Scholar4AI Updated 2026-11-04 18:03 UTC+09:00

Survey of Professional Forecasters

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data category: US macroeconomic data · 0 papers in the last 7 days

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US national accounts, prices, labour statistics and expectation surveys.

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Names searched for: Survey of Professional Forecasters

Key findings#

  • From Nov 2023 to Oct 2026, 66 archived papers mentioned Survey of Professional Forecasters in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Jan 2024 (4).
  • Survey of Professional Forecasters was mentioned in 1 paper in the last 30 days (2026-10-06 to 2026-11-04), ranking #172 of the 255 datasets mentioned.
  • By journal category: Finance (1).
  • Most of them appeared in International Review of Economics & Finance (1).
  • From 2017 to 2026 (so far), Survey of Professional Forecasters was mentioned in 113 papers in the tracked journals, most of them in economics (85), finance (23) and operations research (3).
  • 20 of them were published in 2025, against 8 in 2017.
  • Since 2023, the institutions with the most of these papers were Centre for Economic Policy Research (3), ICMA Centre (3) and Monash University (3).
  • The journals publishing most of them were International Journal of Forecasting (9), Journal of Economic Dynamics and Control (7) and Journal of Monetary Economics (7).
  • The most-cited of them is “The predictive power of Google searches in forecasting US unemployment” (International Journal of Forecasting, 2017), with 241 citations.
  • Papers use Survey of Professional Forecasters most often with Economic Policy Uncertainty index (13), S&P 500 (13) and University of Michigan Surveys of Consumers (12); it has 18 partners in the code and data network, in the group around S&P 500, Economic Policy…, Compustat.

Mentions over 36 months#

Papers mentioning it by publication month, Nov 2023 to Oct 2026 (titles, abstracts and keywords; the full texts of earlier months are still being searched)
TrendNov 23–Oct 24Nov 24–Oct 25Nov 25–Oct 2636 months
25221966

Papers per year#

2017: 8 papers2018: 8 papers2019: 6 papers2020: 9 papers2021: 4 papers2022: 7 papers2023: 9 papers2024: 26 papers2025: 20 papers2026 (so far): 16 papers
20172026 (so far)
Papers per publication year and category
Category2017201820192020202120222023202420252026 (so far)
Economics786834717169
Finance0000131747
Operations Research1000000200
Accounting0001000000
Management0000001000
All categories8869479262016

Where the papers come from#

Institutions with the most papers, since 2023
#InstitutionPapers
1Centre for Economic Policy Research3
2ICMA Centre3
3Monash University3
4Purdue University West Lafayette3
5The University of Sydney3
6Tinbergen Institute3
7University of Amsterdam3
8University of Reading3
9Bank of Spain2
10Banque de France2
Countries with the most papers, since 2023
#CountryPapers
1United Kingdom20
2United States17
3Germany9
4Australia6
5France6
6Italy5
7Canada4
8China4
9Spain4
10Netherlands4
Keywords with the most papers, since 2023
#KeywordPapers
1Survey of Professional Forecasters17
2inflation expectations10
3out-of-sample forecasting9
4forecast accuracy8
5inflation8
6professional forecasters8
7monetary policy6
8European Central Bank5
9forecast revisions5
10inflation forecasting5

Most-cited papers#

Most-cited papers since 2017
#CitationsPer monthTitleJournalPublishedAuthors
12412.1The predictive power of Google searches in forecasting US unemploymentInternational Journal of Forecasting2017-06-15Francesco D’Amuri, Juri Marcucci
2931.0Alternative tests for correct specification of conditional predictive densitiesJournal of Econometrics2018-11-19Barbara Rossi, Tatevik Sekhposyan
3771.2Uncertainty and exchange rate volatility: Evidence from MexicoInternational Review of Economics & Finance2021-05-13Georgia Bush, Gabriela López Noria
4691.2The COVID-19 shock and challenges for inflation modellingInternational Journal of Forecasting2022-01-17Elena Bobeica, Benny Hartwig
5590.5Forecasting Inflation with Online PricesInternational Journal of Forecasting2017-01-01Diego Aparicio, Manuel I. Bertolotto

Archive counts by publication year: a paper counts when its title, abstract or keywords name the dataset, or when OpenAlex's full-text search finds it there (searched for the last 30 days' papers and, by a pass over the past years, for older ones). Names added to the list later are looked for in older papers as the archive is read again.

Used together with#

Papers use Survey of Professional Forecasters most often with Economic Policy Uncertainty index (13), S&P 500 (13) and University of Michigan Surveys of Consumers (12); it has 18 partners in the code and data network, in the group around S&P 500, Economic Policy…, Compustat. The whole network →

What papers use Survey of Professional Forecasters together with (at least 3 papers; lift 1 = chance)
Used withTypePapers using bothLift
Economic Policy Uncertainty indexDataset132.3
S&P 500Dataset132.4
University of Michigan Surveys of ConsumersDataset1226.2
FREDDataset1018.9
VIXDataset83.5
Bureau of Economic AnalysisDataset714.7
WTI crude oilDataset74.6
CRSPDataset66.0
Marketization index (Fan Gang)Dataset53.2
Euro Stoxx / DAXDataset44.0
EurostatDataset41.2
Geopolitical Risk indexDataset47.1
Papers mentioning Survey of Professional Forecasters in the last 30 days, newest first.
DateTitleJournalAuthorsAffiliations
2026-10-14Government-sourced categorical economic policy uncertaintyInternational Review of Economics & FinanceKhanh Cong Gia Hoang, Linh Pham, Thanh Ngo et al.
Cite this page

Scholar4AI. (2026). Survey of Professional Forecasters. Journal and Conference Research Rankings. Retrieved November 4, 2026, from https://scholar4ai.com/datasets/survey-of-professional-forecasters

@misc{scholar4ai-datasets-survey-of-professional-forecasters,
  author = {{Scholar4AI}},
  title = {Survey of Professional Forecasters},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/datasets/survey-of-professional-forecasters}},
  urldate = {2026-11-04},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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