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December 4, 2013

Introducing the FRBNY Survey of Consumer Expectations: Survey Goals, Design, and Content

Olivier Armantier, Giorgio Topa, Wilbert van der Klaauw, and Basit Zafar

Note: We aren’t releasing the underlying data yet, but we’ll be making them available to the public sometime in first-quarter 2014. So please stay tuned.

Starting in the first quarter of 2014, the Federal Reserve Bank of New York (FRBNY) will begin reporting findings from a new national survey designed to elicit consumers’ expectations for a wide range of household-level and aggregate economic and financial conditions. This week, we provide an introduction to the new survey in a series of four blog posts. In this first post, we discuss the overall objectives of the new survey, its sample design, and content. In the posts that follow, we will provide further details and present preliminary findings from the survey on three broad categories of expectations: those relating to inflation, the labor market, and household finance.

The primary goal of the FRBNY Survey of Consumer Expectations (SCE) is to collect timely, rich, and high-quality information on consumer expectations and behavior. The data collected will complement the information gathered from other surveys, such as the Reuters/University of Michigan Survey of Consumers, The Conference Board’s Consumer Confidence Survey, and the Board of Governors’ Survey of Consumer Finances.

The SCE not only elicits information about consumers’ expectations and decisions on a range of economic and financial topics broader than that covered in existing surveys, but also aims to do so in a way that captures respondents’ beliefs more fully. The goal is to measure an individual’s beliefs about the likelihood of future outcomes, thereby capturing how certain or uncertain the person is about future events. In some cases, we do this by eliciting a “density forecast,” where respondents are asked to assign a percent chance to different values (or intervals) for the outcome of interest. Density forecasts allow us to compute a measure of individual forecast uncertainty and yield richer information about how expectations vary across people and over time than do single-value forecasts, or “point predictions.”

The creation of the SCE is the outcome of a five-year collaborative research project with economists, psychologists, and survey design experts. During this period, we conducted a large number of experimental surveys to assess the information content of responses elicited with existing survey questions and to develop new questions, including those for measuring forecast uncertainty.

We believe that more comprehensive data  on consumer expectations regarding inflation, wage growth, house prices, job search, access to credit, and similar topics will enhance our understanding of how expectations are formed and updated, and ultimately of how expectations affect actual behavior. These data will also provide insights into the heterogeneity of views across different groups of consumers. In addition, SCE data will help improve the modeling of expectations formation and updating beyond traditional rational expectations models. More broadly, richer data on consumer expectations and behavior will provide valuable input into policy formulation and the evaluation of the economic outlook.

So how is the SCE actually conducted? The SCE is a nationally representative, internet-based survey of a rotating panel of approximately 1,200 household heads. Respondents participate in the panel for up to twelve months, with a roughly equal number rotating in and out of the panel each month. Unlike comparable surveys based on repeated cross-sections with a different set of respondents in each wave, our panel allows us to observe the changes in expectations and behavior of the same individuals over time. This creates important efficiency gains because it reduces the month-to-month variation in responses that stems from random changes in sample composition, making the responses more reflective of actual changes in beliefs.

The survey is conducted on our behalf by The Demand Institute, a non-profit organization jointly operated by The Conference Board and Nielsen. The sampling frame for the SCE is based on that used for The Conference Board’s Consumer Confidence Survey (CCS). Respondents to the CCS, itself based on a representative national sample drawn from mailing addresses, are invited to join the SCE internet panel. Each survey typically takes about fifteen to twenty minutes to complete. Preliminary evidence from the build-up of the SCE panel during the past few months indicates an initial SCE participation rate of approximately 60 percent, with a steady-state average response rate among repeat respondents of about 75 percent.

The survey consists of two separate components: a monthly core module on expectations about macroeconomic and household-level outcomes and quarterly modules on special topics covering different aspects of household economic behavior. The questionnaires, developed by New York Fed staff (and by staff from other Reserve Banks for some of the quarterly surveys) in collaboration with academic consultants as well as survey design experts at Nielsen, are evaluated through cognitive interviews and tested through pilot surveys prior to fielding.

The monthly core module includes a set of questions on inflation and house price change expectations (at both the one- and the three-year horizon), as well as year-ahead expectations about specific commodity price changes, including the price of food, gas, and medical care, and the cost of a college education and of renting a home. These, like many of our other questions, use a probabilistic format that asks respondents to assign a percent chance to ranges of outcomes. As a result, we will be able to measure forecast uncertainty about overall inflation and house price appreciation.

The core module also collects information about employment status and beliefs among those currently employed about future wage growth, including uncertainty about future wage changes. In addition, it elicits year-ahead expectations of the likelihood of voluntary job exits (quits) and involuntary job exits (layoffs), and the likelihood of finding and accepting a job within three months if the individual were to lose it today. Respondents are also asked about the likelihood of their moving during the next year. Together, these expectations represent a rich set of indicators of real-time current and prospective labor market conditions.

Finally, the core questionnaire includes a set of expectations about household finances. Questions cover year-ahead expectations of household income, spending, taxes, the interest rate on savings accounts, and the likelihood of not being able to make a debt payment over the next three months, as well as expectations and perceptions of changes in access to credit.

For first-time respondents, the core module also contains a set of questions about the respondent and his or her household—including demographic characteristics, homeownership status, current household income, and employment and residential history—and a short numeracy test. For repeat respondents, the core questionnaire instead includes a segment of special questions that vary monthly, focusing on topical issues such as student loan borrowing and repayment behavior, health care insurance cost and coverage, employer-provided benefits, demand and supply of credit, and self-employment.

Finally, among the likely special topics of our quarterly modules will be questions pertaining to conditions in the housing market, the labor market, household balance sheets, and consumption and saving behavior.

In the remaining blog posts this week, we will discuss in greater detail some of the survey questions and the statistics we plan to start reporting at a monthly frequency in 2014, as well as some initial findings from our survey. It is our intention to subsequently release the micro data for research purposes.

The views expressed in this post are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the authors.

Olivier Armantier is an assistant vice president in the Federal Reserve Bank of New York’s Research and Statistics Group.

Giorgio Topa
is a vice president in the Research and Statistics Group.

Wilbert van der Klaauw is a senior vice president in the Research and Statistics Group.

Basit Zafar is a senior economist in the Research and Statistics Group.

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