Results 131 to 140 of about 13,398 (256)

Panel AR(1) estimators under misspecification

This short note derives the probability limits of several estimators for panel AR(1) models under misspecification using sequential asymptotics. The results show that GMM estimators based on the forward orthogonal deviation transformation converge to the
Okui, Ryo
core  

Family Control and Ownership, Corporate Culture, and ESG Performance in Thailand

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Motivated by the growing importance of environmental, social, and governance (ESG) performance in emerging markets, we examine how family control and ownership, together with corporate culture, influence the ESG performance of publicly listed firms in Thailand.
Sirimon Treepongkaruna, Stefano Starita, Kam Fong Chan   +2 more
wiley   +1 more source

Acknowledgement Misspecification in Macroeconomic Theory [PDF]

We explore methods for confronting model misspecification in macroeconomics. We construct dynamic equilibria in which private agents and policy makers recognize that models are approximations.
Sargent, Thomas-J, Hansen, Lars-Peter
core  

Evaluation of Simultaneous Equation Techniques in the Presence of Misspecification Error: A Monte Carlo Approach [PDF]

, 2014
One  of  the  assumptions  of  Classical  Linear  Regression  Model (CLRMA),  is  that  the  regression  model be  ‘correctly’   specified.  If  the  model  is  not  ‘correctly’  specified,  the  problem  of  model  misspecification  error arises.
ADEPOJU, ADEDAYO A., OJO, OLUWADARE O.
core  

The Synergistic Impact of Corporate Social Responsibility and Environmental, Social, and Governance Disclosure on Green Innovation: Practical Implications for Sustainability‐Oriented Innovation Strategies

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT This research examines the synergistic influence of corporate social responsibility (CSR) and environmental, social, and governance (ESG) disclosure on green innovation (GI) within Romanian small and medium‐sized industrial enterprises. In light of growing regulatory requirements and the transformation toward a sustainable economy, the study ...
Melinda Timea Fülöp, Javier Cifuentes‐Faura   +1 more
wiley   +1 more source

Investigating item complexity as a source of cross-national DIF in TIMSS math and science

Large-scale Assessments in Education
Background Large scale international assessments depend on invariance of measurement across countries. An important consideration when observing cross-national differential item functioning (DIF) is whether the DIF actually reflects a source of bias, or ...
Qi Huang, Daniel M. Bolt, Weicong Lyu
doaj   +1 more source

DSGE Estimation Using Generalized Empirical Likelihood and Generalized Minimum Contrast

Entropy
We investigate the performance of estimators of the generalized empirical likelihood and minimum contrast families in the estimation of dynamic stochastic general equilibrium models, with particular attention to the robustness properties under ...
Gilberto Boaretto, Márcio Poletti Laurini   +1 more
doaj   +1 more source

A Cautionary Tale of Model Misspecification and Identifiability

Bulletin of Mathematical Biology
Mathematical models are routinely applied to interpret biological data, with common goals that include both prediction and parameter estimation. A challenge in mathematical biology, in particular, is that models are often complex and non-identifiable, while data are limited.
Alexander P. Browning, Jennifer A. Flegg, Ryan J. Murphy   +2 more
openaire   +3 more sources

Responsible Banking Under Twin Transition: FinTech M&As, ESG Strategy, and Bank Performance

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT This paper investigates how banking innovation strategies, namely FinTech M&As and ESG practices, affect bank performance under rising competitive pressures and regulatory complexity. Using a unique dataset of 543 listed banks across 49 countries from 2000 to 2023, we analyse whether these strategic investments enhance banks' profitability ...
G. B. Ferilli, Y. Altunbas, E. Palmieri
wiley   +1 more source

Minimizing Sensitivity to Model Misspecification

We propose a framework for estimation and inference when the model may be misspecified. We rely on a local asymptotic approach where the degree of misspecification is indexed by the sample size. We construct estimators whose mean squared error is minimax
Stéphane Bonhomme, Martin Weidner
core