3. Empirical Analysis
The main data source is provided by the Relação Anual de Informações Sociais [RAIS, Ministry of Labour and Employment, Brazil] which collects annual information on formal establishments in Brazil and is a rich source for survival studies. In fact, Mata and Portugal (1994) considered an analogous source for the case of Portugal. We were granted special access to the identified microdata over the 1995-2005 period that provides total employment on December 31st each year. It is important to stress that the referred survey has a census character and that non-responses lead to heavy fines. The initial 8 digits of the numerical identifier (cadastro nacional de ...view middle of the document...
Finally, the possibility of wrongful identification of newly created firms does not seem to be a problem. In fact, conversation with an official from the Revenue Services-Ministry of Finance who deals with the issuing of the numerical identifier code (CNPJ) indicated that a non-response would imply the cancellation of the firm’s record. Thus, taking 1995 as reference, a firm that did not file the report in 1996 could at most re-appear again (and induce a mistake) in 1997. Therefore, we considered a 2 years window for defining newly created firms, but in fact there were only 19 of such cases, which were deleted.
In addition to the survival information, some covariates were constructed upon the same data source but alternative data sources were also used. It is worth mentioning that the majority of survival studies in developed countries considered covariates that were not time-varying and thus relied on covariates referring to the initial year of the sample. In the present paper, a more general model is adopted. The following variables are considered in the empirical model and are analogous to those considered by Mata and Portugal (1994). Industry variables were considered in terms of two-digit sectors [classification CNAE4-Instituto Brasileiro de Geografia e Estatística-IBGE]:
. Size: logarithm of firm size (total number of employees). Firm size is reported in different studies to have an important role in facilitating survival, possibly related to scale efficiency aspects. Therefore it is expected to exert a positive effect on firm survival. This is the only explanatory variable of the study defined at firm-level as the remaining covariates are of a sectoral nature;
. Growth: annual industry growth (in terms of the log difference in successive years for total employment in the sector). A more dynamic industry is likely to favour the survival of newly established firms unlike more mature and stable industries which would be less likely to accommodate new entrants. Thus, one would expect a positive effect of that variable on firm survival;
. Entry rate: measured as the proportion of new firms in a given year relative to the total stock of the previous year. This variable is likely to reflect competitive pressures accruing from new competitors and one would expect to entail a negative impact on firm survival if a minimum and non-negligible scale is required in a given sector;
. Industry size: logarithm of the number of firms in the industry. The larger that size the more likely would be the accommodation of new entrants. Apart from the dynamic potential of an industry that is captured by Growth, it aims to indicate static potential for accommodation of new entrants;
. Minimum efficient scale (MES): the proxy was the median size of the firms in each four-digits industry. Despite not being an ideal measure it has been suggested on different occasions [see e.g. Sutton (1991)]. The larger the MES, the more difficult it would be for smaller firms...