Abstract
Following the example of other European countries in recent years, two major reforms of dismissal regulation were implemented in France in 2016 and 2017. The aim of this article is to assess, from a microeconomic perspective, the effects of these reforms on the hiring and dismissal decisions of French firms. Does making dismissals easier increase dismissals and stimulate hiring? We also ask what is the role of this institutional factor in firms' decisions relative to two other factors: the strategies used by firms in their use of the law and in the management of their workforce; as well as the aggregate effects or the business climate. To this end, we constructed an original database that follows a panel of firms between 2016 and 2019. To take into account the great heterogeneity of employment management practices across firm sizes, this database is then divided into 4 bases—from very, very small firms (fewer than 5 employees) to large firms (50 employees or more). Based on the estimation of several fixed-effects models, we show that the reforms may have played a role in employment decisions, but only in hiring, and especially for small firms (less than 10 employees). However, for these small firms, hiring decisions are also, if not more, driven by employee departures in a human resource management logic. Large firms however are less affected. Finally, aggregate effects reflecting the macroeconomic business climate largely explain the trend in hiring and dismissals over the period, except in the case of large firms, where changes in individual practices may have had a temporary effect on these trends without changing the overall trend.
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Source: MMO-DSN, Dares; FARE, Insee; author’s estimations on the balanced panel of 321,725 firms. Note: To obtain these trends in base 100 in 2016:—for the graph on the left, simply multiply the coefficients estimated by the models by 100 to obtain percentage points (see Table 9 in the Appendix) and add 100;—for the graph on the right, calculate the exponentials of the coefficients estimated by the models (see Table 9 in the Appendix), minus 1 and multiply by 100
Source: MMO-DSN, Dares; FARE, Insee; author’s estimations on the balanced panel of 321,725 firms. Note: To obtain these trends in base 100 in 2016:—for the graph on the left, simply multiply the coefficients estimated by the models by 100 to obtain percentage points (see Table 10 in the Appendix) and add 100;—for the graph on the right, calculate the exponentials of the coefficients estimated by the models (see Table 10 in the Appendix) and multiply by 100
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Notes
This research is situated within this framework. More precisely, our research has been used to support the work of the “Evaluation Committee” and has benefited from the financing of the research and statistical department of Ministry of Labor (Dares). France Stratégie is the institute that replaced the former “Commissariat Général au Plan”.
It also depends on the initial level of employment, or the initial level of adjustment costs, or even on the nature and persistence of uncertainty.
The subsidies continued in 2016 but on a smaller scale.
Here and in the rest of the text, the term flexibility refers to the only form of external flexibility.
See Allen et al. (2017) for the example of the use of temporary work according to three factors: institutional, firm characteristics and their business system.
For individual economic reasons, in addition, employers must inform staff representatives, and attempts to reclassify their employees—the latter is also applicable for incapacity.
Until September 2017 (see below), this amount was 1/5th of a month's salary per year of tenure for years up to 10 years of tenure, and 1/3rd of a month's salary per year of tenure after 10 years.
There are differences of up to 10 years of employee seniority between firms with more or less than 11 employees.
They continue a trend of labor law deregulation reforms that began a decade earlier (in 2009 with the creation of the "mutually agreed termination"), with each reform going a little further than the previous one. This makes it difficult to assess and identify the impact of these various reforms.
This hiring bonus applied to firms with fewer than 250 employees. It provided financial support for the hiring of employees on permanent contracts and fixed-term contracts of more than 6 months. It applied to employees paid less than 1.3 times the minimum wage. It amounted to 500€ per quarter for a full-time employee during the first 2 years of the contract, so could theoretically reach 4,000€ per employee.
Precisely, introduced in 2013, the CICE was presented as a corporate tax reduction for all firms, regardless of size. In 2016, its rate was set at 6% of the gross payroll, excluding salaries above 2.5 times the minimum wage, then increased to 7% in 2017, and again to 6% in 2018. In 2019, these 6 points of CICE have been transformed into a definitive reduction of the same level in the employer's social security contribution rate.
Access to some confidential data, on which this work is based, was made possible within a secure environment provided by CASD—Centre d’accès sécurisé aux données (Ref. 10.34724/CASD).
The information is not produced at the same level depending on the database—establishments of a firm (if multi-establishment) for MMOs, firms for FAREs –, nor on the same time unit (monthly, annually), the field may be slightly different, etc., so certain steps must be taken to match the data.
As is often the case with data containing continuous economic and financial variables, it is necessary to remove negative values (for variables that cannot be negative) and outliers.
Indeed, the "total lockdown" measures implemented in France from mid-March to early May slowed, if not stopped, a number of activities in the country. At the time, firms made extensive use of "partial activity" measures ("short-time working" equivalent) to avoid dismissals. Hiring also declined during lockdown. Although there was a catch-up phenomenon in the following two quarters of the year, it was not total. Between 2019 and 2020, there was a 20% drop in permanent hiring, 6% in dismissals, 3% in mutually agreed terminations, and 18% in trial period endings (see for example and in French, Barry 2021). Including this year in our analysis would necessarily distort the results, and it can only be analyzed on its own.
As the panel is balanced, there is virtually no change in distribution over the course of four years.
Among dismissals for economic reasons, mass dismissals or redundancies leading to special procedures are not in the majority and only affect a minority of firms. Therefore, they are not excluded from the analysis. Only the dependent variable of the number of dismissals (whatever the reason) was truncated for the sample of large firms (if more than 200 in the year).
The ROA is the ratio of the gross operating surplus and the firm's economic asset.
The ROE is the net income divided by shareholders' equity.
The investment rate is the ratio of the gross tangible investments excluding contributions and the value-added excluding taxes.
The capital intensity is the gross fixed assets divided by the average number of employees.
GDP grew by 1.1% in 2016, 2.3% in 2017, then slowed down to 1.9% in 2018 and 1.8% in 2019. The business climate showed a steady upward trend between early 2016 and early 2018, followed by a slight decline and stagnation, but still at a higher level than in early 2017. Similarly, the indicator of economic turnaround has remained consistently positive and above 0.8 since the end of 2016. A slight slowdown in GDP is nevertheless observed in the 4th quarter of 2019 (−0.1%).
On condition that there are at least 10 firms in a NAF code (entitled APE for main activity of the firm) in our sample; if there are fewer than 10 firms, the variable is left unchanged.
Including in the event of dismissals for personal reasons, if firms hold their employees to the same level of performance expectations for results as they would in times of growth.
For the technical details of these econometric models, see for example: Croissant and Millo (2019), Woodridge (2010).
As is increasingly common, we prefer to estimate a linear probability model for binary variables, which is simpler to compute for fixed effects specifications.
E.g. in 2018: (0.12)/0.04 = 3.
According to Table 1: for example, for VVSEs in 2017, ((124.7–113.5)/56.6)*100 = 20%.
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Acknowledgements
The author would like to thank Julie Valentin, who participated in the initial research from which this article was drawn, and who also proofread the text. The usual disclaimer applies.
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Dares-Ministère du travail,CASD – Centre d’accès sécurisé aux données,Ref. https://doi.org/10.34724/CASD.
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Appendix 1
See the Table 6
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Signoretto, C. Dismissal regulation and hiring and dismissal decisions: a decisive factor? the case of the French labor market reforms. Eur J Law Econ (2024). https://doi.org/10.1007/s10657-024-09805-z
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DOI: https://doi.org/10.1007/s10657-024-09805-z
Keywords
- Dismissals regulations
- Labor market reforms
- Hiring and dismissal decisions
- Human resource management
- Business cycle
- Firm database