Green lights: quantifying the economic impacts of drought

Publikation: Working paper › Forskning

Standard

Green lights : quantifying the economic impacts of drought. / Fisker, Peter Kielberg.

Frederiksberg : Department of Food and Resource Economics, University of Copenhagen, 2014.

Publikation: Working paper › Forskning

Harvard

Fisker, PK 2014 'Green lights: quantifying the economic impacts of drought' Department of Food and Resource Economics, University of Copenhagen, Frederiksberg. <http://econpapers.repec.org/RePEc:foi:wpaper:2014_11>

APA

Fisker, P. K. (2014). Green lights: quantifying the economic impacts of drought. Department of Food and Resource Economics, University of Copenhagen. IFRO Working Paper Nr. 2014/11 http://econpapers.repec.org/RePEc:foi:wpaper:2014_11

Vancouver

Fisker PK. Green lights: quantifying the economic impacts of drought. Frederiksberg: Department of Food and Resource Economics, University of Copenhagen. 2014.

Author

Fisker, Peter Kielberg. / Green lights : quantifying the economic impacts of drought. Frederiksberg : Department of Food and Resource Economics, University of Copenhagen, 2014. (IFRO Working Paper; Nr. 2014/11).

Bibtex

@techreport{b46bb365a299417f9c41bbb1f77983fb,
title = "Green lights: quantifying the economic impacts of drought",
abstract = "This study investigates the effect of drought on economic activity globally using remote sensing data. In particular, predicted variation in greenness is correlated with changes in the density of artificial light observed at night on a grid of 0.25 degree latitude-longitude pixels. I define drought as greenness estimated by lagged variation in monthly rainfall and temperature. This definition of drought performs well in identifying self-reported drought events since 2000 compared with measures of drought that do not take greenness into account, and the subsequent analysis indicates that predicted variation in greenness is positively associated with year-on-year changes in luminosity: If a unit of observation experiences a predicted variation in greenness that lies 1 standard deviation below the global mean, on average 1.5 - 2.5 light pixels out of 900 are extinguished that year. Finally, an attempt is made to estimate the global cost of drought.",
author = "Fisker, {Peter Kielberg}",
year = "2014",
language = "English",
series = "IFRO Working Paper",
publisher = "Department of Food and Resource Economics, University of Copenhagen",
number = "2014/11",
type = "WorkingPaper",
institution = "Department of Food and Resource Economics, University of Copenhagen",

}

RIS

TY - UNPB

T1 - Green lights

T2 - quantifying the economic impacts of drought

AU - Fisker, Peter Kielberg

PY - 2014

Y1 - 2014

N2 - This study investigates the effect of drought on economic activity globally using remote sensing data. In particular, predicted variation in greenness is correlated with changes in the density of artificial light observed at night on a grid of 0.25 degree latitude-longitude pixels. I define drought as greenness estimated by lagged variation in monthly rainfall and temperature. This definition of drought performs well in identifying self-reported drought events since 2000 compared with measures of drought that do not take greenness into account, and the subsequent analysis indicates that predicted variation in greenness is positively associated with year-on-year changes in luminosity: If a unit of observation experiences a predicted variation in greenness that lies 1 standard deviation below the global mean, on average 1.5 - 2.5 light pixels out of 900 are extinguished that year. Finally, an attempt is made to estimate the global cost of drought.

AB - This study investigates the effect of drought on economic activity globally using remote sensing data. In particular, predicted variation in greenness is correlated with changes in the density of artificial light observed at night on a grid of 0.25 degree latitude-longitude pixels. I define drought as greenness estimated by lagged variation in monthly rainfall and temperature. This definition of drought performs well in identifying self-reported drought events since 2000 compared with measures of drought that do not take greenness into account, and the subsequent analysis indicates that predicted variation in greenness is positively associated with year-on-year changes in luminosity: If a unit of observation experiences a predicted variation in greenness that lies 1 standard deviation below the global mean, on average 1.5 - 2.5 light pixels out of 900 are extinguished that year. Finally, an attempt is made to estimate the global cost of drought.

M3 - Working paper

T3 - IFRO Working Paper

BT - Green lights

PB - Department of Food and Resource Economics, University of Copenhagen

CY - Frederiksberg

ER -

ID: 126067020