This project supported [[Leveraged Buyout Innovation (Academic Paper)]] =Variable List=Jake Complete list: https://docs.google.com/a/rice.edu/spreadsheets/d/1OwcNDYXo_TefwPjUFHo5xVaBpOH4tmTnZmyBsuQRb_s/edit?usp=sharing Abridged list: LBO factors/incidence:*Log assets*R&D*Operating income*Sales*Tax*Liquidity*ROA*ROIC*Growth*Book val per share*Earnings variability*Takeover speculation/competing bid*Tobin's Q*Industry dummies (probably 2 digit NAICS) LBO characteristics*Division or full firm?*acquisition premium*breakdown of financing package:*common equity*preferred equity*senior debt*junior debt*cash =LBO Effects on Innovation Papers=
===Lerner et al 2011===
@article{lerner2011private,
Final sample consists of 6398 patents from 472 firms granted from 1984 through may 2007.
Buyouts of corporate divisions are most common, followed by private-to-private deals (investments in independent unquoted entities), secondary deals (firms that were already owned by another private equity investor), then public-to-private deals
Robustness Checks:
*Concern one: Private equity investments for which there was already an existing investor, patents may be double-counted. Employs these patents only the first time they appear then drops them. Results are little changed
*Concern two: Only measures citation count during the 3 years after the award. Using a longer window increases accuracy but decreases sample size. Repeats the analysis through the end of the second calendar year after the patent grant and after the fourth year and finds that results are quantitatively similar.
*Concert three: In divisional buyouts corporate parents may retain best patents and only give low quality patents to the PE backed division. This may lead to an apparent increase in quality in the patents applied for after the award. Addresses this issue by using the longer window for patents above and by rerunning cross tabulations and regressions with divisional buyouts excluded from the sample. Key results are little changed by this shift.
Variables:
**profitability (profit divided by sales)
**age (log firm age)
===Nadant and Perdreau 2006===
@article{le2006financial,
title={Financial profile of leveraged buy-out targets: some French evidence},
author={Le Nadant, Anne-Laure and Perdreau, Fr{\'e}d{\'e}ric},
journal={Review of Accounting and Finance},
volume={5},
number={4},
pages={370--392},
year={2006},
publisher={Emerald Group Publishing Limited},
abstract={: This paper investigates whether firms, which are taken over on the French market through Leveraged Buyouts (LBOs), possess characteristics prior to the change which differentiate them from firms which are not acquired through LBOs. Contrasting 175 LBO targets on the French market with an industry-matched comparison group, we first run univariate analysis and then multivariate analysis(logit regression). Beyond the underscoring of the LBO targets‟ financial features, we conclude that subdividing our sample according to the vendor and bidder type is beneficial. We thus notice that the so-called outperformance of LBO targets prior to the deal hides in fact different cases.}
filename={Nadant and Perdreau (2006) - Financial Profile of Leveraged Buyout Targets Some French Evidence}
}
Confirms LBO targets are less indebted and possess relatively more liquid assets than their industry counterparts. Contrary to former findings, LBO's business risk also seems to be higher than for non-LBO firms prior to the deal. Also corroborates or disagrees with some dozen other hypotheses.
Data:
List of deals collected from Zephyr database of the BvD Suite for mid 1997 to 2002 and from the french review Capital Finance for the first semester 1997 and for the year 1996. 175 deals
Variables:
Activity and performance:
*FCF/TR “Free cash flows” (1) divided by turnover
*TRGR Turnover growth
*Tax/TR Income tax divided by turnover
*ROIC Return On Invested Capital = (operating income before taxes + interest expenses) divided by “economic assets” (WCR + fixed Assets (net))
*ROE Return On Equity = Net income divided by (stockholders equity - net income)
Business Risk:
*CVTRGR Coefficient of variation of turnover growth computed on the 3 yearperiod preceding the deal
*CVROIC Coefficient of variation of ROIC computed on the 3 year-period preceding the deal
*CVROE Coefficient of variation of ROE computed on the 3 year-period preceding the deal
*CVFCF/TR Coefficient of variation of FCF/turnover computed on the 3 yearperiod preceding the deal
Composition and characteristics of assets and financial structure:
*TanA/TA Tangible assets (net) divided by total assets (net)
*LEV Total debt divided by stockholders equity
*RET/TA Retained earnings/Total assets
*NC/TA Net cash/Total assets
*WCR/TR Working Capital Requirement divided by turnover
Implications for the reasons LBOs occur Confirms LBO targets are less indebted and sources of value in LBO transactionspossess relatively more liquid assets than their industry counterparts. Describes characteristicsContrary to former findings, timelines, and stats of LBOs that return LBO's business risk also seems to be higher than for non-LBO firms prior to public ownershipthe deal. Also corroborates or disagrees with some dozen other hypotheses.
Data:
183 large leveraged buyouts between 1979 and 1986 List of deals collected from Securities Data corporation or Morgan Stanley Zephyr database of the BvD Suite for mid 1997 to 2002 and Company. Post-buyout info obtained from Lotus' Datext databases, Nexis database, Wall street journal articles the year french review Capital Finance for the LBO was completed, first semester 1997 and financial reports filed with for the SECyear 1996. 175 deals
Variables:
Activity and performance:*FCF/TR “Free cash flows” (1) divided by turnover*TRGR Turnover growth*Tax/TR Income tax divided by turnover*ROIC Return On Invested Capital = (operating income before taxes + interest expenses) divided by “economic assets” (WCR + fixed Assets (net))*ROE Return On Equity = Net income divided by (stockholders equity - net income) Business Risk:*CVTRGR Coefficient of variation of turnover growth computed on the 3 yearperiod preceding the deal*CVROIC Coefficient of variation of ROIC computed on the 3 year-period preceding the deal*number CVROE Coefficient of LBO's variation of ROE computed on the 3 year-period preceding the deal*CVFCF/TR Coefficient of variation of FCF/turnover computed on the 3 yearperiod preceding the deal Composition and characteristics of assets and financial structure:*TanA/TA Tangible assets (net) divided by total debt to total capital assets (book valuenet)*total LEV Total debt to initial deal valuedivided by stockholders equity*RET/TA Retained earnings/Total assets*NC/TA Net cash/Total assets*WCR/TR Working Capital Requirement divided by turnover*interest expense to operating incomeFA/TA Financial assets (net)/Total Assets (net)*inside equity ownership fractionTA/TAg Total Assets (net)/Total assets (gross)
===Roden & Lewellen 1995===
*PCASH: the percentage of the total that comes from the use of the target firm's existing cash and marketable securities balances
A comprehensive review of the LBO/private equity literature up to 2009. Should be useful for finding additional sources and catching up with somewhat recent research.
====Cumming et al 2007====
@article{cumming_private_2007,
In addition, should consider difference between hedge fund and private equity-financed buyouts (hedge funds less hands-on).
===Annotated=======Lehn and Poulsen 1989====
@article{lehn_free_1989,
*FOOTSTEPS (=1 if competing bid or takeover speculation in WSJ)
====Jensen 1988====
@article{jensen_takeovers:_1988,
*Warning signs: large cash flows, acquisition activity, low growth prospects
Seeks to establish commonality in the measurement of innovative performance. Its indicators include R&D inputs(expenditures), patent counts, patent citations, and new product announcements. Results of study are that any of these four indicators could be taken as a measure of innovative performance in the broad sense.
=Unsorted=
====Axelson 2013====
@article{axelson_borrow_2013,
title = {Borrow {Cheap}, {Buy} {High}? {The} {Determinants} of {Leverage} and {Pricing} in {Buyouts}},
abstract = {Private equity funds pay particular attention to capital structure when executing leveraged buyouts, creating an interesting setting for examining capital structure theories. Using a large, international sample of buyouts from 1980 to 2008, we find that buyout leverage is unrelated to the cross-sectional factors, suggested by traditional capital structure theories, that drive public firm leverage. Instead, variation in economy-wide credit conditions is the main determinant of leverage in buyouts. Higher deal leverage is associated with higher transaction prices and lower buyout fund returns, suggesting that acquirers overpay when access to credit is easier.},
language = {en},
number = {6},
urldate = {2016-06-17},
journal = {The Journal of Finance},
author = {Axelson, Ulf and Jenkinson, Tim and Strömberg, Per and Weisbach, Michael S.},
month = dec,
year = {2013},
pages = {2223--2267},
file = {Axelson et al (2013) - Determinants of Leverage and Pricing.pdf}
}
Discusses financing and pricing of LBOs. Only tangentially relevant to our project.
====Cloodt et al 2006====
file = {ScienceDirect Full Text PDF:C\:\\Users\\James Chen\\AppData\\Roaming\\Zotero\\Zotero\\Profiles\\g2eepc1b.default\\zotero\\storage\\SEU8CIRN\\Cloodt et al. - 2006 - Mergers and acquisitions Their effect on the inno.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\James Chen\\AppData\\Roaming\\Zotero\\Zotero\\Profiles\\g2eepc1b.default\\zotero\\storage\\RDJIG292\\S004873330600045X.html:text/html}
}
====Van de Gucht 1998====
@article{van_de_gucht_predicting_1998,
title = {Predicting the duration and reversal probability of leveraged buyouts},
abstract = {We examine the probability that a firm will return to public status following a leveraged buyout (LBO) transaction and for those LBOs that will eventually reverse, we examine the factors that impact the timing of the reversal. These two dimensions of the reversal decision are studied by estimating standard and split population hazard models for a sample of 343 LBO transactions. Our results indicate that not all LBO firms eventually will reverse, i.e. the net benefits of private status for some firms appear to be permanent. For those LBOs that will reverse, reversal probabilities are found to increase over the first seven or eight years following a typical LBO, then to decline thereafter.},
number = {4},
urldate = {2016-06-17},
journal = {Journal of Empirical Finance},
author = {Van de Gucht, Linda M. and Moore, William T.},
month = oct,
year = {1998},
pages = {299--315},
file = {ScienceDirect Full Text PDF:C\:\\Users\\James Chen\\AppData\\Roaming\\Zotero\\Zotero\\Profiles\\g2eepc1b.default\\zotero\\storage\\CCNSKDXX\\Van de Gucht and Moore - 1998 - Predicting the duration and reversal probability o.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\James Chen\\AppData\\Roaming\\Zotero\\Zotero\\Profiles\\g2eepc1b.default\\zotero\\storage\\2IA32N4Q\\S0927539897000236.html:text/html}