The impact of climate risk on firm performance and financing choices: An international comparison View Full Text


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Article Info

DATE

2018-07

AUTHORS

Henry He Huang, Joseph Kerstein, Chong Wang

ABSTRACT

Increasingly adverse climatic conditions have created greater systematic risk for companies throughout the global economy. Few studies have directly examined the consequences of climate-related risk on financing choices by publicly listed firms across the globe. We attempt to do so using the Global Climate Risk Index compiled and published by Germanwatch (Kreft & Eckstein, 2014), which captures at the country level the extent of losses from extreme weather events. As expected, we find the likelihood of loss from major storms, flooding, heat waves, etc. to be associated with lower and more volatile earnings and cash flows. Consistent with policies that attempt to moderate such effects, we show that firms located in countries characterized by more severe weather are likelier to hold more cash so as to build financial slack and thereby organizational resilience to climatic threats. Those firms also tend to have less short-term debt but more long-term debt, and to be less likely to distribute cash dividends. In addition, we find that certain industries are less vulnerable to extreme weather and so face less climate-related risk. Our results are robust to using an instrumental variable approach, a propensity-score-matched sample, and path analysis, and remain unchanged when we consider an alternative measure of climate risk. Finally, our conclusions are invariant to the timing of financial crises that can affect different countries at different times. More... »

PAGES

633-656

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    http://scigraph.springernature.com/pub.10.1057/s41267-017-0125-5

    DOI

    http://dx.doi.org/10.1057/s41267-017-0125-5

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    https://app.dimensions.ai/details/publication/pub.1092691962


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    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1057/s41267-017-0125-5'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1057/s41267-017-0125-5'

    RDF/XML is a standard XML format for linked data.

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    276 https://www.grid.ac/institutes/grid.268433.8 schema:alternateName Yeshiva University
    277 schema:name Sy Syms School of Business, Yeshiva University, 10033, New York, NY, USA
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