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Inspecting the Relationship Between Business Confidence and Industrial Production: Evidence on Italian Survey Data

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Abstract

The aim of this paper is to investigate the relationship between the manufacturing confidence indicator (CI) and the industrial production index (IPI) as well as to address the effects of the “Great Recession” on this relation. Some stylized facts about CI are firstly presented and the stability of the relationship in the framework of a linear model is subsequently explored. In addition, the findings are tested to be robust with respect to a “sample selection” effect in survey data and also to the hypothesis that they may suggest a change in the long-term trends in the industrial activity. The empirical evidence shows that: (1) the change in the relationship may be due to some cyclical reasons, rather than structural ones; (2) the performance of CI is not affected by the different permanence of firms in the panel; (3) agents are likely to adjust their production plans during the financial crisis, considering a new lower benchmark for their industrial activity in the long term. In particular, as the capacity utilization that managers consider as “ideal/sufficient” is proven to be changed over time, this finding may be consistent with the presence of non-linearities in the relation between CI and IPI.

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Notes

  1. For a survey on the literature on non-linear time series modelling, see Clements and Hendry (2006).

  2. Indeed, agricultural and service sectors are often found not to display a well-defined cyclical pattern; hence the cyclical behaviour of the manufacturing sector is often considered as a good proxy for the overall business cycle.

  3. See Table 7 in “Appendix”.

  4. The whole sample includes 368 grid cells. For further details, see also the Methodological note, available on the website https://www.istat.it/it/files//2018/06/CS-fiducia-consumatori-e-imprese-giugno-2018.pdf.

  5. For the ROAUST method see Chiodini et al. (2010); concerning the use of mixed sample design characterized by fixed and proportional allocations, see the works of Chiodini et al. (2010) and also Costa et al. (2004).

  6. In particular, the first set of options is usually used for questions asking the entrepreneurs to judge the actual level of certain variables compared to an ideal one usually defined as “normal”,“sufficient” or “satisfying for the season”. In this case no definition or criteria about the“normality” is specified by the survey and respondents are free to put in that category their own subjective meaning of adequacy.

  7. The possible option answers for these questions are shown in Table 8 in the “Appendix”.

  8. An alternative cycle, based on the filter proposed by Baxter and King (1999), was also used. The cycle extracted in this way (considering periodicities between 1.5 and 8 years) has a slightly lower correlation with CI than \(\Delta ^{12}\log {\textit{IPI}}\). Detailed results are available from the authors.

  9. It might also be the case that firms miss out on one or more waves and may return after that. In this circumstance, many tracing procedures are applied to reduce survey non-response, for example, returning the same interviewer every month in order to develop a relationship of trust between the interviewer and the respondent (Laurie et al. 1999) or encouraging panel members to continue their participation by offering them more flexibility to decide whether to respond by one mode or another, for instance, by telephone or by mail (Dillman and Christian 2005).

  10. The econometric analysis presented in Sect. 3 underlines that it is only the steep 2008–2009 that has arguably introduced non linearities in the link between CI and IPI.

  11. So, in a first approximation and with some cautions, it is possible to consider, in the remainder of the analysis, the set of the “non-long-lasting” firms as represented the “counter-factual” case or rather as those firms that present a lesser persistence in the panel over the years 2006–2010.

  12. The same conclusion holds true when looking at the climate component series and also when considering the firms disaggregated by size. The results are not here reported but are available from the authors.

  13. As documented by Wood (2011) on survey answering practices in the UK, more than 60% of survey respondents intend the concept of normality with reference to capacity levels. So, the indicator reflecting the sufficient rate of capacity utilization might be a more accurate measure of the change in the level considered “normal” by respondents than the synthetic confidence indicator (the correlation coefficient with CI is 0.43).

  14. For a detailed description of the possible option answers of these questions, see Table 8 in the “Appendix”.

  15. According to the theoretical literature, firms assessing capacity utilization as sufficient are those with zero investment gap (Caballero et al. 1995; Koeberl and Lein 2011), namely those firms with no pressure to invest. It is possible to suppose that for these firms the current level of economic performance corresponds to the underlying (normal) reference standard level of the business activity; therefore, a change in the level of capacity utilization might indicate a change in the level of the business activity considered as “normal”.

  16. When the seasonal difference of log series is above its average the wealth variable is equal 1, otherwise is equal 0.

  17. A full cycle is at least of 3 years. It is identified by peak to peak or trough to trough respectively, with the peaks and troughs detected on the seasonal difference of log of quarterly IPI through the Harding–Pagan method (Harding and Pagan 2002).

  18. In equation 4 of Table 6 the coefficient of Trough6 increases.

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Authors and Affiliations

  1. ISTAT, Rome, Italy

    G. Bruno, L. Crosilla & P. Margani

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  1. G. Bruno
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  2. L. Crosilla
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  3. P. Margani
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Correspondence to P. Margani.

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The opinions expressed in this paper are solely the responsibility of the authors and should not be interpreted as reflecting the views of ISTAT or its staff. Helpful comments from the participants to the 33rd CIRET Conference held in Copenhagen in September 2016 are gratefully acknowledged. Usual disclaimers apply.

Appendix

Appendix

See Tables 7 and 8.

Table 7 ISTAT Manufacturing tendency sample survey: number of firms by geographical area and sector
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Table 8 ISTAT manufacturing tendency survey: some selected questions
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Bruno, G., Crosilla, L. & Margani, P. Inspecting the Relationship Between Business Confidence and Industrial Production: Evidence on Italian Survey Data. J Bus Cycle Res 15, 1–24 (2019). https://doi.org/10.1007/s41549-018-00033-4

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