Page 76 - Contributed Paper Session (CPS) - Volume 4
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CPS2129 Matilde Bini et al.
                  recession, begun in 2011 and it endured until 2014. The aim of this work is to
                  collect evidence on the Italian manufacturing system with the following goals:
                  to calculate the main financial ratios related to firms’ riskiness and distress risk
                  trend by means of the book-value data (Zeli & Mariani, 2009; Zeli, 2014); to
                  detect the guide-variables outlining the firms’ riskiness and distress risk trend
                  in the period 2008-2017 (Di Clemente, 2008; Kudlyak & Sánchez, 2017); and
                  to investigate the riskiness-distress risk trend for manufacturing industries and
                  try to understand the effects of the Great Recession on this important business
                  indicator trend (Graham et al. 2011; Giroud & Mueller, 2015). To perform this
                  analysis a Latent Growth Curve Model is proposed, using an important Italian
                  private database containing the book-value data of the joint-stock company
                  Italian firms.

                  2.  Measures of firms’ riskiness-distress
                     A  large  part  of  literature  is  aimed  to  properly  classify  the  “signal”  of
                  bankruptcy  coming  principally  from  book  values  and  standard  financial
                  statements (Altman et al., 1994; Bottazzi et. Al, 2011). A lot of indicators are
                  considered in literature, among these, the most largely used ones cover area
                  of economic enterprises’ accounting related with financial distress such as:
                  liquidity, leverage, profitability.
                     The  interest  coverage  compares  net  profits  to  interest  on  loans  and
                  thereby expresses the firm’s vulnerability linked to liquidity. It can be seen as
                  a  short-term  risk  indicator  (the  lower  interest  cover  index,  the  higher  the
                  probability of financial distress). The leverage indicates the best indicators of
                  the financial distress, because the possibility to pay back the debts decreases
                  when the leverage increases (the lower leverage, the lower the probability of
                  financial distress). Profitability, measured by means of ROE, assesses the ability
                  to achieve a minimum profit share level, after covering costs.
                      In  literature  there  are  three  approaches  to  bankruptcy  prediction:
                  accounting  approach,  analytical  approach  and  statistical  one.  This  last
                  approach offers many statistical models that use balance sheet data. Statistical
                  procedures (multiple discriminant analysis, logit or probit) were the most used
                  methods in this kind of problem. Among them the factorial and latent analysis
                  can  be  applied.  A  latent  growth  curve  model  is,  innovatively,  proposed to
                  analyse riskiness-distress trend for manufacturing firms in 2008-2017 period.
                  Unlike  traditional  longitudinal  data  analysis  techniques,  LGM  allows
                  researchers to make inferences about individual level effects as well as group
                  effects.

                  3.  The Data
                     We utilize an important private database AIDA (Analisi Informatizzata delle
                  Aziende Italiane) containing the book-value data of the joint-stock company

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