William Greene

William Greene

New York University

H-index: 98

North America-United States

About William Greene

William Greene, With an exceptional h-index of 98 and a recent h-index of 59 (since 2020), a distinguished researcher at New York University, specializes in the field of Econometrics, Health Economics, Transportation, Production Modeling.

His recent articles reflect a diverse array of research interests and contributions to the field:

Biases in the Maximum Simulated Likelihood Estimation of the Mixed Logit Model

Modelling the Distribution of Cognitive Outcomes for Early-Stage Neurocognitive Disorders: A Model Comparison Approach

Robust maximum likelihood estimation of stochastic frontier models

On hypothesis testing in latent class and finite mixture stochastic frontier models, with application to a contaminated normal-half normal model

Reporting heterogeneity in modeling self-assessed survey outcomes

Robustness in stochastic frontier analysis

Arbitrary inflation in fractional models

Slow recognition of seminal papers and fast growth of author connectivity in economics

William Greene Information

University

Position

Professor of Economics and Statistics Stern School of Business

Citations(all)

154992

Citations(since 2020)

35954

Cited By

127544

hIndex(all)

98

hIndex(since 2020)

59

i10Index(all)

236

i10Index(since 2020)

157

Email

University Profile Page

Google Scholar

William Greene Skills & Research Interests

Econometrics

Health Economics

Transportation

Production Modeling

Top articles of William Greene

Biases in the Maximum Simulated Likelihood Estimation of the Mixed Logit Model

Econometrics

2024/3/27

Modelling the Distribution of Cognitive Outcomes for Early-Stage Neurocognitive Disorders: A Model Comparison Approach

Biomedicines

2024/2/8

William Greene
William Greene

H-Index: 60

Robust maximum likelihood estimation of stochastic frontier models

European Journal of Operational Research

2023/8/16

On hypothesis testing in latent class and finite mixture stochastic frontier models, with application to a contaminated normal-half normal model

Journal of Productivity Analysis

2023/8

Reporting heterogeneity in modeling self-assessed survey outcomes

Economic Modelling

2023/7/1

William Greene
William Greene

H-Index: 60

Mark N Harris
Mark N Harris

H-Index: 19

Robustness in stochastic frontier analysis

2023/6/22

Arbitrary inflation in fractional models

The Sheffield Economic Research Paper Series (SERPS)

2023/2/28

Slow recognition of seminal papers and fast growth of author connectivity in economics

2023/2/6

William Greene
William Greene

H-Index: 60

Comparing the Conditional Logit Estimates and True Parameters under Preference Heterogeneity: A Simulated Discrete Choice Experiment

Econometrics

2023/1/25

Murat Munkin
Murat Munkin

H-Index: 8

William Greene
William Greene

H-Index: 60

The use of multinomial choice analysis in international business research

International Business Review

2022/8/1

Uncertainty and the Bank of England's MPC

Journal of Money, Credit and Banking

2022/6

Heterogeneity in speed of adjustment using finite mixture models

Economic Modelling

2022/2/1

Experience as a conditioning effect on choice: Does it matter whether it is exogenous or endogenous?

Transportation

2020/11/26

The built environment and vehicle ownership modeling: Evidence from 32 diverse regions in the US

Journal of transport geography

2021/5/1

Does the US Navy’s reliance on objective standards prevent discrimination in promotions and retentions?

PloS one

2021/4/28

A guide to observable differences in stated preference evidence

The Patient-Patient-Centered Outcomes Research

2021

Review of difference-in-difference analyses in social sciences: application in policy test research

2021

Technology and technical efficiency change: evidence from a difference in differences selectivity corrected stochastic production frontier model

American Journal of Agricultural Economics

2021/1

William Greene
William Greene

H-Index: 60

Specification and testing of hierarchical ordered response models with anchoring vignettes

Journal of the Royal Statistical Society Series A: Statistics in Society

2021/1

See List of Professors in William Greene University(New York University)

Co-Authors

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