Evidence of Marginal Deterrence: Kidnapping and Murder in Italy

International Review of Law & Economics (2015), vol. 41, pp. 63-67 (with B.McCannon and M.Vannini)

Abstract: Empirical evidence of the marginal deterrent effect is provided. Exploring a data set of kidnapping crimes in Italy between 1960 and 2012 changes in Italian policy regarding sanctions for kidnapping and their associated impact on murders is considered. Deaths associated with kidnappings increase in prevalence when the kidnapping sanction increased, causing a decrease the marginal sanction for murder. Death rates reversed when enhanced sanctions for murder were later introduced.

Understanding ransom kidnappings and their duration

The B.E. Journal of Economic Analysis and Policy (2015), vol 14 (3), pp. 849-871 (with B.McCannon and M.Vannini)

Abstract: What factors drive the length of a kidnapping experience? A theoretical model is developed to conduct comparative statics. A unique data set covering all kidnappings for ransom in Sardinia between 1960 and 2010 is analyzed. Factors related to the ability to pay and cost of abduction matter. The effect of policies aimed at deterring the crime have mixed effects on its duration.

Assessing the productivity of the Italian hospitality sector: a post-WDEA pooled-truncated and spatial analysis

Journal of Productivity Analysis (2014), vol. 42 (2), pp. 103-121  (with M. Pulina and J.G. Brida)

Abstract: This paper analyses the productivity of the hospitality sector (hotel and restaurants) in Italy at a regional level by using a mix of non-parametric and parametric approaches. A novel pooled-truncated and spatial analysis is employed, based upon a window data envelopment analysis (WDEA), where pure technical efficiency is computed. The WDEA results show that Lombardy is the best relative performer. However, overall Italian regions reveal important sources of inefficiency mostly related to their inputs. As a post-WDEA, the pooled-truncated estimation indicates that the rate of utilisation and regional intrinsic features positively affect hospitality efficiency. Nevertheless, the spatial analysis does not support evidence of spill-over effects amongst Italian regions.

Crime as tourism externality

Regional Studies (2014), vol. 48 (4), pp. 693-709  (with B.Biagi)

Abstract: This paper analyses the linkage between tourism and crime with particular focus on the distortions generated onto criminal activities by the presence of visitors. Controlling for socio-demographic and economic variables, we empirically investigate the contribution of tourist arrivals to different types of crimes for 103 Italian provinces and for the year 2005. Possible spill-over effects of crime are taken into account by testing two spatial models (one spatial lag model and one spatial error model). We also test the hypothesis according to which the different geography of tourist destinations - i.e. urban, mountain, marine etc- alters the impact of tourism on crime. Finally, we measure the social cost of crime associated with tourist arrivals. 

Social conformity and suicide

Journal of Socio-Economics (2013), Volume 42, pp. 67-78 (with A.Bussu and V.Sterzi)

Abstract: We study the relationship between suicide rates and socioeconomic factors by using a panel data at Italian province level in the time span 1996-2005. Our analysis focuses on the impact of social norms on suicidal behaviours. In particular, beyond the usual social correlates of suicide rates, we propose an aggregate measure of social conformity which refers to the religious sphere as an area of conflict between individual and social behaviours. GMM and dynamic spatial panel data approach are implemented to control for serial and spatial autocorrelation. The results confirm the primary role of family, alcohol consumption and population density in explaining the suicide rates in Italy, while the economic variables, namely income per capita and economic growth, do not appear to have any effects.

Does more crime mean fewer jobs and less economic growth?

European Journal of Law and Economics (2013), vol. 36 (1), pp. 183-207  (with M.Pulina)

Abstract: This paper employs an Autoregressive Distributed Lags approach to investigate how a set of economic variables and a deterrence variable affect criminal activity. Furthermore, it highlights the extent to which crime is detrimental for the economic activity. The case study is Italy for the time span 1970 up to 2004. A Granger causality test is also implemented to establish temporal interrelationships. The empirical evidence has shown that the lack of deterrence positively affects each type of crime and especially thefts. All crime typologies have a negative effect on legal economic activity, reducing the employment rate. Furthermore, homicides, robbery, extortion and kidnapping have a crowding-out effect on economic growth. 

Cycles in Crime and Economy: Leading, Lagging and Coincident Behaviors

Journal of Quantitative Criminology (2012), vol. 28 (2), pp. 295-317 (with E.Otranto)

Abstract: In the last decades, the interest in the relationship between crime and business cycle has widely increased. It is a diffused opinion that a causal relationship goes from economic variables to criminal activities, but this causal effect is observed only for some typology of crimes, such as property crimes. In this work we examine the possibility of the existence of some common factors (interpreted as cyclical components) driving the dynamics of Gross Domestic Product and a large set of criminal types by using the nonparametric version of the dynamic factor model. A first aim of this exercise is to detect some comovements between the business cycle and the cyclical component of some typologies of crime, which could evidence some relationships between these variables; a second purpose is to select which crime types are related to the business cycle and if they are leading, coincident or lagging. Italy is the case study for the time span 1991 - 1 - 2004 - 12; the crime typologies are constituted by the 22 official categories classified by the Italian National Statistical Institute. The study finds that most of the crime types show a counter-cyclical behavior with respect to the overall economic performance, and only a few of them have an evident relationship with the business cycle. Furthermore, some crime offenses, such as bankruptcy, embezzlement and fraudulent insolvency, seem to anticipate the business cycle, in line with recent global events.

An investigation into the relationship between size and efficiency of the Italian hospitality sector: A window DEA approach

European Journal of Operational Research (2010), vol. 204 (3), 613-620 (with M. Pulina and A. Paba)

Abstract: This paper analyses the efficiency of hotels across all of the 20 regions in Italy using a data envelopment analysis (DEA). The empirical results indicate that Sardinia can be considered as a region “falling further behind”, whereas some regions in the North and Centre of Italy can be regarded as “moving ahead”. Using the island of Sardinia as a case study, approximately 150 firms are analysed in detail over the time span 2002 to 2005. Via a window DEA, both technical and scale efficiencies are computed. An efficiency comparison amongst hotels categorised by size and municipality is run. Finally, policy implications are drawn from the empirical findings that advise how to improve hotels that attained low efficiency scores.

Does crime affect the economic growth?

Kyklos (2010), vol. 63 (3), pp. 330-345 (with E. Otranto)

Abstract: Criminal activity performs like a tax on the entire economy: it discourages domestic and foreign direct investments, it reduces firms’ competitiveness, and reallocates resources creating uncertainty and inefficiency. Although the impact of economic variables on crime has been widely investigated, there is not much concern about crime also affecting the overall economic performance. This work aims to bridge this gap by presenting an empirical analysis of the macroeconomic consequences of criminal activity. Italy is the case study for the time span 1979-2002. Dealing with a state space framework, a time varying parameter approach is employed to measure the impact of criminality on real Gross Domestic Product along time, and to measure the asymmetric impact in recession and expansion periods. The analysis is completed evaluating the effects of crime fluctuations in the long period by an impulse response analysis.