Iván Fernández‐Val

45 papers receiving 1.7k citations

Hit Papers

Handbook of Quantile Regression2017202620202023201750100150200

Peers

Iván Fernández‐Val
Comparison fields: 5 of 122
  • Economics and Econometrics 832
  • Statistics and Probability 609
  • General Economics, Econometrics and Finance 347
  • Finance 214
  • Sociology and Political Science 169
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Citations per year

Countries citing papers authored by Iván Fernández‐Val

Since Specialization
Citations

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

Fields of papers citing papers by Iván Fernández‐Val

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Iván Fernández‐Val. 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 Iván Fernández‐Val. The network helps show where Iván Fernández‐Val may publish in the future.

Co-authorship network of co-authors of Iván Fernández‐Val

This figure shows the co-authorship network connecting the top 25 collaborators of Iván Fernández‐Val. A scholar is included among the top collaborators of Iván Fernández‐Val 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 Iván Fernández‐Val. Iván Fernández‐Val 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 0
4
Shape-Enforcing Operators for Generic Point and Interval Estimators of Functions
1
5 3
6
QRPROCESS: Stata module for quantile regression: fast algorithm, pointwise and uniform inference
3
7 36
8 18
9 19
10 39
11
Supplement to “program evaluation and causal inference with high-dimensional data"
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12 1
13 5
14
Panel data models with nonadditive unobserved heterogeneity : estimation and inference
23
15
Average and Quantile Effects in Nonseparable Panel Models
128
16 30
17
ExtrapoLATE-ing: External Validity and Overidentification in the LATE Framework
6
18
Inference for Extremal Conditional Quantile Models, with an Application to Market and Birthweight Risks
37
19 165
20 38

About Iván Fernández‐Val

Iván Fernández‐Val is a scholar working on Statistics and Probability, General Economics, Econometrics and Finance and Economics and Econometrics, having authored 48 papers that have together received 1.8k indexed citations. Recurring topics across this work include Statistical Methods and Inference (22 papers), Spatial and Panel Data Analysis (16 papers) and Monetary Policy and Economic Impact (14 papers). The work is most often cited by research in Statistics and Probability (609 citations), General Economics, Econometrics and Finance (347 citations) and Economics and Econometrics (832 citations). Iván Fernández‐Val has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Victor Chernozhukov, Martin Weidner, Joshua D. Angrist, Tetsuya Kaji, Alfred Galichon, Whitney K. Newey, Jinyong Hahn, Blaise Melly, Kevin Lang and Adam B. Ashcraft. Their work appears in journals such as Journal of the American Statistical Association, Econometrica and Journal of Political Economy.

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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