000236342 001__ 236342
000236342 005__ 20180123004403.0
000236342 037__ $$a333-2016-14268
000236342 041__ $$aen_US
000236342 084__ $$aC11
000236342 084__ $$aD81
000236342 084__ $$aO12
000236342 084__ $$aO13
000236342 084__ $$aQ16
000236342 084__ $$aQ12
000236342 245__ $$aAgricultural Production, Weather Variability, and Technical Change: 40 Years of Evidence from Indi
000236342 260__ $$c2016
000236342 269__ $$a2016
000236342 270__ $$pMichler,   Jeffrey
000236342 270__ $$pShively,   Gerald
000236342 336__ $$aConference Paper/ Presentation
000236342 520__ $$aWe pose the simple question: how large of a role does the weather play in determining variability of agricultural production in India? Despite the long standing interest in agricultural economics of estimating the effect of weather on crop output, few quantitative measures of impact exist. We use a long panel of parcel level data from six villages in India that covers $44$ seasons from 1976 to 2011. Estimation the impact of weather variability on yield is complicated by the role of technological change over this period. In our descriptive analysis we generate several stylized facts about how agricultural production in the subcontinent has changed over the last $40$ years. Most importantly, mean yields have increased and the variance in crop production, measured relative to the mean, has decreased. In a regression context, using a multilevel model, we find strong evidence of technical change and that weather variability makes up only a small share of total variability in yield. We conclude that Green Revolution technologies have reduced the amount of weather related risk faced by farmers, even when we account for greater amounts of variation in weather due to climate change
000236342 542__ $$fLicense granted by Jeffrey Michler (jmichler@illinois.edu) on 2016-05-31T16:54:58Z (GMT):

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000236342 650__ $$aAgricultural and Food Policy
000236342 650__ $$aCrop Production/Industries
000236342 650__ $$aInternational Development
000236342 650__ $$aProduction Economics
000236342 650__ $$aRisk and Uncertainty
000236342 6531_ $$aWeather Risk
000236342 6531_ $$aAgricultural Production
000236342 6531_ $$aTechnical Change
000236342 6531_ $$aMultilevel Models
000236342 6531_ $$aRural India
000236342 700__ $$aMichler, Jeffrey
000236342 700__ $$aShively, Gerald
000236342 773__ $$d2016
000236342 8564_ $$s2833329$$uhttp://ageconsearch.umn.edu/record/236342/files/Michler_Shively_AAEA.pdf
000236342 887__ $$ahttp://purl.umn.edu/236342
000236342 909CO $$ooai:ageconsearch.umn.edu:236342$$pGLOBAL_SET
000236342 912__ $$nSubmitted by Jeffrey Michler (jmichler@illinois.edu) on 2016-05-31T17:06:25Z
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  Previous issue date: 2016
000236342 982__ $$gAgricultural and Applied Economics Association>2016 Annual Meeting, July 31-August 2, Boston, Massachusetts
000236342 980__ $$a333