Analyzing Panel Data: Fixed- and Random-Effects Models

2012 ◽  
pp. 332-345 ◽  
Author(s):  
TROND PETERSEN
Keyword(s):  
Panel Data ◽  
Random Effects ◽  
Random Effects Models ◽  
Fixed And Random Effects

scholarly journals Non-Negativity of a Quadratic form with Applications to Panel Data Estimation, Forecasting and Optimization

Stats ◽  
2020 ◽  
Vol 3 (3) ◽  
pp. 185-202
Author(s):  
Bhimasankaram Pochiraju ◽  
Sridhar Seshadri ◽  
Dimitrios Thomakos ◽  
Konstantinos Nikolopoulos
Keyword(s):  
Panel Data ◽  
Random Effects ◽  
Symmetric Matrix ◽  
Panel Data Models ◽  
Random Effects Models ◽  
Panel Data Estimation ◽  
Quadratic Minimization ◽  
Fixed And Random Effects ◽  
Estimated Error ◽  
Data Estimation

For a symmetric matrix B, we determine the class of Q such that Q t BQ is non-negative definite and apply it to panel data estimation and forecasting: the Hausman test for testing the endogeneity of the random effects in panel data models. We show that the test can be performed if the estimated error variances in the fixed and random effects models satisfy a specific inequality. If it fails, we discuss the restrictions under which the test can be performed. We show that estimators satisfying the inequality exist. Furthermore, we discuss an application to a constrained quadratic minimization problem with an indefinite objective function.

Bridging Methodological Divides Between Macro- and Microresearch: Endogeneity and Methods for Panel Data

2019 ◽  
Vol 46 (1) ◽  
pp. 70-99 ◽  
Author(s):  
Paul D. Bliese ◽  
Donald J. Schepker ◽  
Spenser M. Essman ◽  
Robert E. Ployhart
Keyword(s):  
Panel Data ◽  
Random Effects ◽  
Fixed Effects ◽  
Theory Development ◽  
Modeling Framework ◽  
Random Effects Models ◽  
Data Support ◽  
Fixed And Random Effects

Both macro- and micro-oriented researchers frequently use panel data where the outcome of interest is measured repeated times. Panel data support at least five different modeling frameworks (within, between, incremental/emergent, cross-level, and growth). Researchers from macro- and micro-oriented domains tend to differentially use the frameworks and also use different analytic tools and terminology when using the same modeling framework. These differences have the potential to inhibit cross-discipline communication. In this review, we explore how macro- and microresearchers approach panel data with a specific emphasis on the theoretical implications of choosing one framework versus another. We illustrate how fixed-effects and random-effects models differ and how they are similar, and we conduct a thorough review of 142 articles that used panel data in leading management journals in 2017. Ultimately, our review identifies ways that researchers can better employ fixed- and random-effects models, model time as a meaningful predictor or ensure unobserved time heterogeneity is controlled, and align hypotheses to analytic choice. In the end, our goal is to help facilitate communication and theory development between macro- and micro-oriented management researchers.

scholarly journals Sars-Cov-2 in Argentina: Lockdown, Mobility, and Contagion

2020 ◽  
Author(s):  
Juan M.C. Larrosa
Keyword(s):  
Panel Data ◽  
Granger Causality ◽  
Random Effects ◽  
Social Costs ◽  
Political Discussion ◽  
Fixed And Random Effects ◽  
The World ◽  
Causality Tests ◽  
Granger Causality Tests ◽  
Over Time

AbstractThere is a debate in Argentina about the effectiveness of mandatory lockdown measures in containing COVID-19 that lasts five months making it one of the longest in the World. The population effort to comply the lockdown has been decreasing over time given the economic and social costs that it entails. We contributes by analyzing the Argentinian case through information of mobility and contagion given answers to recurrent questions on these topics. This paper aims to fill the gap in the literature by assessing the effects of lockdown measures and the regional relaxation on the numbers of rate of new infections. We also respond to issues of internal political discussion on regional contagion and the effect of marches and unexpected crowd events. We use pool, fixed and random effects panel data modeling and Granger causality tests identifying relations between mobility and contagion. Our results show that lockdown in Argentina has been effective in reducing the mobility but not in way that reduces the rate of contagion. Strict lockdown seems to be effective in short periods of time and by extend it without complementary measures loss effectiveness. Contagion rate seems to be discretely displaced in time and resurging amidst slowly increasing in mobility.

Environmental Kuznets Curve for sulfur: evidence using GMM estimation and random coefficient panel data models

2003 ◽  
Vol 8 (4) ◽  
pp. 581-601 ◽  
Author(s):  
George E. Halkos
Keyword(s):  
Panel Data ◽  
Generalized Method Of Moments ◽  
Random Coefficients ◽  
Environmental Damage ◽  
Kuznets Curve ◽  
Random Effects Models ◽  
Econometric Methods ◽  
Fixed And Random Effects ◽  
First Time ◽  
Sulfur Emissions

The purpose of this study is to test empirically the hypothesis of the inverted U-shaped relationship between environmental damage from sulfur emissions and economic growth as expressed by GDP. Using a large database of panel data consisting of 73 OECD and non-OECD countries for 31 years (1960–1990) we apply for the first time random coefficients and Arellano-Bond Generalized Method of Moments (A–B GMM) econometric methods. Our findings indicate that the EKC hypothesis is not rejected in the case of the A–B GMM. On the other hand there is no support for an EKC in the case of using a random coefficients model. Our turning points range from $2805–$6230/c. These results are completely different compared to the results derived using the same database and fixed and random effects models.

scholarly journals Significance of supply chain finance: Insights from Saudi Arabia

2021 ◽  
Vol 9 (3) ◽  
pp. 539-548 ◽  
Author(s):  
Abdul Rahman Shaik
Keyword(s):  
Saudi Arabia ◽  
Supply Chain ◽  
Financial Performance ◽  
Random Effects ◽  
Return On Assets ◽  
Random Effects Models ◽  
Performance Variables ◽  
Operating Profit ◽  
Supply Chain Finance ◽  
Fixed And Random Effects

The study examines the effect of the supply chain finance (SCF) on the corporate financial performance measured in terms of Return on Assets (ROA), Tobin's Q, and Gross Operating Profit (GOP) in the material sector of Saudi Arabia. The study selects a sample of 42 companies from the material sector listed on Tadawul starting in 2008 and ending 2019. A panel regression in terms of pooled OLS, fixed and random effects, and panel GMM is estimated to report the empirical results. The results report a negative and significant effect between the financial performance variables and supply chain finance, specifically with ROA with pooled OLS and fixed and random effects models. The results of panel GMM also show a negative and significant effect between all the financial performance variables and financing supply chain. The results are useful to academicians and the managers in the materials, inventory, and sales sections, and supply chain managers to integrate finance and SCM to achieve corporate benefits.

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