Éva Nagypál

1.2k total citations · 1 hit paper
18 papers, 683 citations indexed

About

Éva Nagypál is a scholar working on Economics and Econometrics, Accounting and General Economics, Econometrics and Finance. According to data from OpenAlex, Éva Nagypál has authored 18 papers receiving a total of 683 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Economics and Econometrics, 6 papers in Accounting and 3 papers in General Economics, Econometrics and Finance. Recurrent topics in Éva Nagypál's work include Labor market dynamics and wage inequality (11 papers), Firm Innovation and Growth (6 papers) and Economic theories and models (5 papers). Éva Nagypál is often cited by papers focused on Labor market dynamics and wage inequality (11 papers), Firm Innovation and Growth (6 papers) and Economic theories and models (5 papers). Éva Nagypál collaborates with scholars based in United States and Germany. Éva Nagypál's co-authors include Dale T. Mortensen, Zvi Eckstein, Steven J. Davis, John Haltiwanger, Javier Miranda, Christopher L. Foote, Ron S. Jarmin, Scott Fulford, Dan Ton and Jianhui Wang and has published in prestigious journals such as The Review of Economic Studies, Scandinavian Journal of Economics and Review of Economic Dynamics.

In The Last Decade

Éva Nagypál

18 papers receiving 628 citations

Hit Papers

More on unemployment and vacancy fluctuations 2007 2026 2013 2019 2007 50 100 150 200 250

Peers

Éva Nagypál
Rasmus Lentz United States
Éva Nagypál
Citations per year, relative to Éva Nagypál Éva Nagypál (= 1×) peers Rasmus Lentz

Countries citing papers authored by Éva Nagypál

Since Specialization
Citations

This map shows the geographic impact of Éva Nagypál'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 Éva Nagypál with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Éva Nagypál more than expected).

Fields of papers citing papers by Éva Nagypál

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Éva Nagypál. 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 Éva Nagypál. The network helps show where Éva Nagypál may publish in the future.

Co-authorship network of co-authors of Éva Nagypál

This figure shows the co-authorship network connecting the top 25 collaborators of Éva Nagypál. A scholar is included among the top collaborators of Éva Nagypál 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 Éva Nagypál. Éva Nagypál is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Fulford, Scott & Éva Nagypál. (2023). The Equilibrium Effect of Information in Consumer Credit Markets: Public Records and Credit. SSRN Electronic Journal. 2 indexed citations
2.
Nagypál, Éva & Scott Fulford. (2023). The Equilibrium Effect of Information in Consumer Credit Markets: Public Records and Credit. SSRN Electronic Journal. 1 indexed citations
3.
Fulford, Scott & Éva Nagypál. (2023). Using the Courts for Private Debt Collection: How Wage Garnishment Laws Affect Civil Judgments and Access to Credit. SSRN Electronic Journal. 4 indexed citations
4.
Nagypál, Éva & Jeremy Tobacman. (2019). Credit Characteristics, Credit Engagement Tools, and Financial Well-Being. SSRN Electronic Journal. 2 indexed citations
6.
Nagypál, Éva, et al.. (2008). Quits, Worker Recruitment, and Firm Growth: Theory and Evidence. SSRN Electronic Journal. 9 indexed citations
7.
Nagypál, Éva. (2007). Learning by Doing vs. Learning About Match Quality: Can We Tell Them Apart?. The Review of Economic Studies. 74(2). 537–566. 77 indexed citations
8.
Mortensen, Dale T. & Éva Nagypál. (2007). Labor‐market Volatility in Matching Models with Endogenous Separations*. Scandinavian Journal of Economics. 109(4). 645–665. 37 indexed citations
9.
Mortensen, Dale T. & Éva Nagypál. (2007). More on unemployment and vacancy fluctuations. Review of Economic Dynamics. 10(3). 327–347. 261 indexed citations breakdown →
10.
Nagypál, Éva. (2007). Labor-Market Fluctuations and On-the-Job Search. SSRN Electronic Journal. 29 indexed citations
11.
Davis, Steven J., John Haltiwanger, Ron S. Jarmin, et al.. (2006). Volatility and Dispersion in Business Growth Rates: Publicly Traded versus Privately Held Firms [with Comments and Discussion]. NBER Macroeconomics Annual. 21. 107–179. 98 indexed citations
12.
Nagypál, Éva. (2005). Amplification of Labor Market Fluctuations: Why Vacancies Don't Like to Hire the Unemployed?. RePEc: Research Papers in Economics. 1 indexed citations
13.
Mortensen, Dale T. & Éva Nagypál. (2005). More on Unemployment and Vacancy Fluctuations. SSRN Electronic Journal. 34 indexed citations
14.
Nagypál, Éva. (2005). On the extent of job-to-job transitions. RePEc: Research Papers in Economics. 41 indexed citations
15.
Nagypál, Éva. (2004). Amplification of Productivity Shocks: Why Vacancies Don't Like to Hire the Unemployed? 1. 7 indexed citations
16.
Eckstein, Zvi & Éva Nagypál. (2004). The Evolution of U.S. Earnings Inequality: 1961–2002. Quarterly Review. 28(2). 52 indexed citations
17.
Nagypál, Éva. (2004). [The Business Cycle and the Life Cycle]: Comment. NBER Macroeconomics Annual. 19. 462–477. 1 indexed citations
18.
Nagypál, Éva. (2004). Optimal application behavior with incomplete information. 19 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.

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