Many IVs Estimation of Dynamic Panel Regression Models with Measurement Error

2015 ◽  
Author(s):  
Nayoung Lee ◽  
Hyungsik Roger Moon ◽  
Qiankun Zhou
Keyword(s):  
Measurement Error ◽  
Regression Models ◽  
Panel Regression ◽  
Dynamic Panel ◽  
Dynamic Panel Regression ◽  
Panel Regression Models

scholarly journals Do larger boards improve shareholder value creation? – Effects of the board size on business performance in Eastern Central Europe

2020 ◽  
Vol 42 (3) ◽  
pp. 245-279
Author(s):  
Zsolt Lakatos
Keyword(s):  
Firm Performance ◽  
Regression Models ◽  
Positive Impact ◽  
Supervisory Board ◽  
Panel Regression ◽  
Board Size ◽  
Dynamic Panel ◽  
Management Board ◽  
Dynamic Panel Regression ◽  
Panel Regression Models

AbstractThe aim of this study is to analyse the impact of board size on a firms' operational and market performance at the largest East Central European listed non-financial, non-public utility firms. The literature debates the effects of the size of the board. While the resource dependency theory supports a positive effect, the agency theory supports a negative impact on firm value. This question is rarely investigated in two-tiered corporate governance models. This paper estimates the effects of management board and supervisory board size, between 2007 and 2016. The results indicate that the effect of management board size depends heavily on the size of the observed company. In both fixed effects and GMM-type dynamic panel regression models, using Tobin's Q, market-to-book ratio, total shareholder value and ROA as firm performance measures, increase in management board size has a significant positive impact on firm performance; however, in the case of larger firms, the effect is significantly negative. Moreover, the increase in the ratio of outside directors has a positive impact on the firm's performance in all dynamic panel regression models and this effect is even more significant in Tobin's Q and market-to-book ratio models. This can indicate the effective monitoring role of the supervisory board.

scholarly journals Relationships between Renewable Energy and the Prevalence of Morbidity in the Countries of the European Union: A Panel Regression Approach

2021 ◽  
Vol 18 (12) ◽  
pp. 6548
Author(s):  
Robert Stefko ◽  
Beata Gavurova ◽  
Miroslav Kelemen ◽  
Martin Rigelsky ◽  
Viera Ivankova
Keyword(s):  
European Union ◽  
Renewable Energy ◽  
Statistical Methods ◽  
Regression Models ◽  
Kidney Diseases ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Panel Regression ◽  
The European Union ◽  
Panel Regression Models

The main objective of the presented study was to examine the associations between the use of renewable energy sources in selected sectors (transport, electricity, heating, and cooling) and the prevalence of selected groups of diseases in the European Union, with an emphasis on the application of statistical methods considering the structure of data. The analyses included data on 27 countries of the European Union from 2010 to 2019 published in the Eurostat database and the Global Burden of Disease Study. Panel regression models (pooling model, fixed (within) effects model, random effects model) were primarily used in analytical procedures, in which a panel variable was represented by countries. In most cases, positive and significant associations between the use of renewable energy sources and the prevalence of diseases were confirmed. The results of panel regression models could be generally interpreted as meaning that renewable energy sources are associated with the prevalence of diseases such as cardiovascular diseases, diabetes and kidney diseases, digestive diseases, musculoskeletal disorders, neoplasms, sense organ diseases, and skin and subcutaneous diseases at a significance level (α) of 0.05 and lower. These findings could be explained by the awareness of the health problem and the response in the form of preference for renewable energy sources. Regarding statistical methods used for country data or for data with a specific structure, it is recommended to use the methods that take this structure into account. The absence of these methods could lead to misleading conclusions.

scholarly journals Macroeconomic, Institutional and Bank-Specific Determinants of Non-Performing Loans in Emerging Market Economies: A Dynamic Panel Regression Analysis

2019 ◽  
Vol 8 (3) ◽  
pp. 95-110
Author(s):  
Yilmaz Bayar
Keyword(s):  
Regression Analysis ◽  
Banking Sector ◽  
Emerging Market ◽  
Dynamic Panel Data ◽  
Emerging Market Economies ◽  
Panel Regression ◽  
Dynamic Panel ◽  
Market Economies ◽  
Nonperforming Loans ◽  
Dynamic Panel Regression

Abstract Banking sector is important for various macroeconomic and microeconomic variables in terms of mobilization of funds, increasing savings, and providing alternative investment instruments suited to the every person by minimizing the risk of adverse selection and moral hazard, allocating funds to most productive projects, risk diversification. Therefore, sound functioning of the banking sector is critical especially for emerging and developing countries. This study explores the macroeconomic, institutional, and bank-specific factors behind nonperforming banking loans as an indicator of banking sector functioning in emerging market economies over the 2000-2013 period by employing the system GMM dynamic panel data estimator. Results of the dynamic panel regression analysis showed that economic growth, inflation, economic freedom (institutional development), return on assets and equity, regulatory capital to risk-weighted assets, and noninterest income to total income affected nonperforming loans negatively, while unemployment, public debt, credit growth, lagged values of nonperforming loans, cost to income ratio and financial crises affected nonperforming loans positively.

scholarly journals Does ESG Disclosure Create Value to Firms? The Malaysian Case

2018 ◽  
pp. 515-521
Keyword(s):  
Social Norms ◽  
Regression Models ◽  
Financial Data ◽  
Panel Regression ◽  
Tobin’S Q ◽  
Publicly Traded ◽  
Tobin's Q ◽  
Publicly Traded Firms ◽  
Governance Disclosure ◽  
Panel Regression Models

We examine whether ESG (Environmental, Social and Governance) disclosure creates value to Malaysian firms. Based on the dataset of 37 Malaysian publicly traded firms, our results obtained from various panel regression models show that the overall ESG disclosure score and its environmental and governance pillars are positively associated with Tobin’s Q. This implies that Malaysian firms which act in accordance to social norms will be rewarded by the market. The outcomes of this research highlight the importance of non-financial data disclosure in Malaysian market.

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