Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
The Effect of Macroeconomic Uncertainty on Household Spending
202441 citationsOlivier Coibion, Dimitris Georgarakos et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Geoff Kenny's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Geoff Kenny with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Geoff Kenny more than expected).
This network shows the impact of papers produced by Geoff Kenny. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Geoff Kenny. The network helps show where Geoff Kenny may publish in the future.
Co-authorship network of co-authors of Geoff Kenny
This figure shows the co-authorship network connecting the top 25 collaborators of Geoff Kenny.
A scholar is included among the top collaborators of Geoff Kenny based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Geoff Kenny. Geoff Kenny is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Christelis, Dimitris, Dimitris Georgarakos, Tullio Jappelli, & Geoff Kenny. (2021). How has the COVID-19 crisis affected different households’ consumption in the euro area?. ETS Research Bulletin Series. 84(84).6 indexed citations
10.
Kenny, Geoff, et al.. (2021). Can consumers’ inflation expectations help stabilise the economy?. ETS Research Bulletin Series. 79(79).
11.
Dovern, Jonas & Geoff Kenny. (2020). Anchoring Inflation Expectations in Unconventional Times: Micro Evidence for the Euro Area. International journal of central banking. 16(5). 309–347.13 indexed citations
Kenny, Geoff, et al.. (2017). EU consumers’ quantitative inflation perceptions and expectations: an evaluation. RePEc: Research Papers in Economics.1 indexed citations
14.
Kenny, Geoff. (2010). Macroeconomic forecasting: can forecast combination help?. ETS Research Bulletin Series. 11. 9–12.1 indexed citations
15.
Genre, Véronique, et al.. (2007). The ECB Survey of Professional Forecasters (SPF): A Review after Eight Years' Experience. Econstor (Econstor).38 indexed citations
16.
Kenny, Geoff, et al.. (2004). Quality adjustment of European price statistics and the role for hedonics. RePEc: Research Papers in Economics.12 indexed citations
17.
Kenny, Geoff, et al.. (1998). Forecasting irish inflation using ARIMA models. RePEc: Research Papers in Economics.57 indexed citations
18.
Kenny, Geoff & Donal McGettigan. (1997). Inflation in Ireland: theory and evidence. Arrow@dit (Dublin Institute of Technology).6 indexed citations
19.
Kenny, Geoff & Donal McGettigan. (1996). Non-Traded, Traded and Aggregate Inflation in Ireland: Further Evidence*. RePEc: Research Papers in Economics.1 indexed citations
20.
Kenny, Geoff & Donal McGettigan. (1996). Non-Traded, Traded and Aggregate Inflation In Ireland (Part 1). RePEc: Research Papers in Economics.1 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.