David T. Jacho‐Chávez

553 citations
46 papers · 299 indexed · h-index 10
Topics
Statistical Methods and Inference (22 papers)Financial Risk and Volatility Modeling (9 papers)Advanced Statistical Methods and Models (8 papers)

In The Last Decade

David T. Jacho‐Chávez

41 papers receiving 278 citations

Peers

David T. Jacho‐Chávez
Comparison fields: 5 of 67
  • Statistics and Probability 141
  • Economics and Econometrics 120
  • General Economics, Econometrics and Finance 87
  • Finance 55
  • Artificial Intelligence 39
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Citations per field
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Citations per year

Countries citing papers authored by David T. Jacho‐Chávez

Since Specialization
Citations

This map shows the geographic impact of David T. Jacho‐Chávez'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 David T. Jacho‐Chávez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David T. Jacho‐Chávez more than expected).

Fields of papers citing papers by David T. Jacho‐Chávez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David T. Jacho‐Chávez. 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 David T. Jacho‐Chávez. The network helps show where David T. Jacho‐Chávez may publish in the future.

Co-authorship network of co-authors of David T. Jacho‐Chávez

This figure shows the co-authorship network connecting the top 25 collaborators of David T. Jacho‐Chávez. A scholar is included among the top collaborators of David T. Jacho‐Chávez 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 David T. Jacho‐Chávez. David T. Jacho‐Chávez 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
#WorkIndexed citations
1 1
2 0
3 13
4 1
5 1
6 3
7 1
8 9
9 13
10 13
11 38
12 6
13
Functional Principal Component Analysis of Density Families with Categorical and Continuous Data on Canadian Entrant Manufacturing Firms
0
14
k -Nearest Neighbour Estimation of Inverse-Density-Weighted Expectations with Dependent Data
2
15 7
16
Uniform in Bandwidth Consistency of Smooth Varying Coefficient Estimators
1
17
k nearest-neighbor estimation of inverse density weighted expectations
4
18 7
19
Conditional density estimation: an application to the Ecuadorian manufacturing sector
8
20
Internally-Corrected Conditional Density Estimation
1

About David T. Jacho‐Chávez

David T. Jacho‐Chávez is a scholar working on Statistics and Probability, General Economics, Econometrics and Finance and Finance, having authored 46 papers that have together received 299 indexed citations. Recurring topics across this work include Statistical Methods and Inference (22 papers), Financial Risk and Volatility Modeling (9 papers) and Advanced Statistical Methods and Models (8 papers). The work is most often cited by research in Statistics and Probability (141 citations), General Economics, Econometrics and Finance (87 citations) and Finance (55 citations). David T. Jacho‐Chávez has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Kim P. Huynh, Juan Carlos Escanciano, Arthur Lewbel, Oliver B. Linton, Robert J. Petrunia, Marcel Voia, Oleksiy Kryvtsov, Xiaohong Chen, Oliver Linton and Oleksandr Shepotylo. Their work appears in journals such as Journal of the American Statistical Association, American Economic Review and Journal of Econometrics.

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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