Describe, explain and understand the causes and consequences of downsizing on corporate performance in France (1996-2016)
In a country where firms’ competitiveness and structural unemployment are priority objectives of economic policy, the analysis of downsizing is critical. This is why MEADOW seeks to describe this phenomenon, to identify its causes and to explain its consequences on business performance. First, MEADOW describes the extent of downsizing, characterize the companies that tend to reduce their workforce, as well as the characteristics of the downsized workforce. Rather than repeating a priori the current typology in the literature - yet ill-established empirically - between «offensive« or «defensive« downsizings, MEADOW proposes a typology based on the accounting, economic and social data that public statistics routinely collects from plus-20-employee companies more. Thus, it becomes possible to assess the extent to which restructuring is preceded or not by business downturns, changes in the scope of business activities or financial difficulties. Econometric models will then test plausible scenarios that explain why a particular type of enterprise tends to reduce its workforce. These scenarios draw from case studies. Finally, it will be necessary to assess the short and medium-term effects of these reductions on the economic and financial performances of companies, as well as on the morphology of the workforce in companies that have resorted to restructuring.
MEADOW resorts to 3 methods.
First, MEADOW builds a data warehouse that allows to combine, for the period 1996-2016, the information contained in 8 series of official statistics: DADS-Posts, DADS-Panel, DADS, DMMO, BRN, FARE, FICUS , LIFI. The data warehouse provides researchers with stable sets of reliable data on labor movements, its characteristics and the accounting of companies. Thus, the documentation and the cleaning of the data are carried out systematically and collectively by MEADOW, upstream of the statistical and econometric analyzes, rather than repeated by each researcher every time she undertakes a new research.
To design plausible scenarios for downsizing, MEADOW also conducts case studies of companies of different sizes, in various sectors and whose accounting statements indicate contrasting economic and financial situations. From these cases stand out several ways to restructure, depending on the management decision to consider labor as an adjustment variable in its adjustment or redeployment strategies.
Eventually, MEADOW uses econometric methods developed for the evaluation of public policies, in particular difference-in-differences analysis with propensity score matching. These econometric methods make it possible to identify the causes of the job cuts, taking into account, in particular, the survival bias inherent in the phenomenon to be explained (the information available concerns only companies that have not disappeared). MEADOW estimates it by reconstructing the probability of a firm going bankrupt (with the inverse Mills ratio).
After 16 months, the first results of MEADOW concern the data warehouse, measuring the extent of job cuts and the constitution of a dozen case studies.
The data warehouse now includes X tera of data searchable through SQL queries and documentation that lists the main characteristics of this data (label, format, size), now homogeneous and without duplication. With the teams of the CSAD, MEADOW plans to design a process for the certification of the warehouse.
The first descriptive analyzes confirm that companies that reduce their workforce have indicators of economic or financial performance that are not as good as the rest of the companies. In addition, industrial firms relied more heavily on job cuts than firms in other industries. Since the beginning of the 21st century (2001-2014), more than one industrial enterprise out of two has reduced its workforce. However, after the start of the financial crisis in 2007, it was the service companies that reduced their workforce the most. Moreover, in services as in commerce, the companies which then reduced their workforce were not distinguished from the others by a less business activity, on the contrary. With regard to the affected workforce, male employees or (skilled) workers seem to be more specifically affected.
For each of the 12 case studies, MEADOW has reconstructed the accounts of the companies (based on the information available in the commercial database DIANE BvD), sorted the information available in the economic press (through the FACTIVA and EUROPRESSE databases) and undertook preliminary interviews with executives of these companies to explain why and how the job cuts were decided.
In collaboration with the CASD team, MEADOW is considering, in addition to the work plan established for the application, to contribute to the continuation of the data warehouse. It would involve designing and implementing a certification procedure for datasets extracted from MEADOW, in order to facilitate its reuse by other teams of researchers. That is why, the principal investigator proposes to the ANR the formalization of a WP 7 dedicated to this certification, on the model of the microsimulator INES(https://www.insee.fr/fr/information/2021951).
Dario Colazzo, Paul Lagneau-Ymonet, Caroline Mai, Benedicte Reynaud, Nesrine Yayahoui have written a first working document that describes the design and implementation of the data warehouse, as well as the information it contains. In electronic form, it aims to become the user guide of the warehouse.
Thibault Darcillon, Paul Lagneau-Ymonet and Bénédicte Reynaud complete the first draft of the exploratory data analysis. This second working document deals with the destruction of jobs in companies with more than 50 employees in France between 2001 and 2014 (pending the availability by DARES of the retrovocated DMMO series).
The interdisciplinary team (business and accounting, computer science, economics, econometrics and sociology) intends to describe the causes and consequences of downsizing and to assess its causal effect upon the performances of companies, at the firm and group levels, in contemporary France (1996-2015). The team uses the econometric methods developed for evaluation studies, notably the differences-in-differences model using propensity-score matching. Then, the team focuses on the impact of sales shocks on employment changes. The team also assesses the survival bias that depends on the probability for a company to go bankrupt. The team combines sources that are hardly matched (LIFI, DADS, DMMO, BRN, FARE, FICUS and BODACC) and develops an original database. It relates these information for stand-alone companies and it enriches these sources for subsidiaries with the consolidated annual accounts of the groups that are listed in the CAC All-Tradable and the downsizing operations that have occured withhin their perimeters.
Madame Benedicte REYNAUD (Institut de Recherche Interdisciplinaire en Sciences Sociales UMR 7170)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
IRISSO Institut de Recherche Interdisciplinaire en Sciences Sociales UMR 7170
Help of the ANR 332,897 euros
Beginning and duration of the scientific project: September 2017 - 42 Months