Making numbers fit economic projections is dangerous

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Information is essential to decision making, whether for an individual, a family, a business, or a government. Without accurate input data, it is virtually impossible to draw meaningful conclusions and make effective decisions.

When it comes to the data that we use to assess the economy, the watchwords are “Just the facts, ma’am!!”

That is why I and my colleagues in the economics profession became more than a little agitated when reports recently surfaced that the Trump Administration had instructed the Council of Economic Advisors to make the data support an unrealistically high growth rate that would allow deficits to fall to fund new programs.

A bit of history is instructive here. There is a longstanding tradition of Presidents issuing forecasts that are a little higher than the consensus of external projections. After all, every President thinks that his policies will make things better (at least we hope they do).

But an optimistic forecast based on historical data and assumptions about future policy is not the same thing as a forecast in which the answer is decided in advance and then the data manipulated to get there.

The types of data which are compiled by various agencies of the U.S. government are many and varied. The U.S. Census Bureau not only collects a wealth of information every 10 years, but also uses sophisticated models to form estimates in between.

Demographic information ranging from numbers of residents by micropolitan area, city, or county (or even census tract, which is very small indeed), incomes, housing characteristics, educational attainment, and much more are available for anyone with an internet connection.

Other agencies such as the U.S. Bureau of Economic Analysis and the U.S. Bureau of Labor Statistics track detailed information (again by small geographic area) related to employment by industry, compensation, worker characteristics, and then some.

Other agencies monitor U.S. exports and imports, energy use and markets, health and wellbeing, education, and just about anything else you could think of. (Believe me, this description only scratches the surface of what’s available.)

Obviously, it’s not mere curiosity that is driving this enormously thorough (and expensive) data collecting effort. This information helps us see how things are going and answers important questions such as how the population is growing and changing and moving, where the economy is expanding/contracting and shifting, and what the situation is with necessary items such as fuels.

Another crucial benefit of the wealth of data is that it helps us determine whether we’re making progress toward important social goals.

If you take a close look at the monthly releases from the U.S. Bureau of Labor Statistics, you can see how many people were hired and in what industries, how many remain unemployed (and how long they’ve been unemployed), how many wish they were working full time but can only find part-time work, and more.

We can gain insight into social changes because many series are collected by race/ethnicity, age, and gender. It’s also possible to check the success or failure of various policies.

Yet another piece of the data puzzle is the wide variety of forecasts which are produced. Various branches of government and agencies are projecting everything from population to the economy to the price of oil to interest rates.

These forecasts are critical to decisions across both the public and private sector. I have been providing forecasts for the economies of Texas and its metropolitan areas for about 30 years, and I know firsthand how many rely on those expectations in making plans for their businesses, schools, and lives.

I also know that they are meaningless without the proper underlying data.

Given the huge importance on so many levels, any plan to make changes in the way the data is collected or defined should be approached with extreme caution.

Yes, sometimes there is a need for tweaking the process such as to improve accuracy, better reflect reality, or take advantage of new capabilities or technologies.

However, it is essential that politics play absolutely no role.

One change which has been suggested involves the way goods that are imported and then exported are counted. The net effect would be to raise the U.S. trade deficit, which could be used as ammunition to support protectionist policies. This is a very bad idea.

Another change deals with the way unemployed people are counted. Currently, anyone who has not looked for work in the past four weeks is no longer counted in certain measures of unemployment.

There could be some merit to looking at better ways to track the status of the labor market, but political maneuvering is no basis. Moreover, the potential negative ramifications and fallout from these changes is so widespread that the benefits would have to be massive.

I have been involved in efforts to refine and improve what we measure and how we measure it for closer to 40 years than I want to admit. I can tell you that the dedicated public servants who compile and report this information, many of whom work in the agencies for decades, are meticulous and methodical in their approach to this important activity. They follow rigid protocols and are not the least bit impacted by the people or parties in power at any given moment.

As someone who has lived and breathed economic data and statistics for decades, I am well aware that there is always room for improvement. What there is not room for, however, are changes driven by politics or situations where the numbers are altered to fit the conclusion.

Dr. M. Ray Perryman is President and Chief Executive Officer of The Perryman Group (www.perrymangroup.com). He also serves as Institute Distinguished Professor of Economic Theory and Method at the International Institute for Advanced Studies.

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