Michigan Survey Of Consumers Research Articles

Learning About Consumer Uncertainty from Qualitative Surveys: As Uncertain as Ever

We study diffusion indices constructed from qualitative surveys to provide real-time assessments of various aspects of economic activity. In particular, we highlight the role of diffusion indices as estimates of change in a quasi extensive margin, and characterize their distribution, focusing on the uncertainty implied by both sampling and the polarization of participants' responses. Because qualitative tendency surveys generally cover multiple questions around a topic, a key aspect of this uncertainty concerns the coincidence of responses, or the degree to which polarization comoves, across individual questions. We illustrate these results using micro data on individual responses underlying different composite indices published by the Michigan Survey of Consumers. We find a secular rise in consumer uncertainty starting around 2000, following a decade-long decline, and higher agreement among respondents in prior periods. Six years after the Great Recession, uncertainty arising from the polarization of responses in the Michigan Survey stands today at its highest level since 1978, coinciding with the weakest recovery in U.S. post-war history. The formulas we derive allow for simple computations of approximate confidence intervals, thus affording a more complete real-time assessment of economic conditions using qualitative surveys.

Predicting gasoline prices using Michigan survey data

This study investigates the predictive power of Michigan Surveys of Consumers (MSC) data for gasoline prices. Specifically, we utilize the MSC data on both expected inflation and consumer sentiment to construct a vector autoregressive (VAR) model for forecasting gasoline prices for 2003–2014. Our findings indicate that the VAR forecasts are superior to the comparable benchmark forecasts obtained from a univariate integrated moving average (MA) model in terms of both predictive information content and directional accuracy. As such, we conclude that the MSC data on both expected inflation and consumer sentiment have significant predictive information for gasoline prices. Further inspection reveals that the VAR forecasts are particularly accurate for the period since 2008, reinforcing the notion that consumers are “economically” rational.

Learning About Consumer Uncertainty from Qualitative Surveys: As Uncertain as Ever

We study diffusion indices constructed from qualitative surveys to provide real-time assessments of various aspects of economic activity. In particular, we highlight the role of diffusion indices as estimates of change in a quasi extensive margin, and characterize their distribution, focusing on the uncertainty implied by both sampling and the polarization of participants' responses. Because qualitative tendency surveys generally cover multiple questions around a topic, a key aspect of this uncertainty concerns the coincidence of responses, or the degree to which polarization comoves, across individual questions. We illustrate these results using micro data on individual responses underlying different composite indices published by the Michigan Survey of Consumers. We find a secular rise in consumer uncertainty starting around 2000, following a decade-long decline, and higher agreement among respondents in prior periods. Six years after the Great Recession, uncertainty arising from the polarization of responses in the Michigan Survey stands today at its highest level since 1978, coinciding with the weakest recovery in U.S. post-war history. The formulas we derive allow for simple computations of approximate confidence intervals, thus affording a more complete real-time assessment of economic conditions using qualitative surveys.

Do Inflation Expectations Propagate the Inflationary Impact of Real Oil Price Shocks?: Evidence from the Michigan Survey

This paper presents evidence that inflation expectations, as measured by the Michigan Survey of consumers, only play a minimal role in the propagation of real oil price shocks into inflation. This is despite evidence which confirms inflation expectations are sensitive to real oil price shocks. Further analysis exploring structural breaks suggest at some point after the mid-1990s, inflation expectations may have played no part in propagating real oil price shocks into inflation.

Inflation expectations and energy price forecasting

AbstractIn this study, we ask whether US consumers' inflation expectations provide useful information for accurately predicting the direction of change in energy prices. As such, we set up a forecasting model to generate the one‐, two‐ and three‐quarter‐ahead random walk forecasts of crude oil, gasoline and heating oil prices. For the period 1987–2012, our test results reveal that the forecasts are free of systematic bias and thus imply symmetric loss. Also, they are generally efficient, where efficiency means the forecast error is uncorrelated with its own past values. The random walk forecast errors are, however, correlated with the change in inflation expectations (measured by the data from the Michigan Surveys of Consumers). Thus, we conclude such expectations may contain useful predictive information for crude oil, gasoline and heating oil prices. Consistent with this conclusion, we show that the change in inflation expectations accurately predicts the direction of change in such energy prices for 1987–2012.

What do consumers believe about future gasoline prices?

A full understanding of how gasoline prices affect consumer behavior frequently requires information on how consumers forecast future gasoline prices. We provide the first evidence on the nature of these forecasts by analyzing two decades of data on gasoline price expectations from the Michigan Survey of Consumers. We find that average consumer beliefs are typically indistinguishable from a no-change forecast, justifying an assumption commonly made in the literature on consumer valuation of energy efficiency. We also provide evidence on circumstances in which consumer forecasts are likely to deviate from no-change and on significant cross-consumer forecast heterogeneity.

Inflation Expectations and Readiness to Spend: Cross-Sectional Evidence

There have been suggestions for monetary policy to engineer higher inflation expectations to stimulate spending. We examine the relationship between expected inflation and spending attitudes using the microdata from the Michigan Survey of Consumers. The impact of higher inflation expectations on the reported readiness to spend on durables is generally small, outside the zero lower bound, often statistically insignificant, and inside of it typically significantly negative. In our baseline specification, a one percentage point increase in expected inflation during the recent zero lower bound period reduces households' probability of having a positive attitude towards spending by about 0.5 percentage points. (JEL D12, D84, E21, E31, E52)

The Case for Higher Frequency Inflation Expectations

I present evidence that higher frequency measures of inflation expectations outperform lower frequency measures of inflation expectations in tests of accuracy, predictive power, and rationality. For decades, the academic literature has focused on three survey measures of expected inflation: the Livingston Survey, the Survey of Professional Forecasters, and the Michigan Surveys of Consumers. While these measures have been useful in developing models of forecasting inflation, the data are low frequency measures that are anachronistic in the modern era of high frequency and real-time data. I present a collection of 37 different measures of inflation expectations, including many previously unexploited monthly and real-time measures of inflation expectations. These higher frequency measures tend to outperform the standard three low frequency survey measures in tests of accuracy, predictive power, and rationality, indicating that there are benefits to using higher frequency measures of inflation expectations. Out of sample forecasts confirm the findings.

Forecasting Gasoline Prices Using Consumer Surveys

This paper analyzes the predictive power of a new data set of consumer gasoline price forecasts taken from the Michigan Survey of Consumers (MSC). MSC data generally perform as well as a no-change forecast in predicting future gasoline prices, and they substantially out-perform the no-change forecast during the recent economic crisis, during which time they track futures market prices. Finally, the cross-respondent dispersion of the MSC forecasts increases substantially during the economic crisis, paralleling the large increase in price volatility at this time.

Measuring and interpreting expectations of equity returns

AbstractWe analyze probabilistic expectations of equity returns elicited in the Survey of Economic Expectations in 1999–2001 and in the Michigan Survey of Consumers in 2002–2004. Our empirical findings suggest that individuals use interpersonally variable but intrapersonally stable processes to form their expectations. We therefore propose to think of the population as a mixture of expectations types, each forming expectations in a stable but different way. We use our expectations data to learn about the prevalence of several specific types suggested by research in finance. Copyright © 2010 John Wiley & Sons, Ltd.

The Effect of Question Wording on Reported Expectations and Perceptions of Inflation

Public expectations and perceptions of inflation may affect economic decisions, and have subsequent effects on actual inflation. The Michigan Survey of Consumers uses questions about “prices in general” to measure expected and perceived inflation. Median responses track official measure of inflation, showing some tendency toward overestimation and considerable disagreement between respondents. Possibly, responses reflect how much respondents thought of salient personal experiences with specific prices when being asked about “prices in general.” Here, we randomly assigned respondents to questions about “prices in general,” as well as “the rate of inflation” and “price you pay.” Reported expectations and perceptions were higher and more dispersed for “prices in general” than for “the rate of inflation,” with “prices you pay” and “prices in general” showing similar responses patterns. Compared to questions about “the rate of inflation,” questions about “prices in general” and “prices you pay” focused respondents relatively more on personal price experiences - and elicited expectations that were more strongly correlate to the expected price increases for food and transportation, which were relatively large and likely salient, but not to the expected price increases for housing, which were relatively small and likely less salient. Our results have implications for survey measures of inflation expectations.

Inflation, earnings forecasts, and post-earnings announcement drift

We examine whether financial analysts fully incorporate expected inflation in their earnings forecasts for individual stocks. We find that expected inflation proxies, such as lagged inflation and inflation forecasts from the Michigan Survey of Consumers, predict the future earnings change of a portfolio long in high inflation exposure firms and short in low or negative inflation exposure firms, but analysts do not fully adjust for this relation. Analysts’ earnings forecast errors can be predicted using expected inflation proxies, and these systematic forecast errors are related to future stock returns. Overall, our evidence is consistent with the Chordia and Shivakumar (J Account Res 43(4):521–556, 2005) hypothesis that the post-earnings announcement drift is related to investor underestimation of the impact of expected inflation on future earnings change.

Momentum Traders in the Housing Market: Survey Evidence and a Search Model

This paper studies household beliefs dur ing the recent US housing boom. The first part presents evidence from the Michigan Survey of Consumers. To characterize the heterogeneity in households’ views about housing and the econ omy, we perform a cluster analysis on survey responses at different stages of the boom. The estimation always finds a small cluster of house holds that believe it is a good time to buy a house because house prices will rise further. The size of this “momentum” cluster strongly increased toward the end of the boom. The second part of the paper provides a simple search model of the housing market to show how a small number of optimistic investors can have a large effect on prices without buying a large share of the housing stock. The raw survey data suggest that the housing boom had two distinct phases. During the early boom years 2002–2003, a large and increasing fraction of households believed that the time for buying a house was good. This fraction peaked at 85.2 percent in 2003:II. The most important reason—cited by up to 72 percent of house

Framing Effects in Stock Market Forecasts: The Difference Between Asking for Prices and Asking for Returns

Studies analyzing return expectations of financial market participants like fund managers, CFOs or individual investors are highly influential in academia and practice. Examples of such surveys in the U.S. are the Livingston Survey of the Federal Reserve Bank of Philadelphia, the Surveys of Consumers of the University of Michigan, the UBS/Gallup survey, and the Duke/CFO Business Outlook survey. An example from Germany is the ZEW Bankprognosen survey. We argue and show that the results in the surveys above are easily influenced by the elicitation mode of return expectations. Surveys that ask for future stock price levels (like the Livingston Survey) are more likely to produce mean reverting expectations than surveys that directly ask for future returns (like the Michigan Surveys of Consumers or the Duke/CFO Business Outlook survey). Furthermore, we conduct a questionnaire study that explicitly analyzes whether the specific elicitation mode affects return expectations in the above direction. In our study, subjects (students in business administration at two large German universities) were asked to state mean forecasts for seven time series. Using a between subject design, one half of the subjects was asked to state future price levels, the other group was directly asked for returns. We observe a highly significant framing effect. For upward sloping time series, the return forecasts stated by investors in the return forecast mode are significantly higher than those derived for investors in the price forecast mode. For downward sloping time series, the return forecasts given by investors in the return forecast mode are significantly lower than those derived for investors in the price forecast mode. We argue that this finding is consistent with behavioral theories of investor expectation formation that are based on the representativeness heuristic.

Can Consumer Attitudes Forecast Household Spending in the United States? Further Evidence from the Michigan Survey of Consumers

1. IntroductionFor many years, indices of consumer sentiment have been used to provide government policy makers, economic forecasters, and business managers with timely and important information on consumer attitudes. This interest in consumer attitudes reflects a widespread belief that the sentiments and expectations of individual consumers directly affect the direction of the U.S. economy. Reinforcing this belief is the fact that consumer spending accounts for about two thirds of the nation's Gross Domestic Product (GDP).Thus far, most analyses of consumer attitudes as a leading indicator of household spending have focused primarily on the predictive power of the Michigan Index of Consumer Sentiment (ICS). The results of these studies have, however, been mixed. For example, an early study by Lovell (1975) finds that measures of consumer attitudes based on the Michigan Survey of Consumers are unreliable predictors of future consumption.1 Mishkin (1978), using a stock adjustment model, shows that the ICS provides good explanatory power for changes in consumer durables. Carroll, Fuhrer, and Wilcox (1994, henceforth CFW) find that the Michigan Index has some incremental predictive power as regards forecasting household spending. Souleles (2001), using the microdata of the Michigan Survey, reports that consumer sentiment is useful in forecasting future consumption, even when controlling for a number of macroeconomic variables. On the other hand, Howrey (2001) finds that both lagged and current-quarter monthly values of the ICS are generally insignificant when control variables are present in the equations of total personal consumption expenditures (PCE), consumer spending on durable goods as well as on services.Lovell (2001) recently suggests that the Index of Consumer Expectations (ICE) developed by the University of Michigan may be a better proxy for consumer confidence than the ICS. This is because the ICE is derived solely from a subset of forward-looking questions, in contrast to the ICS, which is based on both forward-looking questions and current-conditions questions.2 In view of Lovell's (2001) insightful suggestion, the main objective of this article is to empirically examine the predictive power of the ICE in forecasting U.S. consumption growth. Moreover, it would be useful to compare the informational content of the ICE and the ICS to determine whether indices of consumer confidence reflect consumers' perception of future economic conditions.In this article, we use the reduced-form equation given in CFW (1994) to examine the forecasting ability of the ICE and the ICS. Our empirical results indicate that the lagged values of the ICE predict changes in total PCE much better than those of the ICS. Furthermore, when tested separately in the reduced-form equation, the forward-looking questions are generally significant, suggesting that they contain valuable information about consumers' expectations of future economic outlook. We also extend our analysis to the study by CFW (1994). The results of this analysis confirm the view that the ICE has greater incremental predictive power than the ICS.The remainder of this article is structured as follows: Section 2 describes the five core questions used in the Michigan Surveys of Consumers. Section 3 discusses the econometric methodology and data. Section 4 reports our main empirical results. Section 5 is a case study based on CFW's (1994) data set. Section 6 presents some conclusions.2. The Michigan Surveys of ConsumersThe ICS, produced by the Michigan Surveys of Consumers, is derived from the following five core questions:3QFPr (Financial Position realization). We are interested in how people are getting along financially these days. Would you say that you (and your family living there) are better off or worse off financially than you were a year ago?QDurs (Durables purchases). …

Can Consumer Attitudes Forecast Household Spending in the United States? Further Evidence from the Michigan Survey of Consumers

This article examines the usefulness of various measures of consumer confidence in forecasting household spending in the United States. Using the reduced‐form equation of Carroll, Fuhrer, and Wilcox (American Economic Review 84:1397‐1408, 1994), we find that for the post‐World War II period, the Index of Consumer Expectations is incrementally more informative about household spending than the Index of Consumer Sentiment for all categories of consumption examined. A similar conclusion emerges when Carroll, Fuhrer, and Wilcox's data set is used. Our overall results confirm the view that indices of consumer confidence reflect consumers' perception of future economic conditions. Also, the ability of these confidence indices to predict future consumption growth can be construed as a clear rejection of the random walk hypothesis of Hall (Journal of Political Economy 86:971‐87, 1978).

How Should We Measure Consumer Confidence?

Research on consumer confidence has mainly sought to evaluate the power of available data to predict economic outcomes. In contrast, this article considers how best to measure consumer confidence. We analyze the responses to eight questions that have appeared recently on the Michigan Survey of Consumers; four elicit expectations in the traditional qualitative manner and four use a newer “percent chance” format. Examination of the responses suggests three implications. It makes more sense to ask for expectations of events directly relevant to individual economic decisions than for predictions of general business conditions. Surveys should shift away from qualitative questions in favor of ones eliciting subjective probability judgments. While aggregating responses into an index of consumer confidence may provide simple summary statistics, results should also be presented on a question-byquestion basis for different subgroups of the population.