Measuring Inflation Expectations: A Survey Data Approach

Berk, Jan Marc

doi:10.1007/978-1-4757-3405-8_5

Cited by 57 publications

(92 citation statements)

References 54 publications

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“…The LS estimator is also based on on the regression y t = δz t + u t but uses z t as instrument. The asymmetric LS estimator (ALS) of Berk (1999) is based on the LS regression (6), and the PRA denotes the regression approach of Pesaran (1985). Notes: This table shows regressions results of (nonparametrically) estimated threshold parameters ( δ + t , δ − t ) on various determinants.…”

Section: Discussionmentioning

confidence: 99%

“…Orr, 1988, Dasgupta andLahiri, 1992), deviations from the normal distribution and asymmetries (e.g. Berk, 1999, Maag, 2010, and conclude that quantified qualitative survey expectations do not necessarily forecast the target variable better than simple time-series models (e.g. Claveria et al, 2007, Nolte and Pohlmeier, 2007, Breitung 2008, or directly suggested improvements and extensions of the CP approach to alleviate other problems of the method (e.g.…”

Section: Related Literaturementioning

confidence: 99%

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Quantifying survey expectations: What’s wrong with the probability approach?

Breitung

Schmeling

2013

International Journal of Forecasting

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Provided in Cooperation with Quantifying survey expectations:What's wrong with the probability approach? AbstractWe study a matched sample of individual stock market forecasts consisting of both qualitative and quantitative forecasts. This allows us to test for the quality of forecast quantification methods by comparing quantified qualitative forecasts with actual quantitative forecasts. Focusing mainly on the widely used quantification framework advocated by Carlson and Parkin (1975), the so-called "probability approach", we find that quantified expectations derived from the probability approach display a surprisingly weak correlation with reported quantitative stock return forecasts. We trace the reason for this low correlation to the importance of asymmetric and time-varying thresholds, whereas individual heterogeneity across forecasters seems to play a minor role. Hence, our results suggest that qualitative survey data may not be a very useful device to obtain quantitative forecasts and we suggest ways to remedy this problem when designing qualitative surveys.JEL-Classification: C53, D84, G17

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Section: Discussionmentioning

confidence: 99%

Section: Related Literaturementioning

confidence: 99%

Quantifying survey expectations: What’s wrong with the probability approach?

Breitung

Schmeling

2013

International Journal of Forecasting

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“…Svensson (1997) and Berk (1999) examined the measurement of expected inflation, while Pesaran, Pierse and Lee (1993), Rahiala and Teräsvirta (1993), Smith and McAleer (1995), Kauppi, Lassila and Teräsvirta (1996), Öller (1990) and Hanssens and Vanden Abeele (1987) focused on production growth, and Batchelor (1982) considered employment. Authors such as Batchelor (1982), Smith and McAleer (1995) and Alfarano and Milakovic (2010) have explored the use of data from opinion polls as indicators of business behaviour to test different models for the formation of expectations or interactions among agents.…”

Section: Indicators Of Expectationsmentioning

confidence: 99%

“…Those who have engaged with the subject, chiefly for the purpose of identifying and predicting changes in cyclical fluctuations, include Svensson (1997), Berk (1999), Pesaran, Pierse and Lee (1993), Rahiala and Teräsvirta (1993), Smith and McAleer (1995), Kauppi, Lassila and Teräsvirta (1996), Öller (1990), Hanssens and Vanden Abeele (1987) and Alfarano and Milakovic (2010).…”

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confidence: 99%

Expectations and industrial output in Uruguay: Sectoral inter dependence and common trends

M.¹

2014

CEPAL Review

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This paper examines the interdependence between expectations and growth by analysing Uruguayan manufacturing industry, divided for the purpose into four industry groupings differentiated by trade participation and production specialization. The study shows that there is a long-run relationship between industrialists' expectations and output growth in each grouping. In the most trade-oriented groupings the relationship is one of predetermination, showing how useful expectations are as a guide to sectoral growth. Expectations in the four industrial groupings are shown to follow a common long-run trend, identified with the one guiding the export grouping. Impulse-response simulations derived from a multisectoral vector autoregression (var) model confirm the important role of the industries most exposed to international competition in spreading shorter-term shocks.

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“…The quantification depends on the chosen form of the aggregate distribution function. For the calculation we use a standard normal distribution following a number of examples in the literature on transforming qualitative survey data (see Mitchell 2002or Berk 1999. From the survey results we obtain the expected change of inflation for the following six months,…”

Section: Inflation Expectations Of Expertsmentioning

confidence: 99%

Inflation expectations of experts and ECB communication

Ullrich

2008

The North American Journal of Economics and Finance

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Die Dis cus si on Pape rs die nen einer mög lichst schnel len Ver brei tung von neue ren For schungs arbei ten des ZEW. Die Bei trä ge lie gen in allei ni ger Ver ant wor tung der Auto ren und stel len nicht not wen di ger wei se die Mei nung des ZEW dar.Dis cus si on Papers are inten ded to make results of ZEW research prompt ly avai la ble to other eco no mists in order to encou ra ge dis cus si on and sug gesti ons for revi si ons. The aut hors are sole ly respon si ble for the con tents which do not neces sa ri ly repre sent the opi ni on of the ZEW.Download this ZEW Discussion Paper from our ftp server:ftp://ftp.zew.de/pub/zew-docs/dp/dp07054.pdf Non-technical SummaryThe JEL Classification: E52, E58, D83, D84

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Measuring Inflation Expectations: A Survey Data Approach

Cited by 57 publications

References 54 publications

Quantifying survey expectations: What’s wrong with the probability approach?

Quantifying survey expectations: What’s wrong with the probability approach?

Expectations and industrial output in Uruguay: Sectoral inter dependence and common trends

Inflation expectations of experts and ECB communication

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