Direct Democracy, Political Delegation, and Responsibility Substitution

Can direct democracy provisions improve welfare over pure representative democracy? This paper studies how such provisions affect politicians’ incentives and selection. While direct democracy allows citizens to correct politicians’ mistakes, it also reduces the incentives of elected representatives to search for good policies. This responsibility substitution reduces citizens’ ability to screen competent politicians, when elections are the only means to address political agency problems. A lower cost of direct democracy induces a negative spiral on politicians incentives, which we characterize by a disincentive multiplier. As a consequence, introducing initiatives or lowering their cost can reduce voters’ expected utility. Moreover, when elections perform well in selecting politicians and provide incentives, this indirect welfare reducing effect is stronger.Direct Democracy, Initiative, Referendum, Political Agency, Delegation JEL Classification Numbers: D72, D78, P16

Towards a Safe and Secure web semantic framework

This thesis describes the work I did during my internship at the INRIA research center in Sophia-Antipolis, within the INDES team and under the supervision of Ilaria Castellani and Tamara Rezk.The main objectives of the INDES team is to study models and develop languages for Diffuse computing, a computing paradigm in which it is necessary to manage and maintain computing structures distributed on several heterogeneous nodes that usually do not trust each other. INDES focuses on the study of the different concurrency models that underlie these systems and pays particular attention to Multitier programming, an emerging programming paradigm that aims to reduce complexity in the development of web applications by adopting a single language to program all their components. The role played by security issues (and particularly the protection of confidentiality and integrity of data) is crucial in these applications, and ensuring security of web applications is another important goal of the INDES team. My internship took place in the context of the ANR CISC project, whose objective is to provide semantics, languages and attack models for the Internet of Things (IoT), a term that refers to systems composed of a set of interconnected devices, which interact with the environment in which they are placed by means of different sensors and actuators. My individual research took place within Webi, a semantic framework that aims at a primitive simulation of the interactions that take place between servers and clients on the web, developed by Tamara Rezk and her colleagues. In particular, I concentrated on an extension of Webi called WebiLog, which allows one to represent authenticated sessions and to formalize attacks aimed at compromising their integrity

Citizens united: a theoretical evaluation

The 2010 U.S. Supreme Court's decision on Citizens United v. FEC lifted restrictions on the funding by unions and corporations of groups engaging in independent political advertising (outside spending). Many have criticized the majority opinion's premise that outside spending cannot corrupt or distort the electoral process. Fewer have examined the implications of this decision under the Court's assumptions. Using a game-theoretic model of electoral competition, we show that informative outside spending by a group whose policy preferences are partially aligned with the electorate may reduce voter welfare. This negative effect is more likely when policy information is highly valuable for the electorate or congruence between the group and voters is high. We further show that the regulatory environment produced by the Court's decision is always suboptimal: the electorate would be better off if either groups were allowed to coordinated with candidates or if outside spending was banned altogether

Higher campaign costs are not necessarily bad for voters

The increasing cost of political campaigns and its impact on the electoral process are issues of paramount importance in modern democracies but higher campaign spending does not always hamper accountability, write Carlo Prato and Stephane Wolton. Drawing on recent research, they argue that when constituencies are biased towards a party, a higher campaign cost intensifies electoral competition, and is associated with a higher level of constituency service. Costly campaigns can thus have a rebalancing effect that improves electoral accountability

Campaign cost and electoral accountability

The increasing cost of political campaigns and its impact on the electoral process are issues of paramount importance in modern democracies. We propose a theory of electoral accountability in which candidates choose whether or not to commit to constituency service and whether or not to pay a campaign cost to advertise their platform. A higher campaign cost decreases voter welfare when partisan imbalance is low. However, when partisan imbalance is high, a higher campaign cost is associated with a higher expected level of constituency service. More costly campaigns can thus have a rebalancing effect that improves electoral accountability. We discuss the implications of our findings for campaign finance regulation and present empirical evidence consistent with our key predictions

The voters' curses: why we need Goldilocks voters

Scholars have long deplored voters' lack of interest in politics and argued in favor of greater political engagement. We present a formal theory of elections where successful communication of campaign messages requires both effort by candidates and attention from voters. Voters' interest in politics affects their attention, and impacts the effectiveness of the electoral process as a screening and disciplining device. In line with existing theories, there exists a curse of the uninterested voter: When voters have little interest in politics, the electoral process performs poorly, and voters' attention to politics is low. Surprisingly, we uncover a curse of the interested voter, by which the same happens when voters have a strong interest in politics. Our results highlight the importance of distinguishing between voters' interest and attention, two notions often conflated in empirical studies. Moreover, policy interventions aimed at subsidizing the cost of acquiring political information can have unintended consequences

Populism may well be inevitable in democracies, but it is also the cause of democratic disenchantment

Much has been written about populism and its move to the mainstream. Stephane Wolton and Carlo Prato argue that it has arisen, not so much from democratic dissatisfaction but from voters’ demands for reform, which leads politicians to engage opportunistically in a form of populism by campaigning on reformist agendas regardless of their ability to successfully carry them out

Estimating Route Choice Models from Stochastically Generated Choice Sets on Large-Scale Networks Correcting for Unequal Sampling Probability:Correcting for Unequal Sampling Probability

Route choice is one of the most complex decision-making contexts to represent mathematically, and the most frequently used approach to model route choice consists of generating alternative routes and modeling the preferences of utility-maximizing travelers. The main drawback of this approach is the dependency of the parameter estimates from the choice set generation technique. Bias introduced in model estimation has been corrected only for the random walk algorithm, which has problematic applicability to large-scale networks. This study proposes a correction term for the sampling probability of routes extracted with stochastic route generation. The term is easily applicable to large-scale networks and various environments, given its dependence only on a random number generator and the Dijkstra shortest path algorithm. The implementation for revealed preferences data, which consist of actual route choices collected in Cagliari, Italy, shows the feasibility of generating routes stochastically in a high-resolution network and calculating the correction factor. The model estimation with and without correction illustrates how the correction not only improves the goodness of fit but also turns illogical signs for parameter estimates to logical signs

Modeling the Behavior of Novice Young Drivers Using Data from In- Vehicle Data Recorders

Novice young drivers suffer from increased crash risk that translates into over-representation in road injuries. A better understanding of the driving behavior of novice young drivers and of their determinants is needed to tackle this problem. To this extent, this study analyzes the behavior of novice young drivers within a Graduated Driver Licensing (GDL) program. Data on driving behavior of novice drivers and their parents is collected using in-vehicle data recorders, which calculate compound risk indices as measures of the risk taking behavior of the various drivers. Data is used to estimate a negative binomial model to identify the major factors that affect the driving behavior of the young drivers. Estimation results suggest that the risk taking behavior of young drivers is influenced by that of their parents and decreases with higher levels of supervised driving and stricter monitoring by the parents