Short-Time Compensation and Establishment Survival: An Empirical Analysis withFrench Data *Oana Calavrezo∗∗, Richard Duhautois∗∗∗, Emmanuelle Walkowiak∗∗∗∗Extended abstract

This paper questions about the efficiency of the short-time compensation (STC)
program within French establishments by investigating the relationship between the STC use
and establishment survival between 1995 and 2005. The STC program is a device ofemployment protection since it aims at avoiding layoffs in the case of short-term economic
downturns or exceptional circumstances (for instance, disasters). Employers applying STC
can temporarily reduce their employees’ activity below the legal working time or eliminate apart of their total activity. STC allows employees to maintain a contractual bond with theiremployer. They receive a compensation for their wage loss that is partly paid by the State.
Most developed countries use some form of an STC program: the “Chômage Partiel” inFrance, the “Cassa Integrazione Guadagni” in Italy, the “Kurzarbeitergeld” in Germany, andthe “Short-Time Compensation Program” in the United States. Since the beginning of theeconomic crisis, the use of STC programs has been amplified especially in Europe.
From a theoretical point of view, the international literature clearly distinguishes thesecurity and flexibility roles of the STC programs which differentiate North American andcontinental European systems (see the three main papers on this topic: Van Audenrode(1994), Houseman and Abraham (1994) and Burdett and Wright (1989)). The empiricalanalysis of the security role of STC focuses on its relationship regarding layoffs. We candistinguish three experiences concerning this relationship between STC and layoffs: theEuropean experience (Vroman, 1992), the US experience (Needels et al., 1997) and theCanadian experience (the Ekos research, 1993). Most studies find that firms in both theAmerican and the European systems are likely to use some combinations of STC and layoffs
but the implications of STC on layoffs still remain unclear. In a previous study, Calavrezo,∗

This work is an extension of a project financed by the Statistical Department of the French Ministry of Labour(DARES). Data availability: Final sample is available on request from the authors and initial databases can berequested from the institutions which produce them.
∗∗
Corresponding author: University of Orléans - Laboratoire d’Economie d’Orléans (LEO) and Centre d’Etudesde l’Emploi (CEE). Address: LEO, Faculté de Droit, d’Economie et de Gestion, Rue de Blois, BP6739, 45067,Orléans, CEDEX 2. Telephone number: +331 45 92 69 72. Fax: +331 45 92 69 97. E-mail:oana.calavrezo@etu.univ-orleans.fr∗∗∗
CEE-TEPP, University of Paris-Est-Marne-la-Vallée and CREST. richard.duhautois@cee-recherche.fr∗∗∗∗
University of Paris12 - ERUDITE and CEE-TEPP. emmanuelle.walkowiak@univ-paris12.fr1

Duhautois and Walkowiak (2009) analyze the effect of the French STC program on layoffs.
They work with a panel of more than 36,000 French establishments with at least 50
employees and their results show that STC seems to significantly increase the number oflayoffs or the probability of laying off. These empirical studies do not take into account
whether firms survive or not. In this paper, we test the effect of STC on establishment
survival.
We work with several annual samples. Our final samples are original statistical
datasets obtained by merging five data sources. First, the STC databases provide exhaustive
information about the STC authorizations obtained by French establishments. They cover theperiod 1995-2005. These files permit to construct for each establishment and for each year
dummy variables indicating the participation in the STC program. Second, we use theSIRENE file. It is an administrative database indicating the situation of French establishments(establishments are active or they exit) and it also gives information on the date of creation ofestablishments. This file permits to calculate the age of the establishment and three survival
dummy indicators: being active during the year of interest, being active a year after and being
active two years after. Third, we use annual exhaustive administrative sources describing
establishments affiliated to the unemployment insurance system and covering the 1995-2003
period: They give information about establishment size, establishment industry and about thestructure of jobs within the establishment (women rate, etc.). Fourth, additional information is
obtained from firm databases. They cover the period 1994-2005. They permit to constructindicators of the economic health of the firm to which the establishment belongs to (the valueadded variation rate, the labor productivity ratio, investment, etc.). From 1998, several othervariables are also given: the legal status of the firm, a variable indicating whether a firm wasrestructured, a variable indicating whether the firm belongs to a financial group. Finally, some
supplementary information is obtained from other administrative files containing data at theestablishment level. We mainly retain information about employee skill structure.
In order to obtain annual final samples, we impose three stages in the “cleaning”
process. The first stage consists in erasing establishments which are supposed inactive,
establishments which exit before the year of interest or are created after the year of interest(for example, for the year 2002 we erase establishments which “die” before 2002 or arecreated after 2002). In the second stage, we eliminate firms with 0 employees in order not tohave incoherent values in terms of STC use. Finally, we erase all observations with missing
values for our explanatory variables. By merging the five data sources we finally work eachyear with more than 1 million observations.
2The use of STC among French establishments is not randomly distributed. Soselection can be a potential problem because establishments which choose to have STC
authorizations might do it as a consequence of their internal strategy. In order to analyse theeffect of the French STC program on establishment survival and to control for the selection
bias, we implement the propensity score matching methodology developed by Rosenbaumand Rubin (1983) and Heckman et al. (1999). This method consists in comparing the health ofeach establishment which receives the treatment (uses STC) with the health of an identicalcounterfactual establishment which does not receive the treatment (does not use STC). In thiswork, establishment health is given by survival dummy variables (being active during the yearof interest…). To identify statistically the counterfactual establishment, an approach consists
in building a counterfactual population for which the distribution of the propensity score
calculated according to a number of observable characteristics is the same as for the group
receiving the treatment. As the number of establishments which do not use STC is very high(the control group1), we perform matching using the nearest neighbour method (moreprecisely, one-to-one matching). In order to calculate the propensity score, we use threedifferent model specifications (because of the availability of the variables): the first model isestimated on the 1995-2005 period and contains the following variables: establishment’s size,
age, industry and geographic location, firm’s apparent labour productivity and value-added
variation rate; the second model is estimated on the 1998-2005 period and excepting theprevious variables, contains firm’s investment, firm’s legal status, situation regarding firm’srestructuring variables and firm’s membership in a financial group; and the third model isestimated on the 2002-2005 period and contains supplementary variables of employee skillstructure.
Our principal result underlines that the STC use increases significantly the probabilityof establishment exit. For example, in 2002, using STC increases by 3% the probability for an
establishment to exit the same year2. Additional econometric strategies (a Choice BasedSampling approach) and different subsamples are used in this paper for testing the robustnessof results: The results hold.

Key words: Short–time compensation program, establishment survival, nearest neighbour
matching estimates
1

For example for the year 2002, the final sample contains 1.3 million establishments and only less than 4,000
establishments participate in the STC program.
2This result is obtained using the third model specification.

3