A multi-cell experimental design to recover policy relevant treatment effects, with an application to online advertising

Experiments are an important tool to measure the impacts of interventions. However, in experimental settings with one-sided noncompliance, extant empirical approaches may not produce the estimands a decision-maker needs to solve their problem. For example, these experimental designs are common in digital advertising settings, but typical methods do not yield effects that inform the intensive margin -- how much should be spent or how many consumers should be reached with a campaign. We propose a solution that combines a novel multi-cell experimental design with modern estimation techniques that enables decision-makers to recover enough information to solve problems with an intensive margin. Our design is straightforward to implement. Using data from advertising experiments at Facebook, we demonstrate our approach outperforms standard techniques in recovering treatment effect parameters. Through a simple advertising reach decision problem, we show that our approach generates better decisions relative to standard techniques

The development of the brazilian amazon region and greenhouse gases emission: a dilemma to be faced!

The purpose of this work is to verify the existence of possible tradeoffs between policies direct to reduce the emissions of greenhouse gases (GHGs) with the ones direct to foster the development of the Brazilian Amazon Region, which is one of the poorest in the country. In order to achieve this goal, this paper uses an interregional input-output (I-O) model, estimated for the Brazilian economy for the year of 2004. The I-O model is used to make a comparison between the economical and the environmental relevance of each sector in the economies of the Amazon region and the rest of Brazil. This study considers the greenhouse gases emissions not only from the economic activities by itself, but, also for the more important factor of the land-use changes. This is a fact of most importance, given that in 2005, about 60% of the Brazilian GHGs emissions were due to the land-use change in its different biomes. Moreover, in the Brazilian Amazon region, especially in the last decades, the deforestation was linked mainly to economic factors than to policies conducted by the government. The results show that the sectors with the greatest importance in terms of emissions are cattle and soybean production. Also, they are also the most prominent for the region's economic development. This poses a dilemma that needs to be faced not only by Brazil, but also by the developed nations, as the burden of the reduction in the greenhouse gases emission in the Brazilian Amazon region cannot be only put on the poor population of the region!Amazon Region, Greenhouse Gases, Brazil, Input-Output, Economic Development, Productive Structure, Deforestation

Online Causal Inference for Advertising in Real-Time Bidding Auctions

Real-time bidding (RTB) systems, which leverage auctions to programmatically allocate user impressions to multiple competing advertisers, continue to enjoy widespread success in digital advertising. Assessing the effectiveness of such advertising remains a lingering challenge in research and practice. This paper presents a new experimental design to perform causal inference on advertising bought through such mechanisms. Our method leverages the economic structure of first- and second-price auctions, which are ubiquitous in RTB systems, embedded within a multi-armed bandit (MAB) setup for online adaptive experimentation. We implement it via a modified Thompson sampling (TS) algorithm that estimates causal effects of advertising while minimizing the costs of experimentation to the advertiser by simultaneously learning the optimal bidding policy that maximizes her expected payoffs from auction participation. Simulations show that not only the proposed method successfully accomplishes the advertiser's goals, but also does so at a much lower cost than more conventional experimentation policies aimed at performing causal inference

Parallel Experimentation in a Competitive Advertising Marketplace

When multiple firms are simultaneously running experiments on a platform, the treatment effects for one firm may depend on the experimentation policies of others. This paper presents a set of causal estimands that are relevant to such an environment. We also present an experimental design that is suitable for facilitating experimentation across multiple competitors in such an environment. Together, these can be used by a platform to run experiments "as a service," on behalf of its participating firms. We show that the causal estimands we develop are identified nonparametrically by the variation induced by the design, and present two scalable estimators that help measure them in typical high-dimensional situations. We implement the design on the advertising platform of JD.com, an eCommerce company, which is also a publisher of digital ads in China. We discuss how the design is engineered within the platform's auction-driven ad-allocation system, which is typical of modern, digital advertising marketplaces. Finally, we present results from a parallel experiment involving 16 advertisers and millions of JD.com users. These results showcase the importance of accommodating a role for interactions across experimenters and demonstrates the viability of the framework

Regional development and greenhouse gases emission: the case of the Amazon Region

The purpose of this work is to verify the existence of possible tradeoffs between policies direct to reduce the emissions of greenhouse gases (GHGs) with the ones direct to foster the development of the Brazilian Amazon Region, considering its economic relations with the rest of the country and the international markets. In order to achieve this goal, this paper uses an interregional input-output (I-O) model, estimated for the Brazilian economy for the year of 2004. The I-O model is used to make a comparison between the economical and the environmental relevance of each sector in the Amazon region and the rest of Brazil. This study considers the greenhouse gases emissions not only from the economic activities by itself, but, also for the more important factor of the land-use changes. This is a fact of most importance, given that in 2005, about 60% of the Brazilian GHGs emissions were due to the land-use change in its different biomes. Moreover, in the Brazilian Amazon region, especially in the last decades, the deforestation was linked mainly to economic factors than to policies conducted by the government. The results show that the sectors with the greatest importance in terms of emissions are cattle and soybean production. Also, they are also the most prominent for the region's economic development. This poses a dilemma that needs to be faced not only by Brazil, but also by the developed nations, as the burden of the reduction in the greenhouse gases emission in the Brazilian Amazon region cannot be only put on the poor population of the region