Browsing Faculté des arts et des sciences – Département de sciences économiques - Travaux et publications by Author "Rauh, Christopher"

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  • Discrimination without taste : How discrimination can spillover and persist 

    Ramachandran, Rajesh; Rauh, Christopher (Université de Montréal. Département de sciences économiques., 2018-06)
    We introduce coordination failures driven by beliefs regarding the presence of taste discriminators as a channel of discrimination in productive activities requiring the input of multiple agents. We show that discrimination can persist under perfectly ...

  • The growth impact of language standardization : Metcalfe’s Law and the industrial revolution 

    Dudley, Léonard; Rauh, Christopher (2020-01-13)
    During the Industrial Revolution, did population growth stimulate innovation, or did causality run primarily from innovation to growth? Previous research fails to explain why between 1700 and 1850: (i) most innovation originated in three clusters of ...

  • The hard problem of prediction for conflict prevention 

    Mueller, Hannes; Rauh, Christopher (Université de Montréal. Département de sciences économiques., 2019-04)
    There is a rising interest in conflict prevention and this interest provides a strong motivation for better conflict forecasting. A key problem of conflict forecasting for prevention is that predicting the start of conflict in previously peaceful ...

  • Innovation growth clusters : Lessons from the industrial revolution 

    Dudley, Léonard; Rauh, Christopher (Université de Montréal. Département de sciences économiques., 2018-08)
    Over three centuries ago, a new technology suddenly increased the amount and frequency of available information. Might such «Big Data» have disrupted the causal relationships linking economic growth and innovation? Previous research has affirmed that ...

  • Measuring uncertainty at the regional level using newspaper text 

    Rauh, Christopher (Université de Montréal. Département de sciences économiques., 2019-08)
    In this paper I present a methodology to provide uncertainty measures at the regional level in real time using the full bandwidth of news. In order to do so I download vast amounts of newspaper articles, summarize these into topics using unsupervised ...