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The shadow of death: analysing the pre-exit productivity of Portuguese manufacturing firms

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Abstract

The pre-exiting productivity profile of mature firms relative to survivors is examined along with an evaluation of how productivity affects the probability of exit along various dimensions. An empirical approach, based on an unbalanced panel of Portuguese manufacturing firms covering a 10-year period, is used. The findings confirm that market selection forces low-productivity firms to exit, but there is also evidence that a sizeable portion of low-productivity firms do not shut down. Conversely, there is a non-negligible fraction of high-productivity firms that do actually close. Consistent with some key theoretical predictions, our analysis reveals that exiting firms have a falling productivity level over a number of years prior to exit. Finally, the results from the survival model show that both small firms and ones with low productivity are relatively much more likely to exit the market. Industry and macro-environment are also found to have a non-negligible role on the exit of mature firms.

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Notes

  1. Most empirical studies point to firms achieving the mature state somewhere between the sixth and tenth year of existence. In our dataset, the results from using an alternative threshold (e.g. 8 years) are virtually the same as the ones reported in Sect. 4.

  2. As pointed out by Headd (2003) and van Praag (2003), it would be preferable to distinguish voluntary from involuntary closures, but unfortunately (see Sect. 3.2) this distinction is not possible in our dataset. This limitation is present in virtually all empirical studies in the literature, with a few exceptions (e.g. Harada 2007).

  3. The aggregate results for the entire Portuguese manufacturing sector were also weighted. We note that Região Centro represents approximately one-seventh of the Portuguese gross domestic product and one-sixth of total employment. Either in terms of employment or output, the shares of each one of the 17 sub-sectors in the manufacturing aggregate at the national and Região Centro level are virtually the same, with the observed differences in 2000, for example, never exceeding 6% points.

  4. We note that the observation of exit is constrained by the characteristics of the IEH survey. Thus, in our dataset exit comprises bankruptcy and voluntary closure as well as the residual category of mergers/acquisitions, a rare and negligible event which according to Mata and Portugal (2002, 2004) does not exceed 1% of the total number of closures. A change in the sector of activity in turn is taken as diversification, not as an exit. All firms younger than 10 years were dropped from our sample.

  5. See van den Berg (2001) for a detailed technical description of duration models. See also Manjón-Antolín and Arauzo-Carod (2008) for a survey on firm survival methods and evidence.

  6. Right-censoring in our dataset is due to panel rotation, on the one hand, and to firm’s survival (i.e. survival after 2000), on the other. Since all firms in our sample started production some time (at least 10 years) before the beginning of the survey, the dataset is also left-censored. This is not a problem as our focus lies on the conditional probability of exit based on calendar time.

  7. This model was also implemented by Mata and Portugal (2002).

  8. At http://stats.oecd.org/wbos/Index.aspx.

  9. There was an overall slowdown in 1991–1994, followed by a clear economic recovery which in the last sub-period (1997–2000) seemed to have lost some momentum (Carreira and Teixeira 2008).

  10. Since our dataset does not contain information on employer’s attributes nor other firm characteristics, such as liquidity constrains (see Cabral and Mata 2003; Oliveira and Fortunato 2006), we cannot explicitly test the ‘non-economic forced exit’ hypothesis.

  11. Estimation was performed using the stcox command with the efron and shared options of StataSE 9.2. The strata (industry) option was not implemented given that the productivity level of exiting firms was normalized by the average productivity of survivors at the industry level. The null hypothesis of no unobserved heterogeneity was not rejected.

  12. Two explanations for the low (negative) correlation between GDP growth and unemployment are possible: the first one is associated to a wide lag between job creation and the economic cycle observed in the Portuguese economy (e.g. Baptista and Thurik 2007); the second is related to the intense restructuring wave observed in the middle of the 1990s in the Portuguese manufacturing sector (Carreira and Teixeira 2008).

  13. The robustness of the results reported in Table 9 was analysed in the context of the PWCH model. The results from this model (available from the authors upon request) are virtually the same.

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Acknowledgements

We thank two anonymous referees for their most helpful comments on the previous version of this paper.

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  1. Faculdade de Economia/GEMF, Universidade de Coimbra, Coimbra, Portugal

    Carlos Carreira & Paulino Teixeira

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  1. Carlos Carreira
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Correspondence to Carlos Carreira.

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Carreira, C., Teixeira, P. The shadow of death: analysing the pre-exit productivity of Portuguese manufacturing firms. Small Bus Econ 36, 337–351 (2011). https://doi.org/10.1007/s11187-009-9221-7

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