Edward Herbst

1.5k total citations · 1 hit paper
39 papers, 859 citations indexed

About

Edward Herbst is a scholar working on General Economics, Econometrics and Finance, Economics and Econometrics and Artificial Intelligence. According to data from OpenAlex, Edward Herbst has authored 39 papers receiving a total of 859 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in General Economics, Econometrics and Finance, 19 papers in Economics and Econometrics and 7 papers in Artificial Intelligence. Recurrent topics in Edward Herbst's work include Monetary Policy and Economic Impact (22 papers), Economic theories and models (7 papers) and Market Dynamics and Volatility (6 papers). Edward Herbst is often cited by papers focused on Monetary Policy and Economic Impact (22 papers), Economic theories and models (7 papers) and Market Dynamics and Volatility (6 papers). Edward Herbst collaborates with scholars based in United States, United Kingdom and Israel. Edward Herbst's co-authors include Frank Schorfheide, Dario Caldara, Christopher Gust, David López‐Salido, Matthew Smith, W. C. Lineberger, P. F. Zittel, William P. Reinhardt, Stephen V. O'Neil and G. Barney Ellison and has published in prestigious journals such as Journal of the American Chemical Society, American Economic Review and Journal of Econometrics.

In The Last Decade

Edward Herbst

35 papers receiving 828 citations

Hit Papers

Monetary Policy, Real Activity, and Credit Spreads: Evide... 2019 2026 2021 2023 2019 50 100 150
What are hit papers?

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.

  1. Monetary Policy, Real Activity, and Credit Spreads: Evidence from Bayesian Proxy SVARs
    2019 183 citations Dario Caldara, Edward Herbst American Economic Journal Macroeconomics profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Edward Herbst United States 13 573 518 245 88 51 39 859
S. G. B. Henry United Kingdom 17 483 0.8× 610 1.2× 268 1.1× 33 0.4× 32 0.6× 57 875
Christopher Sims United States 11 652 1.1× 689 1.3× 290 1.2× 179 2.0× 3 0.1× 23 1.1k
H. K. van Dijk Netherlands 8 141 0.2× 145 0.3× 107 0.4× 56 0.6× 25 0.5× 15 623
Mathias Trabandt Germany 22 1.2k 2.0× 1.5k 2.8× 472 1.9× 94 1.1× 10 0.2× 53 2.0k
Luca De Angelis Italy 14 31 0.1× 361 0.7× 182 0.7× 52 0.6× 19 0.4× 37 641
Melanie Schienle Germany 13 99 0.2× 268 0.5× 239 1.0× 10 0.1× 4 0.1× 33 536
François Coppens Spain 13 410 0.7× 437 0.8× 203 0.8× 169 1.9× 12 0.2× 26 832
Amadou Sy United States 19 255 0.4× 381 0.7× 719 2.9× 71 0.8× 39 0.8× 86 1.2k
Michel Juillard France 13 391 0.7× 376 0.7× 191 0.8× 7 0.1× 4 0.1× 43 599
Robert Lucas United States 10 1.1k 1.9× 1.4k 2.6× 371 1.5× 20 0.2× 25 0.5× 17 1.7k

Countries citing papers authored by Edward Herbst

Since Specialization
Citations

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

Fields of papers citing papers by Edward Herbst

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Edward Herbst

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

All Works

20 of 20 papers shown
1.
Herbst, Edward, et al.. (2025). Monetary Policy, Uncertainty, and Communications. Finance and Economics Discussion Series. 1–1. 1 indexed citations
2.
Gust, Christopher, Edward Herbst, & David López‐Salido. (2024). Inflation Expectations with Finite Horizon Planning. Finance and Economics Discussion Series. 1–49. 2 indexed citations
3.
Herbst, Edward & Benjamin K. Johannsen. (2024). Bias in local projections. Journal of Econometrics. 240(1). 105655–105655. 12 indexed citations
4.
Gust, Christopher, Edward Herbst, & David López‐Salido. (2022). Short-Term Planning, Monetary Policy, and Macroeconomic Persistence. American Economic Journal Macroeconomics. 14(4). 174–209. 12 indexed citations
5.
Herbst, Edward, et al.. (2021). The Factor Structure of Disagreement. SSRN Electronic Journal. 1 indexed citations
6.
Herbst, Edward & Benjamin K. Johannsen. (2020). Bias in Local Projections. Finance and Economics Discussion Series. 2020.0(10). 15 indexed citations
7.
Negro, Marco Del, et al.. (2020). Online estimation of DSGE models. Econometrics Journal. 24(1). C33–C58. 10 indexed citations
8.
Gust, Christopher, Edward Herbst, & J. David López‐Salido. (2018). Forward Guidance with Bayesian Learning and Estimation. Finance and Economics Discussion Series. 2018.0(72). 6 indexed citations
9.
Gust, Christopher, J. David López‐Salido, Matthew E. Smith, & Edward Herbst. (2016). The Empirical Implications of the Interest-Rate Lower Bound. Finance and Economics Discussion Series. 2016.0(83r1). 1–47. 28 indexed citations
10.
Herbst, Edward & Frank Schorfheide. (2016). Bayesian Estimation of DSGE Models. Princeton University Press eBooks. 90 indexed citations
11.
Caldara, Dario & Edward Herbst. (2016). Monetary Policy, Real Activity, and Credit Spreads: Evidence from Bayesian Proxy SVARs. Finance and Economics Discussion Series. 2016.0(49). 1–51. 21 indexed citations
12.
Herbst, Edward & Doron Shabat. (2016). FRET-based cyanine probes for monitoring ligation reactions and their applications to mechanistic studies and catalyst screening. Organic & Biomolecular Chemistry. 14(15). 3715–3728. 6 indexed citations
13.
Herbst, Edward & Frank Schorfheide. (2015). Bayesian Estimation of DSGE Models. Princeton University Press eBooks. 17 indexed citations
14.
Chung, Hess, Edward Herbst, & Michael T. Kiley. (2015). Effective Monetary Policy Strategies in New Keynesian Models: A Reexamination. NBER Macroeconomics Annual. 29(1). 289–344. 5 indexed citations
15.
Herbst, Edward, et al.. (2014). Estimating (Markov-Switching) VAR Models Without Gibbs Sampling: A Sequential Monte Carlo Approach. SSRN Electronic Journal. 2 indexed citations
16.
Herbst, Edward & Frank Schorfheide. (2013). Sequential Monte Carlo Sampling for DSGE Models. Finance and Economics Discussion Series. 2013.0(43). 1–43. 1 indexed citations
17.
Herbst, Edward & Frank Schorfheide. (2012). Sequential Monte Carlo Sampling for DSGE Models. SSRN Electronic Journal. 7 indexed citations
18.
Schorfheide, Frank & Edward Herbst. (2012). Evaluating DSGE Model Forecasts of Comovements. SSRN Electronic Journal. 1 indexed citations
19.
Herbst, Edward. (2011). Essays on Bayesian macroeconometrics. Scholarly Commons (University of Pennsylvania).
20.
Herbst, Edward, et al.. (1997). Voices in Bali. 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.

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