We investigate financial experts' beliefs about climate risk pricing and analyze how those beliefs influence stock return expectations. In a comprehensive survey, we elicit experts' beliefs using both structured and open-ended questions. We establish that most experts share the view that climate...

We present the first systematic review of the scientific literature on smartphone use and academic success. We synthesise the theoretical mechanisms, empirical approaches, and empirical findings described in the multidisciplinary literature to date. Our analysis of the literature reveals a...

Early research on the returns to higher education treated the postsecondary system as a monolith. In reality, postsecondary education in the United States and around the world is highly differentiated, with a variety of options that differ by credential (associates degree, bachelor's degree,...

We decompose the relationship between food aid and conflict into the channels through which food aid can affect conflict. We address questions of methodological choice and estimation techniques for empirical studies. Our review of the empirical evidence on the effect of food aid on conflict...

As age discrimination hampers the OECD's ambition to extend the working population, an efficient anti-discrimination policy targeted at the right employers is critical. Therefore, the context in which age discrimination is most prevalent must be identified. In this study, we thoroughly review...

Innovative women entrepreneurs can be agents of change and offer novel solutions to global challenges. However, they face multiple barriers to growing their businesses. This paper reviews the literature on strategies to support women entrepreneurs in improving their business outcomes. It focuses...

Using high-quality nation-wide social security data combined with machine learning tools, we develop predictive models of income support receipt intensities for any payment enrolee in the Australian social security system between 2014 and 2018. We show that off-the-shelf machine learning...

A recent literature has used a historical perspective to better understand fundamental questions of urban economics. However, a wide range of historical documents of exceptional quality remain underutilised: their use has been hampered by their original format or by the massive amount of...

In this paper we propose the use of machine learning methods to estimate inequality of opportunity. We illustrate how our proposed methods - conditional inference regression trees and forests - represent a substantial improvement over existing estimation approaches. First, they reduce the risk...

AI is transforming labor markets around the world. Existing research has focused on advanced economies but has neglected developing economies. Different impacts of AI on labor markets in different countries arise not only from heterogeneous occupational structures, but also from the fact that...