The goal is to determine the effect of a repurchase announcement in combination with an increase in leverage

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Problem definition:

The goal is to determine the effect of a repurchase announcement in combination with an increase in leverage (in contrast to only repurchase announcement) on the systematic risk. Therefore I want to run the following regression:

r_(it )-r_(ft )=α_0+α_1 D_1t+α_2 D_2t +α_3 D_3t+b_0 (r_mt-r_ft )+b_1 D_(1t ) (r_mt-r_ft )+b_2 D_2t (r_mt-r_ft )+〖b_3 D〗_1t D_(2t ) (r_mt-r_ft )+e_(t )

r_(it ) stands for the monthly return of firm i and r_(ft ) for the risk free rate

I denote the month in which a firm announced a buyback (innitial announcement) with "t^* ".

〖"l〗_0 " and 〖"l〗_1 " stands for the long term debt divided by total assets at the reporting date before respectively after the repurchase announcement

D_1t is a Dummy Variable which takes the value of 1, if t > "t^* "

D_2t is a dummy variable which takes the value of 1, if 〖"l〗_0 " < 〖"l〗_1 "   

I have different data files containing data about the repurchase announcement (monthl), the returns (monthly), and the the financial numbers such as leverage and assets (which are yearly numbers however) :

Compustat-File: Yearly financial numbers : long term debt (dltt), total assets (as)

CRSP : Monthly returns r_(it ) of companies 

Excel Repurchases : Repurchase announcement dates by month

Excel F-F data : Monthly  market risk premiums (r_mt-r_ft )

So now i need to merge the datas from the different filies in such a way that i can run the regression above

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