My second question is how do i increase my R square(its 2%) although i have added all the variables that was mentioned in previous literature and why they have a large R2(their R2 is 20%) and i don't? is it because of the non linearity of my data. also for the xtreg, fe i will include the dummy condition along with all the other variables however you have mentioned ' provided you do not also include time indicators in the model' i don't completely get what you mean by that, should i remove the economic variables? my question is if i used xtreg, be i will include only the dummy quotation along with all other variables financial and economics or will i have to remove the economic variables as they vary over time not across firms. the rest of the variables are simply financial ratios ( liquidity, profitability and leverage ratios) that vary across firms and over time and i have the macro economic variables ( GDP, interest rate and inflation rate ) that vary over time not across firms as my study is conducted only on a single country (UK). Well i will try to make it more clear, my dependent variable is simply cumulative average abnormal return ( for a 2 days event window day 0 and day 1), as for my independent variables i have the 2 dummy variables which are the main variables of interest one vary within each firm but constant over time and the other dummy variable vary over time but nor related to the firms. secondly, sorry if my explanation was not that clear. so am i using the right model or not?ДЇirst of all, Thank you Clyde for your quick reply. another problem is my adjusted R square is very small although i added all the explanatory variables that was used in previous literature so i think the reason is because of the nonlinearity am i right? i have also tried to use nonliner models but i have found out that its more applicable on small sample which is not my case.

the second problem is that when i checked for the linearity of the relationship between the dependent and the independent variables they all went to be nonlinear so if i will opt for transforming my data should i transform both the dependent and independent, and what kind of transformation and on what basis should i choose it? (keeping in mind that my dependent variables contain negative values). my two main variables of interest are 2 dummy variables the first one is dummy market quotation (vary across firms ) and dummy market condition (vary across time ) so the first question is do i have to run two regression models one for the dummy market quotation using xtregress and the between effect and the other is xtregress using the fixed effect to account for the dummy market conditions while keeping all other independent variables. i am running panel data regression i have 29000 observations, 2 dependent variables and around 15 independent variables. I am working on my masterthesis about the effect of dividends announcements across various market quotations and various market conditions.

Deltagraph nonlinear regression