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1,431 bytes added ,  19:30, 19 February 2012
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The Boehmer reference has a typo - the second author is Mus'''u'''meci. Also, in para 2, p.19, I think it was McKinley that "suggest[ed] a method that combines both cross-sectional and time-series information..."
 
There were a few other typos.
==Rebuilding the Paper==
*LBOs from 1975 to 2011 to ensure that they are not in the control group of privately-held non-VC backed firms)
Returns(from CRSP):
*Stock returns for 1 year (250 Calendar days) for the acquirer, ending 30 days before the announcement. This will be the estimation window.
*Market returns for the same period
Note: an observation must have 50 days of continuous trading in the estimation window, and be traded in the event window, to be included.
Accounting Data (From COMPUSTAT):
*Various accounting variables for our acquirers, drawn for the year of the acquisition, and the lagged year for total assets.
===Supplementary Data===
 
We need to rebuild the industry classification to update it to include NAICS2007 - this has largely been done in another of my papers, but that work was for firms with patents, and it is possible that some codes are still missing.
To determine the information asymmetry ranking of sectors we will need (either for 1 year or across the entire year range):
CRSP:
*idiosyncratic volatility of stock returns: requires returns and mkt returns
*relative trading volume (???this appears to be called TURNOVER, as opposed to absolute volume which is VOLUME. The measure is relative to the exchange's trading volume I think...)
*NAIC
===Raw Variables===
From SDC(for all acquisitions in the sample):
*Transaction Value
*Payment Method
*Total assets of acquirer (if available)
*Payment method (cash/stock/mix)
*PC of stock in the deal
*No. of bidders
*CUSIP (for join to COMPUSTAT)
*Target NAIC
*Intangible Assets (of target)
Notes: convert all TVs in 2011 dollars. From COMPUSTAT(for both all acquirers and for the universe of firms):*Total Assets(in year and 1 year lagged)*Market Value (SHROUT*Price at announcementstart of event window)
*Sales
*Leverage variables
*Intangible Assets
*NAIC
From VentureExpert(all VC backed firms):
*VC (binary variable)
*<math> AR^S_i = R_i - R_m </math>
*Let <math>\epsilon</math> be the residual from the mkt model regression. Then calc: <math>\sigma_{\epsilon}={( \mathbb{E}(\epsilon - \mathbb{E} \epsilon))}^{\frac{1}{2}}</math>
*RMSE of the Mkt Model: <math>RMSE={( \mathbb{E}(X- \mathbb{E} X))}^{\frac{1}{2}}</math> - this is in the ereturn list in STATAand will be used for the Patell Standard Errors.*<math> CAR_i = \sum_t AR_i</math>*Check that the Boehmer standard errors are the cross-sectional ones generated by OLS.*Check the specification of the McKinley standard errors.
SDC:
*No of past acquisitions for each acquirer: Total, VC only, Non-VC only*Target is VC/Non-VC*VCAcq is Horizontal (same 6 digit), Vertical (same 2 digit/ITBT), Conglomerate (other), and Related (not cong.)*3dg NAIC for controls*NonIT/BT/HT and 1dg-NAIC, 2dg-VCNAIC, other classification. Applied to targets and acquirers.
Dataset level calculations:
*Boom: <math>1990\le year \le 1999</math>
*Leverage: <math>\frac{Op.\;Income}{Net\;Income}
*IT/BT/HT and 1dg-NAIC, 2dg-NAIC, other classification. Applied to targets and acquirers.
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