Do firms train older workers when they change?
Evidence from a French linked employer-employee survey
Nathalie Greenan*, Mathieu Narcy** and Stéphane Robin***

Extended abstract
The aim of this paper is to investigate whether the impact of firms’ technical andorganisational changes on their employees’ incidence of training varies with the age of theworkers. To do this, we use 2006 COI survey which is the most recent French matchedemployer-employee data set on firms’ organisational changes and computerization but also
two others databases from government origin: the DMMO files and the “24-83” employers’
tax declarations. The final sample is an original statistical dataset obtained by merging thesethree data sources which allows us to deal with econometric problems such as endogeneity
and selection effects.
The capacity of older workers to adapt to an environment of rapid technical andorganisational changes is crucial in the context of an increase of the employment rate of olderworkers. In fact, according to the so-called age-biased technological change hypothesis, thetechnological and organisational changes would lead to a reduction of the percentage of olderworkers in the workforce, particularly because of the depreciation of their human capital.
Nevertheless, this argument is only partial since the employees’ human capital evolves in
response to these changes trough training. So, as Bartel and Sicherman (1993) point out, if
technical and organisational changes stimulates further training for older workers, then it
gives incentives to stay in the job. From the workers’ point of view, Langot et al. (2009) showthat human capital increases and retirement age decisions are positively related. Furthermore,training responses may be different according the age of workers. Overall, in a theoreticalperspective, the influence of technical and organisational changes on the relative training
investments of older workers compared to younger ones is indeterminate, which motivates ourempirical research.
We use three data sources that we have matched together. First, the data on employee
further training and the measures of technical and organisational changes come from a Frenchlinked employer-employee survey on organisational changes and computerisation(“Changements Organisationnels et Informatisation”, COI) conducted in 2006. Second, the“24-83” employers’ tax declarations for the years 2003-2006 provide firm-level data aboutfurther training practices of employers. Third, the DMMO (“Déclarations de Mouvements deMain d’Oeuvre”) files for the years 2003-2006 also provide firm-level data about all
workforce entry and exit movements within firms.
The COI linked employer-level survey covers 7 700 firms with 20 or more employees
belonging to the private sector. Each firm fills in a self-administrated questionnaire on the use*: Centre d’études de l’emploi and TEPP (FR n°3126, CNRS).
E-mail : nathalie.greenan@cee-recherche.fr**

Corresponding author :Centre d’études de l’emploi and TEPP (FR n°3126, CNRS).
Address: 29 promenade Michel Simon 93 166 Noisy-Le-Grand, France.
Phone number: +331 45 92 69 58
E-mail : mathieu.narcy@cee-recherche.fr***

BETA (UMR 7522 CNRS), Université de Strasbourg, and Centre d’études de l’emploi.
E-mail : robin@cournot.u-strasbg.fr

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of information technologies and new managerial tools in 2003 and 2006. The rich set of
information allows us to built two synthetic indicators. The first one synthesises information
about ten different features of the technology and measures the degree of use of new advanced
technologies (internet access, intranet, data analogies tools…). The second one combines
information about the use of eleven management tools (quality certification practice, just-intime, total productive maintenance…). For each firm, these two synthetic indicators have beencreated for the two years 2003 and 2006. By comparing the level of these two indicators
between 2003 and 2006, we create two dichotomous variables. The first takes the value one if
the firm is characterized by more intensive use of their new advanced technologies between
2003 and 2006 and otherwise zero. The second takes the value one if the firm is characterizedby more intensive use of their managerial tools between 2003 and 2006 and otherwise zero. A
third dichotomous variable has also been considered signalling if the management of the firm
has perceived a major organisational change since 2003. Finally, in our econometric analysis,
we consider the influence of these three different dichotomous variables measuring changes
and derived from the employer-level survey on employees further training incidence.
The employee-level survey concerns 14 369 employees randomly selected within eachsurveyed firm. This survey provides details of employees’ socio-demographic characteristics,
their employment situation and their job characteristics. Moreover, it allows measuring theincidence of several types of training: training in computer skills; training for supervisoryrole; training for client dealings; training for quality control procedure and other type oftraining. The year on which training incidence is observed is known. Consequently, we canprecisely investigate whether employees have or not received training during the period where
the technical and organisational changes have taken place within the firm. Finally, workers
were asked the three following questions: “Has you work or that of your colleagues changed
since 2003: 1. due to one or more changes to technique used? 2. due to one or more changes
in working methods or distribution? 3. due to an financial restructuring buyback ormanagement team changes?”. The influence of these three variables of changes on
employees’ further training incidence will be estimated and the results obtained will beconfronted with those obtained from the variables derived from the employer-level survey.
The COI survey is merged with two firm-level databases: the “24-83” employers’ tax
declarations and the DMMO files. The first data set permits to construct economic indicatorsreflecting the further training practices of employers during the 2003-2006 period. TheDMMO files are quarterly exhaustive administrative databases which measure all workforce
entry and exit movements within establishments with more than 50 employees. They allow
constructing layoff and resignation rates by age class into each firm during the 2003-2006
period. We use these rates in the training equations in order to partially control the selection
effects due to the fact that technological and organisational changes can reduce theemployment of older workers.
The econometric strategy consists in estimating for each type of training measured at theemployee level, the influence of the different employer and employee level variables ofchanges. The analysis is broken down into three different age classes: [20,29], [30,45] and[46,59]. In order to handle endogeneity of each variable of changes, we estimate biprobit andtriprobit models. In fact, the two employer-level variables signalling a more intensive use of
new advanced technologies and management practices between 2003 and 2006 aresimultaneously introduced in training equations whereas the other variables of changes are
considered one by one.
Three main conclusions can be drawn from the preliminary obtained results. First, thepositive relationship between changes and further training incidence is greater when theemployee-level variables of changes are considered rather than those from the employer-level
survey. Second, technical and organisational changes influence positively the further training

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incidence of employees of 30 years old and more with solely weak differences between theage classes [30,45] and [46,59]. Consequently, the changes do not seem to penalise older
workers concerning their probability of further training. Third, the relationship betweenchanges and incidence of training is very weak among the younger workers highlighting theinfluence of their formal qualification.
Keywords: J14, J24, O30.
JEL Classification: Technical and organisational changes, training, older workers.
References
Bartel A. and N. Sicherman (1993), « Technological Change and Retirement Decisions ofOlder Workers », Journal of Labor Economics, 11(1), pp. 162-183.
Chéron F., Khaskhoussi F., Khaskhoussi T. and F. Langot (2009), « Incentives Schemes toDelay Retirement and the Equilibrium Interpaly with Human Capital Investment », Economic
Bulletin, 29(1) pp. 221-229.

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