A Budget That Copes With Reality

Five years ago, I wrote about the possibility of dynamic budgeting.  I was reminded of this again recently after reading Stephanie Kelton’s eye-opening new book, “The Deficit Myth”.

Her argument is that, since the U.S. dropped the gold standard and fixed exchange rates, it can create as much money as it wants.  The limit is not an illusory national debt number, but inflation.  And in an economy with less than full employment, inflation is not now an issue.  Her explanation of the capacity of the Federal government to spend leads to her suggestions for a more flexible approach to dealing with major economic and social issues.

Although Dr. Kelton was the former staff director for the Democrats on the Senate Budget Committee, she doesn’t devote many words to the tools used in budgeting.  However, the argument that she makes reminds me again that the traditional budget itself has to change, especially shifting to a dynamic budget.

While states and localities are not in the same position as the Federal government, they also face unpredictable conditions and could benefit from a more flexible, dynamic budget.  Of course, in the face of COVID and economic retraction the necessity of re-allocating funds has become more obvious.

In an earlier blog, I wrote about a simple tax app that is now feasible and also eliminates the bumps in incentives that are caused by our current, old-fashioned tax bracket scheme.   This was not using some untested, cutting-edge technology.  Instead, the solution could use phones, tablets and laptops doing simple calculations that these devices have done for decades.

Similarly, what is now well-established technology could be used to overcome the problems with traditional fixed budgeting.  (By the way, the same applies to the budgets that corporations devise.)

So, what are the problems that everyone knows exist with budgets?

  1. They’re wrong the day they are approved since they are trying to predict precisely a future that cannot be known precisely ahead of time. This error is made worse by the early deadlines in the typical budget process.  If you run a department, you are likely to be asked by the budget office to prepare estimates for what you’ll need in a period that will go as far as 18 or even 24 months into the future.
  2. It’s not clear how the estimates are derived. Typically, there are no underlying rules or models, just the addition of personnel and other basic costs that are adjusted from the last year.  This is despite the fact that some things are fairly well known.  For example, it is fairly straightforward to estimate the cost of paying unemployment to an average individual.  What is harder is to figure out how many unemployed people there will be – and, of course, you need to know the total number of unemployed and the average cost in order to compute the total amount of money needed.
  3. Given these problems, in practice during any given budget year, all kinds of exceptions and deviations occur in the face of reality. But the rest of the budget is not readjusted, although the budget staff will often hold back money that was approved as it takes from “Peter to pay Paul”.  The process often seems and is very arbitrary.

Operating in the real world, of course, requires continual adjustments.  Such adjustments can best be accommodated if the traditional fixed budget was replaced by a dynamic budget at the start of the budget process.

One way of doing this is familiar to almost every reader of this blog – the spreadsheet.  The cells in spreadsheets don’t always have hard fixed numbers, like fixed budgets.  Instead many of those spreadsheets have formulas.

And Congress could also not so much the individual amounts for each agency or program, but their relative priorities under different scenarios.  Thus, in a recession there would be a need for more unemployment insurance funding, but that would recede in the face of other priorities if the economy is booming.

To go back to the unemployment example, the actual amount needed in the budget will change as we get closer to the month being estimated and can be more accurate in its estimates of the number of people who will be unemployed.

Of course, the reader who knows my background won’t be surprised that I think the formulas in these cells could be derived by the use of some smart analytics and machine learning.  Ultimately, these methods could be enhanced with simulations – after all, what is a budget but an attempt to simulate a future period of financial needs?

More on that in another post sometime in the future.

© 2020 Norman Jacknis, All Rights Reserved

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