The purpose of the present work is to analyze whether—and to what extent—tourism activity affects urban house price dynamics in Italy. Using a system Generalized Method of Moments (GMM‐SYS) approach and after controlling for socioeconomic characteristics of the local housing markets as well as amenities and disamenities, we test for the effect of tourism by employing a composite index that enables us to capture the complexity of the tourism market. Data consist of yearly observations on the average house prices of 103 Italian cities over the period of 1996–2007. The results confirmed by several robustness checks demonstrate that tourism activity positively affects house prices. In addition, this work provides several first hints that this relationship might not be the same for all types of cities; hence, further developments of the present work should proceed in the direction of searching for different potential regimes through the use of mixture models.

Evaluating the impact of tourism on housing prices is an important endeavor, but the usual empirical approach is to estimate a single regression model with house price as a function of tourism and other variables. This approach does not allow for individual heterogeneity. In this article, the authors apply a latent class model to estimate the impact of tourism activities on housing prices in Italy. In particular, they allow for three different unobservable classes or regimes, permitting the impact of tourism on house prices to differ across classes. In other words, they allow for unobservable heterogeneity. The empirical results do support the existence of three classes of house price regressions. Using two different indices of tourism activity, for certain cities (about 21–48% of the sample), increases in tourism activity increase housing prices and for other cities (8–17%) increases in tourism activity decreases housing prices. For approximately half of the sample, increases in tourism activity have no impact on housing prices.

The present paper offers an integrated conceptual framework to jointly analyze demand and supply of agritourism firms and aims to identify motivations along with perceptions of externalities that influence the choice of a firm over another. On the supply side, a cluster analysis identifies homogenous groups of agritourism firms. On the demand side, a factor analysis is run on a set of motivations and environmental externalities and a probabilistic model estimates the determinants that influence the likelihood to choose 1 type of firm over the other. The results show that traditional and genuine food, culture, and authenticity are elements that determine the choice of 1 firm over another. A further contribution of this paper is the identification of environmental externalities as determinants of the attractiveness of a firm. From a marketing perspective, linking demand to supply is essential to determine product development strategies capable of satisfying actual and potential customers. Several strategies are proposed to different types of agritourism firms to attract and retain customers.

The purpose of this paper is to demonstrate that, for the case of Italy, ceteris paribus, tourist areas tend to have a greater amount of crime than non-tourist ones in the short and long run. Following the literature of the economics of crime à la Becker (Crime and Punishment: An Economic Approach, 1968) and Enrlich (Participation in Illegitimate Activities: A Theoretical and Empirical Investigation, 1973) and using a System GMM approach for the time span 1985-2003, the authors empirically test whether total crime in Italy is affected by the presence of tourists. Findings confirm the initial intuition of a positive relationship between tourism and crime in destinations. When using the level rather than the rate of total crime and controlling for the equivalent tourists (i.e. the number of tourists per day in a given destination) the effect of the tourist variable is confirmed. Overall results indicate however that the resident population has a greater effect on crime than the tourist population. Therefore, the main explanation for the impact of tourism on crime seems to be agglomeration effects. Special Issue Tourism ExternalitiesJEL D62; K00; L83

The resilience of cooperatives and their positive contribution to employment in times of crisis is well established. However, their overall economic performance relative to conventional firms is still controversial, casting doubt on the ability of this alternative organizational form to govern the fundamental drivers of productivity. To shed new light on the issue, we study the comparative technical efficiency of agricultural cooperatives (ACs) and conventional firms (CFs), drawing on a unique data set comprising all wine‐producing companies in Sardinia (Italy) from 2004 to 2009. Due to the similarity of the habitats in which the firms operate and the careful measurement of several key inputs, the observed units are ‘twins’ in all non‐organizational respects, providing an ideal setting for comparison. Having generated efficiency scores through Data Envelopment Analysis (DEA), we regressed the scores on external covariates and ownership type using a pooled truncated maximum likelihood formulation. Our findings, which survive correction for spatial correlations, indicate that cooperatives are less technically efficient than their capitalist counterparts and struggle more to adapt to extreme weather fluctuations. Both results are particularly worrying in light of the main challenges facing the wine industry in the near future: liberalization of EU planting rights and climate change.