Jinill Kim

1.9k citations
50 papers · 1.0k indexed · h-index 16

Impact in

Papers in

Jinill Kim

50 papers receiving 950 citations

Peers

Jinill Kim
Comparison fields: 5 of 47
  • General Economics, Econometrics and Finance 781
  • Finance 373
  • Economics and Econometrics 796
  • Accounting 95
  • Computational Mathematics 1
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Bruce Preston United States
Todd B. Walker United States
Troy Davig United States
Malin Adolfson Sweden
Francisco J. Ruge‐Murcia Canada
Filippo Altissimo Italy
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Julien Matheron France
Rochelle M. Edge United States
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Citations per field
00.5×1.5×
Bruce Preston · 1×
Citations per year

Countries citing papers authored by Jinill Kim

Since Specialization
Citations

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

Fields of papers citing papers by Jinill Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Jinill Kim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jinill Kim Line = papers co-authored together Jinill Kim links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20187
2
Designing a Simple Loss Function for Central Banks: Does a Dual Mandate Make Sense?
20171
3 20161
4
Designing a Simple Loss Function for the Fed: Does the Dual Mandate Make Sense?
20159
5 20103
6 20071
7 20072
8 20075
9
RELATIVE PRICE DISTORTION AND OPTIMAL MONETARY POLICY IN OPEN ECONOMIES
20061
10 200526
11 200511
12 200329
13 200341
14
Welfare of Incomplete Markets Economy with Permanent as well as Transitory Shocks
20021
15 20024
16 20015
17 20012
18
Constructing and Estimating a Realistic Optimizing Model of Monetary Policy
199915
19 19991
20 19981

About Jinill Kim

Jinill Kim is a scholar working on General Economics, Econometrics and Finance, Economics and Econometrics, Finance, Accounting and Renewable Energy, Sustainability and the Environment, having authored 50 papers that have together received 1.0k indexed citations. Recurring topics across this work include Monetary Policy and Economic Impact (34 papers), Economic theories and models (32 papers), Economic Theory and Policy (18 papers), Fiscal Policy and Economic Growth (11 papers), Economic Growth and Productivity (9 papers), Banking stability, regulation, efficiency (6 papers), Market Dynamics and Volatility (4 papers) and Financial Literacy, Pension, Retirement Analysis (4 papers). The work is most often cited by research in General Economics, Econometrics and Finance (781 citations), Finance (373 citations), Economics and Econometrics (796 citations), Accounting (95 citations) and Computational Mathematics (1 citation). Jinill Kim has collaborated with scholars based in United States, South Korea and Spain. Frequent co-authors include Sunghyun Kim, Ernst Schaumburg, Christopher A. Sims, Dale W. Henderson, Skander Van den Heuvel, Shane M. Sherlund, Jane Dokko, Michael T. Kiley, Jae Sim and Francisco J. Ruge‐Murcia. Their work appears in journals such as Journal of Economic Dynamics and Control, Computational Economics, International Economic Review, Journal of Monetary Economics and Journal of International Economics.

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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