Can administrative labor market data help policymakers anticipate changes in Unemployment?
Using Saned UI claims data to predict unemployment rate in Saudi Arabia
In 2022, GOSI started publishing for the first-time detailed quarterly figures on the number of citizens who lost their jobs and are receiving unemployment insurance (UI) benefits through Saned. In the past few years, a growing number of countries have begun utilizing alternative labor market data sources such as UI claims as a leading indicator of the private sector’s health and to supplement conventional labor force surveys (LFSs). This is particularly important in countries like Saudi Arabia where LFSs are released every quarter, which leaves policymakers without basic labor market information for 4-5 months. In this article, I argue that policymakers in Saudi Arabia can utilize high-frequency administrative data like Saned UI claims to gauge the direction of the unemployment rate amongst citizens. Specifically, I test whether changes in the number of UI recipients in one period can inform decision-makers about changes in the unemployment rate in the near future by combining 1) labor market administrative and 2) quarterly LFS data sources to
In addition to providing more timely data, another advantage of relying on high-frequency admin-data is that their measurement error is typically lower than other common data sources (e.g. surveys). In fact, the authors of a University of Chicago (2020) paper argue that administrative payroll data are, “are free from measurement error.” In the United States, a policy report by the Indiana Business Review suggests a strong positive correlation between the two indicators where a 1% increase in the number of UI beneficiaries is associated with a 0.80% rise in the unemployment rate. Now going back to our main question: can UI claims tell us about where the unemployed is heading in Saudi Arabia?
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