What are the indicators that policymakers require to measure and understand the behavior of their entrepreneurial ecosystem? How do statistics from research influence policymakers’ decision-making and the potential creation of new programs?
These are among the questions we explored during a GEM webinar held on Tuesday, July 14th. The panelists for the session were policymakers as well as researchers from Global Entrepreneurship Monitor:
Daniel Oviedo, Chief Statistician of Colombia at National Statistics Office of Colombia
Anna Tarnawa, Head of Strategy and Analysis Unit, Analysis and Strategy Department, Polish Agency for Enterprise Development (PARP)
Nihel Chabrak, Professor at the United Arab Emirates University (UAEU)
Leon Dario Parra, Associate Professor at the Universidad EAN and member of the GEM Colombia Team
The session was moderated by GEM Executive Director Aileen Ionescu-Somers.
You can access the recording at the following link.
The following are questions and answers from the session:
1. Does entrepreneurship research impact policymaking differently within Europe? How does this compare to Silicon Valley?
This is a complex question that would probably require several webinars to cover. This is because while there are entrepreneurship policies existing at the EU level, including the 2020 Entrepreneurship Action Plan, most countries set their own policies, depending on factors such as national priorities and income levels. Additionally, some of these countries may rely heavily on entrepreneurship research to develop their policies, while others may not.
However, as GEM’s 2019-2020 Annual Report demonstrates, European countries including Bulgaria, Croatia, Cyprus, Germany, Ireland, Luxembourg, Netherlands, Poland, the Slovak Republic, Slovenia, Spain, Sweden, and the UK have all used GEM research to contribute to some aspect of their country’s entrepreneurship policy. Examples of their contribution include presenting research findings to economic committees or ministries, consulting on new entrepreneurship projects or using GEM indicators to assess a policy’s impact. All these examples are discussed in Part II of our Global Report, “Economy Profiles” starting on page 81.
The second part of your question on Silicon Valley is also complex. Silicon Valley’s success has effectively become a subdiscipline of entrepreneurial research. One of the core questions of this research is how of much Silicon Valley’s success has been driven by deliberate policies vs. a “laissez-faire” approach of letting firms and people experiment with minimal policy intervention. While the debate continues, a Google Scholar search will reveal that GEM data has been used to inform some of this research, both on the subject of Silicon Valley development theory as well as how it may or may not be replicated in other locations.
2. Is it possible to have an access to the row data by researchers?
All of the GEM indicators discussed in the webinar are available by accessing our website: https://www.gemconsortium.org/data. Here, you can download a range of indicators from over 100 countries, dating back to 2001 (in some cases) through 2019 (most recent data available). Additionally, for an explanation of our methodology, please consult our wiki site.
3. Is there any data representing firms’ mortality because of the Covid-19?
Some countries have begun tracking this data, either through their central bank or national statistical office. All data will be preliminary of course and will be difficult to parse in these early stages.
Please note: GEM is asking Covid-19 related questions, including on firm mortality in its 2020 Adult Population Survey (APS); the results of which will be published in early 2021. This will be the definitive global data source of how Covid-19 has impacted entrepreneurship in the nearly 50 participating countries. GEM’s 2020 National Expert Survey (NES) also includes 10 questions on Covid-19, providing national experts with an opportunity to discuss how the pandemic has impacted their country’s framework conditions.
Additionally, GEM will be releasing a Special Topic report, sponsored by Shopify, on how Covid-19 is impacting entrepreneurship, to be published in September 2020. This report will include case studies of how countries are adjusting their entrepreneurial policies and how entrepreneurs are reacting.
4. What is an effective way to monitor and evaluate the performance of programs supported and carried out by the government? Is there any example of such methods you can introduce? Does GEM plan to develop a database showing feedback/contributions of national entrepreneurship and innovation practitioners?
There are several ways to monitor and evaluate governmental program performance. A common method is to compare data before and after a program was introduced, and then determining which “after” cases resulted from the program. Another common method is using qualitative methods, such as interviewing those affected by a government program, to see if the program helped or hindered their goals.
Both have their advantages and disadvantages. Comparing data points can provide some quick and seemingly objective feedback, but it is always difficult to determine causality when so many factors lead someone to say, open a new business. Qualitative research can highlight cases when someone distinctly says they opened a business as a result a government program, but finding and interviewing these individuals is a time-consuming process.
Acknowledging that both methods can provide valuable information, GEM produces annual time series data for quantitative analysis, while also using qualitative methods – such as asking surveyed adults why they started or closed a business in the Adult Population Survey (APS), or asking experts about the strengths and weaknesses of government policies in the National Experts Survey (NES). Both of these surveys generate data points for researchers to use to determine if a government policy worked, and GEM indicators have been used in literally thousands of research papers to demonstrate the efficacy of certain programs.
The most common indicators used to evaluate program effectiveness include our Total-Early Stage Entrepreneurship (TEA) rate, our Motivational Index, and our cultural indicators such as Fear of Failure, all of which can be downloaded here. In most research, regression models are used to compare the presence of a government program with performance on one or many of these indicators. Similarly, researchers use our expert assessment of government policies using the following indicators: Governmental Support and Policies, Taxes and Bureaucracy, and Governmental Programs indicators, produced in our National Expert Survey (NES). You can download these indicators here.
Qualitative data on why individuals may have started or closed their business, including for reasons of government policy, can be found in our full datasets, under the “reason” variables. Other sources of qualitative data on government policy effectiveness can be found in each GEM team’s Economy Profiles, starting on page 81 of the most recent GEM 2019-2020 Annual Report. Teams also regularly address the topic of government effectiveness in the annual reports, which can be found following at this link.
5. What is the role of GEM in low-income countries that lack data?
Many low-income and middle-income countries participate in GEM. This is an excellent opportunity for these countries to obtain granular data on entrepreneurship, particularly because these countries are often ignored by other international business research organizations. In 2019, over 1/3 of the participating GEM countries were low or middle-income. To see a list of all countries that have participated in GEM, categorized by income, please consult our Economy Profiles site.
6. Can you talk about data collection - for example virtual vs. face to face - and implications for representativeness and/or other aspects of the data?
This question on survey response representativeness is one that each participating GEM team is taking very seriously. Each team has worked with their survey vendor to ensure that they collect a representative sample of the adult population, even if the contact methods must be adjusted to reflect the new guidelines associated with Covid-19 safety.
Each participating GEM must also have their vendor proposal approved by GEM’s internal data team to make sure it will generate a statistically sound representative sample (at least 2,000 or more participants), before data can be collected.