Fields of Research
Primary: Development Economics, Environmental and Resource Economics
Secondary: Data Science, Industrial Organization, Trade
Working Papers and Works in Progress (2016-2017)
Platform economics and same-side price competition: Evidence from scraping Airbnb in Boston
Abstract: This paper examines how the price set by a host on Airbnb is affected by the quality of his room and the price set by his rivals in the apartment rental market in Boston. I first draft a theoretical model and derive the strategic responses of the host to the price set by other hosts. I also derive how the price is affected by the quality of the room, the structural characteristics of the apartment as well as the characteristics of the neighborhood. Using Python programming language, I scrap Airbnb website to collect data on each host in the Boston metropolitan area. Results from the spatial hedonic price analysis show that the prices of the apartment rented on Airbnb are strategic substitutes, but within the central business district, they are complements. Host with low-quality room set lower prices than hosts with a higher quality room. The finding suggests that policies that improve the quality of the room of one host will have spillover effects on the quality of the rooms offered by the other hosts.
Impact of eco-friendly attributes on products reviews: Analysis of Amazon reviews using machine learning
Abstract: The interpersonal influence of world-of-mouth (WOM) on customer purchase decision is well established in the marketing literature. With the growth of the internet and of online sale, consumer-generated content (CGC) which includes consumers’ commentaries, opinions, and personal experiences publicly available on diverse online media, can reinforce a decision-making process. For e-marketers, it is important to know which attributes of the products or services affect consumers’ experience. This research examines how eco-friendly attributes affect consumers’ reviews. We build a machine learning model to analyze reviews of different categories of products on amazon and predict their sentiment. We then model the weight of eco-friendly attributes on consumers' sentiments.
Billions of tweets, satellite data and demand for clean air
Abstract: This research uses hedonic price analysis to measure the benefits associated with reduced pollution. We examine satellite data to infer the concentration of particles as a proxy for air quality. We also derive states of air quality from geocoded tweets and use them in our hedonic price model to avoid the identification and statistical power problems that research on non-market good economic evaluation suffer from.
Impact of food reserve programs on price levels and volatility: Natural experiment from Benin cereals markets in West-Africa. (Paper)
Abstract: Following the food price crisis of 2007-2008 many governments has responded with food reserve/stock programs. The role of those programs is to regulate price levels and reduce price volatility. These programs have been controversial for many decades because of the cost associated with their implementation and their effectiveness to regulate and stabilize prices. The present research uses the food reserve program implemented by the Benin government from 2008 to 2016 following the food prices crisis of 2007-2008 as a natural experiment to test the impact of such programs on prices levels and prices volatility. Using the model of competitive storage as theoretical background and the exponential generalized autoregressive conditional heteroskedastic (EGARCH) regression model as an estimation method, the study shows that the food reserve program has been effective in stabilizing prices on rice and maize markets in Benin but ineffective in regulating the prices levels of these two products.
Sustainable management of natural resources with Unmanned Aerial Vehicles (UAV) in the W-Arly-Pendjari parks in West-Africa
Project Synopsis: This project is a series of four (04) research projects that aim at using Unmanned Aerial Vehicles (UAV) also known as drones to identify and reduce unsustainable practices that affect biodiversity in protected areas such as poaching, uncontrolled bushfires, agricultural encroachments, unsustainable harvesting of Non Timber Forest Products (NTFPs), timber and fish overexploitation. The researches being conducted under this project are:
- Coevolution options for the sustainability of the WAP.
- Drones for precision agriculture in developing countries: comparative evaluation of pesticide spraying drones and manual spraying systems.
- Small-scale farmers willingness to pay for drone services: Experimental evidence
- Impact of drone services on farmer’s livelihood in Benin: Evidence from a cluster-randomized control trial
To learn more about this project visit the page: Drone Project