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Testing hypotheses regarding how individual survey respondents form their expectations is susceptible to the multiple testing problem. The probability of falsely rejecting the null hypothesis for one or more respondents will exceed the nominal single-hypothesis significance level. The Bonferroni correction and related approaches control the family-wise error rate, but are conservative and result in low power when the null hypotheses are false. We compare controlling the family-wise error rate with the effect of controlling the false discovery rate and the false discovery proportion, in terms of the conclusions we draw about forecaster behaviour. The effects of adjustments for multiple testing are investigated for tests of weak efficiency and the over-reaction hypothesis, for beliefs about the persistence of shocks to output growth, and for the accuracy of survey respondents' perceptions of the uncertainty they face. [ABSTRACT FROM AUTHOR]

In order to study the expectation formation of financial institutions in the foreign exchange market we develop and apply a recursive selection and estimation algorithm to a dataset of surveyed foreign exchange market expectations. Responses are classified into two groups and forecasting models are endogenously determined within the groups. Estimation results reveal that a fundamentalist–chartist model is capable of explaining a large portion of foreign exchange market expectations. Fundamentalists are found to have mean-reverting expectations whereas chartists have contrarian expectations. Allowing panelists to switch between models significantly improves the fit of the model, especially at the relatively shorter forecast horizons. We find that the fundamentalist model is increasingly used as the forecast horizon extends. Finally, results indicate that model choice is based on a combination of period-specific and individual-specific determinants. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we propose novel techniques for the empirical analysis of adaptive learning and sticky information in inflation expectations. These methodologies are applied to the distribution of households’ inflation expectations collected by the University of Michigan Survey Research Center. To account for the evolution of the cross-section of inflation forecasts over time and measure the degree of heterogeneity in private agents’ forecasts, we explore time series of percentiles from the empirical distribution. Our results show that heterogeneity is pervasive in the process of inflation expectation formation. We identify three regions of the distribution that correspond to different underlying mechanisms of expectation formation: a static or highly autoregressive region on the left hand side of the median, a nearly rational region around the median and a fraction of forecasts on the right hand side of the median formed in accordance with adaptive learning and sticky information. [ABSTRACT FROM AUTHOR]

• We show that survey-based forecasts of the Chilean exchange rate outperform the Driftless Random Walk (DRW) in terms of Mean Squared Prediction Error at several forecasting horizons. • We also show that these survey-based forecasts are able to outperform a "pure luck" benchmark when using the direction-of-change metric. • Our findings suggest that survey-based forecasts of the Chilean exchange rate should be considered as a tough benchmark to beat for economic models, tougher indeed than the traditional driftless random walk. • Survey-based forecasts of the Chilean exchange rate, designed to be used as short run forecasts specifically, are also accurate at a variety of different forecasting horizons. • Our results are consistent with a recent literature that has shown that both the Chilean peso and survey-based forecasts of the Chilean exchange rate have the ability to predict base metals returns. We examine the accuracy of survey-based expectations of the Chilean exchange rate relative to the US dollar. Our out-of-sample analysis reveals that survey-based forecasts outperform the driftless random walk in terms of mean squared prediction error at several forecasting horizons. A similar result is found when precision is measured in a direction-of-change dimension: survey-based forecasts outperform a "pure luck" benchmark at several forecasting horizons. Our findings suggest that survey-based forecasts of the Chilean exchange rate should be considered as a tough benchmark to beat for economic models, tougher indeed than the traditional driftless random walk. [ABSTRACT FROM AUTHOR]