Kazumitsu Nawata

850 citations
56 papers · 628 indexed · h-index 13

Kazumitsu Nawata

52 papers receiving 581 citations

Peers

Kazumitsu Nawata
Comparison fields: 5 of 123
  • Statistics and Probability 80
  • Economics and Econometrics 207
  • Management Science and Operations Research 73
  • General Economics, Econometrics and Finance 43
  • Marketing 41
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Paulo Parente United Kingdom
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Citations per year

Countries citing papers authored by Kazumitsu Nawata

Since Specialization
Citations

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

Fields of papers citing papers by Kazumitsu Nawata

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 12 scholars most cited alongside Kazumitsu Nawata, 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 Kazumitsu Nawata Line = papers co-authored together Kazumitsu Nawata links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20247
2 20234
3 20232
4 20213
5 20218
6 201949
7 201915
8 20151
9
Robust estimation based on the third-moment restriction of the error terms for the Box-Cox transformation model: An estimator consistent under heteroscedasticity
20155
10
A new test for the Box-Cox transformation model: An analysis of length of hospital stay for diabetes patients in Japan
20142
11
A new estimator of the Box-Cox transformation model using moment conditions
20138
12 20080
13 200815
14
Did the Credit Crunch in Japan Affect Household Welfare? An Augmented Euler Equation Approach Using Type 5 Tobit Model
20071
15
[Quantitative analysis of the demand for emergency medicine in Yokohama City, Japan].
20031
16
20035
17 200113
18 19959
19 19941
20 19940

About Kazumitsu Nawata

Kazumitsu Nawata is a scholar working on Statistics and Probability, Finance, Management Science and Operations Research, Economics and Econometrics and Cardiology and Cardiovascular Medicine, having authored 56 papers that have together received 628 indexed citations. Recurring topics across this work include Blood Pressure and Hypertension Studies (11 papers), Advanced Statistical Methods and Models (8 papers), Statistical Methods and Inference (8 papers), Chronic Disease Management Strategies (6 papers), Spatial and Panel Data Analysis (6 papers), Diabetes Management and Education (4 papers), Monetary Policy and Economic Impact (4 papers) and Cardiovascular Health and Disease Prevention (4 papers). The work is most often cited by research in Statistics and Probability (80 citations), Economics and Econometrics (207 citations), Management Science and Operations Research (73 citations), General Economics, Econometrics and Finance (43 citations) and Marketing (41 citations). Kazumitsu Nawata has collaborated with scholars based in Japan, Australia and Taiwan. Frequent co-authors include Chi-Yo Huang, Yu-Sheng Kao, Jie Zhang, Michael McAleer, Hinako Toyama, T Takahashi, Michael McAleer, Yasuyuki Sawada, Osamu Tochikubo and Hisayuki Hara. Their work appears in journals such as Mathematics and Computers in Simulation, Economics Letters, Journal of Econometrics, Econometric Reviews and Frontiers in Public Health.

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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