What is he best known for?
The fields of study he is best known for:
- Statistics
- Normal distribution
- Mathematical analysis
Estimator, Econometrics, Statistics, Nonlinear system and Monte Carlo method are his primary areas of study.
Jinyong Hahn interconnects Estimation theory, Simultaneous equations model, Least squares and Applied mathematics in the investigation of issues within Estimator.
His work on Nonparametric statistics, Panel data and Quantile as part of general Econometrics research is frequently linked to Estimation, bridging the gap between disciplines.
His biological study spans a wide range of topics, including Average treatment effect and Propensity score matching.
His Nonlinear system research is multidisciplinary, relying on both Bias reduction and Fixed effects model.
His Monte Carlo method research incorporates elements of Ordinary least squares and Autoregressive model.
His most cited work include:
- IDENTIFICATION AND ESTIMATION OF TREATMENT EFFECTS WITH A REGRESSION-DISCONTINUITY DESIGN (1621 citations)
- On the role of the propensity score in efficient semiparametric estimation of average treatment effects (654 citations)
- Asymptotically Unbiased Inference for a Dynamic Panel Model with Fixed Effects When Both n and T are Large (330 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Estimator, Econometrics, Applied mathematics, Statistics and Nonparametric statistics.
The concepts of his Estimator study are interwoven with issues in Panel data, Monte Carlo method and Instrumental variable.
His Panel data study combines topics in areas such as Quantile and Consistent estimator.
His studies examine the connections between Monte Carlo method and genetics, as well as such issues in Statistical hypothesis testing, with regards to Estimation theory and Least squares.
His work in the fields of Econometrics, such as Quantile regression, intersects with other areas such as Estimation and Identification.
The various areas that Jinyong Hahn examines in his Applied mathematics study include Fixed effects model, Moment and Nonlinear system.
He most often published in these fields:
- Estimator (63.49%)
- Econometrics (48.41%)
- Applied mathematics (31.75%)
What were the highlights of his more recent work (between 2013-2020)?
- Estimator (63.49%)
- Econometrics (48.41%)
- Applied mathematics (31.75%)
In recent papers he was focusing on the following fields of study:
Jinyong Hahn mostly deals with Estimator, Econometrics, Applied mathematics, Statistics and Panel data.
In the field of Estimator, his study on Semiparametric model overlaps with subjects such as Sieve.
His Econometrics research includes elements of Test and Class.
His Applied mathematics study combines topics from a wide range of disciplines, such as Prediction interval, Statistical inference, Series and Time series.
Many of his research projects under Statistics are closely connected to Random permutation with Random permutation, tying the diverse disciplines of science together.
Jinyong Hahn combines subjects such as Sample size determination, Quantile regression, Quantile and Normal distribution with his study of Panel data.
Between 2013 and 2020, his most popular works were:
- Synthetic Control and Inference (30 citations)
- Asymptotic Efficiency of Semiparametric Two-step GMM (22 citations)
- A quantile correlated random coefficients panel data model (20 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Normal distribution
- Mathematical analysis
His scientific interests lie mostly in Estimator, Statistics, Econometrics, Applied mathematics and Closed-form expression.
He mostly deals with Semiparametric regression in his studies of Estimator.
Jinyong Hahn specializes in Statistics, namely Quantile regression.
His work deals with themes such as Sample size determination and Normal distribution, which intersect with Econometrics.
His Applied mathematics research is multidisciplinary, incorporating elements of Control variable and Joint probability distribution.
His studies in Closed-form expression integrate themes in fields like Nonparametric statistics, Delta method and Asymptotic distribution.
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