Big Social Changes Revive
the False God of Numbers

By John M. Broder


WASHINGTON -- A year ago, after a furious debate within his own party and even among his own advisers, President Clinton signed the most radical revision of the nation's welfare policy in history. Last week the president declared the change an unqualified success.

"I think it's fair to say the debate is over," Clinton said in St. Louis on Tuesday. "We know now that welfare reform works."

His evidence? A 1.4-million-person drop in welfare rolls nationwide over the past year.

But that figure proves only that the number of people on public assistance fell, not that welfare reform "works" to foster self-sufficiency. There are a score of possible explanations for the decline, some attributable to government policy, many wholly unrelated. Clinton is not the first chief executive to draw categorical conclusions from scanty data. But his declaration of victory in the war on welfare based on a single statistic illustrates the political pressure to keep score on complex issues of public policy.

This pressure is especially evident now with so many hotly contested social and economic transformations under way, some only in their early stages. Although Washington places talismanic power in numbers as it tries to judge the good or bad of such changes, statistics have often proved a false god.

Who are the winners and losers in the new budget agreement? Who benefits most from the North American Free Trade Agreement? What are the social costs of affirmative action? Has the quality of health care deteriorated under managed care? How bad is corporate streamlining in a dynamic, competitive economy? Or wage stagnation at a time of low inflation and technology-driven improvements in the lives of ordinary people?

In the national obsession with market statistics, quarterly profits and the won-loss column, government and private experts find themselves trying to measure the largely unmeasurable. They attempt to apply the scientific method to questions that do not lend themselves to simple quantification. In the name of accuracy or advocacy, they fashion a veneer of seeming numerical certainty over what are fundamentally questions of belief.

Americans love to keep score -- look at how much newsprint is devoted each day to the stock tables and the small-type charts in the sports section. But is it possible to reduce to numbers such questions as the success of a major shift in welfare policy or the social value of new pollution rules that will cost industry billions of dollars?

Governments try, every day. Whole bureaus are devoted to assessing the costs and benefits of programs based solely on numbers. Thus welfare reform is declared a success because the rolls are dropping by more than 100,000 people a month. New air-quality standards are justified at any cost because they will supposedly prevent precisely 15,000 deaths a year from respiratory ailments.

"This is the glory and the curse of the one-number summary," said Bruce Levin, a statistician at Columbia University's School of Public Health. "You take a hundred-dimensional problem like welfare reform and reduce it to one number."

While numbers have long been used to deceive and to manipulate public opinion -- Vietnam War "body counts" come to mind -- the more frequent problem is that they tell only part of the story. Statistics can sometimes describe the "what"; they seldom illuminate the "why." Of course, the alternative -- reliance on anecdote or the unsupported testimony of "experts" -- is even less useful.

Robert Reischauer of the Brookings Institution, an economist who oversaw the Congressional Budget Office from 1989 to 1995 and was thus Capitol Hill's chief scorekeeper, said that today's obsession with numbers is an overreaction to the past, when public officials were not held accountable for the results of their actions.

In the search for precision in assessing policies, Washington has stepped off into the realm of the unknowable, he contended.

"We live in a society where policy evaluations have to fit into a sound bite, so there is a tendency to focus on quantitative measures even when they may not be measuring the most important dimensions," he said. "A full evaluation of most policies would be multi-dimensional and include both quantitative indicators and more subjective measures of success and failure."

Reischauer cited as an example studies that show that commuters spend more time in their cars getting to and from work because of traffic congestion and business relocations. According to a 1996 study, the average one-way commuting time lengthened by 40 seconds between 1986 and 1996, to 22.4 minutes. The widely reported conclusion was that since time spent on the freeway is wasted, the American quality of life was diminishing.

But what the survey doesn't reflect is that many of these commuters voluntarily moved farther from their jobs to bigger homes, greener lawns and better schools. And many say they enjoy the added time in their four-wheel-drive, air-conditioned, six-speaker capsules away from the pressures of home and office.

Similarly, raw statistics on divorce and labor force participation of women have been used to support wildly differing interpretations. Soaring divorce rates are cited to "prove" a breakdown in the family and worsening conditions for children. But are women in abusive relationships always better off staying married? Does that improve their children's lot?

And do the growing numbers of women in the work force mark the American family's effort to stay afloat in a time of falling wages -- or the professional liberation of millions of women?

Depends on your point of view.

Meaningful evaluations of public actions and social trends take years, sometimes decades. Only now are the mixed results of President Lyndon B. Johnson's anti-poverty programs becoming clear. Sorting out the effects of the 1996 welfare bill and several years of state welfare experiments that preceded it will similarly take years.

"You can't tell whether welfare reform is working simply from caseload numbers," said Wendell Primus, a welfare expert who quit the administration in protest last summer over Clinton's signing of the welfare bill. Those figures do not tell how many former recipients moved from welfare to work, or simply from dependency to despondency, he said.

"You have to look at where these people went," Primus said.

"In the short run, a year later, we just don't have the measurement tools to really assess the impact of all of this."

While Clinton administration officials admit that there is a paucity of data to explain why so many people are leaving welfare rolls, they nonetheless say the falling number of recipients represents a stunning success.

"Certainly some of the success is due to a booming economy and very low unemployment," said Bruce Reed, the president's chief domestic policy adviser. "But there's also something else going on, which is, for the first time most states are taking welfare reform seriously and putting in place impressive programs to move people from welfare to work."

Analysts are employing ever-more-sophisticated models to measure the behavior of the economy and the consumer, but there will always be things they can't measure in a rapidly changing workplace.

As the United Parcel Service strike has dramatized, more employees are working part-time or on a contract basis than ever before. Has the United States become a nation of temps doing piecework for heartless corporations for want of better jobs? Or do the figures reflect decisions by a growing body of workers to trade full-time work and benefits for more freedom and family time? Do both situations coexist?

And is the current state of the work force only a temporary phenomenon as the global economy undergoes seismic shifts based on new technologies?

Again, statistics can describe what is happening. They cannot necessarily explain why.

Levin said that politicians labor in vain to apply the discipline of the hard sciences to matters of conjecture and opinion. The physical sciences like chemistry and physics proceed by controlled experiment, biology and medicine by longitudinal studies and clinical trials. In scientific inquiry, a statistician can locate sources of bias and error and try to correct for them.

But how does one measure the success of crime-control programs, or pre-kindergarten education or immigration policy? Statistics are tools of the scientist, Levin said. But when numbers are crunched in politics, axes are usually grinding, too.

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