A Multilevel Model with Time Series Components for the Analysis of Tribal Art Prices

In the present work we perform an econometric analysis of the Tribal art market. To this aim, we use a unique and original database that includes information on Tribal art market auctions worldwide from 1998 to 2011. In Literature, art prices are modelled through the hedonic regression model, a classic fixed-effect model. The main drawback of the hedonic approach is the large number of parameters, since, in general, art data include many categorical variables. In this work, we propose a multilevel model for the analysis of Tribal art prices that takes into account the influence of time on artwork prices. In fact, it is natural to assume that time exerts an influence over the price dynamics in various ways. Nevertheless, since the set of objects change at every auction date, we do not have repeated measurements of the same items over time. Hence, the dataset does not constitute a proper panel; rather, it has a two-level structure in that items, level-1 units, are grouped in time points, level-2 units. The main theoretical contribution is the extension of classical multilevel models to cope with the case described above. In particular, we introduce a model with time dependent random effects at the second level. We propose a novel specification of the model, derive the maximum likelihood estimators and implement them through the E-M algorithm. We test the finite sample properties of the estimators and the validity of the own-written R-code by means of a simulation study. Finally, we show that the new model improves considerably the fit of the Tribal art data with respect to both the hedonic regression model and the classic multilevel model.

An Input-Process-Output Approach to Interorganizational Teams: The Influence of Work Group Diversity, Trust and Shared Leadership on Communication Network and Team Outputs.

The market’s challenges bring firms to collaborate with other organizations in order to create Joint Ventures, Alliances and Consortia that are defined as “Interorganizational Networks” (IONs) (Provan, Fish and Sydow; 2007). Some of these IONs are managed through a shared partecipant governance (Provan and Kenis, 2008): a team composed by entrepreneurs and/or directors of each firm of an ION. The research is focused on these kind of management teams and it is based on an input-process-output model: some input variables (work group’s diversity, intra-team's friendship network density) have a direct influence on the process (team identification, shared leadership, interorganizational trust, team trust and intra-team's communication network density), which influence some team outputs, individual innovation behaviors and team effectiveness (team performance, work group satisfaction and ION affective commitment). Data was collected on a sample of 101 entrepreneurs grouped in 28 ION’s government teams and the research hypotheses are tested trough the path analysis and the multilevel models. As expected trust in team and shared leadership are positively and directly related to team effectiveness while team identification and interorganizational trust are indirectly related to the team outputs. The friendship network density among the team’s members has got positive effects on the trust in team and on the communication network density, and also, through the communication network density it improves the level of the teammates ION affective commitment. The shared leadership and its effects on the team effectiveness are fostered from higher level of team identification and weakened from higher level of work group diversity, specifically gender diversity. Finally, the communication network density and shared leadership at the individual level are related to the frequency of individual innovative behaviors. The dissertation’s results give a wider and more precise indication about the management of interfirm network through “shared” form of governance.

Law, Informal Institutions and Trust: an Experimental Perspective

This dissertation has studied how legal and non-legal mechanisms affect the levels of trust and trustworthiness in an economy, and whether and when subtle psychological factors are crucial for establishing trust and even for recovering trust from a breach of contract. The first Chapter has addressed the question of whether formal legal enforcement crowds out or crowds in the amount of trust in a society. We find that formal legal mechanisms, especially formal contracts backed by a powerful authority, normally undermine trust except when they are perceived as legitimate, or when there are no strong social norms of fairness (i.e. the population in a society is considerably heterogeneous), or when the environment in which repeated commercial relationships take place becomes highly uncertain. The second Chapter has examined whether the endogenous adoption of a collective punishment institution can help a society coordinate on an efficient outcome, characterized by high levels of trust and trustworthiness. The experimental results show that the endogenous introduction of collective punishment by means of a majority-voting rule does not significantly improve coordination on the efficient equilibrium. Not all subjects seem to be able to anticipate the change in behavior induced by the introduction of the mechanism, and a majority of them vote against it. The third Chapter has explored whether high-trustors adapt their behavior in response to others’ trustworthiness or untrustworthiness more quickly, which in turn supports them to maintain higher default expectations of others’ trustworthiness relative to low-trustors. Our experimental results reveal that high-trustors are better than low-trustors at predicting others’ trustworthiness because they are less susceptible to the anticipated aversive emotions aroused by the potential betrayal and thereby have a higher willingness to acquire the valuable information about their partner’s actions.