Canada $10/Day Childcare, Maternal Labour Force

Published: 12 July 2026| Version 1 | DOI: 10.17632/82czf3pywx.1
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Description

Canada’s $27 billion $10-a-day childcare initiative is a generational investment, yet its true impact on maternal labour supply remains fundamentally obscured. Utilizing monthly Labour Force Survey microdata (2019–2025) and a doubly robust staggered difference-in-differences design, I estimate an uninformative null effect on maternal labour force participation. I argue that the policy suffers from a two-fold evaluation deficit. First, a power and design constraint due to a rapid national rollout that exhausts clean control groups within eight months, limiting current econometric evaluation to a short 0–7-month window and obscuring long-run effects. Second, and more critically, an irreducible data infrastructure constraint. As Canada does not collect administrative waitlist data, even a well-identified null estimate cannot be definitively decomposed into “no demand” versus “demand blocked by supply.” I demonstrate this empirical limitation via a continuous capacity moderator test, arguing that the policy’s true success is un-evaluable without tracking waitlists. I conclude that Canada is better-suited to invest in, first, childcare capacity, particularly in Early Childhood Educator (ECE) workforce expansion via wage grids and defined benefits, and second, establish the data infrastructure necessary to measure policy success in the future. Please see other description for steps to reproduce.

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Steps to reproduce

Given the fact that the raw data files are very voluminous and heavy, I have included the cleaned data files in the processed data folder. If you would like to run the analysis from scratch, please download the primary data files from Statistics Canada's Labour Force Survey from January 2019 to December 2024, which may be accessed from a variety of ways. The cleaning scripts, which are 00, 01a, and 01b, are included for transparency. Please note that, given the size of the files, the number of observations, and depending on your computing power, the full analysis pipeline could take more than a few minutes.

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Categories

Economics, Labor Economics, Economics of Gender

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