What is he best known for?
The fields of study he is best known for:
- Statistics
- Econometrics
- Normal distribution
His primary scientific interests are in Econometrics, Statistics, Monte Carlo method, Unit root and Estimator.
His work on Cointegration and Panel data as part of general Econometrics study is frequently linked to Interdependence, bridging the gap between disciplines.
His study on Regression analysis, Asymptotic distribution, Regression and Test statistic is often connected to Cross section as part of broader study in Statistics.
His Asymptotic distribution research is multidisciplinary, incorporating perspectives in Score test, Power function and Variables.
He combines subjects such as Range, Principal component analysis, Mathematical analysis and Autocorrelation with his study of Monte Carlo method.
The concepts of his Unit root study are interwoven with issues in Statistical hypothesis testing, Series and Unit root test.
His most cited work include:
- Testing for unit roots in heterogeneous panels (8188 citations)
- Bounds testing approaches to the analysis of level relationships (7642 citations)
- A simple panel unit root test in the presence of cross-section dependence (3419 citations)
What are the main themes of his work throughout his whole career to date?
M. Hashem Pesaran mainly investigates Econometrics, Monte Carlo method, Estimator, Statistics and Panel data.
His Volatility study in the realm of Econometrics connects with subjects such as Context.
His Monte Carlo method research integrates issues from Asymptotic distribution, Factor analysis, Applied mathematics and Autoregressive model.
The study incorporates disciplines such as Heteroscedasticity and Variables in addition to Estimator.
His work on Unit root, Autocorrelation and Statistical hypothesis testing as part of general Statistics research is often related to Cross section, thus linking different fields of science.
M. Hashem Pesaran has researched Unit root in several fields, including Cointegration and Unit root test.
He most often published in these fields:
- Econometrics (91.02%)
- Monte Carlo method (42.96%)
- Estimator (35.39%)
What were the highlights of his more recent work (between 2015-2021)?
- Econometrics (91.02%)
- Estimator (35.39%)
- Monte Carlo method (42.96%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Econometrics, Estimator, Monte Carlo method, Panel data and Applied mathematics.
His research integrates issues of Multiple comparisons problem and Estimation in his study of Econometrics.
His study in the field of Asymptotic distribution also crosses realms of Dimension.
His Asymptotic distribution study incorporates themes from Proxy, Null hypothesis and Consistency.
His Monte Carlo method research is within the category of Statistics.
His work investigates the relationship between Panel data and topics such as Demographic economics that intersect with problems in Economic sector.
Between 2015 and 2021, his most popular works were:
- Multivariate Rational Expectations Models and Macroeconometric Modeling: A Review and Some New Results (119 citations)
- General Diagnostic Tests for Cross Section Dependence in Panels (92 citations)
- General Diagnostic Tests for Cross Section Dependence in Panels (92 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Normal distribution
- Econometrics
His main research concerns Estimator, Monte Carlo method, Econometrics, Applied mathematics and Degree.
His research in Estimator intersects with topics in Inference, Power law and Dominance.
His Monte Carlo method research includes themes of Sample size determination, Random variable, Collinearity, Shape parameter and Extremum estimator.
His Econometrics study combines topics from a wide range of disciplines, such as Multiple comparisons problem and Principal component analysis.
His studies deal with areas such as Covariance matrix, Asymptotic distribution, Bayesian probability and Exponential function as well as Applied mathematics.
His work carried out in the field of Asymptotic distribution brings together such families of science as Score test, Variables, Spatial dependence and Autoregressive model.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
