RDP 2016-02: Disagreement about Inflation Expectations 6. Are Consumer Expectations More Weakly Anchored?

There remains the question as to why disagreement in consumer inflation expectations is so much larger than among other agents. Two main explanations have been proposed (Cavallo, Cruces and Perez-Truglia 2014):

1. Rational inattention: Consumers are typically not professional forecasters, so their ability and incentive to collect and process information relevant to inflation are lower; this is consistent with rational inattention (Carroll 2003; Mankiw et al 2004). However, rational inattention appears insufficient to explain the extent of disagreement among consumers. Models such as that proposed by Carroll (2003) cannot explain the magnitude of disagreement observed for consumers, nor can the sticky-information model (which also has inattentiveness at its heart). For example, these models cannot explain why a large portion of individuals persistently forecast inflation outside the range of historical experience. In addition, inattentiveness might actually suggest a narrow distribution, if many responses are always equal to the inflation target.
2. Individual experience: Alternatively, individuals may use different information sets based on their personal experience, and place excess weight on some items relative to others.^[15] Moreover, there are varying degrees of financial literacy among consumers, and some groups may be more prone to biases than others. Individuals may also base expectations on their lifetime average experience of inflation. As a result, disagreement may reflect different beliefs about long-run inflation, consistent with a lower degree of anchoring among households than professional forecasters.^[16]

In this section, we document evidence that individual household experience explains at least part of the wide disagreement in consumer inflation expectations. There are long-run differences in consumer expectations by demographic group. These appear to be at least partly related to personal inflation experience. While these results explain only a relatively small part of overall disagreement, they are consistent with consumer disagreement being at least partly explained by ‘differences in means’.^[17]

We also find that aggregate consumer inflation expectations over-react to salient prices, particularly petrol. This suggests that consumers' expectations are backward looking and so somewhat non-rational.^[18] It also refutes the rational inattention explanation for consumer disagreement, which would suggest that consumers under-react to new information. One consequence of this result is that movements in relative prices in the CPI basket might see some consumers' expectations become less anchored, even where aggregate inflation outcomes are consistent with the target.

6.1 Disagreement by Demographic Groups

If consumers have different beliefs about long-run inflation, we should expect to see individuals or groups that have persistently high or low inflation expectations. Ideally, we might test this at the individual consumer level; however, the Melbourne Institute data are not panel in nature, as a new sample of individuals is surveyed each month. Accordingly, we look at persistent differences in expectations across observable demographic characteristics to identify long-run differences in mean expectations.

The Melbourne Institute data contain a set of demographic variables including gender, age, education and annual household income.^[19] We divide individuals into a relatively small number of groups, which helps provide statistical power to find significant differences in inflation expectations between groups.^[20] These demographic characteristics most likely serve as a proxy for unobservable factors, such as differences in financial literacy and inflation experience.

To estimate long-run differences between demographic groups we augment our filtering model of consumer inflation expectations detailed in Section 4.2 with demographic dummy variables. We also allow for differences in estimated disagreement within each demographic group by defining the standard deviation as a function of the same dummy variables. As we are interested in persistent differences, we pool the data from the full sample in order to estimate the average difference between groups. Equation (1) is now replaced by

where η^group is a matrix of demographic dummy variables (including a constant) and β and γ are vectors of coefficients.^[21] The likelihood function for observation i is given by

The set of parameters that maximise the joint log-likelihood function for the observed survey data are reported in Table 7. The results are highly statistically significant, in large part due to the very large dataset. In addition, Wald tests confirm that the coefficients estimated for each group are statistically different to the other groups in the same demographic category.

Many of the estimates suggest differences in long-run means across demographic groups: males, those with higher education levels, and those with higher incomes tend to have lower inflation expectations, on average. However, the results for the age dummies do not show a systematic correlation, in line with the mixed findings in the literature (Bryan and Venkatu 2001; Blanchflower and Mac Coille 2009; Bruine de Bruin et al 2010b; Madeira and Zafar 2015).^[22]

Groups that have consistently higher inflation expectations over time also have consistently greater within-group disagreement in expectations. This is in line with the finding in Section 5 that, through time, high expectations have been associated with high levels of disagreement. Rational inattention cannot explain this cross-sectional finding: less attentive groups should have higher disagreement but the same mean over time.

Figure 10 illustrates the evolution of the μ parameter on several key demographic characteristics over time, using a binary split of each demographic category. These differences in expectations by demographic group are quite stable. However, there are some periods during which these differences are smaller or larger; in particular, the higher expectations of older individuals have become statistically insignificant in recent years. There is some tentative evidence that certain groups are more susceptible to macroeconomic shocks. In particular, female respondents show a marked increase in expectations around the time of the global financial crisis. In addition, males and university-educated respondents appear to have had relatively high expectations around the time of the introduction of the GST. However, these two outcomes have opposing implications for interpreting disagreement. The GST episode supports sticky-information models of expectation formation, with males and university-educated consumers showing a greater tendency to update their information sets, whereas the global financial crisis episode implies females were more attentive to macroeconomic developments.

While the differences between some demographic groups are suggestive of differences in means, they only explain a small part of overall disagreement. Efron's pseudo R-squared statistic for the full sample results indicates the demographic variables only explain around 1.4 per cent of the overall variation in expectations. Thus, there is substantial variation in beliefs about inflation expectations not proxied by demographic variables.

6.2 Does Long-run Disagreement Reflect Actual Inflation Experience?

As noted above, one factor that may be related to persistent differences in inflation expectations are differences in inflation experience. Using data on household consumption from the Household Expenditure Survey (HES), we produce realised inflation series tailored to individual households in order to gauge the extent of disagreement in inflation experience.^[23]

Overall, households' expectations are considerably more dispersed than their inflation experience. Across households, inflation expectations are around twice as dispersed as inflation outcomes (Figure 11).^[24] However, the level of dispersion in households' realised inflation is markedly higher than the level of disagreement in professional forecasters' expectations, suggesting that differences in individual inflation experience may still explain an important part of the level, if not variation, of disagreement in consumers' expectations.

There is some evidence that individuals that experience higher inflation also expect higher inflation. While the data available do not link an individual household's expectations and inflation experience, we can again assess this according to demographic characteristics. By income, age and education, demographic groups that have experienced higher inflation outcomes over the past decade have also reported higher inflation expectations on average. Allowing for an approximately 1.5 percentage point upward bias in inflation expectations across all groups, there is an approximately one-for-one relationship between realised and expected inflation expectations by group over the past decade (Figure 12).

Again, these differences only account for a very small portion of the overall disagreement in expectations.^[25] Rather, most of the variation is within demographic groups. Looking within groups, there is also a clear correlation between disagreement in expectations and dispersion in inflation outcomes (Figure 13).^[26]

In part, the results for the consumer survey are likely to reflect the wording of the question that is posed to consumers. In particular, respondents are asked to think about the ‘prices of things [they] buy’. International work has demonstrated that such question wording can engender responses that are quite different from a question about ‘economy-wide inflation’ (Bruine de Bruin et al 2010a). Preliminary analysis of Australian data suggests that survey wording may have a similar effect, and further study in this area is warranted.^[27]

6.3 Response of Consumer Inflation Expectations to Salient Prices

An important implication of individuals relating future inflation to their personal experience is that movements in certain salient prices may have a disproportionate effect on aggregate expectations. Examples of salient prices are petrol prices, utility prices and rents, which tend to be either volatile or move in a discrete fashion. Because changes in petrol prices are essentially unforecastable, a response of consumer inflation expectations to past changes in petrol prices would be suggestive of uninformed behaviour, or beliefs that second-round price effects of petrol price changes are large.

To test for the presence of salient price effects, we regress mean consumer inflation expectations on a range of explanatory variables, including macroeconomic factors (the unemployment rate, the output gap and the level of the cash rate). In addition, lagged movements in three salient prices are included (petrol, housing and rents), as is lagged underlying inflation, so that these salient prices effectively enter the specification as relative prices. A lag of the dependent variable is also included to control for the autoregressive nature of expectations.

The results provide strong evidence that aggregate inflation expectations are positively related to past movements in petrol prices (Table 8). While the size of the coefficient is broadly in line with the weight of petrol in the CPI basket, given that petrol prices are close to a random walk they suggest an uninformed or backward-looking response. Other salient prices are not found to be statistically significant. The sensitivity of inflation expectations to petrol prices but not to most other macroeconomic news (see Section 5) provides evidence against the pure sticky-information model, which supposes time- rather than price-dependent acquisition of information.

Footnotes

See, for example, Bruine de Bruin, van der Klaauw and Topa (2011), Madeira and Zafar (2015) and Malmendier and Nagel (2016). [15]

Inflation learning may also occur more slowly than for professionals, in which case an individual's expectations may appear backward looking. [16]

It may be the case that some consumers fundamentally do not understand the survey question. [17]

Another possibility is that consumers believe there are large second-round price effects of petrol price changes. [18]

The dataset also includes variables for home ownership, voting intention and location. [19]

These groupings are split along a number of dimensions: male and female; ages 18–34, 35–44, 45–64, and 65 years and over; education level non-secondary, secondary, vocational, tertiary (including diplomas and undergraduate degrees) and postgraduate; incomes $30,000 or under, $31,000–80,000, $81,000–100,000, over $100,000 and those who refused to provide their income. [20]

We use males aged 35–44 years with vocational education and income of $30,000–80,000 as our base group, which is captured by the constant. [21]

This is despite there being a clear difference in raw means across the age groups. This is a result of collinearity between age and income; around half of the respondents aged 65 or older also have an annual income of $30,000 or less. Accordingly, the higher raw average inflation expectation of older respondents is empirically explained by their lower income. [22]

See Jacobs, Perera and Williams (2014). [23]

Moreover, periods of elevated disagreement in inflation expectations do not coincide with periods of increased dispersion in inflation outcomes. [24]

Efron's R-squared, equal to 0.0035, suggests that long-run differences in realised inflation between demographic groups explain little of the variation in inflation expectations. [25]

There are some limitations in reaching this conclusion. In particular, differences in measured inflation experience between groups might partly reflect measurement issues – notably, that the dispersion of inflation outcomes is based upon certain assumptions, and so may under-estimate the full dispersion of household experiences. For example, differences in measured inflation experience between groups does not capture differences in inflation rates for the same good or service within a given city. For more details on the construction of these data, see Jacobs et al (2014). [26]

Preliminary analysis has been conducted using data from a trial survey question asking consumers about expected ‘inflation’ rather than changes in the ‘prices of things you buy’. The ‘inflation’ question elicited fewer extreme responses than the ‘prices of things you buy’ question, and a tighter distribution around the midpoint of the RBA's inflation target. [27]