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Pre-funding of the Research Tax Credit

Laurent Bach, Etienne Fize, Arthur Guillouzouic, Clément Malgouyres
April 2025
This project aims to document the impact of CIR pre-funding on innovative firms and focuses on R&D efforts, as well as the performance and survival of participating firms. More broadly, the project also contributes to understanding and evaluating the effects of the CIR.
Reference IPP Report No. 54

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Bach et al. Pre-funding of the Research Tax Credit. IPP Report No. 54. April 2025.
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Presentation

The Research Tax Credit (CIR) is currently the main form of public support for investment in research and development in France. It enables firms to deduct certain research and development expenditure from their tax liability (corporation tax or income tax).

If firms benefiting from the CIR have a positive taxable income, they must set this tax credit against the amount of corporation tax they owe at the end of the financial year. Conversely, if firms are making a loss, they can claim a refund of their CIR after the end of the financial year. This refund is paid between 6 and 12 months after the end of the financial year – sometimes longer – and therefore more than a year after the expenditure was incurred.

This timeframe is long and variable, but means that a receivable from the State remains outstanding for that period. Some firms may therefore choose to utilise this asset and apply to a lending institution to bolster their cash flow.

This project aims to document the impact of CIR pre-funding on innovative firms and examines R&D efforts as well as the performance and survival of the firms that make use of it.

Key Results

Firms that choose to have their CIR pre-financed, and are unable to do so either through a public body or a traditional bank, have some very distinctive characteristics: they are more often found in sectors specialising in R&D and IT, are predominantly young firms, generate low turnover but employ a significant number of staff, particularly engineers.

The study does not provide clear and robust evidence of a positive effect of CIR pre-financing on the survival and performance of the firms using it.

Please note:
These results must, of course, be treated with a degree of caution. On the one hand, the selection of firms for the programme is very stringent, and is based precisely on their fragile financial health, which makes it difficult to interpret changes following their participation. Indeed, despite efforts to identify a group of comparable firms, it is entirely possible that differences in financial fragility and the probability of bankruptcy remain between the groups, preventing the identification of any potential positive effect of the scheme. Despite the fact that the programme includes firms that are financially more vulnerable than others, the probability of bankruptcy following entry into the scheme is comparable to that observed in the control group, and certain positive trends are evident, such as an increase in the number of patents recorded on the balance sheets of the firms covered by the programme.

Method and Data

To construct the treatment and control groups, the authors carried out a stacked difference-in-differences analysis, combined with a propensity score matching stage.

The stacked regression method (Cengiz et al., 2019) involves stacking observations to create a new temporal dimension: distance from the treatment. Indeed, unlike reforms that would affect all firms in the treatment group at the same time (in the year of the reform), in the present case, firms enter the treatment group in a staggered manner over time.

Data used

This study draws on several sources of administrative data at firm level, which are linked via the SIREN identifier of the legal entities under study.

Data on CIR pre-financing. To characterise the use of CIR pre-financing, we use data provided by the funding body Neftys.

Data on the Research Tax Credit (MVC-CIR). The MVC-CIR data (DGFiP) correspond to the flow of receivables between the State and firms benefiting from the CIR, for each CIR year.

Tax returns (BIC-IS). In order to reconstruct all the relevant accounting variables for firms making use of CIR pre-funding – both to assign them to a control group and to measure their development across relevant dimensions – we draw on detailed tax returns from the BIC-IS source (DGFiP).

Employment data (DADS Postes and MMO). In order to characterise employment at the firms under consideration, and in particular employment in research and development, we use the DADS Postes data (INSEE), which contain all salaried jobs in a given year, at the employee–establishment level.

Furthermore, to characterise labour mobility in relation to the use of CIR pre-financing, we use the Labour Mobility (MMO-Dares) data, which enable us to reconstruct the flows of employees joining and leaving a firm on a monthly basis.

Partners

Neftys

This study was funded by Neftys, a private-sector organisation in the banking industry specialising in the pre-financing of the CIR and in supporting innovative firms.

Last modified: July 21, 2026