4/29/2011 5:13:58 AM By
The National Establishment Time-Series (NETS) Database
, a longitudinal database of linked Dun & Bradstreet records, is one of the standout data sources to emerge in the last half decade for the study of entrepreneurship (and businesses, more generally). As an early proponent of the potential of this data, I wanted to offer some commentary now that comes from grantees that have used the NETS data for different purposes such as matching to other data sets, surveys, or just aggregate examinations of firm dynamics. Every data set has its advantages and disadvantages, NETS is no anomaly in this regard, but one of the unique things about my role is that I get to see some of these trends and connect experiences. These comments emerged as the result of an email inquiry I had made to those listed here for a potential new project. I found the comments so valuable I decided they should be published as blog post so that others could see them. All the commentators were allowed to review and modify their comments before posting. I would encourage others who have experiences that can help to hone the use of NETS and hopefully drive improvements to its core to add them as comments to this post.
“The strengths of the NETS are its historical address information, descriptive data (industry, incorporation codes, and CEO and ownership demographics) and survival measures. These traits seem sufficient to conduct event history analysis using quasi-experimental methods.
If your focus is on other types of performance such as growth, then I'm not convinced this is the best dataset. I found in my research that employment and sales figures in the NETS are often estimates and not actual observations of the levels of these measures. It presents a problem when you are dealing with small firms because you lose variation since so many of these small firms appear to reach stability over short periods of time. I'm still using the data for this purpose but I take the results to be more speculative than definitive.
Also, the lack of information on other attributes of organizations (i.e. invested capital, costs, revenue streams, and the education and experience of CEOs) makes it hard to account for unobservable differences that may be the underlying cause of performance when evaluating a policy outcome. There are statistical methods to address these issues but these also open the door to skepticism and criticism.
I'm working on ways to improve on the value of the NETS by merging it with other datasets to add richer data to what I already use. Depending on the types of firms being studied, one may improve on the types of controls that can be accounted for and on the type of performance being evaluated.”
“I agree with Alejandro that NETS is not the best data to see changes in firm level outcomes. In our work we found that the information on sales and credit scores are actually the best of their outcomes variables, and are updated reasonably well. But especially employment variable are very sticky in NETS and do not seem well covered in NETS.
One of the best data set that you could use is probably LBD data at Census, but this data is difficult to access since you need to apply for access.”
“I am less skeptical of the employment measures than Alejandro and Antoinette, although it depends how you are using the data. At the individual establishment level there is clearly a lot of stickiness. But when you are averaging across many establishments (like in our EZ paper
) this doesn't really matter. I think that if you are matching based on geographic location the NETS are very useful although the geocoded information that comes provided with the data might need to be re-geocoded.”
See select other posts dealing with NETS: Comparing Business Registers
; youreconomy.org Updated
11/26/2009 9:00:00 AM By
The 2008 U.S. Global Entrepreneurship Monitor (GEM) report
was released this week from Babson and Baruch Colleges. Showing significantly different trends from the Bureau of Labor Statistics data
which was included for the U.S. in the report from Organisation for Economic Co-operation and Development (OECD)
which I highlighted last week, GEM found increasing trends in "total entrepreneurial activity" in 2008.
For those of you not familiar with GEM, it is collected through a household survey in participating countries on activities related to nascent entrepreneurship - people in the process of starting a business - and people running young businesses. In that sense, GEM is probably closest in measurement concepts to the Kauffman Index of Entrepreneurial Activity
(KIEA). GEM has the advantage of explicitly asking about activities related to nascent entrepreneurship while the KIEA takes advantage of a large-scale government survey to look at transitions from being employed by someone else to being self-employed or a business owner. And while GEM reports to have a large enough sample size to disaggregate different types of growth trajectories, I don't believe it is really possible with a sample size of 2,000 for the whole United States. Perhaps if they had a sample size which was twice its current size.
It used to be that GEM was one of the first indicators to the hit the presses, making it of particular interest to the policy community since official statistics have historically been laggards. But that is no longer the case. Indeed, besides the Kauffman Index of Entrepreneurial Activity and the OECD reports, I know that the Census Bureau is getting very close to releasing its updated Business Dynamics Series
through 2008 and the NETS database
has 2008 data out (I'll be posting on that more in the next couple of days). If GEM loses its timeliness factor and there continue to be concerns on the squishiness of the data it collects, then I fear the last legs of this effort might come off. It is an effort with many merits, which is why we were involved as a funder for many years - don't get me wrong. Being able to buy time on omnibus surveys can be very economical and as such I still know many researchers who utilize this function.
8/11/2009 10:28:06 AM By
Alicia Robb, Denny Dennis, and I did a Professional Development Workshop at the Academy of Management
a couple of days ago. Here I am posting the slides from that workshop, which focused on data available for entrepreneurship research, along with notes from my comments at the event, which I had not put into slides.
Alicia Robb, Kauffman Foundation and University of California, Santa Cruz
Denny Dennis, NFIB
E.J. Reedy, Kauffman Foundation
Additionally, at the meeting, hard copies of the proceedings of the 2007 Kauffman Symposium on Entrepreneurship and Innovation Data
were handed out. Additional copies were requested by some but electronic versions of each paper are available on line
. The 2008 proceedings
, which focused on ideas for improving data are also available.
And lastly, we highlighted a few ways in which scholars could connect with Kauffman and other scholars in this area. There is this blog, Data Maven
, for tracking data developments. On Facebook, join the Kauffman Entrepreneurship Scholars group
. Subscribe to entrepreneurship emails from Social Science Research Network
. Or participate in Kauffman's emerging scholars programs
8/5/2009 11:28:02 AM By
, a resource provided by the Edward Lowe Foundation, uses D&B-based data to provide an interactive means for people to understand businesses in their community. Now in version 2.0, it is a site worth checking out. From conversations with the Lowe Foundation, it seems they will also soon be releasing additional options meant to serve the research community. But more on those details when they become reality. More on their recent updates:
In July 2009 YourEconomy.org (YE) was updated using the 2008 NETS database release. We also developed and introduced two new components to YE, Industry and Rankings. And, there is a new statistical area we designated as the UP (Upper Peninsula) located in Michigan.
YE data is built by tracking individual establishments according to their DUNS number. DUNS numbers start with establishments as they open and stays with them as they grow, contract, move, and even close. Businesses are contacted each year by Dun & Bradstreet (D&B) and asked to report changes in activity, employment and revenue.
Each time we update YE with new NETS data it adds a new year of data and changes the data across the entire timeline not just the most recent year.
The 2008 NETS release uses information from several 2008 D&B databases to better track and confirm changes that happened to establishments in 2007. This process of looking forward a year is combined with a process that looks back across several years to adjust establishment information that may have changed or has been discovered recently. These back and forth adjustments, (we affectionately call this Time Warp), provide a much more complete picture of establishment changes from the beginning of the YE data (1993) through the end of 2007.
YE took the opportunity at this update to adjust the data so it more accurately reflect the actual calendar year reported rather than the date of the NETS release version being used. For example, when you see the label for 2007 in our charts it refers to data for the full year of 2007, rather than the data represented by the NETS 2007 release.
7/23/2009 9:42:12 AM By
One of the first questions when doing a national business survey is the question of what businesses to use as the population for the survey. This is one which many organizations, like ourselves, struggle with in an ongoing basis. While we are a private organization, and as such, could not hope of getting the "gold standard" of frames, a government business register, even with the United States government and within the European Union directorates, few agencies are able to access Census, Bureau of Labor Statistics, or Internal Revenue Service pr similar business lists for the purposes of carrying out surveys. As such, federal agencies and private organizations like Kauffman are forced to go down a different route to obtain business lists which can, if not carefully considered, impact the overall quality of the research. But beyond this, an additional cost is born by taxpayers, businesses, and others more generally, because when using a non-governmental register of businesses, it becomes much more complicated to match survey responses to other administrative data. With this, we end up with a lot of independent surveys, few of which can actually be matched together, causing the surveys to be longer than really necessary and knowledge gained about different issues to be stymied. There are a host of privacy issues here which I am not going to address, but anyone seriously concerned with this topic should look at that topic separately.
Private organizations have popped up to provide these lists, some that are specific to different industries, such as Corptech
, which claims to cover high-tech businesses, while others like Dunn and Bradstreet
report to provide full industry coverage on the national level with international coverages that are very country-specific. And even companies like Dunn and Bradstreet allow others to repackage and sell their data, such as what Don Walls does with the NETS database
But how do these different lists compare to federal government lists? Private companies provide the data in a much quicker fashion and I would say the general consensus is that this benefit is offset by more messiness in the data. While some messiness is involved in any data set, as researchers are increasingly using micro data sets and not just aggregated tabulations, non-random messiness can become a problem. Many of these companies didn't start collecting this data for research purposes but more for marketing or credit checks. As the Internet has blown up, and companies have come to realize the value in some of this data, more products have appeared over time. Some work was done in the 1990s by entrepreneurship scholars to test the coverage of the private sources, but the reality is that not much has been done, to my knowledge, in at least ten years looking at a systematic comparison of advantages and disadvantages of some of these business registers. From conversations with others about the NETS database, as an example, we know that the last ten years have brought about a lot of changes in the population of businesses these private companies are able to find and include in their registers. This can create new opportunities but also real challenges for researchers looking to use the longitudinal component of these data.
I am aware of at least two projects that are underway in this arena that might be able to provide insights into some of the different private business registers (as well as governmental business registers). The first, and it appears furthest along of the projects, is comparing Census data to InfoUSA. I will be attending the 2009 Joint Statistical Meetings (JSM) in Washington, DC, in August and hope to attend the session at which this comparison will be presented
. The second project which I have heard alluded to several times is that Census is matching the California file of businesses from NETS to its business register to study similarities and differences. Both of these efforts should be informative to researchers and I will try to follow-up with additional details of the outcomes of this research in future posts. At the JSM, other register issues will be discussed including some international examples such as that of Finland
. Nordic countries, by most accounts, have the most robust registers so that might be an interesting section. If other projects are underway that are comparing private and governmental registers, I would appreciate an email
1/7/2009 12:26:00 AM By
For anyone reading the morning newspaper or web feed, the recent wave of massive job cut announcements have been startling. Just this morning, Alcoa announced 15,000 job cuts. That's a number I won't soon forget.
Job creation/destruction and entrepreneurship is a key area in which the Foundation has made investments over the last five years. We are not the first to look at this area, David Birch being perhaps the most famous, but it is a topic which remains not well understood nearly thirty years after his early work. Several recent papers from some of our grantees have confirmed using different data sets the relationship between net job creation and entrepreneurship. In "Turmoil and Growth: Young Businesses, Economic Churning, and Productivity Gains," Davis, Haltiwanger, and Jarmin show new establishments play an important role in job creation and that businesses that enter and survive the initial years as a business show strong employment growth. In "Do Small Businesses Create More Jobs? Evidence from the National Establishment Time Series," Neumark, Wall, and Zhang find that small businesses create more jobs in some industries but that it is a nuanced story which they continue to examine in forthcoming working papers which are as yet unreleased.
So if new firms or young firms are big contributors to job creation in the United States, why don't we read more about that? Most of the jobs created by entrepreneurship are added one or two at a time, in an often unheralded manner. The realities of this process make it inherently opaque to coverage. With more microdata available on this topic and better aggregated tables for researchers to mine, maybe this process can become more transparent to everyone? Certainly the U.S. Census Bureau's new series on job creation and destruction by state should prove useful, as should sites like YourEconomy.org.