This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16...

This paper proposes a measure of real-time inflation expectations based on metadata, i.e., data about data, constructed from internet search queries performed on the search engine Google. The forecasting performance of the Google Inflation Search Index (GISI) is assessed relative to 37 other...

We present the methodology for developing a predictive model for identifying homeless persons likely to have high future costs for public services. It was developed by linking administrative records from 2007 through 2012 for seven Santa Clara County agencies and identifying 38 demographic,...

The Covid-19 crisis has highlighted innovative high-frequency dataset allowing to measure in real-time the economic impact. In this vein, we explore how satellite data measuring the concentration of nitrogen dioxide (NO2, a pollutant emitted mainly by industrial activity) in the troposphere can...

Objectives: Theory development enables the modeling of relationships in physical functioning (PF), demonstrating the practical value of measurement theory relative to predictive control of the modeled parameters. Methods. Predictive theories provide highly practical foundations for efficient...

This paper exploits daily infrared images taken from satellites to track economic activity in advanced and emerging countries. We first develop a framework to read, clean, and exploit satellite images. Our algorithm uses the laws of physics (Planck's law) and machine learning to detect the heat...

This collection of papers analyzes the versatility and predictive power of survey expectations data in asset pricing and macroeconomic forecasting. The first paper, Using Sentiment Surveys to Predict GDP Growth and Stock Returns sheds new light on the question of whether or not sentiment...

This study aims to refine unemployment forecasts by incorporating the degree of consensus in consumers’ expectations. With this objective, we first model the unemployment rate in eight European countries using the step-wise algorithm proposed by Hyndman and Khandakar (J Stat Softw...

We describe a new mechanism that induces accurate forecasts within an organization while reducing moral hazards and the stigma associated with negative opinions. It is based on the notion of identity escrow, whereby the identity of a forecaster is kept anonymous and only revealed when a number...

In this paper we propose a new explanation for Favourite-Longshot Bias (FLB). FLB refers to a well known phenomenon, pervasive in many sport betting markets. As measured by historically realised gains, bets on favourites appear to be more favourable than longshot bets. We show that FLB can be...