I recently came across the BuzzFeed article “24 Pictures Old Millennials Can Hear, Even if They Haven’t Heard Them in Years.” As a sucker for ’90s nostalgia, I couldn’t click fast enough. Picture number three is of the iconic America Online (AOL) mailbox, which, as promised, immediately caused my brain to chime “You’ve Got Mail.” Unfortunately, it then also dredged up the grating sound of a dial-up modem.
Jarring sounds notwithstanding, this little trip down memory lane reminded me of how fast technology has changed in the past twenty years. For most of us, that’s been a good thing. From better health care to streaming video to worldwide communication options, technology has improved our lives in countless ways.
From an economic perspective, new technologies are associated with reduced production costs and increased investment. They enhance productivity gains, boost competitiveness, and augment the cultural and political development of societies. In short, they drive economic growth and improve our quality of life by making us more efficient. But only if people have the skills to use the tech effectively.
As new technologies seem to emerge faster than ever, concerns are being raised that the skills needed to succeed in the workplace are changing more quickly than they can be developed. In fact, Canada is investing in a Future Skills Centre to address such concerns.
Given the growing importance of skills development to the modern economy, it may come as a surprise to learn that skills are not entirely well defined. Indeed, there are many competing definitions and different ways to describe them. This lack of clarity makes measuring the supply and demand of skills extremely difficult. Since understanding where skills shortages exist is essential for policy makers and Canadians alike, this represents a major gap in Canadian labour market information.
Recognizing the importance of identifying skills shortages has produced some preliminary insights, but much work remains to be done. For example, the most common method used to measure skills shortages relies entirely on proxying skills with observable labour market characteristics such as education, occupation, and/or field of study. My recent article in LMI Insights delves deeper into the different approaches for measuring skills shortages and provides some suggestions for how to move forward.
One avenue that should be explored, for instance, is the creation of a Canadian skills-to-occupation mapping, which lists specific skills associated with each occupation. Another is the application of machine learning and text analysis algorithms to online job postings and user data. While both approaches have advantages and limitations, they nonetheless offer potential solutions for producing more reliable and timely estimates of the skills shortages in Canada, and thus, the skills most needed to move our economy forward.
Further details about these definitions and the rationale behind them are available in LMI Insights No. 14, “Is this a skill which I see before me? The challenge of measuring skills shortages.”
As an economist with LMIC, Anthony Mantione contributes to advancing LMIC’s mandate through the application of computational techniques to data analysis. email@example.com