scholarly journals Comparison of Competing Approaches to Analyzing Cross-Classified Data: Random Effects Models, Ordinary Least Squares, or Fixed Effects with Cluster Robust Standard Errors

2021 ◽  
Author(s):  
Young Ri Lee ◽  
James E Pustejovsky
Keyword(s):  
Least Squares ◽  
Random Effects ◽  
Fixed Effects ◽  
Good Alternative ◽  
Ordinary Least Squares ◽  
Alternative Methods ◽  
Least Squares Regression ◽  
Monte Carlo Simulation Study ◽  
Random Effects Models ◽  
Fixed Effects Regression

Cross-classified random effects modeling (CCREM) is a common approach for analyzing cross-classified data in education. However, when the focus of a study is on the regression coefficients at level one rather than on the random effects, ordinary least squares regression with cluster robust variance estimators (OLS-CRVE) or fixed effects regression with CRVE (FE-CRVE) could be appropriate approaches. These alternative methods may be advantageous because they rely on weaker assumptions than what is required by CCREM. We conducted a Monte Carlo Simulation study to compare the performance of CCREM, OLS-CRVE, and FE-CRVE in models with crossed random effects, including conditions where homoscedasticity assumptions and exogeneity assumptions held and conditions where they were violated. We found that CCREM performed the best when its assumptions are all met. However, when homoscedasticity assumptions are violated, OLS-CRVE and FE-CRVE provided similar or better performance than CCREM. FE-CRVE showed the best performance when the exogeneity assumption is violated. Thus, we recommend two-way FE-CRVE as a good alternative to CCREM, particularly if the homoscedasticity or exogeneity assumptions of the CCREM might be in doubt.

scholarly journals Impact of Full IFRS, Accounting Standards for SMES and Company Demographics on Firms’ Return on Asset and Return on Equity using Panel Data Regression

2019 ◽  
Vol 8 (6S) ◽  
pp. 589-601 ◽  
Keyword(s):  
Least Squares ◽  
Random Effects ◽  
Fixed Effects ◽  
Random Effect ◽  
Ordinary Least Squares ◽  
Lagrangian Multiplier ◽  
Random Effects Model ◽  
Fixed Effects Model ◽  
Real Property ◽  
The Impact

Due to globalization, markets are becoming more interconnected as the companies are engaged in doing cross-border offerings. Currently, competitions are intensified because Domestic organizations discover themselves competing with each nearby opposite numbers and worldwide companies. But one component that hinders SMEs is the need for reliable and similar monetary data. According to Abarca (2014), adoption of a high-quality and consistent set of accounting requirements is critical so as for the businesses to remain competitive in ASEAN member states. This paper ambitions to answer the query, what modified into the extent of the impact of compliance with full IFRS and IFRS for SMEs on profitability of agencies belong to real property enterprise? This paper moreover sought to decide whether there may be a sizeable distinction among the groups’ compliance with the overall PFRS and the PFRS for SMEs and to determine whether or now not there is a massive distinction among the companies’ financial normal overall performance earlier than and after the adoption of the PFRS for SMEs.Paired T-test have become employed in case you need to determine whether there is a big distinction between the agencies’ compliance with the entire PFRS and the PFRS for SMEs and to decide whether or not there may be a big difference some of the groups’ monetary performance earlier than and after the adoption of the PFRS for SMEs. Using STATA, the great appropriate version for every economic ratio on the subject of degree of compliance emerge as determined on. First, take a look at parm command became used to find out which most of the Least Squares Dummy Variable Regression Modes (LSDV1, LSDV2, LSDV3) underneath the Fixed Effects Model is the ideal version. Afterwards, Hausman Fixed Random Test changed into used to pick out out which is more suitable amongst Fixed Effects Model and Random Effects Model. If Fixed Effects Model modified into the more appropriate one, the Wald’s test turn out to be used to determine the best version among Fixed Effects Model and Ordinary Least Squares Model. On the alternative hand, if Random Effects Model became the more suitable one, the Breusch and Pagan Lagrangian Multiplier Test for Random Effect have become used to decide the satisfactory version amongst Random Effects Model and Ordinary Least Squares. Moreover, if Ordinary Least Squares became the splendid model, it is going to be in addition tested to check for heteroscedasticity and multicollinearity. White’s test became used to check for heterescedasticity and Variance Inflation Factor have become used to test if multicollinearity is gift. The results display that the adoption of PFRS for SMEs stepped forward the compliance of Philippine real property SMEs. However, no vast alternate became said inside the financial average performance of those companies (as measured with the resource of cross back on assets and go back on equity). This was further supported by the results of the panel regression. This means that despite having a relatively

scholarly journals Correcting measurement error bias in interaction models with small samples

2006 ◽  
Vol 3 (2) ◽  
Author(s):  
Josep Bisbe ◽  
Germà Coenders ◽  
Willem Saris ◽  
Joan Batista-Foguet
Keyword(s):  
Measurement Error ◽  
Least Squares ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Ordinary Least Squares ◽  
Alternative Methods ◽  
Small Samples ◽  
Least Squares Regression ◽  
Interaction Terms ◽  
Error Bias

Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression.

scholarly journals A closer look at fixed effects regression in SEM

2019 ◽  
Author(s):  
Henrik Kenneth Andersen
Keyword(s):  
Least Squares ◽  
Latent Variables ◽  
Latent Variable ◽  
Fixed Effects ◽  
Structural Equation ◽  
Panel Data Analysis ◽  
Ordinary Least Squares ◽  
Equation Modeling ◽  
Real World Data ◽  
Fixed Effects Regression

This article provides an in-depth look at the method of fixed-effects regression in the structural equation modeling (SEM) framework. It is meant for those who are less familiar with SEM but interested in panel data analysis as well as those familiar with SEM but new to fixed-effects regression. It demonstrates the decomposition of observed variables into within- and between-unit variance components using latent variables and gives an intuitive least squares-based explanation of latent variable estimation. The estimation of the substantive effect coefficients is shown analytically. The procedure is demonstrated on simulated as well as real-world data using the German Family Panel Survey (pairfam). The example analyses show the SEM results are identical to the conventional methods of pooled ordinary least squares on demeaned data. The supplementary materials provide the model code for use in replication and further study.

In hotel REITs, are institutional investors beneficial for firm value?

2020 ◽  
pp. 135481662090870
Author(s):  
Soyon Paek ◽  
Jin-Young Kim ◽  
Sung Gyun Mun ◽  
Chulhee Jun
Keyword(s):  
Least Squares ◽  
Random Effects ◽  
Institutional Investors ◽  
Firm Value ◽  
Negative Relationship ◽  
Institutional Ownership ◽  
Ordinary Least Squares ◽  
Random Effects Models ◽  
Fixed And Random Effects ◽  
Quadratic Models

Motivated by growing attention to the agency problems of institutional investors, along with recent changes that have identified real estate investment trusts (REITs) as a separate industry segment, this study investigates the impacts of institutional ownership on the firm value of hotel REITs. Hotel REITs provide unique regulatory and operational settings in which it is appropriate to investigate the potential adverse consequences of institutional investments on firm value. This study performs additional analyses using non-REIT hotel corporations (hotel C-corporations) for comparison. After testing pooled ordinary least squares, fixed and random effects, and two-stage least squares in quadratic models, the results of the random effects models are found to be valid and are thus adopted to examine the hypothesized relationship. The analysis showed a U-shaped relationship between institutional ownership and firm value (as measured using Tobin’s q) but a dominantly negative relationship in the majority of observations, whereas no significant relationship is found for hotel C-corporations.

scholarly journals Impact of gender and nationality diversity on financial performance: A study of listed banks in Morocco

2020 ◽  
Vol 18 (1) ◽  
pp. 56-68 ◽  
Author(s):  
Mhamed Chebri ◽  
Abdeaziz Bahoussa
Keyword(s):  
Financial Performance ◽  
Least Squares ◽  
Fixed Effects ◽  
Stock Exchange ◽  
Gender Diversity ◽  
Ordinary Least Squares ◽  
Empirical Literature ◽  
Depth Analysis ◽  
Fixed Effects Regression ◽  
The Impact

The purpose of this article is to explore the effect of the diversity of boards on the financial performance of banks. Based on an in-depth analysis of the theoretical and empirical literature, this study aims to examine the impact of gender diversity and the diversity of nationalities on the financial performance of Moroccan banks. To this end, the study uses a set of panel data from all Moroccan banks listed on the stock exchange for the period 2014-2018. The model was estimated by an ordinary least squares (OLS) regression equation , by the time fixed-effects regression model, and then by three-stage least squares (3SLS) regression analysis with time fixed effects to better understand the endogeneity problem variables of the model. The results of the study reveal that gender diversity has a negative and significant effect on the financial performance of listed Moroccan banks measured by both return on assets (ROA) and return on equity (ROE), while the national diversity is not significantly related to the financial performance of these banks. Likewise, the interaction between the two measures of diversity has no significant impact on financial performance.

scholarly journals Robust Standard Errors for Panel Regressions with Cross-Sectional Dependence

2007 ◽  
Vol 7 (3) ◽  
pp. 281-312 ◽  
Author(s):  
Daniel Hoechle
Keyword(s):  
Least Squares ◽  
Fixed Effects ◽  
Weighted Least Squares ◽  
Ordinary Least Squares ◽  
Standard Errors ◽  
Least Squares Regression ◽  
Finite Sample ◽  
Cross Sectional ◽  
Finite Sample Properties ◽  
Cross Sectional Dependence

I present a new Stata program, xtscc, that estimates pooled ordinary least-squares/weighted least-squares regression and fixed-effects (within) regression models with Driscoll and Kraay (Review of Economics and Statistics 80: 549–560) standard errors. By running Monte Carlo simulations, I compare the finite-sample properties of the cross-sectional dependence–consistent Driscoll–Kraay estimator with the properties of other, more commonly used covariance matrix estimators that do not account for cross-sectional dependence. The results indicate that Driscoll–Kraay standard errors are well calibrated when cross-sectional dependence is present. However, erroneously ignoring cross-sectional correlation in the estimation of panel models can lead to severely biased statistical results. I illustrate the xtscc program by considering an application from empirical finance. Thereby, I also propose a Hausman-type test for fixed effects that is robust to general forms of cross-sectional and temporal dependence.

The antecedents of corporate social and environmental responsibility discourse in Pakistan: Multiple theoretical perspectives

2019 ◽  
Author(s):  
Muhammad Farhan Basheer ◽  
Saqib Muneer ◽  
Muhammad Atif ◽  
Zubair Ahmad
Keyword(s):  
Institutional Theory ◽  
Least Squares ◽  
Agency Theory ◽  
Stakeholder Theory ◽  
Fixed Effects ◽  
Ordinary Least Squares ◽  
Environmental Responsibility ◽  
Legitimacy Theory ◽  
Discourse Practices ◽  
Corporate Social

The primary purpose of the study is to explore the antecedents of corporate social and environmental responsibilities discourse practices in Pakistan. The industry sensitivity, government shareholding, block holder ownership, print media coverage, environmental monitoring programs, and strategic posture are examined as antecedents of corporate social and environmental responsibility practices. A multidimensional theoretical perspective namely stakeholder theory (ST), institutional theory (IT), agency theory (PAT), and legitimacy theory (LT) is used to conceptualize the phenomena. All the four of perspective theories (positive accounting theory, legitimacy theory, stakeholder theory, and institutional theory) claim that there are ‘pressures’ that impact the organization. How much ‘pressures’ are recognized, managed or satisfied differs from one perspective of theory to the other. To estimate the data, this study uses three sets of panel data models, i.e., the pooled ordinary least squares model (POLS) or constant coefficients model, fixed effects (FEM or least squares dummy variable/LSDV model) and random-effects models. The final sample is comprising of 173 firms over eight years from 2011 to 2017. The firms listed in PSX are included in the sample. Overall the findings of the study have shown agreement with the proposed results. However, the study has provided more support to the institutional theory and stakeholder theory. Keywords: Corporate Social Responsibility, Stakeholders Theory, Agency Theory, Pakistan

scholarly journals Association of bisphenol A with puberty timing: a meta-analysis

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Hui Meng ◽  
Yunping Zhou ◽  
Yunxia Jiang
Keyword(s):  
Bisphenol A ◽  
Confidence Intervals ◽  
Random Effects ◽  
Strong Correlation ◽  
Fixed Effects ◽  
Meta Analysis ◽  
Random Effects Models ◽  
Study Heterogeneity ◽  
The Relationship ◽  
Prevalence Ratios

AbstractObjectivesThe results of existing studies on bisphenol A (BPA) and puberty timing did not reach a consensus. Thereby we performed this meta-analytic study to explore the association between BPA exposure in urine and puberty timing.MethodsMeta-analysis of the pooled odds ratios (OR), prevalence ratios (PR) or hazards ratios (HR) with 95% confidence intervals (CI) were calculated and estimated using fixed-effects or random-effects models based on between-study heterogeneity.ResultsA total of 10 studies involving 5621 subjects were finally included. The meta-analysis showed that BPA exposure was weakly associated with thelarche (PR: 0.96, 95% CI: 0.93–0.99), while no association was found between BPA exposure and menarche (HR: 0.99, 95% CI: 0.89–1.12; OR: 1.02, 95% CI: 0.73–1.43), and pubarche (OR: 1.00, 95% CI: 0.79–1.26; PR: 1.00, 95% CI: 0.95–1.05).ConclusionsThere was no strong correlation between BPA exposure and puberty timing. Further studies with large sample sizes are needed to verify the relationship between BPA and puberty timing.

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