This is my assignment:

One of the learning outcomes for this class is to appreciate the connection between descriptive and model-based analyses of agricultural markets and prices. Farmdoc daily (farmdoc.illinois.edu) is an outlet that frequently uses such descriptive analysis. It is a leading source for information and analysis of issues related to US cornbelt agriculture, broadly defined. A typical farmdoc article is 1000-1500 words with 2-4 figures. Articles are frequently based on academic research but written to be broadly accessible to non-economists.

Your assignment is to write a farmdoc style article on a topic related to agricultural markets and prices. Ideally, this article captures some of the descriptive analysis (see: Mahoney, 2022) necessary to support your research paper for this class. In the first stage of this assignment, you will draft an article that follows the parameters above for review by me and your peers. In addition to the article, you must submit the data and code used to generate the figures or tables in your article.

Here is what I wrote:

Austin Belman
ACE 527
Understanding Local Corn Basis Behavior During Harvest Periods in Illinois: Insights into Broader Futures Market Trends
Introduction
In agricultural markets, the relationship between local cash prices and futures prices is pivotal for producers, traders, and policymakers. The "basis"—defined as the difference between the local cash price of corn and the futures price—reflects local supply and demand conditions relative to the broader market. For Illinois, a leading corn-producing state, local market dynamics such as harvest pressures can significantly impact the basis, especially during harvest periods when supply surges temporarily.
Research Question: To what extent does local corn basis behavior during harvest periods in Illinois reflect broader trends in futures prices?
This article explores this question by analyzing and comparing the local corn basis during harvest and non-harvest periods in three key regions: Decatur, Peoria, and East St. Louis. Understanding these relationships is crucial for stakeholders to make informed decisions about marketing, storage, and hedging strategies in the agricultural economy.
Data Overview
The data used in this study comprise local basis values for three major corn market locations in Illinois—Decatur, Peoria, and East St. Louis—and corresponding futures price data. The dataset spans from 2005 to 2024, covering 17 years of harvest and non-harvest periods. Data sources include:
•	Local Basis Values: Collected from regional grain elevators and market reports, representing the difference between local cash prices and futures prices at each location.
o	DEC_BASIS (Decatur, IL): Represents the local corn basis where Archer Daniels Midland (ADM) operates a major grain facility.
o	PEO_BASIS (Peoria, IL): Represents the local corn basis in Peoria, another key market with significant grain handling facilities.
o	ESL_BASIS (East St. Louis, IL): Represents the local corn basis where Cargill operates a major grain facility.
•	Futures Prices: Obtained from the Chicago Mercantile Exchange (CME) Group.
o	FUT_1: The nearby futures contract (typically the contract with the nearest delivery month).
o	FUT_2: The second nearby futures contract.
•	Harvest Period: Defined based on the typical corn harvest season in Illinois, from September 1st to November 30th each year, allowing for a comparison between harvest and non-harvest periods.
Understanding the Basis
The basis is significant because it captures local market conditions not reflected in futures prices. A stronger (more positive) basis indicates higher local demand relative to supply, whereas a weaker (more negative) basis suggests that local supply exceeds demand. Monitoring basis levels helps farmers decide whether to sell immediately or store grain for future sale, impacting profitability.
Analysis and Results
1.	Time Series of Futures Prices and Basis (2005–2024)
 
Figure 1: Time Series of Futures Prices and Local Basis Values (2005–2024)
Description: The top panel displays futures prices (FUT_1 and FUT_2), and the bottom panel shows local basis values for Decatur, Peoria, and East St. Louis. Harvest periods are shaded in gray.
Futures Prices Behavior (2005–2024)
•	Cyclical Patterns: Futures prices exhibit cyclical trends with peaks around 2008, 2012, and 2021, corresponding to significant market events like the global financial crisis, the 2012 U.S. drought, and recent supply chain disruptions.
•	Price Range: Prices fluctuate between approximately $3 and $8 per bushel.
•	Contract Correlation: FUT_1 and FUT_2 move closely together, indicating a strong correlation between nearby and second nearby contracts.
Basis Values Behavior (2005–2024)
•	General Trend: Basis values fluctuate around zero, typically ranging between -$0.50 and $0.50 per bushel.
•	Harvest Impact: During harvest periods, basis values tend to dip, reflecting increased local supply and downward pressure on local cash prices relative to futures prices.
•	Post-Harvest Recovery: Basis values often recover after harvest as supply pressures ease.
Regional Observations
•	Decatur: Shows less variability in basis during harvest periods compared to Peoria and East St. Louis.
•	Peoria and East St. Louis: Exhibit more pronounced dips in basis during harvest, suggesting greater local supply pressures.
Key Insights
•	Local Harvest Pressure: The basis tends to weaken during harvest periods due to the influx of new crop supplies, which aligns with the expected behavior under increased local supply.
•	Broader Market Correlation: Basis values fluctuate around futures prices but react to localized conditions like harvest, indicating that while local markets are sensitive to local supply, they are still influenced by broader futures trends.
•	Regional Market Connectivity: Similar basis movements across the three regions suggest strong regional market integration, with markets reacting similarly to broader economic pressures and harvest dynamics.
 
2.	Comparison of Mean Prices During Harvest and Non-Harvest Periods
 
Figure 2: Comparison of Mean Basis Values and Futures Prices During Harvest and Non-Harvest Periods
Description: Bar charts compare average basis values and futures prices during harvest (red bars) and non-harvest (blue bars) periods for each crop year.
Findings
•	Decatur (DEC_BASIS)
o	Stability: Basis values are relatively stable across years, with minimal differences between harvest and non-harvest periods.
o	Implication: Decatur's market may have robust local demand or sufficient storage capacity, mitigating harvest supply impacts.
•	Peoria (PEO_BASIS)
o	Significant Differences: Notable differences between harvest and non-harvest basis values, especially post-2015.
o	Non-Harvest Strength: Higher basis values during non-harvest periods suggest tighter supply or increased demand outside harvest.
•	East St. Louis (ESL_BASIS)
o	High Variability: Most variability between harvest and non-harvest periods.
o	Recent Trends: Non-harvest basis values are notably higher in recent years, indicating pronounced local market pressures when harvest supply is absent.
•	Futures Prices (FUT_1 and FUT_2)
o	Higher Non-Harvest Prices: Futures prices are generally higher during non-harvest periods, reflecting broader market anticipation of tighter supply post-harvest.
Key Insights
1)	Local Basis Behavior: The basis generally weakens during harvest due to increased supply, but the extent varies by region.
2)	Regional Differences: Decatur's stability contrasts with Peoria and East St. Louis, highlighting how local market conditions affect basis behavior differently across regions.
3)	Futures Prices Alignment: The trend of higher futures prices during non-harvest periods aligns with supply-demand economics at the broader market level.

 
3.	Correlation Analysis Between Basis Values and Futures Prices
 
Figure 3: Correlation Matrices for Harvest and Non-Harvest Periods
Description: Heatmaps display correlation coefficients between local basis values and futures prices during harvest and non-harvest periods. Positive correlations are in blue; negative correlations are in red.
Harvest Period Correlations
•	Futures Contracts: FUT_1 and FUT_2 are highly correlated (correlation ≈ 1), moving in tandem.
•	DEC_BASIS
o	Strong Positive Correlation: Correlates strongly with futures prices (≈ 0.84), indicating Decatur's basis moves in line with futures even during harvest.
•	PEO_BASIS and ESL_BASIS
o	Moderate to Weak Correlations: Peoria shows moderate correlations with futures prices, while East St. Louis exhibits weak or negative correlations, suggesting local factors dominate during harvest.
Non-Harvest Period Correlations
•	Futures Contracts: Maintain high correlation.
•	DEC_BASIS
o	Very Strong Correlation: Increased correlation with futures prices (≈ 0.91), showing close alignment with broader market trends outside harvest.
•	PEO_BASIS and ESL_BASIS
o	Increased Correlations: Both show higher correlations with futures prices compared to harvest periods, though still less than Decatur's.
Inter-Regional Basis Correlations
•	Stronger During Non-Harvest: Correlations between basis values at the three locations are higher outside the harvest season, indicating increased regional market integration when local supply fluctuations are minimized.
Key Insights
•	Stronger Relationship Outside Harvest: Local basis values, especially in Decatur, align more closely with futures prices during non-harvest periods.
•	Weaker Correlations During Harvest: Local supply conditions have a larger, independent influence on the basis during harvest, particularly in East St. Louis.
•	Regional Differences: Decatur is more integrated with broader market movements, while East St. Louis is influenced more by local dynamics during harvest.
 
Discussion
Understanding Regional Differences
•	Decatur
o	Market Integration: Its strong correlation with futures prices suggests higher market integration due to infrastructure advantages, such as superior transportation links and larger processing facilities.
o	Consistent Local Demand: Stable demand from ethanol plants and feed mills may buffer against supply fluctuations.
o	Storage Capacity: Greater storage facilities may reduce the immediate impact of harvest supply surges on local prices.
•	Peoria
o	Moderate Integration: Shows some alignment with futures markets but is more affected by local supply demand dynamics, particularly during harvest.
o	Local Demand Variability: Demand may fluctuate more, or storage capacity may be less than Decatur's.
•	East St. Louis
o	Local Factors Dominant: Weak correlation with futures prices during harvest suggests local supply conditions heavily influence the basis.
o	Infrastructure Constraints: Possible limitations in storage and transportation could amplify the impact of local supply surges.
o	Market Structure: Fewer buyers or less diversified demand might lead to greater price sensitivity during harvest.
Implications for Stakeholders
•	Farmers
o	Marketing Strategies: Understanding basis patterns can inform decisions on when to sell or store grain. In regions where the basis weakens significantly during harvest such as East St. Louis, storing grain for sale during stronger basis periods could enhance profitability.
o	Risk Management: Awareness of local basis behavior aids in developing effective hedging strategies to manage price risks.
•	Traders and Merchandisers
o	Procurement Timing: Insights into regional basis movements help optimize buying and selling schedules.
o	Arbitrage Opportunities: Differences in basis behavior across regions may present opportunities for spatial arbitrage.
•	Policymakers
o	Infrastructure Investment: Identifying regions with high basis volatility can guide investments in storage facilities and transportation infrastructure to improve market efficiency.
o	Support Programs: Tailored support for regions more affected by local supply pressures can help stabilize local economies. 
Conclusion
The behavior of local corn basis values during harvest periods in Illinois provides valuable insights into the interplay between local market conditions and broader futures market trends. While increased local supply during harvest generally weakens the basis across all regions, the degree of impact varies.
Decatur's strong correlation with futures prices suggests a high degree of market integration, with local basis movements closely mirroring broader market trends, especially outside harvest periods. Peoria and East St. Louis exhibit more pronounced local effects during harvest, indicating that local supply and demand dynamics play a more significant role.
Understanding these regional differences is crucial for stakeholders. Farmers can optimize marketing and storage decisions based on local basis behavior, while traders and policymakers can work toward enhancing market efficiency through infrastructure improvements and supportive policies.
Overall, the study underscores the importance of local market analysis within the context of global futures markets. Recognizing how local conditions interact with broader trends enables more informed decision-making and contributes to the resilience and efficiency of the agricultural sector.
 
References
•	U.S. Department of Agriculture (USDA) Market Reports
•	Chicago Mercantile Exchange (CME) Group Futures Data
•	Illinois Department of Agriculture Crop Progress Reports