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Published in: Small Business Economics 1/2022

14-01-2021

What happens in criminal firms after godfather management removal? Judicial administration and firms’ performance

Author: Francesca M. Calamunci

Published in: Small Business Economics | Issue 1/2022

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Abstract

In this paper, I assess the causal effects of judicial administration on a sample of Italian criminal firms in the period 2004–2016 to shed light on the dynamic path of the firm’s performance from pre-seizure to the post-entry judicial administration phase. By using exogenous enforcement law decisions imposed by authorities for each case, I estimate their impact, highlighting the economic consequences of having new legal governance aiming to establish legality and the perpetuation of activities. The results show that there are adverse effects on profitability and efficiency with an increase in the leverage level. The empirical evidence shows how organised crime firms are intrinsically managed by their dark criminal side; removing the criminal ties makes it challenging to maintain profitability and efficiency. Overall, the negative results are due to difficulty in establishing a new economic framework for (ex-criminal) firms in which they are able to operate efficiently and according to market rules.

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Appendix
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Footnotes
1
For the purpose of this study, I use the expression criminal firm to indicate those companies that have been confiscated due to the connection with members of criminal organisations.
 
2
Financial information was not available before 2004 and 2016 is the latest available period.
 
3
The literature(Athanassopoulos and Ballantine 1995; Clementi and Maruotti 2007) emphasises that efficient frontier approaches seem to appear superior compared to the use of traditional financial ratios from accounting statements in terms of measuring performance. Both approaches contribute to obtaining a complete analysis of the performance profiles.
 
4
The register is online recently and the total official number of judicial administrators is not available (UNODC 2014).
 
5
For example, it is required not to undertake relations with suppliers in the case of suspicious connections, or to nullify agreements incurred with organised crime affiliates.
 
6
In January 2020, the ANBSC presented a case study on the Immobiliare Strasbourg company with the aim of ‘recognising reliability’, using digitalised reputational rating as a tool to evaluate the entire production chain and distributional network of the firm.
 
7
Known as Protocollo d’intesa per la gestione dei beni sequestrati e confiscati, it is signed between courts—preventive measure section—and various local authorities (prosecutors, ANBSC, municipalities, council of accountants and accounting experts, trade unions, anti-mafia associations, etc.).
 
8
Even if the reliability of accounting data can be questioned, it can help to understand its role in the mechanism of the criminal economy. In this respect, accounting contributes to the concealment of crime by conferring the impression of rationality and credibility (Compin 2008). This understanding of accounting data derives from recent research in which financial statement information is used to understand the characteristics and the mechanisms of criminal companies (Fabrizi et al. 2017; Transcrime 2013; Ravenda et al. 2015a; Bianchi et al. 2017).
 
9
Although this aspect deserves more research attention, empirical investigation is problematised by difficulties in obtaining adequate data, since (1) it is difficult to compare pre-JA and JA management qualities, given that such firms are usually managed by an OC owner, replaced by a figurehead in official documentation, meaning that the observed change in management quality would not be real; and (2) the profile of the appointed judicial administrator is not always available. Ideally, surveys could provide detailed information on various aspects of entrepreneurs and firms (e.g. Carbonara et al. 2019.
 
10
This aspect will be taken up in Section 7.
 
11
When estimating each ratio including controls for sector-by-year FE and region-by-sector-by-year FE, the results were unchanged.
Table 3
Leverage aspect
 
(1)
(2)
(3)
 
Leverage
Leverage
Leverage
JA
− 0.0003
0.0721**
0.0597***
 
(0.0325)
(0.0291)
(0.0267)
Profit
–0.4341***
   
(0.1183)
Size
− 0.0203*
   
(0.0112)
Fix asset
0.0866
   
(0.0955)
Year FE
YES
YES
YES
Firm FE
NO
YES
YES
Observations
1957
1957
1957
R-squared
0.0090
0.7791
0.8053
Number of firms
413
413
413
Dependent variable are indicated in the first row: Leverage. The estimated coefficients are from model (1) in the text. Models estimated are with OLS. Standard errors clustered at the firm level are in parentheses. Significance at the 10% level is represented by *, at the 5% level by **, and at the 1% level by ***
 
12
The non-linearity of the econometric specification for the stochastic efficiency analysis obstructs the convergence of the two stochastic frontiers using the subsamples, leading to imprecise results. However, the precisely estimated coefficients are consistent with the main results and coherent with the results provided by Table 6.
Table 6
Effects of judicial administration by sectors
 
(1)
(2)
(3)
(4)
(5)
(6)
 
ROA
ROI
Leverage
ROA
ROI
Leverage
Panel A
 
Labour-intensive
  
Capital-intensive
  
JA
− 4.1613*
− 1.4210
0.0754*
− 4.6104**
− 3.0396
0.0832**
 
(2.4311)
(1.6444)
(0.0435)
(2.1375)
(2.4657)
(0.0393)
Year FE
YES
YES
YES
YES
YES
YES
Firm FE
YES
YES
YES
YES
YES
YES
Observations
1033
1033
1033
924
924
924
R-squared
0.4771
0.4711
0.8032
0.5340
0.4115
0.7619
Number of Firms
222
222
222
191
191
191
Panel B
 
Tradable
  
Non-tradable
  
JA
− 3.3182*
− 2.2999
0.0510*
− 5.0261**
− 2.5419*
0.0852**
 
(1.9257)
(3.0764)
(0.0291)
(2.1595)
(1.3348)
(0.04123)
Year FE
YES
YES
YES
YES
YES
YES
Firm FE
YES
YES
YES
YES
YES
YES
Observations
605
605
605
1352
1352
1352
R-squared
0.6077
0.4356
0.7989
0.4704
0.4440
0.7770
Number of Firms
124
124
124
289
289
289
Models estimated are with OLS. Standard errors clustered at the firm level are in parentheses. Significance at the 10% level is represented by *, at the 5% level by **, and at the 1% level by ***
 
13
Leads and lags are estimated separately to preserve a meaningful number of observations.
 
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Metadata
Title
What happens in criminal firms after godfather management removal? Judicial administration and firms’ performance
Author
Francesca M. Calamunci
Publication date
14-01-2021
Publisher
Springer US
Published in
Small Business Economics / Issue 1/2022
Print ISSN: 0921-898X
Electronic ISSN: 1573-0913
DOI
https://doi.org/10.1007/s11187-020-00439-4

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