How Smart Is Big Brother?

James L. Payne has taught political science at Yale, Wesleyan, Johns Hopkins, and Texas A&M. His latest book, The Culture of Spending, examines the popular arguments for big government.

One of the attractions of government as a problem-solver is its presumed advantage in information and technical expertise. We tend to assume that government will be better informed than anyone else, and therefore better able to deal with the complex problems of our age.

To some extent, this faith in government is just a blind, primitive trust. For centuries, men were conditioned to believe that the king was always right. He was supposed to be God’s agent, and therefore he knew better than anyone else what was good for the country. We have done away with kings, but an aura of divine wisdom still surrounds the state and its officials. When you complain about a law, someone is likely to say, “But Congress wouldn’t have approved it if it weren’t right.”

Another reason we attribute extraordinary powers to government is its size. We assume that the larger an organization, the more it knows. After all, aren’t two heads better than one? By this logic, a government agency with thousands of employees must have enormous knowledge.

Normally, we don’t get a chance to check this belief in governmental wisdom, since government agencies rarely put what they know into testable form. A recent General Accounting Office (GAO) study of the Department of Agriculture for the years 1972 through 1986, however, has uncovered a case where an agency took, in effect, a quantitative test of its knowledge. The results are dismaying.

Each year, the Department of Agriculture attempts to estimate how much all the farm subsidy programs are going to cost, so that it can submit its budget requirements to Congress. To arrive at this figure, it employs an extensive procedure involving 18 sub-units within the Department. These different offices funnel information into the decision-making process: projected supply and demand for commodities, projected prices for commodities, farmer participation in various programs, and so on.

The expense of operating this system easily runs into the millions; depending on how you do the accounting, it may be as much as 100 million dollars each year. For example, one unit in the process is the Foreign Agricultural Service; its 1985 budget was $86 million. A $2 million World Agricultural Outlook Board also plays a role, as does the Agricultural Stabilization and Conservation Service ($119 million) and the Agricultural Marketing Service ($32 million), not to mention budget offices, under-secretaries, and assistant secretaries. Arriving at agricultural projections isn’t the only function of these bodies, but it is one of their major responsibilities.

With all these resources, how well does the Department of Agriculture do in forecasting its commodity subsidy costs? The GAO found the Department’s budget estimates were “substantially incorrect,” with an average absolute error of 4.3 billion dollars. To put this figure in perspective, if you predicted that this year’s costs would be the same as last year’s, your error would have been 4.1 billion. In other words, the most simple-minded extrapolation would have done a better job in predicting the Department of Agriculture’s commodity expenditures than the Department’s own multi-million dollar forecasting organization!

Government, it appears, may not be smart at all. If the experience at the Department of Agriculture is any indication, its intellectual competence rates below that of an ordinary citizen. Why should this be? The problem is not with the intelligence of the public officials themselves. Individually, they are as bright as the rest of us. It is the system in which they function that produces the feeble-mindedness.

First, government information systems are biased. Government agencies always have something to defend or sell, and this prompts their employees to distort facts and estimates. The cumulative result of these distortions can be whopping misconceptions about the world.

In the case of the Department of Agriculture, it wants Congress and the public to approve of its subsidy programs. It wants to make these programs seem less expensive, so people won’t be shocked by the high price. This bias encourages officials in the budget forecasting process to underestimate: over the years, the average net error in the commodity budget forecasts has been $3.1 billion below the actual cost.

The second problem with government information systems is size. It is not true that more people means more knowledge. Useful knowledge about what will happen in the world doesn’t come from just collecting more and more facts and opinions in one building or in one report. It involves rejecting points, too, leaving aside that which is unsound, misleading, or irrelevant. Large entities typically lack this ability to discriminate. Every cook is given a chance to spoil the broth. In the Department of Agriculture’s forecasting system, the inputs from the different sub-agencies all go into the final estimate, yielding an unfocused blend of true, false, and irrelevant.

When it comes to knowing things, government agencies are inherently flawed. Those who are looking to the intelligence of government to solve our problems may be waiting a long time.

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