For some time I have stayed away from venture capital data.  It is very popular territory for academics to research in as it is data rich (or at least data are readily purchasable, if very expensive); often includes actual company names that can be used in research through matching, surveys, or other web scraping; and VCs are just sexy (at least within the range of topics studied within entrepreneurship).  Personally, I have chosen not to focus on VC data since it seemed just about everyone else was.  My comparative advantage was to study the more boring topics like financing patterns in non-VC companies, angel capital, and just about any other topic.  But I've avoided educating myself for too long, so please help me. 

But VC data, although arguably the most developed in the entrepreneurship space, is so messy and debatable.  Take for example this posting by Brad Feld which points out many errors he is aware of in the published PWC Moneytree data.  Now, Brad wasn't really concerned here with the accuracy of the underlying data but was pointing out that the data is really difficult to use in looking at start-up funding.  Most VCs actually fund companies which the academic community would consider beyond start-up phase.

So, I don't have a lot more to say right now on this, but I wanted to throw this out there in the hopes of getting some comments on the different VC databases, as well as their perceived strengths and weaknesses.  I know the basics on the data here but I am really hoping that readers will provide some education.  Many thanks in advance. 

The two surveys have different definitions and different methods, but general trends can be seen in both surveys.

• Of all the industries that contain green jobs, the construction industry has added the most green jobs out of any other. These construction jobs are those that are either geared to energy efficiency or are related to renewable energy.
• Green jobs have a higher than average wage, and many green jobs don’t require a bachelor’s degree. However, the highest paying green jobs do require higher education.
• Individual occupations are becoming green, but the often-talked-about green industry is generally non-existent. Most green jobs today are old jobs with a green focus. Few are brand-new, and just about all of them retain the same title as before (exceptions are those like wind turbine technician). Both researchers refer to this as the “greening” of the economy.

There was a lot of advice given on how to run a survey and how the researchers might have run their own surveys differently. Major points break down as follows:

• The Bureau of Labor statistics has not issued a standard definition of a “green job” yet, but there are already a lot of guidelines out there (both from surveys like these and other sources). If a researcher were to develop his/her own definition, a good jumping off point would be to examine a paper put together by the Workforce Information Council which can be found here.
• As stated above, there is no specific green area of the economy; all parts of the economy are experiencing “greening” to some extent. Therefore, in future studies, individual jobs must be the unit of analysis. Aggregating to the firm level (or even across occupations with the same title) will tend to bias results.
• Response rates of surveys mailed to firms (who then tally green occupations) are typically low. Both surveys had response rates of about half. Therefore, when conducting future surveys, substantial follow-up efforts are necessary to try to minimize non-response bias.
• Other ways to increase the response rate are to:

I am not at the American Economic Association (AEA) meeting this year as I recently became a father and am not going to be traveling for a while but that doesn't mean there aren't some really exciting sessions/papers being presented related to new advances in measuring innovation and entrepreneurship.  Ken Jarboe at the Athena Alliance did a great post on some of the papers focusing on intangible assets so I'll simply defer to Ken on that topic, but there are some other data papers worth a review:

• Science & Technology Agents of Revolution (STAR) Database: A Progress Report

• The Redesign of the National Science Foundation's Business R&D and Innovation Survey: What Worked and What Didn't in Trying to Measure Global R&D, Intellectual Property, Technology Transfer, and Innovation

• Extending the Surveys on R&D to Measure Intangibles: Evidence from a Pilot Survey in the UK and the Kauffman Firm Survey

There are a couple of other great sessions on the agenda which don't have papers listed which I am trying to gather more info on, like one on measuring broadband impact, so I'll hopefully be able to post more in the coming week.  For those at the AEA meeting who I've missed, hope it's going great!

Published every two years, the OECD Science, Technology and Industry (STI) Scoreboard brings together internationally comparable indicators in the area.  The 2009 edition was recently published.  Read the English language summary.  One bullet point of likely interest:

• Historical data show that research and development (R&D) and venture capital are among the first expenditures to be cut during recessions in OECD countries. Preliminary data confirm this finding for the first half of 2009.

The Association of University Technology Managers (AUTM) will be having their annual meeting on March 18-20, 2010.  AUTM collects most of the standard metrics related to university technology transfer which are used in the United States.  Although the National Science Foundation has proposed beginning collection of some data in this area, that effort did not receive final approval in 2009. 

A couple of things which looked interesting to me on the AUTM annual meeting agenda:

• Session with the Despande Center, Lemuelson Foundation, and MIT Venture Mentoring.  These are great programs/organizations for practitioners looking to advance high-growth entrepreneurship.
• Session on data sharing among university and non-university partners. 
• Session on AUTM metrics.  This session looks to help integrate global AUTM metrics with local discussions of meaningful comparisons.

I was reminded last week of some work I had done a couple of months back which looked at COBRA health insurance.  The reminder came from a posting the Bureau of Economic Analysis did to clarify its treatment of COBRA payments in the national accounts. 

My earlier work was to comment on the Bureau of Labor Statistics' (BLS) Current Population Survey module on displaced workers.  I had earlier posted draft comments but received some great input from a colleague, Margo Quiriconi, on that draft so here are my final comments submitted to BLS.  What amazed me in reviewing this module was that in the midst of a national debate on health insurance and the Great Recession that BLS hadn't taken more care to revise the module.  Set to go to the field in January in the exact same form it was fielded two years ago no one seems to be worried about measuring really important aspects of health insurance in the displaced worker population like COBRA insurance or where people displaced from their job in this Great Recession are receiving their health insurance (if they are).  At this point, it is too late to change anything for this module, but it is, in my opinion, a real missed opportunity to collect relevant and meaningful information on an important population.  This could be a great module to someday finally answer the question about health care job lock by looking at people who are displaced but had access to health insurance through another source and whether that effects one way or the other their propensity to start a business. 

According to a new Intel/Newsweek survey, consumers remain confident in the role that innovation will play in driving future economic growth.  While this is survey I suspect knew the storyline that it wanted to tell before even going to the field, I did find some aspects of their survey about perceptions of future technological innovation to be interesting.  Here are a couple of paragraphs from their press release: 


We have asked a similar question before (not that that makes me any more confident in its predictive nature).  Think back to the perceptions created of Japan in the 1980s.  As such, I'd take this with a grain of salt.  Certainly media can influence attitudes significantly when it comes to a countries confidence.  But I can also recognize how self-fulfilling defeatists attitudes can become.  That is part of why we engaged in Global Entrepreneurship Week to try to positively affect the images and opportunities young people can find in entrepreneurship.  Perhaps next years theme should try to take on perceptions of our abilities to innovate technologically? 

The National Science Foundation has released new current and historical tabulations on bachelors and graduate degree completion by race/ethnicity/gender through 2006.  In scanning the report, the real movement over time appears in the graduate data with an ever increasing international component to degrees awarded.  Additionally, they have data out through 2008 on doctoral awards. 

The National Institute of Standards and Technology's (NST) Technology Innovation Program (TIP) has posted a call for comments on working papers which outline possible future areas of funding for its programs.  TIP is a very critical program in the U.S. portfolio of programs working to advance entrepreneurship and innovation. 

After the crazy financial environment of the last year, consumer finance (or household financial usage) surveys appear to be increasing in popularity or frequency.  The Federal Reserve Board of Governors made a really astute decision to refield their popular Survey of Consumer Finance, last done in 2007, but not to implement a new 2009 cohort but rather to go back to their respondents from 2007 and collected panel data on the finances of these households.  And apparently, they have added in some logic to their questionnaire such that if a respondent was a business owner in 2007 but not in 2009 they will ask what happened to that business.  This holds great potential in studing entrepreneurial households.  Unfortunately, the sample sizes here are so small that it the utility of the data could be limited depending on incidence rates.

Additionally, the World Bank is considering some expanded work in this area that if approved could be quite exciting.  Also from the World Bank, a recent paper highlights some methodological issues about collecting data on financial service usage: