population (and not just those who have a job) our data can be used to study changes in employment in response to the policy.

We also observe in the data the employer of the worker (or self-employment). For employers with double-entry bookkeeping we can merge balance sheet information from the Hungarian tax authority.<sup>19</sup> We restrict our main analysis to men because there was a change in retirement rules affecting women throughout the period studied here. We document women’s employment responses in Section 7.1.

An individual is defined to be a private sector employee if she is employed on the 15th of a month at a private sector firm with double-entry bookkeeping.<sup>20</sup> We include part-time workers, but adjust the employment indicator by working hours (e.g. working 20 hours per week is considered as 0.5 employment). Our main outcome in the wage regression is the (full-time equivalent) net wage as of May of each year. We follow Saez, Schoefer and Seim (2019) and define net wage (sometimes abbreviated to wage) as wage earnings net of employer payroll tax. This net wage measure is calculated before income tax and employee social security contributions are deducted and includes base payment, bonuses and overtime pay.

Appendix Table B1 provides a comparison of employment statistics based on the administrative data we use with official statistics which are based on the Hungarian Labor Force Survey. These statistics are very similar, indicating the reliability of the employment indicators we based on the administrative data.

We generate firm-specific indicators that we use in the heterogeneity analyses. Our baseline indicator of firm quality is the value added-based total factor productivity (TFP).<sup>21</sup> As another indicator of firm quality, we perform an Abowd, Kramarz, Margolis (AKM) style decomposition of wages (Abowd, Kramarz and Margolis, 1999) and calculate firm wage 19The monthly labor force status and wage indicators originate from the Hungarian Social Security Administration. The demographic indicators originate from the National Health Insurance Fund Administration of Hungary. The firm-specific indicators originate from the National Tax and Customs Administration of Hungary.

> 20We focus on firms with double-entry bookkeeping as most quality measures (e.g. TFP) are only available for them. In addition to that we exclude from the benchmark analysis seven firms which have more than 10,000 workers—very large and unique firms in the Hungarian context—to avoid outliers driving the results. Appendix Table B2 shows that our results are robust to the inclusion of the largest firms and single-entry bookkeeping firms—the estimated employment effects and heterogeneity results by firm quality are stronger under the extended

21 We use the _prodest_ Stata module of Rovigatti and Mollisi (2020) and apply the estimation procedure of Wooldridge (2009). We regress the logarithm of value added (gross revenue minus the cost of goods sold) on year effects, the logarithm of firm size (variable input) and the logarithm of subscribed capital (state variable), while using material and service costs as proxies for unobserved productivity. The TFP is the residual estimated from this regression. Finally, we take the firm-specific average of the TFP indicator over 2010-2015.

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