Panel Data modelling:applicationto Financial Performance of Non-financial Firms Listed at Nairobi Securities Exchange

Abstract

Background: Financial performance has always been estimated using cross-sectional data. However, because typical firm heterogeneity is not effectively controlled, biased results have been reported. Both specific and general group behaviors can be designed using panel data. They provide useful information, are more efficient, and have larger fluctuations than cross-sectional data. Data that is cross-sectional or time series in nature, as opposed to data that is a panel in form, is incapable of detecting and quantifying the statistical effect. With the most appropriate panel data model to predict and monitor the factors associated with the financial performance of non-financial firms as listed on the Nairobi Securities Exchange, researchers will get to find the relevant elements using panel data rather than cross-sectional data, especially in finance. It will also make it easier for investors to spot trends among the NSE’s listed companies. This study thus sought to bring into light the most appropriate panel model in analysing the different factors that affect the financial performance of non-financial firms listed on the Nairobi Securities Exchange. Objective This study’s primary objective was to determine the most appropriate panel data model to predict and monitor the factors associated with the financial performance of non-financial firms as listed on the Nairobi Securities Exchange. The findings will thus add to the existing body of knowledge and enlighten potential investors on how to evaluate performance over time. Other stakeholders who will find the findings useful include the Kenyan government and Capital Markets Authority and will use the results in formulating regulations and policies for publicly listed companies. Methods: This study adopted a panel data approach in the attempt to investigate the factors influencing the financial performance of non-financial institutions listed at the Nairobi Securities Exchange, Kenya. The study used the data obtained from the Nairobi securities exchange on the financial performance of non-listed firms. Descriptive statistics was also used to understand the nature of the data in relation to the research interest.