In academic and policy circles, there has been considerable interest in the impact of “big data” on firm performance. We examine the question of how the amount of data impacts the accuracy of Machine Learned models of weekly retail product forecasts using a proprietary data set obtained from...

Policymakers can take actions to prevent local conflict before it begins, if such violence can be accurately predicted. We examine the two countries with the richest available sub-national data: Colombia and Indonesia. We assemble two decades of fine-grained violence data by type, alongside...

The Chinese automobile market is the largest in the world with annual sales exceeding 20 million vehicles. The tremendous growth in sales---over 200 percent from 2008 to 2015---and concerns over local air quality have prompted China's policy makers to incentivize the adoption of more fuel...

A full understanding of how gasoline prices affect consumer behavior frequently requires information on how consumers forecast future gasoline prices. We provide the first evidence on the nature of these forecasts by analyzing two decades of data on gasoline price expectations from the Michigan...

Projection bias is the tendency to overpredict the degree to which one's future tastes will resemble one's current tastes. We test for evidence of projection bias in two of the largest and most important consumer markets - the car and housing markets. Using data for more than forty million...

We investigate whether the first digit of an odometer reading is more salient to consumers than subsequent digits. We find that retail transaction prices and volumes of used vehicles drop discontinuously at 10,000-mile odometer thresholds, echoing effects found in the wholesale market by...

Social media data presents challenges for forecasters since one must convert text into data and deal with issues related to these measures being collected at different frequencies and volumes than traditional financial data. In this paper, we use a deep learning algorithm to measure sentiment...

We explore the in- and out- of sample robustness of tests for consumer choice inconsistencies based on parameter restrictions in parametric models, with a focus on tests proposed by Ketcham, Kuminoff and Powers (2015). We start by arguing that non-parametric alternatives are inherently...

We present theory and evidence that challenges the view that forward premia contain little information regarding subsequent spot rate movements. Using weekly dollar-mark and dollar sterling data, we find that spot and forward exchange rates together are well represented by a vector error...