A note on convergence of Peck-Shell and Green-Lin mechanisms in the Diamond-Dybvig model

We study the effects of population size in the Peck-Shell analysis of bank runs. We find that a contract featuring equal-treatment for almost all depositors of the same type approximates the optimum. Because the approximation also satisfies Green-Lin incentive constraints, when the planner discloses positions in the queue, welfare in these alternative specifications are sandwiched. Disclosure, however, it is not needed since our approximating contract is not subject to runs.

The role of media networks in compensating political biases: evidence from radio networks in Brazil

A central question in political economy is how to incentivize elected socials to allocate resources to those that need them the most. Research has shown that, while electoral incentives lead central governments to transfer fewer funds to non-aligned constituencies, media presence is instrumental in promoting a better allocation of resources. This study evaluates how these two phenomena interact by analyzing the role of media in compensating political biases. In particular, we analyze how media presence, connectivity and ownership affect the distribution of federal drought relief transfers to Brazilian municipalities. We find that municipalities that are not aligned with the federal government have a lower probability of receiving funds conditional on experiencing low precipitation. However, we show that the presence of radio stations compensates for this bias. This effect is driven by municipalities that have radio stations connected to a regional network rather than by the presence of local radio stations. In addition, the effect of network-connected radio stations increases with their network coverage. These findings suggests that the connection of a radio station to a network is important because it increases the salience of disasters, making it harder for the federal government to ignore non-allies. We show that our findings are not explained by the ownership and manipulation of media by politicians.

Internet share of advertising expenditure : growth drivers and inhibitors in the brazilian market

Os investimentos com publicidade na Internet como uma percentagem das despesas totais de publicidade variam significativamente de um país para outro. O número é tão baixo quanto 4,7% no mercado brasileiro e tão alto como 28,5% no mercado britânico (ZenithOptimedia, 2011b). Algumas razões explicam tal disparidade. No nível macro, a participação dos gastos com publicidade na Internet está fortemente ligada a variáveis como o produto interno bruto per capita e à penetração da Internet na população. No nível micro, uma pesquisa qualitativa foi feita para identificar os fatores que contribuem e inibem o crescimento da participação da publicidade online no mercado brasileiro. A vasta lista de inibidores parece ter profundo impacto sobre como os profissionais de mercado tomar decisões de alocação de investimento em publicidade por tipo de mídia. Devido à legislação, à auto-regulamentação e às dinâmicas da indústria, grande parte da tomada de decisão é realizada por agências de publicidade. Estas parecem ter fortes incentivos econômicos para selecionar outros tipos de mídia e não a Internet ao definir planos de mídia. Ao mesmo tempo, a legislação e a auto-regulamentação fornecem desincentivos para corretores de mídia a operar no mercado local. A falta de profissionais qualificados e a padronização limitada também desempenham papéis importante para inibir uma maior participação da Internet nos gastos com publicidade no Brasil. A convergência dos resultados quantitativos com os qualitativos indica possíveis motivos pelos quais a participação da publicidade online no Brasil é tão baixa. Em primeiro lugar, a participação é explicada pelo estágio de desenvolvimento dos países. Quanto mais rico e mais desenvolvido um país, maior a proporção de gastos com publicidade online tende a ser. Em segundo lugar, o estágio econômico emergente do Brasil potencialmente dá espaço para o aumento do ineficiências do mercado, tais como programas de descontos oferecidos de forma desproporcional para os principais decisores de alocação de investimentos de mídia. Este fato aparentemente produz um feedback negativo, contribuindo para manter a baixa participação da publicidade online no total dos investimentos publicitários.

Content marketing and brand engagement on social media: a study of Facebook´s posts in the ecommerce industry in Brazil

Content marketing refers to marketing format that involves the creation and sharing of media and publishing content in order to acquire customers. It is focused not on selling, but on communicating with customers and prospects. In today world´s, a trend has been seen in brands becoming publishers in order to keep up with their competition and more importantly to keep their base of fans and followers. Content Marketing is making companies to engage consumers by publishing engaging and value-filled content. This study aims to investigate if there is a link between brand engagement and Facebook Content Marketing practices in the e-commerce industry in Brazil. Based on the literature review, this study defines brand engagement on Facebook as the numbers of "likes" "comments" and "shares" that a company receives from its fans. These actions reflect the popularity of the brand post and leads to engagement. The author defines a scale where levels of Content Marketing practices are developed in order to analyze brand posts on Facebook of an ecommerce company in Brazil. The findings reveal that the most important criterion for the company is the one regarding the picture of the post, where it examines whether the photo content is appealing to the audience. Moreover, it was perceived that the higher the level of these criterion in a post, the greater the number of likes, comments and shares the post receives. The time when a post is published does not present a significant role in determining customer engagement and the most important factor within a publication is to reach the maximum level in the Content Marketing Scale.

Convergence analysis of sampling-based decomposition methods for risk-averse multistage stochastic convex programs

We consider a class of sampling-based decomposition methods to solve risk-averse multistage stochastic convex programs. We prove a formula for the computation of the cuts necessary to build the outer linearizations of the recourse functions. This formula can be used to obtain an efficient implementation of Stochastic Dual Dynamic Programming applied to convex nonlinear problems. We prove the almost sure convergence of these decomposition methods when the relatively complete recourse assumption holds. We also prove the almost sure convergence of these algorithms when applied to risk-averse multistage stochastic linear programs that do not satisfy the relatively complete recourse assumption. The analysis is first done assuming the underlying stochastic process is interstage independent and discrete, with a finite set of possible realizations at each stage. We then indicate two ways of extending the methods and convergence analysis to the case when the process is interstage dependent.