WWW.DISSERTATION.XLIBX.INFO
FREE ELECTRONIC LIBRARY - Dissertations, online materials
 
<< HOME
CONTACTS



Pages:     | 1 |   ...   | 9 | 10 || 12 |

«John R. Graham, Co-Supervisor David T. Robinson, Co-Supervisor Manuel Adelino Alon P. Brav Manju Puri Aaron K. Chatterji Dissertation submitted in ...»

-- [ Page 11 ] --

in columns (3) and (4), the sample is restricted to firms of which the cash flow over asset ratio is above industry median. IpCV Cqi,t is equal to one if firm i launches a Corporate Venture Capital unit in year t, and zero otherwise. ∆Innovationi,t´1 is the innovation change over the past three years (i.e., the innovation change from t ´ 4 to t ´ 1). Innovation is measured using innovation quantity (the natural logarithm of the number of new patents in each firm-year plus one), shown in columns (1) and (3) and innovation quality (the natural logarithm of average citations per new patent in each firm-year plus one), shown in columns (2) and (4). The model is estimated using Two-stage Least Squares, and ∆Innovation is instrumented using knowledge Obsolescence. Firm-level controls Xi,t´1 include ROA, size (logarithm of total assets), leverage, and R&D ratio (R&D expenditures scaled by total assets). Industry-by-year dummies are included in the model to absorb industry-specific time trends in CVC activities and innovation. T-statistics are shown in parentheses and standard errors are clustered by firm. *, **, *** denote statistical significance at the 10%, 5%, and 1% levels, respectively.

–  –  –

95 Table E.4: This table documents the relation between innovation deterioration and the initiation of Corporate Venture Capital. The analysis is performed using the following specification: IpCV Cqi,t “ αindustryˆt ` β ˆ ∆Innovationi,t´1 ` γ ˆ Xi,t´1 ` εi,t, The panel sample is described in Table III in the paper. IpCV Cqi,t is equal to one if firm i launches a Corporate Venture Capital unit in year t, and zero otherwise.

∆Innovationi,t´1 is the innovation change over the past four years (that is, the innovation change from t ´ 5 to t ´ 1) in columns (1) and (2), and over the past two years (that is, the innovation change from t ´ 3 to t ´ 1) in columns (3) and (4). Innovation is measured using innovation quantity (the natural logarithm of the number of new patents in each firm-year plus one), shown in columns (1) and (3) and innovation quality (the natural logarithm of average citations per new patent in each firm-year plus one), shown in columns (2) and (4). The model is estimated using Twostage Least Squares, and ∆Innovation is instrumented using knowledge Obsolescence during the same period as in ∆Innovation. Firm-level controls Xi,t´1 include ROA, size (logarithm of total assets), leverage, and R&D ratio (R&D expenditures scaled by total assets). Industry-by-year dummies are included in the model to absorb industry-specific time trends in CVC activities and innovation. T-statistics are shown in parentheses and standard errors are clustered by firm. *, **, *** denote statistical significance at the 10%, 5%, and 1% levels, respectively.

–  –  –

96 Table E.5: This table documents the relation between innovation deterioration and the initiation of Corporate Venture Capital under different sampling criterion. The analysis is performed using the following specification: IpCV Cqi,t “ αindustryˆt ` β ˆ ∆Innovationi,t´1 ` γ ˆ Xi,t´1 ` εi,t, The original panel sample is described in Table III in the paper.

IpCV Cqi,t is equal to one if firm i launches a Corporate Venture Capital unit in year t, and zero otherwise. ∆Innovationi,t´1 is the innovation change over the past three years (i.e., the innovation change from t ´ 4 to t ´ 1). Innovation is measured using innovation quantity (the natural logarithm of the number of new patents in each firm-year plus one), shown in columns (1), (3), (5), and (7), and innovation quality (the natural logarithm of average citations per new patent in each firm-year plus one), shown in columns (2), (4), (6), and (8). The model is estimated using Two-stage Least Squares, and ∆Innovation is instrumented using knowledge Obsolescence during the same period as in ∆Innovation. In columns (1) and (2), firms with total assets above industry median are dropped. In columns (3) and (4), firms with total assets below industry median are dropped. In columns (5) and (6), firms headquartered in California are dropped. In columns (7) and (8), firms in the Business Services industry (categorized using Fama-French 48 industry categorization) are dropped.

Firm-level controls Xi,t´1 include ROA, size (logarithm of total assets), leverage, and R&D ratio (R&D expenditures scaled by total assets). The model is estimated using Ordinary Least Squares (OLS) and Logit, respectively. Industry-by-year dummies are included in the model to absorb industry-specific time trends in CVC activities and innovation. T-statistics are shown in parentheses and standard errors are clustered by firm. *, **, *** denote statistical significance at the 10%,

–  –  –

98 Observations 11,413 11,413 14,563 14,563 21,338 21,338 16,616 16,616 Pseudo R-squared 0.506 0.476 0.389 0.375 0.380 0.380 0.350 0.339 Yes Yes Yes Yes Yes Yes Yes Yes Industry ˆ Year FE Table E.6: This table documents the relation between product market performance changes and the initiation of Corporate Venture Capital. The analysis is performed using the following specification: IpCV Cqi,t “ αindustryˆt ` β ˆ ∆P erf ormancei,t´1 ` γ ˆ Xi,t´1 ` εi,t,The panel sample is described in Table III in the paper. IpCV Cqi,t is equal to one if firm i launches a Corporate Venture Capital unit in year t, and zero otherwise. ∆P erf ormancei,t´1 is the product market performance change over the past three years (i.e., the performance change from t ´ 4 to t ´ 1). Product market performance is measured using Return-on-Assets (ROA), shown in column (1) and sales growth, shown in column (2). Firm-level controls Xi,t´1 include ROA, size (logarithm of total assets), leverage, and R&D ratio (R&D expenditures scaled by total assets). The model is estimated using Ordinary Least Squares (OLS). Industryby-year dummies are included in the model to absorb industry-specific time trends in CVC activities and innovation. T-statistics are shown in parentheses and standard errors are clustered by firm. *, **, *** denote statistical significance at the 10%, 5%, and 1% levels, respectively.





–  –  –

99 Table E.7: This table studies levels and characteristic of innovation around the start of CVC investment. The analysis is based on the following standard difference-in-differences (DiD) framework: yi,t “ αF E ` β ¨ IpCV CP arentqi ˆ IpP ostqi,t ` β 1 ¨ IpCV CP arentqi ` β 2 ¨ IpP ostqi,t ` γ ˆ Xi,t ` εi,t. To construct a proper control group for CVC parent firms, I employ the propensity score matching method and match each CVC parent firm that launches CVC in year t with two non-CVC firms from the same year and 2-digit SIC industry, that has the closest propensity score estimated using size (logarithm of total assets), market-to-book ratio, ∆Innovation, and patent stock. The CVC launching year for a CVC parent firm is also the “pseudo-CVC” year for its matched firms, and I include firm data beginning five years before the (pseudo-) event year through five years afterward. The dependent variables yi,t are innovation quantity (columns (1) and (2)), quality (columns (3) and (4)), new cite ratio (columns (5) and (6)) and explorativeness (columns (7) and (8)). IpCV CP arentqi is a dummy variable indicating whether firm i is a CVC parent or a matched control firm. IpP ostqi,t indicates whether the firm-year observation is within the rt ` 1, t ` 5s window after (pseudo-) CVC initiations. The model includes industry-by-year fixed effects αindustryˆt to absorb time-variant industrial technological trends. Firm-level control variables include ROA, size (logarithm of total assets), leverage, and R&D ratio (R&D expenditures scaled by total assets). T-statistics are shown in parentheses and standard errors are clustered by firm. *, **, *** denote statistical significance at the 10%, 5%, and 1% levels, respectively.

–  –  –

Acemoglu, Daron, Ufuk Akcigit, Nicholas Bloom, and William R. Kerr, 2013, Innovation, reallocation and growth.

Acemoglu, Daron, and Dan Cao, 2015, Innovation by entrants and incumbents, Journal of Economic Theory 157, 255–294.

Acs, Zoltan J., and David B. Audretsch, 1988, Innovation in large and small firms:

an empirical analysis, American Economic Review 678–690.

Adelino, Manuel, Song Ma, and David T. Robinson, 2016, Firm age, investment opportunities, and job creation, Journal of Finance Forthcoming.

Aghion, Philippe, Ufuk Akcigit, and Peter Howitt, 2014, What do we learn from schumpeterian growth theory?, in Handbook of Economic Growth, volume 2, 515– 563 (Elsevier).

Aghion, Philippe, and Jean Tirole, 1994, The management of innovation, Quarterly Journal of Economics 109, 1185–1209.

Akcigit, Ufuk, Murat Alp Celik, and Jeremy Greenwood, 2013, Buy, keep or sell:

Economic growth and the market for ideas.

Alcacer, Juan, and Michelle Gittelman, 2006, Patent citations as a measure of knowledge flows: The influence of examiner citations, Review of Economics and Statistics 88, 774–779.

Allen, Jeffrey W, and Gordon M Phillips, 2000, Corporate equity ownership, strategic alliances, and product market relationships, Journal of Finance 55, 2791–2815.

Almeida, Heitor, Po-Hsuan Hsu, and Dongmei Li, 2013, Less is more: Financial constraints and innovative efficiency.

Arrow, Kenneth, 1962, Economic welfare and the allocation of resources for invention, in The rate and direction of inventive activity: Economic and social factors, 609–626 (Princeton University Press: Princeton, NJ).

102

Autor, David H, David Dorn, and Gordon H. Hanson, 2013, The china syndrome:

Local labor market effects of import competition in the united states, American Economic Review 103, 2121–2168.

Basu, Sandip, Corey Phelps, and Suresh Kotha, 2011, Towards understanding who makes corporate venture capital investments and why, Journal of Business Venturing 26, 153–171.

Bena, Jan, and Kai Li, 2014, Corporate innovations and mergers and acquisitions, Journal of Finance 69, 1923–1960.

Bennedsen, Morten, Francisco P´rez-Gonz´lez, and Daniel Wolfenzon, 2010, The e a governance of family firms, Corporate governance: A synthesis of theory, research, and practice 371–390.

Benson, David, and Rosemarie H. Ziedonis, 2010, Corporate venture capital and the returns to acquiring portfolio companies, Journal of Financial Economics 98, 478–499.

Bernstein, Shai, 2015, Does going public affect innovation?, Journal of Finance 70, 1365–1403.

Bernstein, Shai, Xavier Giroud, and Richard R. Townsend, 2014, The impact of venture capital monitoring: Evidence from a natural experiment, Rock Center for Corporate Governance at Stanford University Working Paper.

Bloom, Nicholas, 2009, The impact of uncertainty shocks, Econometrica 77, 623–685.

Bloom, Nicholas, Max Floetotto, Nir Jaimovich, Itay Saporta-Eksten, and Stephen J Terry, 2012, Really uncertain business cycles, Technical report, National Bureau of Economic Research, Inc.

Bloom, Nicholas, Mark Schankerman, and John Van Reenen, 2013, Identifying technology spillovers and product market rivalry, Econometrica 81, 1347–1393.

Bond, Philip, Alex Edmans, and Itay Goldstein, 2012, The real effects of financial markets, Annual Review of Financial Economics 4, 339–60.

Bottazzi, Laura, Marco Da Rin, and Thomas Hellmann, 2004, The changing face of the european venture capital industry: Facts and analysis, Journal of Private Equity 7, 26–53.

Brav, Alon, Wei Jiang, Song Ma, and Xuan Tian, 2016, How does hedge fund activism reshape corporate innovation, Available at SSRN 2409404.

Brown, James R, Steven M Fazzari, and Bruce C Petersen, 2009, Financing innovation and growth: Cash flow, external equity, and the 1990s r&d boom, Journal of Finance 64, 151–185.

–  –  –

Chemmanur, Thomas J., and Paolo Fulghieri, 2014, Entrepreneurial finance and innovation: An introduction and agenda for future research, Review of Financial Studies 27, 1–19.

Chemmanur, Thomas J, Elena Loutskina, and Xuan Tian, 2014, Corporate venture capital, value creation, and innovation, Review of Financial Studies 27, 2434–2473.

Chen, Qi, Itay Goldstein, and Wei Jiang, 2007, Price informativeness and investment sensitivity to stock price, Review of Financial Studies 20, 619–650.

Chesbrough, Henry W, 2002, Making sense of corporate venture capital, Harvard Business Review 80, 90–99.

Cohen, Wesley M., and Daniel A. Levinthal, 1990, Absorptive capacity: a new perspective on learning and innovation, Administrative science quarterly 128–152.

Cust´dio, Cl´udia, Miguel A Ferreira, and Pedro Matos, 2013, Do general managerial o a skills spur innovation?.

Da Rin, Marco, Thomas F Hellmann, and Manju Puri, 2011, A survey of venture capital research.

Dimitrova, Lora, 2013, Strategic acquisitions by corporate venture capital investors.

Dosi, Giovanni, 1988, Sources, procedures, and microeconomic effects of innovation, Journal of Economic Literature 1120–1171.

Dow, James, and Gary Gorton, 1997, Stock market efficiency and economic efficiency:

Is there a connection?, Journal of Finance 52, 1087–1129.

Dushnitsky, Gary, 2006, Corporate venture capital: past evidence and future directions (Oxford University Press: Oxford, UK).

Dushnitsky, Gary, and Michael J. Lenox, 2005a, When do firms undertake r&d by investing in new ventures?, Strategic Management Journal 26, 947–965.

Dushnitsky, Gary, and Michael J. Lenox, 2005b, When do incumbents learn from entrepreneurial ventures?: Corporate venture capital and investing firm innovation rates, Research Policy 34, 615–639.

Dushnitsky, Gary, and Michael J. Lenox, 2006, When does corporate venture capital investment create firm value?, Journal of Business Venturing 21, 753–772.

104 Fee, C Edward, Charles J. Hadlock, and Shawn Thomas, 2006, Corporate equity ownership and the governance of product market relationships, Journal of Finance 61, 1217–1251.

Fleming, Lee, and Olav Sorenson, 2004, Science as a map in technological search, Strategic Management Journal 25, 909–928.

Frydman, Carola, and Dimitris Papanikolaou, 2015, In search of ideas: Technological innovation and executive pay inequality.



Pages:     | 1 |   ...   | 9 | 10 || 12 |


Similar works:

«Faculty of Economics and Business Administration Second generation biofuel production in the Netherlands Research Memorandum 2012-4 Vasco Diogo Eric Koomen Floor van der Hilst SECOND GENERATION BIOFUEL PRODUCTION IN THE NETHERLANDS a spatially-explicit exploration of the economic viability of a perennial biofuel crop Vasco Diogo, Eric Koomen Department of Spatial Economics/SPINlab, VU University Amsterdam, The Netherlands. Email: v.pintonunesnogueiradiogo@vu.nl, e.koomen@vu.nl Floor van der...»

«American Economic Journal: Applied Economics 2 (July 2010): 46–59 http://www.aeaweb.org/articles.php?doi=10.1257/app.2.3.46 Information from Markets Near and Far: Mobile Phones and Agricultural Markets in Niger† By Jenny C. Aker* Price dispersion across markets is common in developing countries. Using novel market and trader-level data, this paper provides estimates of the impact of mobile phones on price dispersion across grain markets in Niger. The introduction of mobile phone service...»

«Banking Integration and House Price Comovement Augustin Landier David Sraer Toulouse School of Economics UC Berkeley and NBER and CEPR David Thesmar HEC and CEPR Abstract The correlation across US states in house price growth increased steadily between 1976 and 2000. This paper shows that the contemporaneous geographic integration of the US banking market, via the emergence of large banks, was a primary driver of this phenomenon. To this end, we first theoretically derive an appropriate...»

«WORKING PAPER 2012-04-ccr April, 2012 WHEN THE STATE MIRRORS THE FAMILY: THE DESIGN OF PENSION SYSTEMS Vincenzo Galasso Università della Svizzera Italiana, Dondena, IGIER and CEPR, Switzerland Paola Profeta Econpubblica and Dondena, Università Bocconi, Italy CONDORCET CENTER FOR POLITICAL ECONOMY UNIVERSITY OF RENNES 1 – CREM – www.condorcet-center.fr Faculty of Economics – University of Rennes 1 – 7 place Hoche, CS 86514, 35065 Rennes Cedex, France WORKING PAPER 2012-03-ccr April,...»

«UNIVERSITY OF MICHIGAN JOHN M. OLIN CENTER FOR LAW & ECONOMICS THE NONDISCHARGEABILITY OF STUDENT LOANS IN PERSONAL BANKRUPTCY PROCEEDINGS: THE SEARCH FOR A THEORY Published in 44 Canadian Bus. Law J., 2006, 245 JOHN A.E. POTTOW PAPER #07-005 SSRN Abstract AVAILABLE AT HTTP://SSRN.COM/ABSTRACT=967379 THIS PAPER CAN BE DOWNLOADED WITHOUT CHARGE AT: MICHIGAN JOHN M. OLIN WEBSITE HTTP://WWW.LAW.UMICH.EDU/CENTERSANDPROGRAMS/OLIN/PAPERS.HTM THE NONDISCHARGEABILITY OF STUDENT LOANS IN PERSONAL...»

«DOWNTOWN CONCEPT PLAN STOUGHTON, MASSACHUSETTS STOUGHTON REDEVELOPMENT AUTHORITY Candeub, Fleissig, Adley and Associates DOWNTOWN CONCEPT PLAN STOUGHTON, MASSACHUSETTS June, 1965 The preparation of this report was financed in part through a Federal advance from the Urban Renewal Administration of the Housing and Home Finance Agency under the provisions of Title I of the Housing Act of 1949, as amended. Consultants: Candeub, Fleissig, Adley and Associates Boston, Massachusetts STOUGHTON...»

«Advocates for Ohio’s Future 510 East Mound Street, Suite 200 Columbus, OH 43215 (614) 602-2463 | (614) 602-2464 | Fax (614) 228-5150 www.advocatesforohio.org Testimony on HB 153, The Biennial Budget Before the House Finance Committee April 14, 2011 By Scott Britton, Coordinator Chairman Amstutz, Ranking Member Sykes, and Members of the Committee: My name is Scott Britton, and I am coordinator of Advocates for Ohio’s Future, a statewide coalition of health, human service, and early care &...»

«OF TAXES AND DUTIES: TAXING THE SYSTEM WITH PUBLIC EMPLOYEES' TAX OBLIGATIONS by Kenneth H. Ryesky* I. INTRODUCTION Clearly, the tax laws in America are growing increasingly complex.' The tax system has steadily become more intricate despite Presidential acknowledgment more than a decade ago that [t]he system is too complicated. 2 Yet, the tax laws * B.B.A., Temple University, 1977; M.B.A., La Salle University, 1982; J.D., Temple University, 1986; M.L.S. degree candidate, Queens College CUNY;...»

«Big Data, Model Complexity, and Interpretability: Machine Learning and Finance Sanmay Das Washington University in St. Louis MFM Summer School 2016 Sanmay Das (WUSTL) Machine Learning and Finance MFM Summer School 2016 1 / 54 Statistics/Econometrics “vs.” Machine Learning Differences in communities, culture, practices BUT: communities are learning a lot from each other and coming closer Ideas come from both sides (e.g. bootstrap came from statistics to ML) (Supervised) ML has more of a...»

«Minority Governments and Party Politics: The Political and Institutional Background to the “Danish Miracle” Christoffer Green-Pedersen 01/1 Max-Planck-Institut für Gesellschaftsforschung Paulstrasse 3 50676 Köln Germany Telephone 0221/2767 -0 Fax 0221/2767-555 MPIfG Discussion Paper 01/1 E-Mail info@mpi-fg-koeln.mpg.de ISSN 0944–2073 Home Page http://www.mpi-fg-koeln.mpg.de March 2001 Green-Pedersen: Political and Institutional Background to the “Danish Miracle” 2 Abstract The...»

«WP/12/251 Workers’ Remittances: An Overlooked Channel of International Business Cycle Transmission? Adolfo Barajas, Ralph Chami, Christian Ebeke, and Sampawende J. A. Tapsoba © 2012 International Monetary Fund WP/12/251 IMF Working Paper Middle East and Central Asia Department Workers’ Remittances: An Overlooked Channel of International Business Cycle Transmission? Prepared by Adolfo Barajas, Ralph Chami, Christian Ebeke, and Sampawende J.A. Tapsoba1 Authorized for distribution by Ralph...»

«Financial Transactions and Fraud Schemes Asset Misappropriation: Cash Receipts © 2016 Association of Certified Fraud Examiners, Inc. Fraud Tree 2 of 27 © 2016 Association of Certified Fraud Examiners, Inc. Two Types of Schemes  Skimming  Larceny  Difference depends completely on when the cash is stolen 3 of 27 © 2016 Association of Certified Fraud Examiners, Inc. Skimming  Removal of cash from a victim entity before it is recorded in the victim organization’s accounts  Known...»





 
<<  HOME   |    CONTACTS
2016 www.dissertation.xlibx.info - Dissertations, online materials

Materials of this site are available for review, all rights belong to their respective owners.
If you do not agree with the fact that your material is placed on this site, please, email us, we will within 1-2 business days delete him.