 1994(2). The data set comprises of nondurable consumption expenditure (C), Disposable Household Income (DHY) and Total Credit Available (TCA). DHY is calculated by the ABS and reports on the total amount of disposable income available for all Australian households as an industry sector, while TCA data is the difference between total bank credit card limits outstanding and total bank credit card advances outstanding.5 Strictly speaking this is not the most accurate measure of credit available to Australian households as it ignores other credit facilities such as overdrafts, credit cards supplied by nonbank financial institutions and store credit accounts; however, the credit accessible via credit cards is more likely to be employed in the purchase of nondurable goods and services.
The objective of this investiga~on is to produce a consumption function that is behavioral in nature and comparable with the REPIH. To achieve this, we utilize the variables chosen as important considerations in the nondurable expenditure decision making process by our respondents. The nominated variables are then obtained in a time series format (where possible) and analyzed using an Ordinary Least Squares regression analysis. We also expose this model to the rigors of the White (1980) test for hetroskedasticity, the Ljung-Box6 (1978) test for autocorrelation and the Chow (1960) test for structural stability, in an attempt to discover any econometric irregularities.
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RESULTS Turning our attention to Figure 2, we note that the economic agents surveyed indicated that the decision to expend on nondurables is very much centered around: (a) their previous purchases, (b) the need for the product, (c) the economic agents’ financial situation, (d) price, (e) the amount of available credit and (f) the quality of the nondurable good or service. In the construction of our Behavioral Consumption Function (BCF), restrictions were placed upon the variables that could be utilized, as all were not available in a time series format. Only three variables chosen by respondents are conducive to an analysis that is comparable with the REPIH; these are (a), (c) and (e) above. Thus the BCF denotes nondurable consumption expenditure to be a function of net income less financial obligations (Y, _fi,), the amount of credit available (Cr) and a lagged value of the dependent variable (depicting previous purchases) (C t _ ,). Consequently the BCF takes the following form:
When attempting to produce a numerical aggregate value for the variable net income less financial obligations, it was noted that the disposable measure of household income produced by the ABS in the national accounts satisfied this notion. This measure of income includes: earnings from wages and salaries plus government supplements, net income from dwellings7 income earned in the form of profits, farm income, personal benefit payments, grants and unrequited transfers from overseas. From this measure of household income, the ABS deduct the following disbursements: income tax, government fees, fines, utilities payments, consumer debt interest and unrequited transfers to overseas. This produces at an 80
26
25
Avail Credit
QUiilii
Response Figure 2.
Most Frequently Chosen Considerations
When Purchasing Nondurables
Nondurable Consumption
Expenditure
2‘37
aggregate level a measure of disposable household income akin to the variable net income less financial obligations. We also note that this data is nonstationary and requires differencing in the first instance to return the data to a stationary series. Hence we produce a BCF that is empirically testable in the following form: (3) where Dhy depicts disposable household income, a denotes the fixed coefficient, 13,h, G the variable coefficients, and u is a random error teirm8 The econometric results obtained from the BCF are reported in Table 1. From these results we make two interesting observations. First, the data provides weak evidence against Hall’s REPIH, as the lagged value of available credit has proven to be a significant predictor of changes in nondurable consumption expenditure at the 0.20 level.’ Secondly (and more encouraging), is the significance (as denoted by the t-statistic) of all of the variables chosen by the respondents as considerations in the nondurable expenditure decision.” This result appears to suggest that the methodology we have employed in the construction of our BCF may prove to be superior to the positivist approach currently pursued by many economists, or at the very least this occurrence indicates that economic research that employs a behavioral methodology is a justifiable exercise. Examination of Table 1 indicates that the BCF produces a Marginal Propensity Consume (MPC) of 0.185. In comparison to other MPC’s produced with Australian data, our MPC approximates those of Bladen-Hovel1 and Richards (1983) and Dixon and Rimmer (1995).’ ’ However, we are unable to make direct comparisons between our MPC and that of Johnson (1983) as Johnson has only employed lagged values of income and consequently the MPC’s produced are significantly smaller. The results produced from our employment of the Ljung-Box test for autocorrelation (LB), the Chow test for structural stability (C) and the White test for hetroskedasticity (W) are all presented in Table 1. The LB statistic was not significant at the 0.05 level of significance, allowing us to reject the null hypothesis that the data is autocorrelated and hence conclude that the time series was generated by a white noise process. The results obtained from the White test indicate an absence of hetroskedasticity at the 0.05 significance level and supports the null hypothesis that the residuals are both homoskedastic and independent of the regressors and that the linear specification of the BCF is correct. Finally, the result obtained from the Chow test supports the null hypothesis that the BCF is structurally stable at the 0.05 level of significance. In our attempt to produce the BCF we have been impaired by the inability to obtain time series data that corresponds to all of the variables chosen by the respondents as important considerations when expending upon nondurable goods and services. It is also important to note that all of the variables chosen by
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respondents are not conducive to inclusion in the BCF and probably explain the low R2 values obtained in the production of the BCF. However, despite the low R2 value obtained by the BCF, it performs comparably with Hall’s proposed model in explaining changes in nondurable consumption. Looking at the results produced by two of the more recent examination of the REPIH, we note that MacDonald and Kearney produce an R2 value of 0.29 when employing the change in the sum of disposable income as the additional independent variable. In comparison Acemoglu and Scott utilize a one and two period lagged consumer confidence index as additional variables in their exa~nation of the REZPIH, producing R2 values of 0.440 and 0.292, respectively. Although the R2 values obtained by Acemoglu and Scott are considerably higher than those produced by MacDonald and Kearney and the BCF, it should be noted that Acemoglu and Scott examine the REPIH on UK data in comparison to Macdonald and Kearney’s and our employment of Austrian data. Secondly, the higher R” value obtained by Acemoglue and Scott can also be explained in terms of the high t-statistic produced by the consumer confidence index in explaining changes in nondurable consumption expenditure. l2 Returning our attention to Figure 2, we note that the variable ‘need’ is an important consideration by respondents when expending upon nondurables. However, this variable is impossible to quantify in terms of time series data. The only manner in which we could encompass such a consideration into onr model is via the inclusion of a dummy variable if employing cross sectional data. The variables ‘price’ and ‘quality’ also suffer from the aforementioned difficulty, as we are investigating the existence or absence of relationships with time series data, as opposed to the utilization of cross sectional data. With respect to the variable ‘price’, it is important to clarify that we interpret this variable to refer to relative price as opposed to absolute price. That is, when choosing between nondurable goods or services, the respondents take into consideration relative prices among these goods or services. Like ‘price’, ‘quality’ appears to be a determining factor when choosing between nondurables, as opposed to deciding to expend on nond~rables. Once the individual is dete~~ng which alternative products or services to purchase, the decision to expend has already been made. Thus the variables ‘quality’ and ‘price’ are no longer applicable to the BCF, as the BCF is designed to model the decision whether or not to expend on nondurables, as opposed to deciding which particular nondurables to purchase once the expenditure decision has been made.13 The selection of the variable, previous purchases by the respondents is an interesting inclusion, as it not only improves the econometric model by making it more dynamic in nature, but it also provides some support for the REPIH. However, as this was not the only variable suggested by respondents as an important consideration, the anecdotal evidence as well as the econome~c evidence leads to rejection of the REPIH.
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CONCLUSIONS
In summary we make three observations as a consequence of our investigation: first, the results obtained by the BCF are comparable with those obtained with the REPIH model of nondurable consumption expenditure, while the employment of the nonquantifiable variables and shorter time framed time series data could have only improved the predictability of our model, thus raising the low R2 value obtained. Secondly, after making adjustments to the BCF in order to make it strictly comparable with the REPIH, the data provides weak evidence against Hall’s model of nondurable consumption expenditure. Finally (and more importantly), all of the variables chosen by the respondents have proven to be significant predictors of changes in nondurable consumption expenditure, thus lending support for the adoption of behavioral methodologies in the production of nondurable consumption functions. Based upon this preliminary study, we conclude that econometric models that employ behavioral methodologies in their development may at best improve their forecasting ability and at least improve their theoretical appeal as a consequence of the adoption of behavioral research techniques in their development. NOTES 1.
2. 3. 4. 5. 6. 7.
8. 9. 10. 11.
12. 13.
14.
“Permanent income is roughly akin to lifetime income, based upon the real and financial wealth at the disposal of an individual plus the value of one’s inherent and acquired skills and training” (Peterson, 1988, p. 178). This is a consequence of the greater uncertainty that exists as to making future repayments. ABS Catalogue No. 5206.0. RBA Monthly Bulletins. This data is presented in a monthly format; thus to obtain quarterly data, we had to average out the data on a three monthly basis. We have employed the Ljung-Box test since the Durbin Watson test is invalid as a result of the inclusion of a lagged dependent variable. Net income earned from dwelling refers to the difference between money received as rental income and interest and the amount that is paid out as rent or home loan interest repayments (see ABS cat. no. 5216.0). It is important to note that in order to make the BCF strictly comparable with the REPIH, both the TCA and the DHY data needs to be employed in a lagged form. See Equation 2 in Table 1. See Equation 2 in Table 1. These variables prove to be significant at the 0.01,0.05 and 0.20 levels, respectively. Dixon and Rimmer produce a MPC for total consumption. Following Lewis’ et al. (1994) suggestion that nondurable consumption constitutes 28.6% of total consumption, the MPC’s are comparable. The t-statistic produced by Acemoglu and Scot for the lagged value of consumer confidence is 7.869. Some will argue that the quality of a product will be reflected in the price of the nondurable in question, thus effecting the amount expended. We recognize this argument; however, data on quality is not available in a time series format. This argument is consistent with Haug (1991).
nondurable Consu~pt;on
301
Ex~endjture
REFERENCES Acemoglu, Daron, & Scott, Andrew. (1994). Consumer confidence and rational expectations: are agents beliefs consistent with the theory? The Economic Journal, 104, 1-19. Barro, Robert J. (1976). Rational expectations and the role of monetary policy. Journal of Monetary Economics, I, l-32. Batchelor, Roy, & Dua, Pami. (1992). Survey expectations in the time series consumption function. The Review of Economics and Statistics, 73,598-606. Bladen-Hovell, R.C, & Richards, G.M. (1983). Inflation and Australian savings behavior, 19591981. Australian Economic Papers, 22(41), 290-301. Chow, G.C. (1960). Tests of equality between sets of coefficients in two linear regressions. Econometrica, L&3(2),591-606. Colander, DC. & Guthrie, R.S. (1980). Great expectations: what the dickens do rational expectations’ mean? Journal of Post Keynesian Economics, 3,219-234. Dixon, Peter. B, & Rimmer, Maureen, T. (1995). Macro and sectoral implications of tax increases with differing distributional impacts. The Australian Economic Review, Jan-Mar, 11 l-l 17. Earl, Peter E. (1986). Li&style economics, consumer behavior in a turbulent world. Brighton: Wheatsheaf Books. Fisher, Irving. (1930). 7%e theory ofinferest. New York: Macmillian. Fissel, Gary, & Jappelli, Tullio. (1990). Do liquidity constraints vary over time? Evidence from survey and panel data. Journal of Money, Credit, and Banking, 22(2), 252-261. Flavin, Marjorie A. (1981). The adjustment of consumption to changing expectations about future income. Journal of Pohtical Economy, 89,974-1009. Flavin, Marjorie A. (1985). Excess sensitivity of consumption to current income: liquidity constraints or myopia?. Canadian Journaf of Economics, 18, 11-136. Friedman, Milton. (1957) A theory of the consumption function. New York: Princeton University Press. Hall, Robert. E. (1978). The stochastic implications of the life cycle-permanent income hypothesis: theory and evidence. Journal of Political Economy, 8697 l-87. Haug, Alfred A. (1991). The random walk hypothesis of consumption and time aggregation. Journal of Macroeconomics, 13(4), 691-700. Johnson, Paul. (1983). Life-cycle consumption under rational expectations: some Australian evidence. Economic Record, 59( 167), 345350. Keynes, J.M. ([1921] 1952). A treatise onprobubili~. London: Macmillian. Keynes, J.M. (119361 1991). The general theory of empLoyFnent, interest and money. London: Macmillian. Keynes, J.M. (1937). The general theory of employment. Quarterly Journal of Economics, 51, 209-233. Ljung, G.M., & Box, G.P.E. (1978). On the theoretical specification of sampling properties of autocorrelated time series. Journal of the Royal Statistical Society, Series B, 27, 27-41. Lewis, Philip, et al. (1994). A guide to the Australian economy. Melbourne: Longman Cheshire. Lucas, Robert. (1972). Expectations and the neutrality of money. Journal of Economic Theory, 4, 1033-1024. MacDonald, Ronald, & Keamey, Colm. (1990). Consumption, cointergration and rational expectations: some Australian evidence. Australian Economic Papers, June, 40-52. Mankiw, Gregory, 8c Shapiro, Matthew. (1985). Trends, random walks, and tests of the permanent income hypothesis. Journey of~oneta~ Economics. f6, 165-174. Mil~ume, Ross, & Otto, Glen. (1992). Consumption smoothing and the current account. Ausrraljun Economic Paper, 31,44-53. Modigliani, F. (1949). Studies in income and wealth, vol. 2. National Bureau of Economic Research.
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Muth, John. (1961). Rational expectations and the theory of price movements. Econometrica, 29, 315-335. Peterson, W.C. (1988). Income, employment and economic growth. New York: W.W. Norton. Pickering, J.F. (1981). A behavioral model of the demand for consumer durables. In Peter Earl (Ed.), Behavioral economics, vol. 2. Aldershot: Edward Elger. Rutherford, Malcom. (1984). Rational expectations and Keynesian uncertainty: a critique. Journal of Post Keynesian Economics. 6, 377-387. Sargent. T.J. (1973). Rational expectations: the real rate of interest and the natural rate of unemployment. Brookings Papers On Economic Activity, 2,429-472. Sargent, T.J, & Wallace. N. (1973a). The stability of models of money and growth with perfect foresight. Ec~~nometrica, 41, 1043-1048. Sargent, T.J, & Wallace, N. (1973b). Rational expectations and the dynamics of hyperInflation. International Economic Review, 14, 328-350. Sargent, T.J, & Wallace, N. (1975). Rational expectations, the optimal monetary instrument and the optimal money supply rule. Journal Of Political Economy, 83,241-254. Tolar, Martin. M. (1995). Satisficing versus optimising behavior in the nondurable consumption expenditure decision making process: an empirical examination of Australian data for the period 1976( l)- 1994(2). Unpublished manuscript, M. Comm (Hons). University of Western Sydney, Macarthur. White, H. (1980). A hetroskedasticity-consistent covariance estimator and a direct test for hetroskedasticity. Economefrica, 48,817.838. Zikmund, William G. (1994). Business research methods. Fort Worth: Dryden.
MARTIN MICHAEL TOLAR” University of Western Sydney
ABSTRACT:
This paper employs survey data in an attempt to produce a behavioral model of nondurable consumption expenditure. This model is then applied to Australian data for the period 1976(l) to 1994(2). Despite empirical difficulties associated with the attainment of some time series data, our results prove encouraging for the adoption of behavioral methodologies in the production of nondurable consumption functions, while casting doubts upon the currently accepted rational expectations permanent income model of nondurable consumption expenditure.
INTRODUCTION
In recent times the neoclassical concept of ration~ity has come to do~nat~ the manner in which economists model expectations formation and economic decision making. This study challenges this concept within the context of the nondurable consumption expenditure decision making process. Rational economic man was reintroduced into economic debate by Muth (1961), within the context of expectations formation. However, it was not until the works of Lucas (1972), Sargent (1973), Sargent and Wallace (1973a, 1973b, 1975) and Barre (1976) that rational expectations and the concept of rationality re-entered mainstream macroeconomic debate. By definition, rational expectations propounds that the expectations formed by economic agents are equivalent to those produced by the relevant economic model, and any errors that occur are of a random nature, resulting from unavailable information (see Mum, 1961). *Direct all correspondence to: Martin Michael Tolar. University of Western Sydney, Macarthur Faculty Business and Technology, P.O. Box 555, Campbelltown, NSW, Australia 2560: e-mail: [email protected]. Journal of S~i~~connmi~, Volume 26, No. 3, Pp. 291-302 Copyright 0 1997 by JAI Press, Inc. All rights of reproduction in any form reserved. ISSN: 10534357
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Following F~edman (1957) and Muth (1961), Hall (1978) produces a model of nondurable consumption expenditure that models individuals as forward looking rational economic beings that form nondurable consumption expenditure decisions on the basis of their permanent income.’ Despite this approach’s widespread acceptance, empirical examinations of the hypothesis have produced inconclusive results (see Flavin, 1981, 1985; Mankiw & Shapiro, 1985, MacDonald & Kearney, 1990; Milbourne & Otto, 1992 for a general overview), while on a theoretical level there exist a number of anomalies between the underlying assumptions of human behavior in Hall’s model and the economic actuality. This study attempts to rectify the theoretical shortcomings of Hall’s approach by employing a behavioral methodology in the development of an alternate model of nondurable consumption expenditure. It is envisaged that the employment of this methodology will produce a model that will capture both economic and noneconomic information that individuals consider to be important in deciding to expend upon nondurable goods and services that are currently not contained within the method proposed by Hall. We conclude that based upon this preliminary study, econometric models that employ behavioral methodologies in their development may at best improve their forecasting ability and at least improve their theoretical appeal as a consequence of the adoption of behavioral research techniques. The remainder of this study is set out as follows: Section 2 provides a review of the literature pertaining to the rational expectations permanent income hypothesis, and Section 3 presents an outline of the data and methodology employed in this paper. We present our results in Section 4 and then draw together our conclusions in Section 5. LITERATURE REVIEW Friedman’s (1957) Permanent Income Hypothesis (PIH) has been adopted by the neoclassical school as their model of optimizing behavior in the context of nondurable consumer expenditure decision making. The PIH follows Fisher’s (1930) model of intertemporal optimization and Modigliani’s (1949) Life Cycle Hypothesis. Initially the PIH was developed by Friedman as a forward looking model of consumption expenditure. However, as a consequence of empirical difficulties, the PIH was tested in and hence has come to be associated with the backward looking adaptive expectations hypothesis. Hall (1978) rectifies this occurrence by placing the PIH into a rational expectations framework, returning the PIH to its intended context, which can be represented as follows:
Cff1 = a+ l3c,+ u,, ,,
(1)
where C denotes nondurable consumption expenditure, a is the fixed coefficient, 13is a regression coefficient, and u is the random error coefficient.
Nondurable Cons~~ptjon
~xfendjture
293
Equation 1 is the result of economic agents forming nondurable expenditure decisions for the next period (t + 1) based upon the information available at time t. Thus Hall produces the testable null hypothesis that: Rational economic agents utilize all of the information available at time t in their planned nondurable consumption expenditure in period t + 1. Consequently, the only significant predictor of nondurable consumption expenditure in any given period is the previous periThus a regression equation that ods nondurable consumption expenditure. includes additional lagged parameters, other than a one period lagged value of nondurable consumption expenditure, will not improve the model’s predictability. Hall’s approach presents some diff%ulties, in that his exa~nation is a test of a joint hypothesis, that of the method in which consumers expend on nondurables and the manner in which they form their expectations about the future. The proposition that current consumption is an unbiased predictor of future consumption, thus consumption expenditure behaves as a random walk, appears to place more emphasis on the second of the joint hypotheses. Consequently, rejection of Hall’s methodology may not be a result of a rejection of the PIH, but rather the Rational Expectations Hypothesis (REH). As a consequence of Hall’s unification of the REH with the PIH (REPIH), a number of theoretical problems arise, most of which are inherited from the adoption of the REH. First, it is assumed that economic agents have a complete understanding of the workings of the economy and that information is perfect, in the sense that everybody has equal access to the same informational set. Hence Hall assumes that economic actors have the cognitive capability and information to calculate their permanent income, thus being in a position to balance current and future nondurable consumption expenditure accordingly. Such an assumption ignores the intellectual, informational, time and opportunity cost constraints placed upon an individual, in their attempt to calculate their permanent income and expend upon nondurables accordingly. Our second criticism of the assumption of rational economic agents stems from the Post-Keynesian school’s advocacy of an uncertain and unknowable future. Following Keynes (1921, 1936), the Post-Keynesian school dispute the REH, on the grounds of fundamental or incalculable uncertainty. As a consequence of an uncertain and unknowable future, it is impossible for individuals to form accurate predictions, while providing models to calculate predictions of these future economic occurrences proves to be just as difficult (see Colander & Guthrie, 1980). Keynes raises doubts as to the ability of economic actors to assign numerical probabilities to uncertain future events, hence placing them in a position that does not allow them to maximize their utility (see Rutherford, 1984). It is from this explanation of uncertainty that the Post-Keynesian school approaches its critique of the REH. The problem for Keynes and Post-Keynesian economists is not that long term predictions have low probabilities, but that “. . . there is no scientific basis on which to form any calculable probability whatever. We simply do not know” (Keynes,
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1937 p. 214). It is from the uncertain nature of the future and the associated lack of available knowledge, that Post-Keynesians attack the REH, that is, “. . . if rational action requires true or probable knowledge and true or probable knowledge eludes us, then so does rational action itself’ (Rutherford, 1984, p. 384). Finally, the theoretical framework in which Hall’s model of the REPIH has been developed is based upon the assumption “. . . that consumers face a known, constant, real interest rate” (Hall, 1978, p. 977). Such a proposition has two shortcomings. In the first instance, this supposition makes a strong cognitive assumption about the level of understanding possessed by economic agents in respect to not only economics, but more specifically interest rates and supposes that individuals are capable of making distinctions between economic variables in both nominal and real terms. Secondly real interest rates appear to be highly variable in the Australian experience over time, (see Figure 2). Although our approach is novel, it is not the first to utilize survey data in an examination of consumption expenditure. Pickering (198 1) and Earl (1986) develop behavioral models of durable consumption expenditure by employing expectations data. They conclude that as the time frame of a durable purchase is increased (in terms of repayments), then the level of a consumer’s confidence will be reduced2 and hence so will the likelihood of individuals committing themselves to the purchase. While Fissel and Jappelli (1990) Batchelor and Dua (1992), and Acemoglu and Scott (1994) explore the ability of panel data, consumer survey data and consumer sentiment indices to explain changes in nondurable consumption expenditure. They find that the explanatory ability of such data and the methodologies employed in past examinations call into question the REPIH.
l-_--l short
_-_--.
Figure 1.
Real Interest Rates (1958-l
992)
Long
Nondurable Consumption
295
Expenditure
DATA AND METHODOLOGY Data Our investigation ondary data.
involves the collection
and analysis of both primary and sec-
Primary Data
We employ the use of survey data which is obtained from the administration of a telephone questionnaire. Following Zikmund (1994), a sample size of 100 respondents was chosen using a systematic sampling technique. This questionn~re was employed to determine which variables are implant in the respondents nondurable expenditure decision. To achieve this, respondents were questioned on what pieces of economic information they considered when deciding to expend upon nondurables. Here respondents were presented with 13 alternatives, and space was allocated for other economic and noneconomic considerations. Secondary
Data
The secondary data employed in this analysis is obtained from the Australian Bureau of Statistics (ABS13 and the Reserve Bank of Australia (RBA).4 The data is quarterly, seasonally adjusted in real terms {base year 1989/90) and covers the period 1976(l) to 1994(2). The data set comprises of nondurable consumption expenditure (C), Disposable Household Income (DHY) and Total Credit Available (TCA). DHY is calculated by the ABS and reports on the total amount of disposable income available for all Australian households as an industry sector, while TCA data is the difference between total bank credit card limits outstanding and total bank credit card advances outstanding.5 Strictly speaking this is not the most accurate measure of credit available to Australian households as it ignores other credit facilities such as overdrafts, credit cards supplied by nonbank financial institutions and store credit accounts; however, the credit accessible via credit cards is more likely to be employed in the purchase of nondurable goods and services.
The objective of this investiga~on is to produce a consumption function that is behavioral in nature and comparable with the REPIH. To achieve this, we utilize the variables chosen as important considerations in the nondurable expenditure decision making process by our respondents. The nominated variables are then obtained in a time series format (where possible) and analyzed using an Ordinary Least Squares regression analysis. We also expose this model to the rigors of the White (1980) test for hetroskedasticity, the Ljung-Box6 (1978) test for autocorrelation and the Chow (1960) test for structural stability, in an attempt to discover any econometric irregularities.
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RESULTS Turning our attention to Figure 2, we note that the economic agents surveyed indicated that the decision to expend on nondurables is very much centered around: (a) their previous purchases, (b) the need for the product, (c) the economic agents’ financial situation, (d) price, (e) the amount of available credit and (f) the quality of the nondurable good or service. In the construction of our Behavioral Consumption Function (BCF), restrictions were placed upon the variables that could be utilized, as all were not available in a time series format. Only three variables chosen by respondents are conducive to an analysis that is comparable with the REPIH; these are (a), (c) and (e) above. Thus the BCF denotes nondurable consumption expenditure to be a function of net income less financial obligations (Y, _fi,), the amount of credit available (Cr) and a lagged value of the dependent variable (depicting previous purchases) (C t _ ,). Consequently the BCF takes the following form:
When attempting to produce a numerical aggregate value for the variable net income less financial obligations, it was noted that the disposable measure of household income produced by the ABS in the national accounts satisfied this notion. This measure of income includes: earnings from wages and salaries plus government supplements, net income from dwellings7 income earned in the form of profits, farm income, personal benefit payments, grants and unrequited transfers from overseas. From this measure of household income, the ABS deduct the following disbursements: income tax, government fees, fines, utilities payments, consumer debt interest and unrequited transfers to overseas. This produces at an 80
26
25
Avail Credit
QUiilii
Response Figure 2.
Most Frequently Chosen Considerations
When Purchasing Nondurables
Nondurable Consumption
Expenditure
2‘37
aggregate level a measure of disposable household income akin to the variable net income less financial obligations. We also note that this data is nonstationary and requires differencing in the first instance to return the data to a stationary series. Hence we produce a BCF that is empirically testable in the following form: (3) where Dhy depicts disposable household income, a denotes the fixed coefficient, 13,h, G the variable coefficients, and u is a random error teirm8 The econometric results obtained from the BCF are reported in Table 1. From these results we make two interesting observations. First, the data provides weak evidence against Hall’s REPIH, as the lagged value of available credit has proven to be a significant predictor of changes in nondurable consumption expenditure at the 0.20 level.’ Secondly (and more encouraging), is the significance (as denoted by the t-statistic) of all of the variables chosen by the respondents as considerations in the nondurable expenditure decision.” This result appears to suggest that the methodology we have employed in the construction of our BCF may prove to be superior to the positivist approach currently pursued by many economists, or at the very least this occurrence indicates that economic research that employs a behavioral methodology is a justifiable exercise. Examination of Table 1 indicates that the BCF produces a Marginal Propensity Consume (MPC) of 0.185. In comparison to other MPC’s produced with Australian data, our MPC approximates those of Bladen-Hovel1 and Richards (1983) and Dixon and Rimmer (1995).’ ’ However, we are unable to make direct comparisons between our MPC and that of Johnson (1983) as Johnson has only employed lagged values of income and consequently the MPC’s produced are significantly smaller. The results produced from our employment of the Ljung-Box test for autocorrelation (LB), the Chow test for structural stability (C) and the White test for hetroskedasticity (W) are all presented in Table 1. The LB statistic was not significant at the 0.05 level of significance, allowing us to reject the null hypothesis that the data is autocorrelated and hence conclude that the time series was generated by a white noise process. The results obtained from the White test indicate an absence of hetroskedasticity at the 0.05 significance level and supports the null hypothesis that the residuals are both homoskedastic and independent of the regressors and that the linear specification of the BCF is correct. Finally, the result obtained from the Chow test supports the null hypothesis that the BCF is structurally stable at the 0.05 level of significance. In our attempt to produce the BCF we have been impaired by the inability to obtain time series data that corresponds to all of the variables chosen by the respondents as important considerations when expending upon nondurable goods and services. It is also important to note that all of the variables chosen by
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respondents are not conducive to inclusion in the BCF and probably explain the low R2 values obtained in the production of the BCF. However, despite the low R2 value obtained by the BCF, it performs comparably with Hall’s proposed model in explaining changes in nondurable consumption. Looking at the results produced by two of the more recent examination of the REPIH, we note that MacDonald and Kearney produce an R2 value of 0.29 when employing the change in the sum of disposable income as the additional independent variable. In comparison Acemoglu and Scott utilize a one and two period lagged consumer confidence index as additional variables in their exa~nation of the REZPIH, producing R2 values of 0.440 and 0.292, respectively. Although the R2 values obtained by Acemoglu and Scott are considerably higher than those produced by MacDonald and Kearney and the BCF, it should be noted that Acemoglu and Scott examine the REPIH on UK data in comparison to Macdonald and Kearney’s and our employment of Austrian data. Secondly, the higher R” value obtained by Acemoglue and Scott can also be explained in terms of the high t-statistic produced by the consumer confidence index in explaining changes in nondurable consumption expenditure. l2 Returning our attention to Figure 2, we note that the variable ‘need’ is an important consideration by respondents when expending upon nondurables. However, this variable is impossible to quantify in terms of time series data. The only manner in which we could encompass such a consideration into onr model is via the inclusion of a dummy variable if employing cross sectional data. The variables ‘price’ and ‘quality’ also suffer from the aforementioned difficulty, as we are investigating the existence or absence of relationships with time series data, as opposed to the utilization of cross sectional data. With respect to the variable ‘price’, it is important to clarify that we interpret this variable to refer to relative price as opposed to absolute price. That is, when choosing between nondurable goods or services, the respondents take into consideration relative prices among these goods or services. Like ‘price’, ‘quality’ appears to be a determining factor when choosing between nondurables, as opposed to deciding to expend on nond~rables. Once the individual is dete~~ng which alternative products or services to purchase, the decision to expend has already been made. Thus the variables ‘quality’ and ‘price’ are no longer applicable to the BCF, as the BCF is designed to model the decision whether or not to expend on nondurables, as opposed to deciding which particular nondurables to purchase once the expenditure decision has been made.13 The selection of the variable, previous purchases by the respondents is an interesting inclusion, as it not only improves the econometric model by making it more dynamic in nature, but it also provides some support for the REPIH. However, as this was not the only variable suggested by respondents as an important consideration, the anecdotal evidence as well as the econome~c evidence leads to rejection of the REPIH.
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CONCLUSIONS
In summary we make three observations as a consequence of our investigation: first, the results obtained by the BCF are comparable with those obtained with the REPIH model of nondurable consumption expenditure, while the employment of the nonquantifiable variables and shorter time framed time series data could have only improved the predictability of our model, thus raising the low R2 value obtained. Secondly, after making adjustments to the BCF in order to make it strictly comparable with the REPIH, the data provides weak evidence against Hall’s model of nondurable consumption expenditure. Finally (and more importantly), all of the variables chosen by the respondents have proven to be significant predictors of changes in nondurable consumption expenditure, thus lending support for the adoption of behavioral methodologies in the production of nondurable consumption functions. Based upon this preliminary study, we conclude that econometric models that employ behavioral methodologies in their development may at best improve their forecasting ability and at least improve their theoretical appeal as a consequence of the adoption of behavioral research techniques in their development. NOTES 1.
2. 3. 4. 5. 6. 7.
8. 9. 10. 11.
12. 13.
14.
“Permanent income is roughly akin to lifetime income, based upon the real and financial wealth at the disposal of an individual plus the value of one’s inherent and acquired skills and training” (Peterson, 1988, p. 178). This is a consequence of the greater uncertainty that exists as to making future repayments. ABS Catalogue No. 5206.0. RBA Monthly Bulletins. This data is presented in a monthly format; thus to obtain quarterly data, we had to average out the data on a three monthly basis. We have employed the Ljung-Box test since the Durbin Watson test is invalid as a result of the inclusion of a lagged dependent variable. Net income earned from dwelling refers to the difference between money received as rental income and interest and the amount that is paid out as rent or home loan interest repayments (see ABS cat. no. 5216.0). It is important to note that in order to make the BCF strictly comparable with the REPIH, both the TCA and the DHY data needs to be employed in a lagged form. See Equation 2 in Table 1. See Equation 2 in Table 1. These variables prove to be significant at the 0.01,0.05 and 0.20 levels, respectively. Dixon and Rimmer produce a MPC for total consumption. Following Lewis’ et al. (1994) suggestion that nondurable consumption constitutes 28.6% of total consumption, the MPC’s are comparable. The t-statistic produced by Acemoglu and Scot for the lagged value of consumer confidence is 7.869. Some will argue that the quality of a product will be reflected in the price of the nondurable in question, thus effecting the amount expended. We recognize this argument; however, data on quality is not available in a time series format. This argument is consistent with Haug (1991).
nondurable Consu~pt;on
301
Ex~endjture
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Muth, John. (1961). Rational expectations and the theory of price movements. Econometrica, 29, 315-335. Peterson, W.C. (1988). Income, employment and economic growth. New York: W.W. Norton. Pickering, J.F. (1981). A behavioral model of the demand for consumer durables. In Peter Earl (Ed.), Behavioral economics, vol. 2. Aldershot: Edward Elger. Rutherford, Malcom. (1984). Rational expectations and Keynesian uncertainty: a critique. Journal of Post Keynesian Economics. 6, 377-387. Sargent. T.J. (1973). Rational expectations: the real rate of interest and the natural rate of unemployment. Brookings Papers On Economic Activity, 2,429-472. Sargent, T.J, & Wallace. N. (1973a). The stability of models of money and growth with perfect foresight. Ec~~nometrica, 41, 1043-1048. Sargent, T.J, & Wallace, N. (1973b). Rational expectations and the dynamics of hyperInflation. International Economic Review, 14, 328-350. Sargent, T.J, & Wallace, N. (1975). Rational expectations, the optimal monetary instrument and the optimal money supply rule. Journal Of Political Economy, 83,241-254. Tolar, Martin. M. (1995). Satisficing versus optimising behavior in the nondurable consumption expenditure decision making process: an empirical examination of Australian data for the period 1976( l)- 1994(2). Unpublished manuscript, M. Comm (Hons). University of Western Sydney, Macarthur. White, H. (1980). A hetroskedasticity-consistent covariance estimator and a direct test for hetroskedasticity. Economefrica, 48,817.838. Zikmund, William G. (1994). Business research methods. Fort Worth: Dryden.