What is he best known for?
The fields of study he is best known for:
- Statistics
- Macroeconomics
- Econometrics
Yongcheol Shin mostly deals with Econometrics, Cointegration, Statistics, Unit root and Autoregressive model.
As a part of the same scientific family, Yongcheol Shin mostly works in the field of Econometrics, focusing on Exchange rate and, on occasion, Interest rate and Normal distribution.
Yongcheol Shin interconnects Vector autoregression, Asymptotic distribution and Interest rate parity in the investigation of issues within Cointegration.
His Unit root study combines topics from a wide range of disciplines, such as Statistical hypothesis testing, Regression analysis and Mathematical economics.
His biological study spans a wide range of topics, including KPSS test and Unit root test.
His work carried out in the field of Unit root test brings together such families of science as One- and two-tailed tests, Size, Null distribution, Portmanteau test and Order of integration.
His most cited work include:
- Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root? (8711 citations)
- Testing for unit roots in heterogeneous panels (8188 citations)
- Bounds testing approaches to the analysis of level relationships (7642 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Econometrics, Monte Carlo method, Autoregressive model, Panel data and Statistics.
His study in the field of Cointegration and Null hypothesis also crosses realms of Inference.
As part of the same scientific family, Yongcheol Shin usually focuses on Cointegration, concentrating on Asymptotic distribution and intersecting with Variables.
His Monte Carlo method study incorporates themes from Asymptotic theory and Autocorrelation.
His Autoregressive model research is multidisciplinary, incorporating elements of Distributed lag, Quantile, Wald test and Applied mathematics.
In the field of Statistics, his study on Unit root, Test statistic, Unit root test and Statistic overlaps with subjects such as Null.
He most often published in these fields:
- Econometrics (60.69%)
- Monte Carlo method (18.62%)
- Autoregressive model (18.62%)
What were the highlights of his more recent work (between 2017-2021)?
- Econometrics (60.69%)
- Estimator (13.10%)
- Panel data (17.24%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Econometrics, Estimator, Panel data, Autoregressive model and Monte Carlo method.
His study in Econometrics is interdisciplinary in nature, drawing from both Stylized fact and Flexibility.
In Estimator, Yongcheol Shin works on issues like Gravity model of trade, which are connected to Asymptotic theory.
His Autoregressive model study integrates concerns from other disciplines, such as Distributed lag, Probability density function and Economic cost.
While the research belongs to areas of Distributed lag, Yongcheol Shin spends his time largely on the problem of Wald test, intersecting his research to questions surrounding Error correction model.
His Instrumental variable research incorporates themes from Endogeneity, Spatial dependence, Asymptotic distribution and Variables.
Between 2017 and 2021, his most popular works were:
- Quantile Connectedness: Modelling Tail Behaviour in the Topology of Financial Networks (7 citations)
- Estimation and Inference for Multi-dimensional Heterogeneous Panel Datasets with Hierarchical Multi-factor Error Structure (6 citations)
- Testing for Unit Roots in Dynamic Panels with Smooth Breaks and Cross-Sectionally Dependent Errors (5 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Macroeconomics
- Econometrics
His primary areas of study are Econometrics, Estimator, Inference, Asymptotic theory and Quantile.
His work in the fields of Econometrics, such as Error correction model, overlaps with other areas such as Limit.
His research in Estimator intersects with topics in Gravity model of trade, Monte Carlo method and Conditional expectation.
Inference overlaps with fields such as Statistics, Unit root test, Nonparametric statistics, Panel data and Data mining in his research.
His Asymptotic theory research is multidisciplinary, relying on both Instrumental variable and Autoregressive model.
His Quantile study combines topics from a wide range of disciplines, such as Quantile regression, Tail dependence and Credit risk.
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