JAR paper by Chicago author has issues... shocker! This isn't surprising or new.
Chicago alums tend to get members of their dissertation committee and dissertation chairs as editors, and other Chicago affiliates as reviewers.
Shocker... U.Chicago is the institution with the most papers in JAR year after year.
Again you are confusing tax rules for consolidation with book rules. If the paper is about whether private firms produce audited GAAP financials, who cares whether the partnership subs file separate returns and aren't "consolidated" in the corporate 1120.
The paper claims to be about whether private firms produce GAAP financials. But, as explained thoroughly here and as is otherwise obvious, the data DOES NOT capture private firms. It captures tax returns which are often subsidiaries. If a parent produces audited GAAP FS, does the sub? Probably not. Do subs even produce FS? In rare cases that the sub does, are they meaningful? Of course, when a parent is audited, the sub is too, but it does not produce is own audited FS
So the study vastly undercounts audited GAAP FS. Many accounting numbers on the returns are also entirely meaningless because they aren't consolidated. Correlate meaningless # with meaningless # = JAR Pub for PL and MM. What do we learn? How is our field served by this mi$rep/re$entation?
Oh yeah, the econ. sig is VASTLY overstated because the sample is full of the parent AND their subs. Again, how is this hard to understand?
Perhaps the word "firm" is confusing. Someone else here was confused by the term "illegal"
But seems a new low to need to use "private data" that doesn't exist
JAR paper by Chicago author has issues... shocker! This isn't surprising or new.
Chicago alums tend to get members of their dissertation committee and dissertation chairs as editors, and other Chicago affiliates as reviewers.
Shocker... U.Chicago is the institution with the most papers in JAR year after year.
I am not in accounting, but if any of these allegations are true, why not write a thoughtful response paper demonstrating the institutional details you claim are incorrect? Show how the results are wrong. It would be a much greater service to the profession than arguing (or slandering) here.
I hope AY does this. He's already blacklisted so has no cost to doing so. Amazing how in this profession fra/udsters are protected but whistleblowers arent
all the l\sers keep posting under similar titles when the rejection grudge against editors or the journal kicks in now and then.
go back to your desk and once in your life do something publishable. stop wasting your time like this.
Would you kindly direct us to the other post? (not the call and sharp as that's not dealing made up data)
If bogus sheet like this is what counts a publishable research in "top" journals, what value is there in publishing?
The issue is pretty straightforward, despite the trolls here. PL MM study an RQ that requires consolidated GAAP parent level data. They obtain IRS data, which contains UNCONSOLIDATED tax data.
To "solve" this problem, they claim to have consolidated parent level data from the IRS. They do not have this data, and it does not exist. 09f9 is correct. This is not poor design, this is misconduct.
The issues raised here assume that some data exists - there is no guarantee that is even true.
"PL MM study an RQ that requires consolidated GAAP parent level data. They obtain IRS data, which contains UNCONSOLIDATED tax data."
Look at the top of a Schedule M-3 and tell me again why you can't isolate consolidated corporate parents. I would say the dependent variable is pretty well defined for corporations.
For the other entities reporting on either an 1120S or 1065, it has already been acknowledged that there are questions on the tax return that indicate whether you are dealing with a lower tier sub in a bigger structure. Is it impossible that the IRS and/or PL can approximately identify ultimate parents for flowthroughs? How many identification errors do you really think there are and in what category of entities?
There is no perfect dataset for examining this question, but IRS data is arguably as close as you can get to the right data for the RQ. They do extensive comparisons to other private company datasets such as Sageworks.
This whole criticism is a quibble about identification and research design, quit calling stuff fraud that clearly is not.
The top of the M-3 asks about TAX consolidated returns. Perhaps you should look at the M-3 (perhaps even the instructions!)
As is well known (even to trolls here) GAAP and tax consolidations are completely different. Not even close.
There are ways to ID a structure from a tax return, yet PL MM completely ignore these (as already mentioned). They do not even acknowledge this issue. As noted earlier, PL MM use MORE than all partnerships, showing that they make no adjustment for structure. (Under AAA guidelines, covering up limitations is search misconduct). If it was a non issue, why would they l|e and say they have consolidated parents when they don't? Why not explain that they have unconsolidated tax return data and let readers/reviewers decide on the validity?
PL and MM state that they use IRS data because it is different than sageworks. Then they show in a "robustness test" that they are the same. Can't be both! Also, both data sets are "proprietary" so no way to know if valid at all. This is complete fr/aud.
Based on an earlier comment, there are about 5 partnership subs per 1 corporate parent. 5 to 1 is major misclassification.
"PL MM study an RQ that requires consolidated GAAP parent level data. They obtain IRS data, which contains UNCONSOLIDATED tax data."
Look at the top of a Schedule M-3 and tell me again why you can't isolate consolidated corporate parents. I would say the dependent variable is pretty well defined for corporations.
For the other entities reporting on either an 1120S or 1065, it has already been acknowledged that there are questions on the tax return that indicate whether you are dealing with a lower tier sub in a bigger structure. Is it impossible that the IRS and/or PL can approximately identify ultimate parents for flowthroughs? How many identification errors do you really think there are and in what category of entities?
There is no perfect dataset for examining this question, but IRS data is arguably as close as you can get to the right data for the RQ. They do extensive comparisons to other private company datasets such as Sageworks.
This whole criticism is a quibble about identification and research design, quit calling stuff fraud that clearly is not.