Labor markets desperately need information to function effectively and efficiently, making labor market information systems critical public investments. Yet government systems face significant challenges in collecting quality data, turning it into useable market intelligence, and disseminating it in a timely, relevant manner, a situation more acute in developing countries. The rise of private, real-time labor market information (LMI), such as web-based job posting analytics, social network inferences, crowdsourcing, and mobile phone polling, has garnered interest and questioned the dominance of traditional approaches. This brief explores the use of real-time LMI and presents interviews conducted with international donor officials to gain their perspectives on its applicability in developing countries. I suggest that real-time LMI is unlikely to supplant traditional LMI collection anytime soon, and I dispel notions that these new approaches might leapfrog current data collection challenges. Real-time LMI can provide useful in special cases and for supplemental analysis, an additional lubricant for labor markets that suffer from weak data. Policy that supports the improvement of traditional LMI and promotes access to real-time LMI is warranted.
Challenges to Traditional LMI
Even the best LMIS suffer shortcomings, and less-developed countries encounter these problems to a greater degree. Traditional LMI is challenged in six key areas: timeliness, accuracy, integration, analysis, usage, and cost.
Timeliness: Survey results are too slow or are based on outdated classi cations, calling into question the temporal validity of results when published.
Accuracy: Poorly constructed surveys, nonrepresentative samples, and missing administrative data lead to questions of construct validity and selection bias.
Analysis: Countries lack ability to turn labor market information into intelligence, leading to analytic bias and inaccurate result reporting.
Integration: Data collected for multiple sources are not integrated into one system, leading to reporting bias.
Usage: Usage challenged by access barriers and relevance/ demand issues are caused partly by funding bias.
Cost: LMI systems are expensive, even cost prohibitive in low-resource regions, leading to government monopoly.
The United States spends nearly $1 billion per year on labor market data collection and dissemination. The LMIS of the United States, Canada, the United Kingdom, and Singapore, among several others, are touted as exemplary systems, although each has its own strengths and weaknesses.
Key Policy Implications
• Traditional approaches to providing labor market information (LMI) su er from a number of challenges. These challenges are addressable but will need the attention of governments and their donor partners to resolve them.
• Real-time LMI has made advances with the rise of computational science techniques and the “big data” revolution. Use of these data approaches
by high-pro le actors in the United States (Federal Reserve Bank), Canada (Ministry of Finance), and Government of Singapore has provoked some to question how large of a role these data can and should have and to what extent big data are applicable to less-developed LMI systems.
• Given signi cant limitations to real-time LMI itself, including examples where real-time LMI leads to suspect policy action, some experts see it as a useful supplement—or an additional labor market “lubricant”—but not as a replacement for or savior of traditional systems.
• Real-time LMI for special purposes and supplementary analysis is promising. Bringing these capabilities to developing world economies should be a priority for donors working in these areas.
Chosen excerpts by Job Market Monitor. Read the whole story at Can big data save labor market information systems? | RTI
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