Marco Maria Mattei

Un nuovo approccio statistico per l’individuazione delle manipolazioni degli utili: evidenze empiriche dal mercato italiano

Mediante uno studio di simulazione, questo articolo si propone di valutare l’efficacia nel mercato italiano dei metodi comunemente utilizzati nella letteratura nord-americana per individuare le manipolazioni di bilancio. Inoltre, viene proposta una nuova metodologia di stima degli accrual model - il modello delle misture - che non si basa su nessuna classificazione industriale e risolve alcuni dei problemi che questi metodi di indagine manifestano nei paesi con mercati finanziari di minori dimensioni. Dalle analisi svolte emerge che le tecniche d’indagine ampiamente utilizzate a livello internazionale sono efficaci anche nel nostro Paese e che il modello delle misture aumenta significativamente la potenza del test piu efficace per ricercare la presenza di manipolazioni di bilancio. Complessivamente questi risultati indurrebbero a concludere che gli accrual model potrebbero essere utilizzati maggiormente dai ricercatori interessati ad investigare la presenza di politiche di bilancio in Italia.

Estimating accruals models in Europe: industry-based approaches versus a data-driven approach

Abstract Accruals models have been estimated using a variety of approaches, but the industry-based cross-sectional approach currently seems to be the standard method. This estimation approach cannot be easily used in the vast majority of European countries where several industry groups do not have sufficient yearly observations. Using data from France, Germany, Italy and the UK, we artificially induce earnings manipulations to investigate how the ability to detect those manipulations through accruals models is affected by the use of different industry classifications. Moreover, we propose an alternative estimation approach based on a data-driven statistical procedure that provides an optimal choice of estimation samples. Our analyses show that enlarging the industry classification and/or pooling observations across years reduces the probability of discovering earnings manipulations but allows for the estimation of abnormal accruals (AA) for more firms. The data-driven approach, however, in most cases outperforms the industry-based estimation approaches without sample attrition. This result suggests that there is still ample room for improving the accruals model estimation process for capital markets of European countries. Furthermore, the analysis documents which accruals model outperforms the others in each of the four countries and the probabilities to detect earning management in a high variety of circumstances.

Does Intellectual Capital Affect Business Performance

The aim of this paper is to assess the impact of intellectual capital (IC) on firms’ financial performance with reference to a sample of companies operating in the European Union (EU) area during the period from 2006 to 2013. The analyses are further differentiated by country of domicile, industry sector, and historical period (pre-crisis and crisis). We investigate whether the value of the components of IC is a relevant factor that influences firms’ performance, proposing and testing a modified version of the value added intellectual capital (VAIC TM ) model which also considers country-specific differences in terms of default risk. The empirical results evidence the relevance of the information on IC disclosed by companies. Differences arise depending on the reference country, industry, and historical period examined. The main limitations of the research are the unbalanced structure of the sample among countries and industries and the specificity of the examined sample (listed firms applying IAS/IFRS system). The main implication of the study is that, since we demonstrate the value relevance of IC, our findings could be of interest for standard setters for defining a standard (qualitative and quantitative) level of information on human resources to be disclosed by companies in their financial statements. Our contribution to the literature is the proposal of some relevant modifications to the original VAIC TM model and providing new evidence on the

Toward a Gov 2.0 Society for All: European Strategies for Public Service Delivery

To what extent the shift to Gov 2.0 technologies required by the latest EU strategies is changing public service delivery in practice? This chapter presents an overview of the consequences that Gov 2.0 technologies, embedded in European governments’ strategies, have on public service delivery at a practical stage. The research draws upon an in-depth study of the Gov 2.0 strategies of the European Union and the four major European economies, namely, Germany, France, Italy, and the United Kingdom. We aim at assessing the extent of the shift from Gov 1.0 to Gov 2.0 technologies in the declared strategies of the analyzed countries, and ascertaining alignment among declared strategies and actual practices put in place to foster public sector democracy in service delivery.

Analisi di sensitività al tasso di cambio: un’informazione utile per gli investitori?

Il lavoro analizza gli effetti dell’entrata in vigore dell’IFRS 7, emanato dallo IASB con lo scopo di aumentare l’informazione sull’esposizione delle imprese ai rischi di mercato. La nostra ricerca indaga l’utilita per gli investitori dell’analisi di sensitivita al rischio di tasso di cambio fornita dalle societa quotate italiane. I risultati mostrano che prima dell’introduzione dell’IFRS 7 il mercato stimava erroneamente l’esposizione al tasso di cambio, mentre successivamente la sensitivita dei rendimenti al tasso di cambio sembra allinearsi con le esposizioni dichiarate. Dall’analisi, inoltre, emerge che l’informazione sull’esposizione riduce la sensitivita dei volumi al tasso di cambio. I nostri risultati integrano la letteratura statunitense fornendo evidenze di come un’analisi di sensitivita anche backward-looking sia utile al mercato.