My sample comprises of data on accounting performance of companies that had their IPOs between 2009-22. I want to examine if companies which had more foreign investor participation in their IPOs outperform the companies which had more domestic investor participation in their IPOs. For this, my dependent variable is return on assets (roa) and my independent variable is domestic participation (domperc) and foreign participation in IPO (forperc). There are also some control variables impacting return on assets such as liquidity (cr), leverage (der) etc. I was wondering if this dataset would qualify for a panel data regression analysis or pooled OLS regression analysis? My confusion stems from the following facts:
- My sample is not fixed like most panel datasets. Some IPOs take place in 2009, some in 2010, others in 2012. For each of these IPOs, I want to examine the return on assets for 3 years after the IPO. Therefore, for companies which had their IPO in 2010, I am looking at return on assets from 2011-2013 and for companies which had their IPO in 2017, I am looking at the return on assets data from 2018-20. This gives the data its time series nature. However, not all companies return on assets can be analyzed for the same years due to difference in IPO dates.
- My sample has time invariant variables. While return on assets for each IPO differs from one year to other, extent of foreign participation in its IPO remains fixed as the IPO is not taking place every year. Same goes for extent of domestic participation in IPOs.
Here's a snapshot of my data for clarity:
Any help in this matter will be highly appreciated!
