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.