BW #25: Entrepreneurship
Where are people more likely to start their own businesses? How much has this changed in recent years? And are people really more pessimistic in China than elsewhere?
[Hey — Are you at the Euro Python conference in Prague? Find me and say “hi”! I’m around through Friday afternoon.]
I've recently written a number of times about how we're in a funny period, economically. On the one hand, individuals are worried about their economic futures, in no small part because of the highest inflation in decades, layoffs at well-known technology companies, and worries about the future of work, given the recent release of high-quality AI tools that might replace some jobs. On the other hand, people seem to be spending money, and unemployment (especially in the US) hasn't been lower in a long time, pointing to a pretty good situation. Kyla Scanlon has called this a “vibesession.”
I was thus intrigued when I read an article in the Economist that talked about the many challenges facing China's economy. The world expected China to come roaring back after doing away with its "zero covid" policy and mass lockdowns, but that hasn't really happened. This has been covered in numerous places, most recently the New York Times podcast, "The Daily," which you can read at https://www.nytimes.com/2023/07/17/podcasts/the-daily/china-economy.html?action=click&module=audio-series-bar®ion=header&pgtype=Article.
The Economist's article said that people in China are less optimistic than they used to be about their country's economic future, and that they're thus less likely to start businesses. The article referenced an annual survey from GEM, the Global Entrepreneurship Monitor (https://gemconsortium.org) as the source of this information.
I hadn't ever heard of GEM, but I checked them out a bit, and found that they have been doing two types of entrepreneurship surveys for quite some time.
The first, the overall "adult population survey" (APS), asks at least 2,000 adults in each of dozens of countries what they think and feel about starting and continuing to run businesses. The questions they ask here reflect individuals' thoughts about potential failure, motivation, innovation, and even female participation in entrepreneurship.
The second, the "national expert survey" (NES), asks experts in each economy what they think about the environment and ecosystem for entrepreneurship in their country -- the ease with which companies can get funding, the burden of taxes and bureaucracy, the country's physical infrastructure, and even cultural norms that can make it easier.
The latest GEM report came out earlier this year; you can download it from /content/files/file/open.pdf .
This week, we'll be looking at some of the data behind this report. Where do people see opportunities to start businesses? Have these changed over time? And where are women finding new opportunities?
I should add that while I speak of "countries," the GEM report talks about "economies." That's because several of the regions in the survey are independent economies, but whether they're countries is a deep and complex political question.
Data and questions
This week's data comes from the the latest GEM report, from the adult population study (APS) reflecting what people on the ground think about starting a business. The data can be downloaded in CSV format, but it takes a little work to get it:
- Go to https://www.gemconsortium.org/data/key-nes the page for downloading the study data
- Click on all three of the "all" boxes (for choosing an economy, an indicator, and a year)
- Click on "export" to get the CSV file downloaded to your computer.
I considered also including data from the NES (the survey of national experts), but decided that the APS data was rich enough for us to work with. If you're interested in that data, you can go to https://www.gemconsortium.org/data/key-nes and follow the same instructions (selecting all three "all" boxes) before clicking on "export."
This week, I'm giving you 8 questions and tasks. The learning goals include pivot tables, calculating differences, finding correlations, and making comparisons.
- Import the APS data into a data frame. Use the short name of each column as the column name.
- In 2022, which 10 countries had the highest "Perceived Opportunities" scores?
