2.1. Methodology

To quantify the condition of the alfalfa hay market at a given point in time, we rely on the real monthly national average alfalfa hay price series. Months within this series with prices in the bottom 25th percentile of all monthly average prices were labeled with a dummy variable, DP, equal to 1 if the average monthly price was in the bottom 25th percentile (depressed price) and equal to 0 otherwise. Similarly, months with average prices in the top 25th percentile (elevated prices) were designated with the dummy variable, EP. Months falling between the 25th and 75th percentiles were considered to reside in a “typical price (TP) period.”

Real prices are necessary to use to identify the price periods (EP, DP, and TP) primarily when you consider the upward-trending nominal alfalfa hay prices in conjunction with upward-trending inflation throughout the period of our dataset (2003–2024). Considering these trends suggests that if nominal prices are used to determine the EP and DP periods, the likelihood of identify EP periods would increase with time, while the likelihood of identify DP periods would decrease with time. This implies that inflation must be controlled for to more accurately identify EP and DP periods. With upward-trending inflation, it is not possible to correctly identify the market price periods through time without analyzing real prices. Prices within this study were deflated using a general consumer price index published by the Bureau of Labor Statistics (BLS) (BLS, 2024) with 2023 used as the base or reference year.

After categorizing monthly observations within the USDA NASS national average price dataset into their respective price periods, all observations in the alfalfa direct hay report dataset were similarly categorized into their respective periods. This was accomplished by aligning each observation with the appropriate price period dummy variable based on the month and year in which the hay transaction took place. As an example, the average real alfalfa price as reported by USDA NASS in January 2000 was among the bottom 25th percentile of all months’ average real prices. Consequently, all hay transactions from January 2000 were coded as belonging to a DP period. Designating the hay transactions as belonging to DP and EP periods based on the national average real price offers a consistent and interpretable framework for identifying significant deviations from typical market conditions. This method is not without limitations. Using the national average price series to quantify market price strength assumes that national average prices adequately reflect localized market conditions despite potential regional variations in supply and demand. Local market conditions may vary from national trends due to factors such as regional weather and other production conditions. While regional variations exist, the national average serves as a reasonable proxy for underlying market strength, especially in the absence of localized data that comprehensively covers all relevant regions and time periods. The method is both practical and effective for identifying broad economic trends and dynamics that affect localized hay market prices.

An ordinary least squares (OLS) regression model was developed to evaluate the effect of the price periods (DP and EP) on the real price received for alfalfa as in

(1)

where Real_Hay_Price _i is the real sales price of alfalfa hay (2023 dollars) for the ith observation received by the seller; Year _i is a continuous time trend; Delivered _i is a binomial variable indicating if delivery to the buyer was included in the real sales price; Utility/Fair _i , Premium _i , and Supreme _i are binomial variables indicating the quality grade of an observation; Large_Round _i , 2_Tie_Small_Square _i , 3_Tie_Small_Square _i , 3x3_Square _i , and 3x4_Square _i are binomial variables indicating the bale type of an observation; EP _i and DP _i are binomial variables which indicate if an observation occurred in either a EP or DP period, respectively; and ε _i is the random error term. Table 3 provides definitions for all variables used in the analysis.

Table 3.

Variable definitions

It was hypothesized that the parameter estimate for Delivered would have a positive sign. This can be deduced as it is a reasonable assumption that there is added value in the product being delivered, which would be reflected in the price received. All quality grades were included in the model with the exception of Good. The remaining three quality grades (Utility/Fair, Premium, and Supreme) would have parameter estimates that show the expected relationship between each grade relative to Good quality. Thus, it was hypothesized that Utility/Fair would have a negative sign for the parameter estimate while Premium and Supreme would have positive signs for their respective parameter estimates as suggested by previous literature (Hopper et al., Reference Hopper, Peterson and Burton2004; McCullock et al., Reference McCullock, Davidson and Robb2014; Peake et al., Reference Peake, Burdine, Mark and Goff2019). The bale type 4 × 4 Square was dropped from the model, resulting in the parameters for all other bale types being estimated relative to 4 × 4_Square. Based on the work of McCullock et al. (Reference McCullock, Davidson and Robb2014) and Peake et al. (Reference Peake, Burdine, Mark and Goff2019), it was hypothesized that Large_Round would have a negative sign for its parameter estimate and both 2_Tie_Small_Square and 3_Tie_Small_Square would have a positive sign for their respective parameter estimates. Peake et al. (Reference Peake, Burdine, Mark and Goff2019) concluded that bale weight had a negative effect on price/ton. For this reason, it was hypothesized that the parameter estimates for 3 × 4_Square and 3 × 3_Square would have positive signs, indicating a positive impact on price/ton compared to the relatively heavier 4 × 4_Square bales.

It was hypothesized that the variables representing DP periods and EP periods would have negative and positive parameter estimates, respectively. Intuitively, one would expect a negative marginal effect to be estimated for DP, suggesting the price of alfalfa hay transactions would be lower on average during DP periods, with the opposite intuition holding true for EP. Interaction terms for the respective price periods and quality grades were included within equation (1). Due to limited knowledge from prior research, no attempt was made at hypothesizing signs for the parameters of these interaction variables. Evaluating the signs, magnitudes, and statistical significance of these parameter estimates is central to the objectives of this study. Plausible arguments could be made for both negative and positive signs for these variables. For example, it could be hypothesized that the DP X Supreme parameter might be negative. If high supply drives the lower relative prices, and demand for supreme-quality hay is relatively less elastic than for good-quality graded hay, this would result in a decreased price for supreme-quality hay relative to good-quality hay in DP periods. Conversely, if the demand for supreme-quality hay in a DP period is more elastic than good-quality graded hay, then a positive parameter estimate would be expected. Additional supply and demand relationships, together with strategic production decisions in times of relatively low/high prices, may result in positive or negative estimated effects for these interaction terms. This study seeks to provide evidence for the direction and magnitude of movement in the premiums and discounts associated with quality grades during the EP and DP periods.

3. Results and implications

Equation (1) was estimated using ordinary least squares regression, and the results are summarized in Table 4. The results indicate that bale type, quality grade, Year, and Delivered all significantly influenced the price received. The adjusted R-squared of 0.5669 indicates that over half of the variation in the real price received for the observations in the model is explained by the included explanatory variables. The intent of this model was not to capture all variables that affect alfalfa hay prices. Rather, the model intends to understand the effect of the relative price level of the alfalfa hay market on prices received for individual transactions. Additional variables could have been included in the model to increase the goodness of fit.Footnote ³ However, if omitted variables are uncorrelated with quality grades and the DP and EP periods, their omission is expected not to affect the model findings with respect to the objectives. The parameter estimate for Year is 1.971, statistically significant at the 1% level. This indicates that the marginal effect of each additional year is an increase of $1.91/ton of alfalfa hay on average. This suggests that even after accounting for inflation, prices are trending upward year over year on average by $1.91/ton. Increased export demand over the years of this dataset (Putnam et al., Reference Putnam, Matthews and Sumner2016) in conjunction with decreased US production of approximately 31.6 million tons from 2000 to 2023 helps explain this positive trend (USDA NASS, 2024c). Delivered has a parameter estimate of 37.830 and is significant at the 1% level. On average, if the transaction included delivery to the buyer, this hay received a premium of $37.83/ton over hay that did not include delivery. This aligned with the hypothesized sign for this variable indicating increased marginal value for delivered hay.

Table 4.

OLS results (Equation 1) for the effect of elevated and depressed price periods on alfalfa hay prices of varying quality grades

Notes: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively.

N = 26,696; F-value = 1942; adjusted R-squared = 0.5669.

The parameter estimates for each of the three quality grades included in the model relative to Good quality are statistically significant at the 1% level. Utility/Fair had a parameter estimate of −19.043, indicating that on average, holding all else equal, each ton of Utility/Fair hay received a price $19.04/ton lower than hay that was of the quality grade good. Premium and Supreme had parameter estimates of 41.86 and 54.52, respectively, indicating the average premiums in dollars per ton received for these respective quality grades relative to Good. These findings are consistent with both the hypothesized signs for these variables and the existing literature (Dant et al., Reference Dant, Burdine and Sears2017; Hopper et al., Reference Hopper, Peterson and Burton2004; Mayland et al., Reference Mayland, Shewmaker, Burns and Fisher1998; McCullock et al., Reference McCullock, Davidson and Robb2014; Peake et al., Reference Peake, Burdine, Mark and Goff2019).

The parameter estimates for each bale type included in the model are statistically significant at the 1% level. The 4x4 square bale type was omitted from the model and serves as the reference bale type when interpreting the parameter estimates of other bale types. Large round bales, 3 × 3 square bales, and 3 × 4 square bales are estimated as having average discounts relative to 4 × 4 square bales of $58.98, $25.33, and $17.61/ton, respectively, whereas 2-tie small square bales and 3-tie small square bales are expected to receive average premiums of $61.01 and $35.82/ton, respectively, relative to 4 × 4 square bales. These results align with the hypothesized sign for each variable with the exception of 3 × 4_Square and 3 × 3_Square. Contrary to the findings of Peake et al. (Reference Peake, Burdine, Mark and Goff2019), even though these bales are lighter than a 4 × 4 square bale, they were discounted relative to the large 4 × 4 square bale. Though these bales are lighter, it is hypothesized that they receive a discounted price due to the limited popularity of these bale types within our dataset. As outlined in Table 2, there are over 10.5 and 1.6 times more observations for 4 × 4 square than 3 × 3 and 3 × 4 square bales, respectively. With 4 × 4 square bales being the most common bale size within the dataset, it could be hypothesized that other large bale sizes receive a discount because many operations may be set up to use 4 × 4 square bales. Therefore, it is possible that these bales receive less value due to the inefficiencies experienced by incorporating these smaller bale sizes.

Parameter estimates for both DP and EP were statistically significant at the 1% level. The results suggest that prices in DP periods and EP periods are expected to be $29.04/ton less and $53.32/ton more, respectively, on average than prices in TP periods. The price period variables were constructed as percentiles (top and bottom 25th percentile) of the national average real alfalfa prices reported by USDA NASS. The national average alfalfa prices are expected to correlate highly with the direct hay report prices in the corresponding time periods. Thus, the findings of direction and significance of the marginal effects of the price period variables are expected (nearly predetermined).

The parameter estimates for the interaction between each of the three quality variables and price period variables are of much more importance to the accomplishment of this study’s objectives. The coefficients for the quality interactions with the DP period were each estimated with a negative sign and are statistically significant at a maximum of the 5% level. The results suggest that utility/fair-quality hay in a DP period receives an additional price reduction on average of $15.67/ton relative to good-quality hay in the same price period. This discount would be applied together with the average discount of $19.04 for utility/fair hay regardless of the price period. Premium and supreme-quality hay in a DP period receive a price reduction of $10.11 and $5.21/ton, respectively, in comparison to good-quality hay in a DP period. This suggests that the price premiums for premium and supreme-quality hay shrink during DP periods, whereas the discount of utility/fair hay expands (larger disparity in favor of good-quality hay).

The parameter estimates for the interactions between the EP periods and the three included quality grades within the model vary in estimated sign, but none are found to be significant at the 5% level. Additionally, the magnitudes of these EP × quality grade interactions are much smaller compared to their DP period counterparts. The results imply that there is not enough evidence to suggest that periods of relatively high alfalfa prices have a consistent and significant effect on the marginal effects of quality grade premiums and discounts relative to good-quality hay.

Table 5 demonstrates the expected price of alfalfa hay by quality grade and price period while holding all else constant within equation (1). Additionally, the expected price premium/discount between each quality grade relative to “good” quality is displayed within Table 5. When comparing the premiums or discounts for each quality in the DP periods with the premiums or discounts in the TP periods, it becomes clear that the price premiums for premium and supreme-quality hay are reduced, whereas the price discount for utility/fair-quality hay widens. A comparison of the price premiums or discounts for each quality in the EP periods with the premiums or discounts during TP periods reveals no expected differences.

Table 5.

Expected alfalfa hay price ^a received by quality grade during periods of elevated, typical, and depressed average prices

^a Prices were calculated by holding all variables from the estimated equation (1) at their means with the exception of price periods and quality grade. Coefficient estimates that were not found to be statistically significant were excluded.

^b Typical price period is composed of all observations that do not fall into depressed or elevated price periods.

^c Premium or discount is taken as the difference between the expected price of alfalfa hay in an assumed price period at a given quality grade and quality grade “good” within the same price period.

After empirical analysis through estimation of equation (1), a graphical analysis is completed for comparison. Figure 1 graphs the observed average price premiums or discounts by quality grade (relative to good) and price period within the dataset. A trendline was added for each quality grade spanning all three categories. Comparing the graphical results to those outlined in Table 5 adds robustness to the empirical findings. In the low-price era, average price premiums for premium and supreme-quality hay are reduced, while the average price discount for utility/fair-quality expands (more negative) in comparison to the TP periods. In EP periods, there is little variation in the price premiums or discounts for each quality grade when compared relative to TP periods. The linear trendlines in Figure 1 illustrate the idea that as transaction prices increase from depressed periods, the premiums received for premium and supreme-quality hay increase while the discounts received for utility/fair-quality hay are reduced.

Figure 1.

Average Price Differences by Quality Grade Relative to “Good” Quality by Price Period.

Figure 2 similarly complements the empirical findings by graphing the price premiums and discounts relative to “good” quality through time. The same DP and EP variables used in the regression model are overlaid on this graph to highlight the price periods through time. If a given month had a value of 1 for DP, it was shaded red. Likewise, if a given month had a value of 1 for EP, it was shaded in green. While the trends may not be immediately clear, there are periods in Figure 2 where the findings from the regression model can be seen. For example, around 2009–2010, average prices were low, as indicated by the red shading, reflecting a DP price period. During this period, a trend emerged showing that utility/fair-quality hay was receiving a greater discount in comparison to good-quality hay. Two examples from the 2012–2014 and 2022–2023 periods illustrate similar findings to the regression model during these EP periods. Although there is variability in the premium received for supreme-quality hay compared to good quality, on average, the premiums received during these EP periods do not appear to differ significantly from those received in a normal era.

Figure 2.

Average Price Premium or Discount through Time by Quality Grade Relative to “Good” Quality Notes: The premiums or discounts are calculated as is the difference from the average price for good quality hay for each of the average prices for the other hay quality grades. Elevated Price (EP) Period is all months that had an average price in the top 25% of all months. Depressed Price (DP) Period is all months that had an average price in the bottom 25% of all months.

3.1. Implications

Understanding the effect of the relative strength of the alfalfa hay market on premiums and discounts received for varying qualities of hay could affect the decision-making for both producers and consumers. In DP periods, there may be occasions when pursuing increases in quality is not the optimal economic decision. As the premiums for premium and supreme-quality hay shrink relative to good, the economic advantage of producing higher-quality hay might be offset or even overcome by the increased yield of lower-quality hay. Individual producers must weigh the expected decrease in quantity with the decreased premiums for higher-quality grades during periods of low market prices when making production decisions. In periods of low average prices, if the added benefit of increased yield outweighs the now-reduced benefit of higher-quality hay, it may be in the best interest of the operation to, on the margin, forgo quality and pursue yield. Understanding the effect of average market prices on premiums and discounts for quality aids producers in making this decision.

Producers may often target higher-quality production, yet adverse production conditions or weather events may lead to undesirable reductions in quality. Our results suggest that, particularly in periods of low average prices, producers should make every effort to avoid utility/fair-quality production as prices for these low-quality grades are decreased disproportionately relative to good-quality hay.

Because this study found no statistically significant evidence suggesting that high average market prices affect individual quality grade premiums/discounts, producers should not become enamored with the comparatively higher average prices for premium and supreme-quality grade hay as compared to good during periods of relatively high prices. Our findings indicate that during periods of high prices, the value of good-quality hay increases by a similar magnitude as that of utility/fair, premium, and supreme-quality hay. The baseline price premiums/discounts associated with utility/fair, premium, and supreme-quality hay during TP periods remain unchanged during EP periods. There is no evidence found in this study suggesting that producers need to consider changes in production practices solely due to periods of above-average market prices.

Understanding the effects of low average prices could aid consumers in reducing their input costs. While alfalfa hay does not have an indefinite storage life, it is common for consuming firms to maintain stocks on hand. While all prices, regardless of quality grade, are expected to be reduced in periods of depressed average prices, the price for utility/fair is the most heavily discounted quality grade during DP periods. If a consuming firm can purchase and store utility/fair alfalfa hay for later use, they could potentially reduce their input costs by capitalizing on the heavily discounted expected prices for utility/fair-quality hay during these periods. On the contrary, the premiums received for supreme-quality hay are not as significantly impacted by low average prices. While consumers can still expect comparatively lower premiums required for these higher-quality grades relative to good quality during DP periods, the discounts expected for utility/fair hay would be of a comparatively larger magnitude. It is likely that operations that can feed utility/fair-quality hay already do so. If an operation typically purchases utility/fair-quality hay and it is anticipated that average prices will rise, there is no better time to purchase utility/fair-quality hay with the intent to create a supply stock than in a DP period.

Because the premiums and discounts received for varying qualities of alfalfa hay during EP periods are not significantly different than during TP periods, there is not a specific quality grade that is comparatively a better purchasing option during EP periods. During these periods, all quality grades are affected similarly, resulting in increased costs that are consistent across grades. There is not a particular quality grade that stands out as a comparatively better deal, and consumers should not expect to find one grade more advantageous than another solely based on being in an EP period.

When considering the practical implications of our results, it is perhaps not reasonable to expect that producers/consumers would be able to empirically identify the current price period in any given future week. To do so, it would first require referencing the current national average nominal alfalfa price. This price would then require adjustment for inflation using the CPI to accommodate comparison with the national average real price from 2003 to 2023. This limits the practical application of our results from an empirical perspective. Yet, this does not imply that the results are without practical implications. Extension educators armed with our results could identify the price period at any given time and could provide enhanced Extension education and recommendations to alfalfa producers during a production period. On an even more practical level, producers/consumers may benefit as they undoubtedly have a sense of the market in light of current nominal prices in conjunction with their own historical recollection of prices. Using this practical sense of the current strength of the market, producers and consumers could adjust decision-making at the margin to align with the implications of our findings.

4. Conclusions and discussion

This study revealed that various factors, such as quality and bale type, significantly influence the reported sale prices of alfalfa hay. Holding all other factors constant, utility/fair-quality alfalfa hay is expected to receive an average price of $19.04/ton less than good-quality hay. In contrast, premium and supreme-quality hay is expected to garner prices of $41.86/ton and $54.52/ton more than good-quality hay, respectively. Additionally, 2-tie small square and 3-tie small square bales garner premiums of $61.01/ton and $35.82/ton, respectively, compared to 4 × 4 square bales. Conversely, large round, 3 × 3 square, and 3 × 4 square bales are expected to incur discounts of $58.98, $25.33, and $17.61/ton, respectively, in comparison to 4 × 4 square bales.

This study successfully achieved its primary objective by uncovering how the level of the average market price for alfalfa hay influences the price premiums and discounts associated with quality grades. Particularly, in periods of low prices relative to average price levels, the impact on premiums for higher-quality hay and discounts for lower-quality hay varies. Transitioning from a normal average market price to a low average market price is expected to result in an additional decrease of $15.67/ton in the discount for utility/fair-quality hay compared to the price for good-quality hay. During this same transition, price premiums for premium and supreme-quality hay are expected to decline but to a lesser extent than the impact to the price discount for utility/fair hay. The price premium for premium quality hay is expected to decrease by $10.10/ton, while the premium for supreme-quality hay is expected to decrease by only $5.21/ton. When average market prices are high, however, the effect on the price premiums/discounts across quality grades is expected to be much more homogeneous. We estimate that all hay qualities experience an approximate increase in value of $53.32/ton with no significant differences across grades.

Although data from 15 states/regions was included, the results are limited by an imbalance in the observations across states/regions. The majority of observations originate from Texas and Kansas, accounting for 75.03% of all data points. Outcomes might vary if this imbalance could be corrected. Moreover, results may diverge for hay varieties beyond alfalfa. Subsequent investigations could concentrate on employing similar methodologies to explore diverse geographical markets and other types of hay.

One additional limitation of this study lies in the methodology used to identify EP and DP price periods. The chosen methodology does not capture whether EP or DP prices are driven by shocks to supply, demand, or a combination of both. Gaining insights into the factors influencing market price variation would enhance the study. For example, while it’s reasonable to assume that abundant supply could lead to lower average prices, this study does not fully grasp how excess supply affects the premiums and discounts for various quality grades of alfalfa hay. Similarly, high demand might contribute to an upward trend in average alfalfa hay prices.

The method used for price period identification is also limited in its technical deployment by producers and consumers. This suggests that extension educators should aid in the more technical aspects of the dissemination of these results. However, producers and consumers are not constrained from benefiting from the result from an applied perspective given their own intuition concerning the current strength of the market. Future research should explore alternative methods for characterizing the market price level to better discern the impact of supply and demand dynamics on the premiums and discounts associated with different quality grades of alfalfa hay and enable producers/consumers to more fully participate in the technical aspects of price period identification.

Understanding the relationship between the average price level and the premiums/discounts for varying qualities of alfalfa hay is important for both producers and consumers. In times of low average prices, the decision to prioritize yield over quality may vary among operations, with some benefiting from pursuing higher yields considering reduced premiums for higher-quality hay. Conversely, operations specializing in lower-quality hay (utility/fair) may find it advantageous to improve quality during these times to offset the effect of expected increased discounts for lower-quality hay during these periods. However, during periods of elevated average prices, all quality grades are similarly affected, resulting in a consistently increased price for producers across the board. Therefore, there’s no single quality grade that stands out as a better purchasing option for consumers during such times. Overall, understanding these dynamics can aid producers in optimizing production decisions and can assist consumers in managing input costs.