Demographic Differences in Inflation Expectations: What Do They Really Mean?

Meyer, Brent; Venkatu, Guhan

doi:10.26509/frbc-ec-201107

Cited by 8 publications

(10 citation statements)

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“…Still, the eyeball metric suggests that infl ation expectations did not decline in earnest until about the same time. (2011) andNeely (2015) also fi nd that infl ation expectations are highly responsive to energy prices. 6.…”

Section: Resultsmentioning

confidence: 99%

“…8. A number of other factors are believed to infl uence infl ation expectations, such as demographic characteristics (see, e.g., Souleles 2004), education and economic literacy (see, e.g., Bruine de Bruin et al 2010 or Meyer andVenkatu 2011), the actual infl ation experiences of consumers (see, e.g., Malmendier and Nagel 2016), consumer attitudes (see, e.g., Ehrmann et al 2015), and media exposure (see, e.g., Carroll 2003). 9.…”

Section: Resultsmentioning

confidence: 99%

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Digging into the Downward Trend in Consumer Inflation Expectations

Verbrugge

Binder²

2016

EC (FRB Cleveland)

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Digging into the Downward Trend in Consumer Inflation Expectations

Verbrugge

Binder²

2016

EC (FRB Cleveland)

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“…Consistent with Jonung (1981) and Bryan and Venkatu (2001a), we find that women tend to both perceive and expect higher inflation than men. The differences are more notable for the trimmed means than for the medians, indicating that the differences are more pronounced toward the top of the distributions (see also Meyer and Venkatu, 2011). The difference in the trimmed means for both perceived and expected inflation are statistically significant at the 1% level.…”

Section: Differences Across Demographic Groupsmentioning

confidence: 88%

Perceptions and Expectations of Inflation by U.S. Households

Axelrod

Lebow

Peneva

2018

FEDS

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To better understand inflation expectations, we examine newly available data on U.S. households' inflation perceptions-what people think inflation has been in the past. The overarching summary is that inflation perceptions look similar to inflation expectations. The central tendencies of the responses for perceived inflation over the past five to ten years are similar to those of expected inflation for the next five to ten years, and all are a little above official estimates of inflation. Thus, survey respondents overall do not expect long-term inflation to change in the future relative to the recent past. Moreover, individuals who perceive higher inflation in the past tend to expect higher inflation in the future; people whose perceptions change tend to revise their expectations in the same direction; and perceptions and expectations vary similarly by gender and income. These results suggest that if inflation perceptions were to change, they could lead inflation expectations to change as well.

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“…It reports the personal characteristics of the respondents, such as gender, age, marital status, education, race, and income level. The findings generally suggest that white men with more than high-school educational level, within the 55-65 years-old range provide more accurate inflation forecast 12-month-ahead (Bryan and Venkatu, 2001a,b;Souleles, 2004;Pfajfar and Santoro, 2008;Meyer and Venkatu, 2011;Madeira and Zafar, 2015). The "race" variable is included in Bryan and Venkatu (2001a), Meyer and Venkatu (2011), Madeira and Zafar (2015), Axelrod et al (2018) when using the Survey of Consumers, and Rossouw et al (2011) analysing the South African case, playing a role in forecast accuracy.…”

Section: Discussion and Directions For Further Researchmentioning

confidence: 99%

Searching for the Best Inflation Forecasters within an Employment Survey: Microdata Evidence from Chile

Medel

2022

ECONOMIA

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This article aims to evaluate quantitative inflation forecasts for the Chilean economy, taking advantage of a specific survey of consumer perceptions at the individual microdata level, which, at the same time, is linked to a survey of employment in Chile’s capital city. Thus, it is possible to link, with no error, consumer perceptions and 12-month-ahead inflation forecasts with personal characteristics such as gender, age, educational level, county of living, and the economic sector in which they are currently working. By using a sample ranging from 2005.III to 2018.IV, the results suggest that women aged between 35 and 65 years old, with a college degree, living in the North-eastern part of Santiago (the richest of the city), and working in the Community and Social Services sector are the best forecasters. Men aged between 35 and 65 years old, with a college degree, in a tie living in the North-eastern and South-eastern zones but working in Government and Financial Services and Retail sectors, respectively, come in second. Some econometric exercises reinforce and give greater support to the group of most accurate forecasters and reveal that another group of forecasters, different from the second-best in terms of forecast accuracy, displays the characteristics required of a forecasting variable. Remarkably, this group has the same specifications as the most accurate group, with the only difference being that it is composed of men instead of women. Thus, it looks promising for further consideration. Importantly, a forecast accuracy test reveals that no factor comes out as superior to the naïve random walk forecast used as a benchmark. These results are important because they help to identify the most accurate group when forecasting inflation and, thus, help refine the information provided by the survey for inflation forecasting purposes.

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Demographic Differences in Inflation Expectations: What Do They Really Mean?

Cited by 8 publications

References 0 publications

Digging into the Downward Trend in Consumer Inflation Expectations

Digging into the Downward Trend in Consumer Inflation Expectations

Perceptions and Expectations of Inflation by U.S. Households

Searching for the Best Inflation Forecasters within an Employment Survey: Microdata Evidence from Chile

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