DYNAMIC PANEL DATA GENERALIZED METHOD OF MOMENT ARELLANO-BOND APPROACH IN ECONOMETRIC MODEL RETURN ON ASSETS OF PHARMACEUTICAL COMPANIES

Abstract

The impact of the Covid-19 pandemic has resulted in a significant decline in the pharmaceutical sector's stock price, so investors are hesitant to invest in the pharmaceutical sub-sector. This study aims to apply dynamic panel data regression analysis with the Arellano-Bond Generalized Method of Moment (GMM) approach to model the profitability of pharmaceutical sub-sector companies on the Indonesia stock exchange. Therefore, investors need to know the profitability of the pharmaceutical sub-sector to make an investment decision. This research will produce a profitability model for pharmaceutical sub-sector companies. The data in this study was obtained from observations of stock price movements of pharmaceutical sub-sector companies listed on the Indonesia Stock Exchange (IDX) in 2013-2022. From the resulting model, it is hoped that it can provide an overview for investors to take action to invest in shares of the pharmaceutical sub-sector. The study results show that the model meets the consistency of parameters based on the results of the Arellano-Bond test and valid instruments based on the results of the Sargan test. The t-test results show that the previous period's ROA has a positive and significant influence on ROA, CR has a negative and significant influence on ROA, DR has no significant effect on ROA, and inflation has a positive and significant effect on ROA. So, the variables that significantly affect ROA are the ROA of the previous period, CR, and inflation. Based on the study's results, investors must choose companies with a higher ROA value compared to the ROA of the previous year. And choose a company that has a low CR value.