Minimum Variance Quadratic Unbiased Estimation Approach in Panel Data Regression Analysis with Two-Way Error Component Estimation Using Biggers Method

Andi Atirah Arumtiwi; Raupong Raupong; Siswanto Siswanto

doi:10.20956/j.v21i2.37325

Authors

Andi Atirah Arumtiwi Department of Statistics, Hasanuddin University, Indonesia
Raupong Raupong Department of Statistics, Hasanuddin University, Indonesia
Siswanto Siswanto Department of Statistics, Hasanuddin University, Indonesia

DOI:

https://doi.org/10.20956/j.v21i2.37325

Keywords:

Incomplete Panel Data, Two-way Error Component, MIVQUE, ML, Stock Return

Abstract

Panel data that have missing observations can be known as incomplete panel data. The model used is a two-way error component. The missing data estimation used is the Biggers method. This study aims to model the incomplete panel data regression of two-way error components on Manufacturing Company Stock Return data. The method used for estimating the error variance component is Minimum Variance Quadratic Unbiased Estimation (MIVQUE) with parameter estimation using Maximum Likelihood (ML). The method was applied to IDX data for 10 companies from 2014-2021. The results obtained using the MIVQUE method are σ ̂_v^2= 0.1142, σ ̂_μ^2=-0.0107, and σ ̂_λ^2=0.0068, for the ML method produces β ̂_0=0.0304719 〖 β ̂〗_1= -0.021107, and β ̂_2=0.0087936. Based on these methods, if there is an increase in the Debt to Equity Ratio, there is a decrease in the value of stock returns, and vice versa for Net Profit Margin.

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