Post on 22-Apr-2023
Reap the Whirlwind Microclimate effects of wind farms on crop yields
Dan Kaffine CU Dept. of Economics and RASEI
7/22/2014
Mo8va8on
• US electricity from wind has grown from <1% in 2007 to nearly 5% currently – growth likely to conKnue • With that growth, increased interest in understanding potenKal posiKve and negaKve externaliKes associated with wind • Emissions, property values, health, wildlife, grid stability, O&M impacts on fossil fuel plants, jobs
• Given overlap of “Wind Belt” and “Farm Belt” – might wind power affect crops? • If so, important implicaKons for private and social welfare
Why might there be a link?
• We know that climate (temp, precip, etc) affects crops • We also know that wind turbines create “microclimate” effects
• Mixing of air temperatures • Mixing of CO2 • Humidity effects • Wind speed • Scale 10-‐60km downwind
• Do these microclimate effects also impact crops? • If so, is it a posiKve or negaKve impact?
Basic idea
• Examine impact of wind farms on crop yields following Deschenes and Greenstone (2007) – county-‐level panel
𝑦↓𝑐𝑡 = 𝛼↓𝑐 +𝛽𝑊↓𝑐𝑡 + 𝛾𝑋↓𝑐𝑡 + 𝑌↓𝑡 + 𝜀↓𝑐𝑡
• Regress yield 𝑦↓𝑐𝑡 in county c at Kme t against wind capacity 𝑊↓𝑐𝑡 • Control for precipitaKon, temperature, etc in 𝑋↓𝑐𝑡 • County fixed-‐effects and year fixed-‐effects to remove Kme-‐invariant county characterisKcs and common yield shocks over Kme
• Data sources • Wind capacity – EIA-‐860 • Yields, acreage, producKon – NASS census (every 5 years) • Precip, temp – various sources
Preliminary work
• Start by looking at Iowa • Lots of wind, small counKes • Average county size is 30 km x 30 km • 99 counKes, 4 censii of data (1997-‐2012) • Corn is king (also look at soy, oats and silage)
• First cut: simple county and year FE model • While this ignores important factors, useful first akempt to see if the relaKonship we expect to see exists • Will be further refined in the months to come
Preliminary results -‐ IA Crop yield
Corn grain (bu) 0.0197 11.80* 3,495* 0.0187* 10.24* 3,075*
(0.0136) (7.32) (1,957) (0.0114) (6.18) (1,691)
Wind measure MW MW/sqmi MW/acre MW MW/sqmi MW/acre
County FE Y Y Y N N N
Ag District FE N N N Y Y Y
Year FE Y Y Y Y Y Y
N 396 396 396 396 396 396
Preliminary results -‐ IA Crop yield
Corn grain (bu) 0.0197 11.80* 3,495* 0.0187* 10.24* 3,075*
(0.0136) (7.32) (1,957) (0.0114) (6.18) (1,691)
Soy (bu) -‐0.0030 -‐0.941 -‐206 -‐0.0030 -‐1.16 -‐263
(0.0032) (1.71) (328) (0.0030) (1.58) (310)
Oats (bu) 0.0014 0.963 0.704 0.008 4.84 2.12
(0.009) (4.90) (1.61) (0.007) (4.22) (1.41)
Corn silage (t) -‐0.000 -‐0.715 -‐7.76* 0.002 0.874 -‐1.38
(0.003) (1.69) (4.34) (0.003) (1.39) (3.44)
Wind measure MW MW/sqmi MW/acre MW MW/sqmi MW/acre
County FE Y Y Y N N N
Ag District FE N N N Y Y Y
Year FE Y Y Y Y Y Y
N 396 396 396 396 396 396
Next steps
• Modestly encouraging results • Lots to do
• Definitely need to include precipitaKon and temperature data • More states • More Census data (<1997)
• Hopefully preliminary finding holds up • Point esKmate on corn suggests about ~$6/MWh posiKve benefit • Smaller than ~$30/MWh CO2 avoidance benefit BUT it’s all local • At 2013 generaKon levels and prices, ~$100 million in benefit to Iowans