Testing for Periodicity Effects in a Panel Data Regression Model

Adeboye, Nurain Olawale and Agunbiade, Dawud Adebayo (2017) Testing for Periodicity Effects in a Panel Data Regression Model. Caribbean Journal of Science and Technology, 5. 040-050. ISSN 0799-3757

Text N.-O-Adeboye-et-al-Carib.j.SciTech-2017-Vol.5-040-050-2-2.pdf Download (338kB)

Abstract

This research attempts to investigate the effect of periodicity usually occasioned by the presence of serial correlation in panel data, through the estimation of pooled ordinary least square estimator (POLS) of a specified audit fees PDRM. Other analytical techniques employed through derivation are Fixed Effect Least Square dummy variable (where all coefficient vary over time), and Random Effect estimator (REM). A conditional Lagrange multiplier test was developed via a two-way error components model, to examine the presence of serial correlation in the fitted POLS model while Hausman test was used to ascertain the suitability of the LSDV Model over Random effect model and vice-versa. The conditional LM test gave a value of 35.3806 with P-value of 0.0001075 which shows that there is presence of serial correlation among the residuals of the fitted Pooled OLS model, thereby rendered the estimator inconsistent. Both LSDV and RE models captured the goodness of fit better when compared to the Pooled OLS model. However, the hausman test revealed that fixed effect model will be a preferable model since its results support the rejection of null hypothesis.

Item Type:	Article
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics
Divisions:	Faculty of Engineering, Science and Mathematics > School of Mathematics
Depositing User:	Mr Taiwo Egbeyemi
Date Deposited:	13 Jul 2020 11:19
Last Modified:	13 Jul 2020 11:19
URI:	http://eprints.federalpolyilaro.edu.ng/id/eprint/998

Actions (login required)

View Item