By Jamie Pietruska

Special to The Washington Post

The recently announced relocation of the U.S. Department of Agriculture’s Economic Research Service (ERS) from Washington, to the Kansas City region is more than an office move. While it will cost more than two-thirds of its 300 employees their jobs, White House Chief of Staff Mick Mulvaney has celebrated it as “a wonderful way to sort of streamline government.” The implication? That the federal statistical agency is expendable.

But the ERS is essential. This independent research arm of the USDA draws on massive amounts of data about the agricultural economy to produce objective analysis on issues that touch every household in the country: commodity supply, demand and trade, as well as questions of food security and safety and climate change. ERS is an indispensable resource for farmers, food manufacturers and policymakers — but its work affects all our lives.

And that is the danger of gutting this agency. Part of a larger movement by the Trump administration to dismantle the federal government from within, this latest move seeks to undermine expertise, data and nonpartisan scientific knowledge. The beneficiaries? Large corporations that stand to profit from ideologically motivated agriculture policy. But with deep cuts to ERS, consumers may suffer if they aren’t able to learn about trends in food product recalls or know whether their grocery bills might increase.

The nation’s oldest and most important federal agricultural statistics agency has a long history and reputation for objectivity. The USDA established its Division of Statistics in 1863, just a year into its existence. Created during the Civil War — a period of federal government expansion — this agency was the first long-term commitment to collecting national agricultural statistics. Its founding mission was to produce “disinterested” agricultural statistics as a public good. It sought to protect farmers from market-manipulating middlemen and crop forecasters who had previously wreaked havoc on the agricultural economy.

Nearly 150 years before the term “Big Data” was coined, the Division of Statistics linked farmers, government experts and markets in a vast information network that aggregated data on crop condition, acreage and yield for many crops that Americans depended on to eat and thrive. After the Civil War, the Division of Statistics grew until its virtual army of state crop reporters and local volunteers numbered nearly a quarter-million people.

By the early 20th century, they were submitting 2.5 million reports annually to be analyzed. The purpose of this “statistical machinery” was to produce more precise calculations of national and regional crop yields to reduce the uncertainties of supply and lessen the risk for farmers, merchants and brokers. They protected farmers’ livelihoods during a time when the rise of commodity futures — trading predictions of future prices rather than physical goods themselves — made speculators richer and farmers poorer.

What looked like tedious columns of numbers became powerful weapons on commodity exchanges, where predictions of a crop’s yield determined prices. In what newspapers called a “battle of crop estimates,” the USDA, with its unbiased crop figures, faced off against forecasters who moved prices up with rumors of a damaged crop or down with inflated forecasts of a record harvest.

The most notorious of the bear-market forecasters was British “cotton prophet” Henry M. Neill, whose occasionally accurate predictions of record-setting yields dropped prices to record lows and depressed the U.S. cotton economy in the 1890s. Lauded by British spinners who wanted cheap cotton, Neill was reviled by Southern growers who called him a fraud and blamed him for their poverty. Ultimately, the USDA’s chief statistician discovered that Neill’s cotton forecasts were based on falsified data, and his reputation as “the greatest cotton crop estimate expert in the world” was ruined. The Neill controversy helped lead to a series of reforms that stabilized cotton markets and regulated commodity futures trading, making it harder for forecasters to manipulate prices at farmers’ expense.

Not everybody embraced the USDA’s statistics, especially those who didn’t benefit from them. Cotton brokers, in particular, faulted the USDA for dressing up “guesswork” in the guise of mathematical precision, because they believed the USDA’s numbers, which trusted farmers’ assessments of their own crops, threatened their profits.

But by the early 20th century, the value of accessible, robust, unbiased and national agricultural statistics was clear to many farmers, academics and journalists. As a 1906 handbook on cotton production published in Doubleday’s “The Farm Library” series acknowledged, “everyone interested has come to recognize the need of some strong disinterested agency to make reports of actual facts so that all concerned may be better guided as how to buy or sell.”

The good data of the USDA didn’t eliminate every single attempt at manipulating agricultural commodity markets with rumors or misleading forecasts. But, as the head of the USDA’s agricultural statistics program explained in 1915, government crop figures functioned “in the same way that a police or constable force tends to check but not entirely prevent crime in a community.”

Contemporary lawmakers agreed that although the federal crop reporting program was not perfect — predicting the future remained elusive — it was far preferable to having none at all and far better than ceding control of commodity markets to speculators and their self-interested statistics. In the early 20th century, the USDA began issuing regular market outlooks, which tracked price trends and provided more extensive data on the current and future state of crops — all of which gave farmers a big-picture view of the agricultural economy and helped them manage their operations more efficiently and profitably as farm production skyrocketed in the 20th century.

While the federal agricultural statistics program moved within the federal bureaucracy during the 20th century, its mission of providing objective economic data as a public good remained unchanged. During World War I, expanded crop reports and data on the process of agricultural production were necessary for wartime agencies to function. The Great Depression and Dust Bowl brought an urgent need for agricultural statistics to implement federal disaster relief and New Deal farm programs, and World War II food rationing and price controls depended on accurate figures on current and future food supply.

With increased research funding for postwar agriculture — an era of improved farming technologies, supermarkets and agribusiness — the USDA consolidated and enhanced its research on agricultural economics and statistics. The ERS (alongside the Statistical Reporting Service) was established in 1961, broadening the scope of federal agricultural statistics beyond the farm to conduct research on the entire food system to be used by farmers, consumers and policymakers.

This systems-oriented research framework makes the ERS crucial today because it addresses the interconnectedness of the food system with other aspects of the economy and society. Objective statistical analysis by ERS on topics such as the immigration status of hired crop farmworkers, the costs of foodborne illnesses to consumers who seek medical care and the economic benefits of increasing SNAP (food stamp) benefits is crucial for ensuring the well-being of the country. At a time when the current administration deploys false statements about immigration, health care and social welfare programs on a regular basis, being able to trust the nonpartisan and objective data produced by this government agency is even more important.

The market volatility created by self-interested crop forecasters in the 19th-century United States should remind us of the power of private firms to manipulate commodity prices and the danger of allowing them to do so unchecked. At the time, the government, growers and manufacturers came to see the urgent need for a robust federal agency to counter inaccurate, biased or falsified agricultural statistics. It worked. But now the Trump administration is crippling the ERS, facilitating the entrance of biased statistics and market manipulators into the market once again. At a time when public trust in government is near historic lows, preserving federal agricultural statistics as a public good should be a top priority that everyone can support.

Jamie Pietruska is associate professor at Rutgers University and author of “Looking Forward: Prediction and Uncertainty in Modern America” and “‘A Tornado is Coming!’: Counterfeiting and Commercializing Weather Forecasts from the Gilded Age to the New Era.”