A loop of cross-sectional regressions for calculating abnormal accruals in Stata. Posted on November 7, 2015 by Kai Chen. I write a loop of cross-sectional regressions for calculating abnormal accruals. This program can be easily modified and replaced with Jones, modified Jones, or Dechow and Dichev model.
Mar 16, 2015 · Tip 1: Steps for preparing data for Stata (panel format): 1. In Excel, insert letter 'y' in front of each year, for example: 2. Import the data into Stata, 3. Create unique IDs for Accounts and Companies: 4. Transpose data into long format:
To install, type in Stata literally the following: findit grouplabs Stata will respond with a link to the program. Click it and in the popup viewer window with program description click "install". Syntax. The main syntax is trivial, basically mirroring the egen statement that was used to create the group variable: grouplabs varlist, groupvar ...
sort layer grp x y1 y2 cap drop ymin ymax *cap drop tag bysort x order: egen ymin = min(y1) bysort x order: egen ymax = max(y2) egen wedge = group(x order) and plot it:
What egen, max() does is exclude missings from the calculation, and, only if all the values in each group are missing, will the maximum be returned as missing. Although Stata has a general rule that numeric missing is larger than any other numeric value, it assumes when calculating maxima that you really want the largest nonmissing value.
Stata has two built-in variables called _n and _N. _n is Stata notation for the current observation number. _n is 1 in the first observation, 2 in the second, 3 in the third, and so on. _N is Stata notation for the total number of observations. Let's see how _n and _N work. input score group 72 1 84 2 76 1 89 3 82 2 90 1 85 1 end generate id ...
The DIY method extends easily to by variables: sort byvar x by byvar: gen ptile = int(100*(_n-1)/_N)+1 taking advantage of _n and _N referring to position in the current by group. -egen- helps us generalize to by variables and weights at the same time: sort byvar x by byvar: egen sumwgt = sum(wgt) by byvar: gen rsum = sum(wgt) by byvar: gen ...
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