When trying to understand labor market dynamics, it can be hard to separate the signal from the noise. That’s why we work to transform data from the Economic Graph into crisp, relevant insights for policymakers, complementary to the traditional data sources at their disposal. And that’s why, today in Buenos Aires, we are sharing labor market insights with some of the world’s foremost political and economic leaders as part of a G20 workshop designed to explore the Future of Work.

In this endeavor, we are fortunate to partner with the Labor Markets division at the Inter-American Development Bank (IDB), whose economists are regional experts on Latin America, as well as knowledgeable about labor market data currently available to governments. During our joint presentation to the G20 with the IDB today, we will outline traditional sources of labor market data, and illustrate how non-traditional data sources like the Economic Graph can complement policymakers’ understanding of the economy.

Some of the insights we’re sharing in today’s G20 workshop can also be viewed here. Read on for a quick overview.

Traditional sources of labor market data

Governments have two primary sources of labor market data: administrative data and survey data. Administrative data is collected directly by government from employers and workers. The nature of the information shared varies by jurisdiction, but typically includes wage records (through tax and/or payroll records), job postings, and education (especially for federally subsidized institutions and students). Survey data is collected periodically, every 1 to 10 years, and is used to estimate productivity, consumer spending, or build occupational and skill taxonomies (see the US Bureau of Labor Statistics information guide for other examples).

Government sources of data on workforce are some of the best available, but have limitations. Because much of the data is collected via survey and curated manually, the rate of change in the workforce can outpace the availability of workforce data and insights.

For example, in the United States, the government’s primary skill taxonomy comes from O*NET, the Department of Labor’s Occupational Information Network. To build that data set, its Data Collection Program contacts employers to update the skills required for around 100 occupations each year. O*NET’s taxonomy includes ~1,000 occupations. Because only a fraction of occupations are updated each year, skills that are new and growing very quickly in relevance are often left out. For example, a search for the skill “machine learning” on O*NET’s site returns a seemingly random list of occupations including kindergarten teachers, coin vending and amusement machine repairers and sewing machine operators.

LinkedIn’s labor market data

LinkedIn’s Economic Graph data is the downstream result of hundreds of millions of workers using LinkedIn to apply to jobs, build their networks, and stay informed on industry trends. This data, generated from activity on our network, helps us measure and understand labor market dynamics. As a members-first organization, the privacy of our members is our first priority: when analyzing labor market insights, we only use anonymized, aggregated data.

The Economic Graph makes it possible to understand how hiring for different occupations has changed over time, and consequently, which occupations are emerging or declining. And with LinkedIn’s unique view into skills, we can further break these trends down to understand which skills are in demand, and how transferable a skill may be among different industries or roles. And by analyzing how members have moved from region to region we can understand how talent migrates from place to place.

Below is a look at some of the insights we’ll be presenting at the G20 workshop (see more here). The goal of this overview is not to fully describe G20 economies, but rather to demonstrate the types of insights that are possible.

1. Changes in Hiring Trends

Understanding how hiring for different occupations has changed over time allows us to see patterns in how demand for occupations have risen or fallen, indicating which occupations are emerging or declining (i.e., those that are rising or falling fastest).This type of benchmarking can help leaders understand how quickly changes are happening, and whether the changes are unique to a particular jurisdiction.

2. Emerging and Declining Occupations & Skills

Once we identify which occupations are emerging or declining, we can cross-reference with our skills data to identify the associated skills that may be rising or falling in demand. By understanding how the demand for skills changes over time, policymakers can design more effective education and workforce programs to better retain workers with low-demand skills to areas of higher-demand.

Once we identify which occupations are emerging or declining, we can cross-reference with our skills data to identify the associated skills that may be rising or falling in demand. By understanding how the demand for skills changes over time, policymakers can design more effective education and workforce programs to better retain workers with low-demand skills to areas of higher-demand.

3. Talent and Skill Migration

Since LinkedIn’s membership is global, the Economic Graph can reveal trends in international people movements, including net talent gains and losses for specific regions. In the future, policymakers could use this kind of information to design programs to build and retain a skilled workforce.

Next steps

We look forward to sharing these ideas with the G20 and working with IDB and other partners to develop them further. Our vision is that our data could one day be used to help policymakers design education and workforce policies that create economic opportunity for every member of the global workforce.

For a deeper look and to see insights country-by-country for the areas we analyzed, click through for an interactive report here.

The work we are doing to support the G20 exploration of Future of Work has benefited greatly from our collaboration with the Labor Markets Division at the Inter-American Development Bank under the direction of Carmen Pages-Serra. To follow their work, subscribe to Factor Trabajo.

We would also like to recognize the support of Beatriz Nofal, T20 member and former Argentina G20 Sherpa, for her valuable contribution in this G20 Future of Work project.  We would also like to recognize the support of Alejandra Kern, Esteban Eseverri and the Argentine Ministry of Labor for providing project guidance and support.