weather, production, crop yield, agriculture, economics, Crop Production/Industries, Land Economics/Use, Production Economics, Productivity Analysis, Resource /Energy Economics and Policy,

Jiang, Yong

Koo, Won W.

English

Research Papers in Economics

Identifying the Impact of Weather Variation on Crop Yield in 
the Northern Plains 
Center for Agricultural Policy and Trade Studies  
Dept. of Agribusiness and Applied Economics 
North Dakota State University, Fargo, ND 58103 
Phone: (701)231-7451, Email: yong.jiang@ndsu.edu  
Yong Jiang and Won Koo 
Poster prepared for presentation at the Agricultural & Applied Economics Association 2011 AAEA & NAREA Joint Annual Meeting, Pittsburgh, Pennsylvania, July 24-26, 2011 
Copyright 2011 by Yong Jiang and Won Koo.  All rights reserved.  Readers may make verbatim copies of this document for non-commercial purposes by any means, provided that this copyright notice 
appears on all such copies. Identifying the Impact of Weather Variation on Crop Yield in 
the Northern Plains  
Yong Jiang and Won W. Koo, Center for Agricultural Policy and Trade Studies  
North Dakota State University, Fargo, ND 58103 
Phone: (701)231-7451, Email: yong.jiang@ndsu.edu  
Crop Reporting Districts in North Dakota 
Research Objective 
•   Examine weather variation and its impact on 
spring wheat yield in North Dakota   
•   Understand the role of weather in spring 
wheat production and growth, agroecosystem 
vulnerability to weather, and possible spatial 
heterogeneity  
•   Simulate the impact of climate change on 
spring wheat yield 
Background and Motivation 
•  Varying weather patterns have partially 
contributed to global food market instability.  
•  Changing climate raises concerns on 
agroecosystem vulnerability and food security . 
•  Information on the weather-food production 
linkage is needed to inform government actions 
to better help agroecosystem adaptation to 
climate change 
Econometric Estimation 
•  Approach: seemingly unrelated regression 
•  Modeling tool: Matlab  
Research Challenges and Issues 
•  Stochastic weather process and crop growth 
    Weather as a stochastic process can be 
measured by different variables and in many 
different ways.  How to characterize weather 
variation in relation to the physiology of crop 
growth is an open empirical question.    
•  Dynamic and adaptive production process 
    Agricultural production may be a dynamic 
process, with input decision depending on 
current prices, weather turnout, and crop growth 
progress.   
•  Spatial heterogeneity and production 
adaptation 
   Biophysical conditions for crop growth are 
heterogeneous across space.  Agricultural 
production can vary among regions and may 
have well adapted to local production conditions, 
including both infrastructure investment and 
biophysical conditions.  
Research Findings 
•  There is significant spatial heterogeneity in the effect of 
precipitation on crop yield. 
•  The effect of temperature on crop growth are similar, despite minor 
differences, across space. 
•  The effect of weather variation on crop yield might be local specific, 
depending on other biophysical conditions and perhaps reflecting 
farm adaptation to local production conditions.  
SW Yield v.s. Precipitation1  
Data 
•  Yield 
    crop reporting district total production output divided by planted 
acreage, both of which are from USDA NASS 
•  Weather variables 
   cooperative observations of daily weather (temperature and 
precipitation)  from national climatic data center 
•  Soil quality and prices 
   variation in soil quality measured by variation in acreage, prices 
including  output price, and fertilizer price index, all of which are from 
USDA NASS 
 
An Integrated Bioeconomic Model of Weather and Crop Yield  
Crop Production Function 
•  Assumption: farmers tend to maximize their production profits once 
crops have been planted 
•  Economic model:  
    Max   Profit = PriceOutput X Acreage X Yield(fixed inputs, variable inputs, 
biophysical conditions, production technology) – Inputvariable X Acreage X 
PriceInput  
•  Empirical specification of production function:  
    Yield = Y(priceinput /priceoutput, biophysical conditions, production 
technology) 
Physiology of crop growth 
•  Physiological characteristics and assumptions: 
•  The effects of temperature and precipitation may be cumulative 
•  The effects of temperature and precipitation may vary depending on 
the stage of crop growth 
•  There may exist optimal temperature and precipitation for crop 
growth 
•  Empirical specification:   
    ln(Yield) =, f(priceinput /priceoutput, cumulative heat and precipitation, soil 
quality, production technology) 
SW Yield v.s. Temperature2  
West  East  Central  West  East  Central 
North 
Central 
South 
1. Yield in natural logarithm with other 
variables evaluated at sample means 
2. Yield is relative growth 
rate, y axis being indicative  

Identifying the Impact of Weather Variation on Crop Yield in the Northern Plains

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