Identifying Ambiguity Shocks in Business Cycle Models Using Survey Data

Bhandari, Anmol; Borovička, Jaroslav; Ho, P.

doi:10.2139/ssrn.2763942

Cited by 15 publications

(22 citation statements)

References 117 publications

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“…But this does not imply that the individual would report the beliefs associated with the worst-case scenario when asked about her expectations in a survey. Bhandari, Borovička, and Ho (2016), for example, assume so, but this is an additional assumption that does not follow from ambiguity aversion theory.…”

Section: Socioeconomic Status and Macroeconomic Beliefsmentioning

confidence: 99%

Socioeconomic Status and Macroeconomic Expectations

Das¹,

Kuhnen

Nagel

2019

The Review of Financial Studies

156

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We show that individuals’ macroeconomic expectations are influenced by their socioeconomic status (SES). People with higher income or higher education are more optimistic about future macroeconomic developments, including business conditions, the national unemployment rate, and stock market returns. The spread in beliefs between high- and low-SES individuals diminishes significantly during recessions. A comparison with professional forecasters and historical data reveals that the beliefs wedge reflects excessive pessimism on the part of low-SES individuals. SES-driven expectations help explain why higher-SES individuals are more inclined to invest in the stock market and more likely to consider purchasing homes, durable goods, or cars. Received November 13, 2017; editorial decision February 12, 2019 by Editor Wei Jiang. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

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Section: Socioeconomic Status and Macroeconomic Beliefsmentioning

confidence: 99%

Socioeconomic Status and Macroeconomic Expectations

Das¹,

Kuhnen

Nagel

2019

The Review of Financial Studies

156

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“…In asset pricing, a distorted probability measure that overweights bad outcomes can be used to represent ambiguity aversion or concerns about model misspecification (Hansen and Sargent (2001)). Bhandari, Borovička, and Ho (2016) use survey expectations of macroeconomic variables to estimate such distorted probabilities. However, the fact that decision-making of ambiguity averse or robustness-seeking individuals can be modeled using a distorted probability measure does not imply that survey responses would necessarily reflect such distorted probabilities.…”

Section: Introductionmentioning

confidence: 99%

Do survey expectations of stock returns reflect risk adjustments?

Adam

Matveev

Nagel

2021

Journal of Monetary Economics

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We would like to thank Jarda Borovicka, James Choi, Charles Manski and seminar participants at the CESifo Venice Summer Institute Workshop on "Expectation Formation" for helpful comments and suggestions. The views expressed in this paper do not necessarily represent those of the Bank of Canada. Nagel thanks the Fama-Miller Center at the University of Chicago for research support. Klaus Adam thanks the Collaborative Research Center Transregio 224 sponsored by the German Research Foundation (DFG) for research support. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

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“…Bhandari, Borovička and Ho (2016) is an example of a rational model that explicitly accounts for survey evidence.41 The first block is familiar from a long literature in finance going back toShiller (1981) that has attempted to explain the excess volatility of asset prices compared to fundamentals via the excess volatility of agents' expectations (of either fundamentals or returns) compared to rational expectations. The second block is more nuanced: for movements in expectations to move asset prices in general equilibrium, these same movements of expectations have to move asset demand in partial equilibrium.…”

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confidence: 99%

Five Facts about Beliefs and Portfolios

Giglio¹,

Maggiori²,

Stroebel³

et al. 2019

123

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We administer a newly-designed survey to a large panel of retail investors who have substantial wealth invested in financial markets. The survey elicits beliefs that are crucial for macroeconomics and finance, and matches respondents with administrative data on their portfolio composition and their trading activity. We establish five facts in this data: (1) Beliefs are reflected in portfolio allocations. The sensitivity of portfolios to beliefs is small on average, but varies significantly with investor wealth, attention, trading frequency, and confidence. (2) It is hard to predict when investors trade, but conditional on trading, belief changes affect both the direction and the magnitude of trades. (3) Beliefs are mostly characterized by large and persistent individual heterogeneity; demographic characteristics explain only a small part of why some individuals are optimistic and some are pessimistic. (4) Investors who expect higher cash flow growth also expect higher returns and lower long-term price-dividend ratios. (5) Expected returns and the subjective probability of rare disasters are negatively related, both within and across investors. These five facts challenge the rational expectation framework for macrofinance, and provide important guidance for the design of behavioral models.

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Identifying Ambiguity Shocks in Business Cycle Models Using Survey Data

Cited by 15 publications

References 117 publications

Socioeconomic Status and Macroeconomic Expectations

Socioeconomic Status and Macroeconomic Expectations

Do survey expectations of stock returns reflect risk adjustments?

Five Facts about Beliefs and Portfolios

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