This paper uses machine learning (ML) to estimate hedonic price indices at scale from item-level transaction and product characteristics. The procedure uses state-of-the-art approaches from hedonic econometrics and implements them with a neural network ML approach. Applying the methodology to...

In response to the COVID-19 pandemic two new timely poverty measures have been developed to monitor fast-changing economic conditions for the most deprived. The Han et al. near real-time poverty measure uses responses to a global income question on the Monthly Current Population Survey (CPS)...

As distorted maps may mislead, Natural Language Processing (NLP) models may misrepresent. How do we know which NLP model to trust? We provide comprehensive guidance for selecting and applying NLP representations of patent text. We develop novel validation tasks to evaluate several leading NLP...

We estimate the effects of robot adoption on firm-level and worker-level outcomes in the Netherlands using a large employer-employee panel dataset spanning 2009-2020. Our firm-level results confirm previous findings, with positive effects on value added and hours worked for robot-adopting firms...

Happiness data--survey respondents' self-reported well-being (SWB)--have become increasingly common in economics research, with recent calls to use them in policymaking. Researchers have used SWB data in novel ways, for example to learn about welfare or preferences when choice data are...

This article provides an overview of the literature on mobility in developing countries. Explicit distinctions are drawn between directional and non-directional measures, absolute and relative measures, and combinations thereof. We note that the scarcity of panel data has hindered the...