Reviews of Important Papers on Forecasting,
1985-1995 Reviews
Review of:

Clifford Winston, 1993, Economic deregulation: Days of reckoning for microeconomists, Journal of Economic Literature, 31, 1263-1289.

I have often wondered why academic forecasters are not more closely involved with forecasting the outcomes of social and economic legislation. However, I was asked to comment on forecasting procedure concerning the impact of Clinton’s health plan for the US. Because this plan adds regulation to an industry that is already subject to much regulation, an obvious first step is to examine the outcomes of previous efforts to regulate or deregulate industries. This led me to the fascinating study by Winston. He examined the impact of deregulation by finding studies that had predicted the effects of deregulation in various industries, and then comparing these forecasts with the actual outcomes. His study has some important messages for forecasters.

  1. Scholarly research does affect policy. In 1887, when the US government was moving towards a national policy favoring regulation, scholarly writings were in support of such a change. Of course, this research typically lacked an empirical basis. The empirical research over the past half century has concluded that economic regulation has negative effects for society. This research has apparently contributed to extensive changes. From 1977 to 1987, the percent of the US GNP that was regulated fell from 17% to less than 7%.
  2. Subjective evaluations often provide poor criteria. The public often perceives that deregulation is harmful to them. This is because many people start with the impression that deregulation will be harmful. Their unaided observation then leads them to retrieve evidence that confirms their beliefs (Wason, 1968). Winston reports on a Business Week survey in 1988 showing that only 32% of the respondents thought the airline deregulation of 1987 was a good idea. Thus, in evaluating the impact of deregulation, Winston relied on objective measures of the outcomes. As it turned out, the use of objective measures led to the conclusion that deregulation is beneficial. The deregulation of airlines, railroads, trucking, telecommunications, cable TV, and banking led to gains of at least 8% in the parts of the GNP affected by the reforms. This represents a gain of over $40 billion (1990 dollars) .
  3. Forecasts can provide good benchmarks for the evaluation of experiments. ‘Before and after’ experimental designs are often deficient because other things change. Evaluations that use ex ante forecasts offer advantages in that they take account of the other things that are expected to change. Winston conducted what seems to be a thorough search for studies with ex ante forecasts (although he does not tell how the search was conducted). He found almost 30 studies that had predicted the effects of deregulation. He then compared the ex ante predictions with the outcomes. The ex post analysis is informal. For example, none of the forecasters of the effects of banking deregulation had examined the impact of the government’s policy of insuring the investments made by savings and loan institutions.
  4. The use of complex methods led to no obvious gains in forecast accuracy.
  5. The use of complex theories seems to have been associated with less accurate prediction. The simple economic prediction that regulation is harmful to consumers proved to be robust. Also, wages typically went down, as predicted. Employment predictions varied depending upon the impacts of improved efficiency (which would reduce employment) and increased consumer demand (due to improvements in price and service).
  6. The biggest errors in the economists’ predictions came about when they failed to consider important causal factors. In particular, the omitted factors usually involved technological change. My speculation is that this is likely to occur when factors that have been constant in the past change significantly over the forecast horizon. While these factors cannot be identified by formal analyses of historical data, they can sometimes be anticipated by asking a number of experts to brainstorm the factors that might possibly change in the future. When one looks at the problem retrospectively, it seems surprising that certain factors were overlooked. Surely someone would suggest that the government’s policy of insuring against loss in investments by savings and loan institutions might have an influence on the S&L’s investment policies, or that the failure to develop an efficient pricing scheme for airports would create service restrictions.

Winston’s paper deals with an important subject. The design, which compares actuals against forecasted results, represents a marked improvement over the commonly used ‘before-after’ studies in economics. Finally, the writing is a model of clarity.


Watson, P.C., 1986, Reasoning about a rule, Quarterly Journal of Experimental Psychology, 20, 273-281.