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How Coal Production Changed during the Week Ended September 10


Aug. 18 2020, Updated 9:32 a.m. ET

Weekly coal production

According to EIA (U.S. Energy Information Administration) estimates, US coal shipments fell to 15.1 million short tons during the week ended September 10, 2016. This production estimate is nearly 6.2% lower than last week’s production estimate of 16.1 million short tons and 14.5% lower than the comparable week in 2015.

Of the total estimated shipments, 3.5 million short tons were estimated to come from the Appalachian region, 2.8 million from the Interior region, and the remaining 8.8 million from the Western region. Among the major coal-producing regions, the Interior region saw a major fall in coal production on a week-over-week basis.

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Why is this coal shipment indicator important?

Every week, the EIA publishes shipment data based on coal railcar loadings. Coal is an important commodity for railroad companies such as Union Pacific (UNP) and CSX (CSX). However, coal’s importance in freight has been falling due to the emergence of shale oil. It’s also been falling due to competition from other commodities and the reduced propensity of utilities (XLU) to stock coal.

More importantly, coal producers mine coal based on demand, so coal shipments mirror production over the long term. In this sense, a sustained rise or fall in coal shipments over a few weeks compared to the previous year is a significant indicator for coal producers (KOL). These producers include Peabody Energy (BTUUQ), Alliance Resource Partners (ARLP), Arch Coal (ACIIQ), and Cloud Peak Energy (CLD). However, there could be some deviations in the short term.

Key takeaways from the state of coal shipments

It’s important to remember that shipments are a function of demand and other factors such as rail availability and competition from other commodities. In this sense, weekly coal shipment data can be misleading. Apart from genuine demand-side issues, factors such as railcars not being available, bad weather, and supply issues can distort the data.


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