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.
Place of Work and Place of Residence: Informal Hiring Networks and Labor Market Outcomes
2008450 citationsGiorgio Topa et al.Journal of Political Economyprofile →
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 Giorgio Topa'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 Giorgio Topa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Giorgio Topa more than expected).
This network shows the impact of papers produced by Giorgio Topa. 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 Giorgio Topa. The network helps show where Giorgio Topa may publish in the future.
Co-authorship network of co-authors of Giorgio Topa
This figure shows the co-authorship network connecting the top 25 collaborators of Giorgio Topa.
A scholar is included among the top collaborators of Giorgio Topa 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 Giorgio Topa. Giorgio Topa is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Armantier, Olivier, et al.. (2020). How Widespread Is the Impact of the COVID-19 Outbreak on Consumer Expectations?. Liberty Street Economics.3 indexed citations
7.
Armantier, Olivier, et al.. (2020). Inflation Expectations in Times of COVID-19. Liberty Street Economics.2 indexed citations
8.
Armantier, Olivier, et al.. (2020). Coronavirus Outbreak Sends Consumer Expectations Plummeting. Liberty Street Economics.2 indexed citations
9.
Armantier, Olivier, Giorgio Topa, Wilbert van der Klaauw, & Basit Zafar. (2016). How Do People Revise Their Inflation Expectations. Liberty Street Economics.3 indexed citations
10.
Armantier, Olivier, Giorgio Topa, Wilbert van der Klaauw, & Basit Zafar. (2016). An Overview of the Survey of Consumer Expectations. Econstor (Econstor). 23(2). 51–72.13 indexed citations
Armantier, Olivier, Giorgio Topa, Wilbert van der Klaauw, & Basit Zafar. (2013). Introducing the FRBNY Survey of Consumer Expectations: Labor Market Expectations. Liberty Street Economics.2 indexed citations
13.
Armantier, Olivier, Giorgio Topa, Wilbert van der Klaauw, & Basit Zafar. (2013). Introducing the FRBNY Survey of Consumer Expectations: Survey Goals, Design and Content. Liberty Street Economics.4 indexed citations
14.
Armantier, Olivier, Giorgio Topa, Wilbert van der Klaauw, & Basit Zafar. (2013). Introducing the FRBNY Survey of Consumer Expectations: Measuring Price Inflation Expectations. Liberty Street Economics.9 indexed citations
15.
Armantier, Olivier, Scott Nelson, Giorgio Topa, Wilbert van der Klaauw, & Basit Zafar. (2012). Nudging Inflation Expectations: An Experiment. Liberty Street Economics.1 indexed citations
Orr, James & Giorgio Topa. (2006). Challenges Facing the New York Metropolitan Area Economy. SSRN Electronic Journal. 12.
19.
Bisin, Alberto, Giorgio Topa, & Thierry Verdier. (2004). Religious Intermarriage and Socialization in the United States. SSRN Electronic Journal.16 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.