1989 - Fellows of the Econometric Society
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.
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.
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.
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.
Bounds testing approaches to the analysis of level relationships
M. Hashem Pesaran;Yongcheol Shin;Richard J. Smith.
Journal of Applied Econometrics (2001)
Testing for unit roots in heterogeneous panels
Kyung So Im;M.Hashem Pesaran;Yongcheol Shin.
Journal of Econometrics (2003)
An Autoregressive Distributed-Lag Modelling Approach to Cointegration Analysis
M. Hashem Pesaran;Yongcheol Shin.
Research Papers in Economics (1999)
A simple panel unit root test in the presence of cross-section dependence
M. Hashem Pesaran.
Journal of Applied Econometrics (2007)
Estimating long-run relationships from dynamic heterogeneous panels☆
M.Hashem Pesaran;Ron Smith.
Journal of Econometrics (1995)
Pooled Mean Group Estimation of Dynamic Heterogeneous Panels
M. Hashem Pesaran;Yongcheol Shin;Ron P. Smith.
Journal of the American Statistical Association (1999)
General Diagnostic Tests for Cross Section Dependence in Panels
M. Hashem Pesaran;M. Hashem Pesaran.
Social Science Research Network (2004)
Impulse response analysis in nonlinear multivariate models
Gary Koop;M.Hashem Pesaran;Simon M. Potter.
Journal of Econometrics (1996)
Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure
M. Hashem Pesaran.
Working with Microfit 4.0 : interactive econometric analysis
M. Hashem Pesaran;Bahram Pesaran.
Profile was last updated on December 6th, 2021.
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