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Do USDA Reports Move the Markets?

Do USDA Reports Move the Markets?

The answer is typically yes, although previous studies differ in terms of measures of information, market reaction, time periods, and evaluation methodology.  Regardless of these differences, most of these studies follow what is known an event study approach. The basic notion of the event study is simple: if prices react to the announcement of information (“the event”) in an efficient market, then the information is valuable to market participants (Campbell, Lo, and MacKinlay, 1997) as it helps find new, better informed, equilibrium price.  Thus, market reaction to report releases is considered evidence of their informational value.

Specifically, variability of futures prices around important scheduled news announcements should be characterized by a “spike” in variability on the announcement date and “normal” variability on non-announcement dates (Sumner and Mueller, 1989).  For example, figure 4 shows corn market reaction to WASDE report release (Isengildina-Massa et al., 2008) across the reaction window (5 days before and after report release). Since, under market efficiency, futures prices represent the conditional expectation of spot prices at contract maturity, the spike in futures return variance reflects the change in market participants’ expectation of spot prices due to the news announcement.  Note that the change in futures prices can be either positive or negative depending on the implications of the news for the level of prices, therefore the analysis focuses on changes in volatility as a measure of market reaction, typically measured as price changes (futures returns).  The purpose of the statistical tests is to determine whether futures return variability on event (report release) sessions is significantly different from normal variability on non-report days.

Table 4 provides a summary of the first set of event studies where the event is measured by the date and time of USDA report release and indicates plentiful evidence of corn market reaction to USDA reports.  Most of these studies (e.g., Isengildina-Massa et al, 2021; Ying, Chen, and Dorfman, 2019; Dorfman and Karali, 2015) measured unconditional market impact (where other factors were not considered) and measure market reaction using various parametric and non-parametric tests.  For example, figure 5 shows corn market reaction to USDA reports over 1985-2018 (Isengildina-Massa et al, 2021) and suggests that markets move the most when several reports are released at the same time, such as WASDE, Grain Stocks, and Crop Production Annual Summary in January, Prospective Plantings and Grain Stocks reports in March, Acreage and Grain Stocks in June and WASDE and Crop Production in August.  On the other hand, most WASDE reports released by themselves do not cause significant market information (significance indicated by horizontal black line) with the exception of May WASDE that contain first estimates for the next marketing year. Thus, report clustering may have led to overestimation of WASDE market impact in some of the earlier studies that did not take it into account.

Several of these studies (e.g., Fortenbery and Sumner, 1993; Isengildina-Massa et al, 2008; Ying, Chen, and Dorfman, 2019; and Isengildina-Massa, et al, 2021) also examined changes in the impact of USDA reports over time. For example, Ying, Chen, and Dorfman (2019) found that the impact of Prospective Plantings, Acreage, Grain Stocks, WASDE and Crop production reports increased over time, while the impact of Crop Progress reports decreased.  On the other hand, Isengildina-Massa, et al (2021) found a slight decrease in impact of August and November Crop Production reports over time, while the impact of other reports has remained strong, as shown in figure 6.  Thus, there is some evidence that the impact of the reports focused on estimating production may have declined in recent years, likely due to increased competition from private data sources and expansion of remote sensing technology for crop production estimation.

Another group of studies measure the release of USDA reports using dummy variables, along with modeling the underlying market dynamics to control for effects like daily, monthly and seasonal patterns, inventory conditions and delivery horizon to better isolate the report impact (e.g., Karali, 2012; Mattos and Silveira, 2016).  These studies demonstrate the impact of USDA reports on not just volatility but the co-movement (covariances) across various commodities (Karali, 2012), and reveal that markets react to both USDA and international market information (Mattos and Silveira, 2016).  For example, Mattos and Silveira (2016) find that USDA reports increase the conditional standard deviation of corn futures returns by 28.13% during August-October and 11.91% during the rest of the year.  On the other hand, the impact of CONAB (Brazilian Food Supply Company) reports are statistically distinguishable from zero only in the November-January period, when they increase the conditional standard deviation of futures returns by 11.42%.  Thus, corn market reaction to USDA reports is much stronger than that to Brazilian market reports.

Overall, these studies examined market reaction to Crop Production reports (e.g., Isengildina-Massa et al, 2020; Good and Irwin, 2006; Milonas, 1994; Fortenbery and Sumner, 1993; French, Leftwich and Uhrig, 1989; Sumner and Muller, 1989; Fackler, 1985), Prospective Plantings reports and Acreage reports (e.g., Ying, Chen, and Dorfman, 2019; Dorfman and Karali, 2015; Karali, 2012; Isengildina-Massa et al, 2021); Grain Stocks reports (Isengildina-Massa et al, 2021; Ying, Chen, and Dorfman, 2019; Dorfman and Karali, 2015; Karali, 2012), WASDE reports (Arnade, Hoffman, and Effland, 2021; Isengildina-Massa et al, 2021; Ying, Chen, and Dorfman, 2019; Mattos and Silveira, 2016; Dorfman and Karali, 2015; Karali, 2012; Isengildina et al, 2008), Crop Progress reports (Lehecka, 2014), and Export Sales reports (Patterson and Brorsen, 1993; Conklin, 1983).