5/12/2010 9:12:58 AM By
3/25/2010 3:00:00 PM By
The National Science Foundation (NSF) has released a report highlighting the role of small businesses in R&D activities in the United States
. It shows increasing R&D activity by small businesses but also something I found troubling:
Microfirms spent 2.6% of company sales revenues on R&D activities in 2003, 10.1% in 2005, and 15.8% in 2007 (table 1). However, the change over time reflects more a drop in company sales revenues than growth in R&D performance.
Here, microfirms are defined as firms with 5-24 employees. It'd seem for this particular group, many of which are likely younger firms, sales were being negatively effected well before the current recession. NSF is in the process of developing a new microbusiness R&D survey (under 5 employees) to be implemented in the next year or two. It's one of the most exciting projects I see going on at the U.S. statistical agencies currently as it will really be breaking new ground in survey work on small businesses and innovation. I'll be posting more on that work as it becomes available.
While on the topic of NSF, an information webinar in April should be of interest.
“Human Resources in Science and Technology: Surveys, Data, and Indicators from the National Science Foundation” will be presented by Nirmala Kannankutty on Tuesday, April 6, 2010, 1:00 PM - 3:00 PM Eastern time.
The Division of Science Resources Statistics (SRS) is a federal statistical agency housed at the National Science Foundation (NSF). SRS's role within NSF is to "provide a central clearinghouse for the collection, interpretation, and analysis of data on scientific and engineering resources, and to provide a source of information for policy formulation by other agencies of the Federal Government..." Within this mandate SRS is involved in collecting and disseminating information on R&D expenditures and activities and on human capital issues. The United States is unique among major industrialized nations in that it has directly invested in collecting detailed data from a variety of sources on the entire science and engineering pipeline. Each of the data sources came about from U.S. federal administrative needs. The sources have evolved into important elements for the study of higher education and the scientific workforce. In this webinar, these surveys and data sources are described. Key indicators regarding trends in U.S. science and engineering degree production, enrollments, and workforce are defined and described. The “Science and Engineering Indicators: 2010 and “Women, Minorities and Persons with Disabilities in Science and Engineering” reports will be used as examples for these indicators. At the end of the webinar participants should be aware of data sources and how data are collected, indicators and reports from the NSF, and where to find more information from the NSF.
To register, please visit the SRMS web site at: http://www.amstat.org/sections/SRMS/webinar.cfm
3/10/2010 1:00:00 PM By
This year the Census Bureau finally received full funding of their plan to expand coverage of the service sector. On Friday, March 12, the Brookings Institution will host a workshop
that will examine this expanded service sector work. I won't be there but this is without a doubt among the most important improvements underway to our timely measurement of the economy.
1/22/2010 3:00:00 PM By
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.
11/30/2009 3:00:00 PM By
11/24/2009 5:00:00 PM By
Update 11/24/2009: The Heritage Foundation has posted proceedings (including video and PPTs)
from the recent event I spoke at. It was a really nice event with a diverse crowd. Nice to see Brookings and Heritage coming together to focus on developing better data. I most enjoyed the mornings speakers who really offered a wide range of comments on the state of current economic statistics and needed improvements.
Original Post 11/6/2009: The Brookings Institution and the Heritage Foundation are hosting an event on "Measuring Innovation and Change During Turbulent Economic Times"
on November 17, 2009, 9:30 a.m. - 4:30 p.m. The topics on the agenda go much beyond just innovation measurement into many different aspects of change so it will be interesting to see how it all comes together at the event. Oh, and I will be serving as a discussant for one of the sessions so if you want to say hi, you will catch me at Heritage for this event.
11/24/2009 9:00:00 AM By
I have enjoyed watching reactions to Josh Lerner's new book - Boulevard of Broken Dreams
- over the last few weeks from the Economist
, the New York Times
, and also state-level development groups
. Lerner's book, which is a part of a new Kauffman series at Princeton University Press
, and flows in large part from his experience running the Entrepreneurship Working Group at the National Bureau of Economic Research
, is an easy read, in my opinion, but one which is likely to simultaneously scare and excite policymakers. Excitement will come from having something which is so comprehensive in its global policy review, but one does get scared at reading the many things which appear can go wrong with usually well-intentioned interventions. For those not having read the book, the SSTI has a nice summary of key points
For me, Josh's book highlights two things related to measurement:
- Knowing What to Measure is Hard. In most cases, the items which Josh highlights as keys to success or failure are not things which I would have initially thought to measure about a specific intervention although I think I'd have a better idea what to measure about a venture capital-focused policy. Since I am not trying to do such an assessment currently, I am focused on trying to improve data available from the federal agencies so that granular and consistent data on things like business dynamics, gazelle companies, and high-growth firms are available at the regional or subregional level in the United States. Releasing such data in a timely fashion could greatly aid regional economic development.
- Database on Policy Interventions. Tracking substantive changes to program implementations such as the many that Josh describes is too often left to oral history or chance capture. I would love to see some sort of open-source development of a database of key programmatic interventions to support entrepreneurship and/or innovation over time and major timelines, events, changes, etc. Such data would aid so much in looking for impacts but to my knowledge, no such compilation exists for scholars interested in studying policy to draw from (or add to). If anyone has ideas of data products available here or means by which such data could be collected, I would love to hear suggestions. Perhaps its possible mine things like Wikipedia in an automated fashion for some of this info?
11/23/2009 4:00:00 PM By
Two short courses for economic development professionals offered through Georgia Tech look to have a focus on entrepreneurship in 2010:
11/13/2009 9:18:05 AM By
Looks like I will be heading to Connecticut on Saturday, November 21 for a one day event at the Yale Law School on Data and Code Sharing in Computational Science. This is the first event I have ever been to which is being completely organized by wiki which means that the agenda, attendee list, and other logistics are all password protected. So, to give a sense of the event, I pulled down a PDF of the agenda
(realizing that it is being constantly edited). It is part of something called the Information Society Project
. We have worked for some time to try to make research data more accessible so the particular focus here on making data available to encourage replicability will be of great interest. I've pulled down the "resources and readings
" page, as well, as it is the most authoritative list of articles, blogs, and important background material
on data sharing that I have ever seen in this area.
11/10/2009 9:43:09 AM By
The European Regional Science Association has a call posted for a special session
at their 2010 conference on entrepreneurship in rural regions. Deadline for submission is January 15, 2010, with actual event to take place in Jönköping, Sweden, on August 19-23, 2010.