Italy, Rome 28th of May: The strength of basic income. Technological innovation, new welfare and experiments all around the world

Italy, Rome 28th of May: The strength of basic income. Technological innovation, new welfare and experiments all around the world

On the the 28th of May, at 17h, Fondazione Basso hosts in via della Dogana Vecchia 5, in Rome, a book presentation and discussion titled “The strength of the basic income. Technological innovation, new welfare and experiments all around the world“.

The event will be an opportunity to compare and discuss different analysis and approaches on issues regarding the basic income proposal, as described in three different recently published books.

The authors of these three books will be present:

Roberto Ciccarelli, author of “Forza lavoro. Il lato oscuro della rivoluzione digitale [Workforce. The dark side of digital revolution]” (Derive Approdi, 2018)

Giuseppe Bronzini, author of “Il diritto ad un reddito di base. Il welfare nell’era dell’innovazione [The right to a basic income. Welfare in the age of innovation]” (Gruppo Abele, 2017)

Sandro Gobetti and Luca Santini, authors of “Reddito di base tutto il mondo ne parla. Esperienze, proposte e sperimentazioni [Basic income, all the world talks about it. Experiences, proposals and experiments]” (GoWare, 2018)

Giuseppe Allegri (University of La Sapienza) and Giacomo Marramao (University Roma Tre) will also talk at the event. The meeting is organized by the Basic Income Network Italia.

 

(Thanks to Anna Maria Catenacci)

New Book: Basic income, the whole world talks about it. Experiences, proposals and experiments.

New Book: Basic income, the whole world talks about it. Experiences, proposals and experiments.

Basic income, the whole world talks about it. Experiences, proposals and experiments this is the title of a new book by Sandro Gobetti and Luca Santini, with a preface by Andrea Fumagalli, published by GoWare Edizioni (March 2018).

Description

At the dawn of a new great transformation with the advent of the technological revolution, robotics and artificial intelligence, and in the age of major crises (economic, financial, political and ecologic), comes the echo of a proposal that opens unpublished scenarios: a basic income for all. In the era of the capitalism as a unique economic model, the idea of ​​ a guaranteed income rises up as one of the main human rights.

From experiences of minimum income inEuropean countries to the experimentation of an unconditional basic income around the planet, the right to a guaranteed income becomes key to fully enter, with confidence, in the third millennium. A book of agile and quick reading, written by two major Italian experts, helps to understand where we are and what we can expect.

Summary
Preface by Andrea Fumagalli
Introduction
Guaranteed minimum income and basic income
universal
Protection against social risks and minimum income: from welfare state to guarantee income
Unemployment insurance and minimum income in Europe
Systems and models of protection in European countries
What this means in practice: some examples
The universal and unconditional basic income
People talk about it everywhere. The state of the art of experimentation in the world
Africa at the forefront
What happens in Latin America
Back in the “first world”: North America
Asia, a crossroads of experimentation
The old continent that wants to reinvent itself
The debate and the proposals in Italy
Without income, without a network
A categorial and fragmented welfare
Moving situation
Essential principles for a possible proposal
Relations with unemployment benefits
Beneficiaries’ platform
The question of accessibility
Basic Income amount
Connection with the service system
Individuality 
Basic Income duration
The principle of congruence
To find out more: bibliographic references for topics
European models of guaranteed minimum income
Social and labor transformations and basic income
The fourth industrial revolution, artificial intelligence, robotics and basic income

Authors

Sandro Gobetti, independent researcher and author of articles with a particular enphasis on guaranteed income. He collaborated on the 4/2009 law definition about minimum guaranteed income in the Lazio Region, and the national proposal law for guaranteed income. He is a founding member and coordinator of the Basic Income Network-Italy.

Luca Santini, lawyer, expert on migration law and social security law and has signed several articles. Has collaborated on the proposed law for guaranteed minimum income in Italy. He is the president and founder of the Basic Income Network-Italy.

Sandro Gobetti, Luca Santini, “Reddito di base – Tutto il mondo ne parla [Basic income – the whole world talks about it]“, Goware, 2018 (in Italian)

This article has been reviewed by André Coelho

The Basic Income Guarantee Experiments of the 1970s: a quick summary of results

So many countries are currently conducting or seriously talking about starting Universal Basic Income (UBI) experiments that it’s becoming hard to keep track. These are not the first experiments in UBI or other forms of Basic Income Guarantee (BIG). Namibia and India conducted UBI experiments in the late 2000s and early 2010s. And between 1968 and 1980, the U.S. and Canadian Government conducted five Negative Income Tax (NIT) experiments. They were the world’s first major social science experiments of any kind. They are worth reviewing because they provide not only inspiration and precedent but also relevant data and important lessons for the current experiments.

I’m working on a book (tentatively titled Basic Income Experiments: The Devil’s in the Caveats) drawing lessons from the ’70s experiments for the current round of experiments. This blog post previews a chapter from that upcoming book providing a review of results from the 1970s experiments. The chapter, in turn, draws heavily on my earlier work on BIG experiments including “A Failure to Communicate: What (if anything) Can We Learn from the Negative Income Tax Experiments” and “A Retrospective on the Negative Income Tax Experiments: Looking Back at the Most Innovative Field Studies in Social Policy.” Next week, I’ll make a blog post showing how poorly understood the NIT experiments were in the media at the time.

Labor market effects

Unfortunately, most of the attention of the 70s experiments was directed not at the effects of the policy (how much does it improve the welfare of low-income people) but to one potential side effect (how does it affect labor hours of test subjects). And so that issue takes up most of the discussion here.

Table 1 summarizes the basic facts of the five NIT experiments. The first, the New Jersey Graduated Work Incentive Experiment (sometimes called the New Jersey-Pennsylvania Negative Income Tax Experiment or simply the New Jersey Experiment), was conducted from 1968 to 1972. The treatment group originally consisted of 1,216 people and dwindled to 983 (due to dropouts) by the conclusion of the experiment. Treatment group recipients received a guaranteed income for three years.

The Rural Income Maintenance Experiment (RIME) was conducted in rural parts of Iowa and North Carolina from 1970 to 1972. It began with 809 people and finished with 729.

The largest NIT experiment was the Seattle/Denver Income Maintenance Experiment (SIME/DIME), which had an experimental group of about 4,800 people in the Seattle and Denver metropolitan areas. The sample included families with at least one dependent and incomes below $11,000 for single-parent families or below $13,000 for two-parent families. The experiment began in 1970 and was originally planned to be completed within six years. Later, researchers obtained approval to extend the experiment for 20 years for a small group of subjects. This would have extended the project into the early 1990s, but it was eventually canceled in 1980, so that a few subjects had a guaranteed income for about nine years, during part of which time they were led to believe they would receive it for 20 years.

The Gary Income Maintenance Experiment was conducted between 1971 and 1974. Subjects were mostly black, single-parent families living in Gary, Indiana. The experimental group received a guaranteed income for three years. It began with a sample size of 1,799 families, which (due to a large drop-out rate) fell to 967 by the end of the experiment.

The Canadian government initiated the Manitoba Basic Annual Income Experiment (Mincome) in 1975 after most of the U.S. experiments were winding down. The sample included 1,300 urban and rural families in Winnipeg and Dauphin, Manitoba with incomes below C$13,000 per year. By the time the data collection was completed in 1978, interest in the guaranteed income was seriously on the wane and the Canadian government canceled the project before the data was analyzed.

 

Table 1: Summary of the Negative Income Tax Experiments in the U.S. & Canada

Name Location(s) Data collection Sample size:

Initial (final)

Sample Characteristics G* t**
The New Jersey Graduated Work Incentive Experiment (NJ) New Jersey & Pennsylvania 1968-1972 1,216 (983) Black, white, and Latino, 2-parent families in urban areas with a male head aged 18-58 and income below 150% of the poverty line. 0.5

0.75

1.00

1.25

0.3

0.5

0.7

The Rural Income-Maintenance Experiment (RIME) Iowa & North Carolina 1970-1972 809 (729) Both 2-parent families and female-headed households in rural areas with income below 150% of poverty line. 0.5

0.75

1.00

0.3

0.5

0.7

The Seattle/Denver Income-Maintenance Experiments (SIME/DIME) Seattle & Denver 1970-1976,

(some to 1980)

4,800 Black, white, and Latino families with at least one dependant and incomes below $11,00 for single parents, $13,000 for two parent families. 0.75, 1.26, 1.48 0.5

0.7,

0.7-.025y,

08-.025y

The Gary, Indiana Experiment (Gary) Gary, Indiana 1971-1974 1,799 (967) Black households, primarily female-headed, head 18-58, income below 240% of poverty line. 0.75

1.0

0.4

0.6

The Manitoba Basic Annual Income Experiment (Mincome) Winnipeg and Dauphin, Manitoba 1975-1978 1,300 Families with, head younger than 58 and income below $13,000 for a family of four. C$3,800

C$4,800

C$5,800

0.35

0.5

0.75

* G = the Guarantee level.

** t = the marginal tax rate

Source: Reproduced from Widerquist (2005)

 

Scholarly and popular media articles on the NIT experiments focused, more than anything else, on the NIT’s “work-effort response”—the comparison of how much the experimental group worked relative to the control group. Table 2 summarizes the findings of several of the studies on the work-effort response to the NIT experiments, showing the difference in hours (the “work reduction”) by the experimental group relative to the control group in foregone hours per year and in percentage terms. Results are reported for three categories of workers, husbands, wives, and “single female heads” (SFH), which meant single mothers. The relative work reduction varied substantially across the five experiments from 0.5% to 9.0% for husbands, which means that the experimental group worked less than the control group by about ½ hour to 4 hours per week, 20 to 130 hours per year, or 1 to 4 fulltime weeks per year. Three studies averaged the results from the four U.S. experiments and found relative work reduction effects in the range of 5% to 7.9%.[i]

The response of wives and single mothers was somewhat larger in terms of hours, and substantially larger in percentage terms because they tended to work fewer hours, to begin with. Wives reduced their work effort by 0% to 27% and single mothers reduced their work effort by 15% to 30%. These percentages correspond to reductions of about 0 to 166 hours per year. The labor market response of wives had a much larger range than the other two groups, but this was usually attributed to the peculiarities of the labor markets in Gary and Winnipeg where particularly small responses were found.

 


 

Table 2: Summary of findings of work reduction effect

Study Data Source Work reduction*

in hours per year ** and percent

Comments and Caveats
Husbands Wives SFH
Robins (1985) 4 U.S. -89

-5%

-117

-21.1%

-123

-13.2%

Study of studies that does not assess the methodology of the studies but simply combines their estimates. Finds large consistency throughout, and “In no case is there evidence of a massive withdrawal from the labor force.” No assessment of whether the work response is large or small or its effect on cost. Estimates apply to a poverty-line guarantee rate with a marginal tax rate of 50%.
Burtless (1986) 4 U.S. -119

-7%

-93

-17%

-79

-7%

Average of results of the four US experiments weighted by sample size, except for the SFH estimates, which are a weighted average of the SIME/DIME and Gary results only.
Keeley (1981) 4 U.S. -7.9% A simple average of the estimates of 16 studies of the four U.S. experiments
Robins and West (1980a) SIME/

DIME

-128.9

-7%

-165.9

-25%

-147.1

-15%

Estimates “labor supply effects.” It goes without saying that this is different from “labor market effects.”
Robins and West (1980b) SIME/

DIME

-9% -20% -25% Recipients take 2.4 years to fully adjust their behavior to the new program.
Cain et al (1974) NJ -50

-20%

Includes caveats about the limited duration of the test and the representativeness of the sample. Notes that the evidence shows a smaller effect than nonexperimental studies.
Watts et al (1974) NJ -1.4% to

-6.6%

Depending on size of G and t
Rees and Watts (1976) NJ -1.5 hpw**

-0.5%

-0.61% Found anomalous positive effect on hours and earnings of blacks.
Ashenfelter (1978) RIME -8%

 

-27% “There must be serious doubt about the implications of the experimental results for the adoption of any permanent negative income tax program.”
Moffitt (1979a) Gary -3% to -6% 0% -26% to -30% No caveat about missing demand, but careful not to imply the results mean more than they do.
Hum and Simpson (1993a) Mincome -17

-1%

-15

-3%

-133

-17%

Smaller response to the Canadian experiment was not surprising because of the make-up of the sample and the treatments offered.

* The negative signs indicate that the change in work effort is a reduction

** Hours per year except where indicated “hpw,” hours per week.

NJ = New Jersey Graduated Work Incentive Experiment

SIME/DIME = Seattle / Denver Income Maintenance Experiment

Gary = Gary Income Maintenance Experiment

RIME = Rural Income Maintenance Experiment

Mincome = Manitoba Income Maintenance Experiment

SFH = Single Female “head of household.”

Source: Reproduced from Widerquist (2005)

 

 

All or most of the figures reported above are raw comparisons between the control and experimental groups: they are not predictions of how labor market participation is likely to change in response to an NIT or UBI. There are many reasons why these figures can’t be taken as predictions of responses to a national program. The many difficulties of relating experimental results to such predictions is a major theme in the book I’m writing. I’ll mention just four of them now.

First, the study participants were drawn only from a small segment of the population: people with incomes near the poverty line, about the point at which people are most likely to work less in response to an income guarantee because the potential grant is high relative to their earned income. Thus, the response of this group is likely to be much larger than the response of the entire workforce to a national program. One study using computer simulations estimated that the work reduction in response to a national program would be only about one-third of reduction in the Gary experiment (1.6% rather than 4.5%).[ii] Although simulations are an important way to connect experimental data with what we really want to know, the more researchers rely on them the less their reports are driving by their experimental data.

Second, the figures do not include any demand response, which economic theory predicts would lead to higher wages and a partial reversal of the work-reduction effect. One study using simulation techniques to estimate the demand response found it to be small.[iii] Another found, “Reduction in labor supply produced by these programs does tend to raise low-skill wages, and this improves transfer efficiency.”[iv] That is, it increases the benefit to recipients from each dollar of public spending.

Third, the figures were reported in average hours per week and very often misinterpreted to imply that 5% to 7.9% of primary breadwinners dropped out of the labor force. The reduction in labor hours was not primarily caused by workers reducing their hours of work each week (as few workers are able to do even if they want to). Moreover, few if any workers simply dropped out of the labor force for the duration of the study, as knee-jerk reactions to guaranteed income proposals often assume.[v] Instead, it was mainly caused by workers taking longer to find their next job if and when they became nonemployed.

Fourth, the experimental group’s “work reduction” was only a relative reduction in comparison to the control group. Although this language is standard for experimental studies, it doesn’t imply that receiving the NIT was the major determinate of labor hours. In fact, in some studies, labor hours increased for both groups, and the labor hours of both groups tended to rise and fall together along with the macroeconomic health of the economy—implying that when more or better jobs were available, both groups took them, but when they were less available, the control group searched harder or accepted less attractive jobs.[vi]

As I’ll show in my next article about the NIT experiments, most laypeople writing about the results assumed any work reduction, no matter how small, to be an extremely negative side effect. But it is not obviously desirable to put unemployed workers in the position where they are desperate to start their next job as soon as possible. It’s obviously bad for the workers and families in that position. It’s not only difficult to go through but also it reduces their ability to command good wages and better working conditions. Increased periods of nonemployment might have a social benefit if they lead to better matches between workers and firms.

Non-labor-market effects

The focus of the 1970s experiments on work effort is in one way surprising because presumably, the central goals of a UBI involve its effects on poverty and the wellbeing of relatively low-income people, and assessing these issues requires look at non-labor-market effects.

The experimental results for various quality-of-life indicators were substantial and encouraging. Some studies found significant positive influences in elementary school attendance rates, teacher ratings, and test scores. Some studies found that children in the experimental group stayed in school significantly longer than children in the control group. Some found an increase in adults going on to continuing education. Some of the experiments found desirable effects on many important quality-of-life indicators, including reduced incidents of low-birth-weight babies, increased food consumption, and increased nutritional content of the diet. Some even found reduced domestic abuse and reduced psychiatric emergencies.[vii]

Much of the attention to non-labor market effects focused not on the presumed goals of the policy but on another side effect: a controversial finding that the experimental group in SIME-DIME had a higher divorce rate than the control group. Researchers argued forcefully on both sides with no conclusive resolution in the literature. The finding was not replicated by the Manitoba experiment, which found a lower divorce rate in the experimental group. The higher divorce rate in some studies examining SIME-DIME was widely presented as a negative effect, even though the only explanation for it that researchers on either side were that the NIT must have relieved women from financial dependence on husbands.[viii] It is at the very least questionable to label one spouse staying with another solely because of financial dependence as a “good” thing.

An overall comparison?

Most of the researchers involved considered the results extremely promising overall. Comparisons of the control and experimental group indicated that the NIT was capable of significantly reducing the material effects of poverty, and the relative reductions in labor effort were probably within the affordable range and almost certainly within the sustainable range.

But experiments of this type were not capable of producing a bottom line. Non-specialists examining these results might find themselves asking: What was the cost exactly? How much were the material effects of poverty reduced? What is the verdict from an overall comparison of costs and benefits?

Experiments cannot produce an answer to these questions. Doing so would involve taking positions on controversial normative issues, combining the experimental results with a great deal of nonexperimental data, and plugging it into a computer model estimating the micro- and macroeconomic effects of a national policy. The results of that effort would be driven more by those normative positions, nonexperimental data, and modeling assumptions than by the experimental results that such a report would be designed to illustrate.

Whichever strategy experimental reports take, nonspecialists will have difficulty grasping the complexity of the results and the limits of what they indicate about a possible national policy. No matter how well the experiment is conducted, the results are vulnerable to misunderstanding, misuse, oversimplification, and spin. My blog post next week will show how badly this happened when the results of NIT experiments were reported in the United States in the 1970s.

[i] G. Burtless, “The Work Response to a Guaranteed Income. A Survey of Experimental Evidence,” in Lessons from the Income Maintenance Experiments, ed. A. H. Munnell (Boston: Federal Reserve Bank of Boston, 1986). M.C. Keeley, Labor Supply and Public Policy: A Critical Review (New York: Academic Press, 1981). P.K. Robins, “A Comparison of the Labor Supply Findings from the Four Negative Income Tax Experiments,” Journal of Human Resources 20, no. 4 (1985).

[ii] R.A. Moffitt, “The Labor Supply Response in the Gary Experiment,” ibid.14 (1979).

[iii] D.H. Greenberg, “Some Labor Market Effects of Labor Supply Responses to Transfer Programs,” Social-Economic Planning Sciences 17, no. 4 (1983).

[iv] J.H.  Bishop, “The General Equilibrium Impact of Alternative Antipoverty Strategies205-223,” Industrial and Labor Relations Review 32, no. 2 (1979).

[v] Robert Levine et al., “A Retrospective on the Negative Income Tax Experiments: Looking Back at the Most Innovative Field Studies in Social Policy,” in The Ethics and Economics of the Basic Income Guarantee, ed. Karl Widerquist, Michael A. Lewis, and Steven Pressman (Aldershot: Ashgate, 2005).

[vi] Karl Widerquist, “A Failure to Communicate: What (If Anything) Can We Learn from the Negative Income Tax Experiments?,” The Journal of Socio-Economics 34, no. 1 (2005).

[vii] Levine et al, 2005.

[viii] Levine et al, 2005; Widerquist, 2005.

Public Reaction to the Basic Income Guarantee Experiments in the 1970s: a case of misunderstanding, misuse, oversimplification, and spin

This post is one of several previewing the book I’m writing on Universal Basic Income (UBI) experiments, and it is the second of two reviewing the five Negative Income Tax (NIT) experiments conducted by the U.S. and Canadian Government in the 1970s. This post draws heavily on my earlier work, “A Failure to Communicate: What (if anything) Can We Learn from the Negative Income Tax Experiments.”

Last week I argued that the results from the NIT experiments for various quality-of-life indicators were substantial and encouraging and that the labor-market effects implied that the policy was affordable. As promising as the results were to the researchers involved the NIT experiments, they were seriously misunderstood in the public discussion at the time. But the discussion in Congress and in the popular media displayed little understanding of the complexity. The results were spun or misunderstood and used in simplistic arguments to reject NIT or any form of guaranteed income offhand.

The experiments were of most interest to Congress and the media during the period from 1970 to 1972, when President Nixon’s Family Assistance Plan (FAP), which had some elements of an NIT, was under debate in Congress. None of the experiments were ready to release final reports at the time. Congress insisted researchers produce some kind of preliminary report, and then members of Congress criticized the report for being “premature,” which was just what the researchers had initially warned.[i]

Results of the fourth and largest experiment, SIME/DIME, were released while Congress was debating a policy proposed by President Carter, which had already moved quite a way from the NIT model. Dozens of technical reports with large amounts of data were simplified down to two statements: It decreased work effort and it supposedly increased divorce. The smallness of the work disincentive effect hardly drew any attention. Although researchers going into the experiments agreed that there would be some work disincentive effect and were pleased to find it was small enough to make the program affordable, many members of Congress and popular media commentators acted as if the mere existence of a work disincentive effect was enough to disqualify the program. The public discussion displayed little, if any, understanding that the 5%-to-7.9% difference between the control and experimental groups is not a prediction of the national response. Nonacademic articles reviewed by one of the authors[ii] showed little or no understanding that the response was expected to be much smaller as a percentage of the entire population, that it could potentially be counteracted by the availability of good jobs, or that it could be the first step necessary for workers to command higher wages and better working conditions.

The United Press International simply got the facts wrong, saying that the SIME/DIME study showed that “adults might abandon efforts to find work.” The UPI apparently did not understand the difference between increasing search time and completely abandoning the labor market. The Rocky Mountain News claimed that the NIT “saps the recipients’ desire to work.” The Seattle Times presented a relatively well-rounded understanding of the results, but despite this, simply concluded that the existence of a decline in work effort was enough to “cast doubt” on the plan. Others went even farther, saying that the existence of a work disincentive effect was enough to declare the experiments a failure. Headlines such as “Income Plan Linked to Less Work” and “Guaranteed Income Against Work Ethic” appeared in newspapers following the hearings. Only a few exceptions such as Carl Rowan for the Washington Star (1978) considered that it might be acceptable for people working in bad jobs to work less, but he could not figure out why the government would spend so much money to find out whether people work less when you pay them to stay home.[iii]

Senator Daniel Patrick Moynihan, who was one of the few social scientists in the Senate, wrote, “But were we wrong about a guaranteed income! Seemingly it is calamitous. It increases family dissolution by some 70 percent, decreases work, etc. Such is now the state of the science, and it seems to me we are honor bound to abide by it for the moment.” Senator Bill Armstrong of Colorado, mentioning only the existence of a work-disincentive effect, declared the NIT, “An acknowledged failure,” writing, “Let’s admit it, learn from it, and move on.”[iv]

Robert Spiegelman, one of the directors of SIME/DIME, defended the experiments, writing that they provided much-needed cost estimates that demonstrated the feasibility of the NIT. He said that the decline in work effort was not dramatic, and could not understand why so many commentators drew such different conclusions than the experimenters. Gary Burtless (1986) remarked, “Policymakers and policy analysts … seem far more impressed by our certainty that the effective price of redistribution is positive than they are by the equally persuasive evidence that the price is small.”[v]

This public discussion certainly displayed “a failure to communicate.” The experiments produced a great deal of useful evidence, but for by-far the greatest part, it failed to raise the level of debate either in Congress or in public forums. The literature review reveals neither supporter nor opponents who appeared to have a better understanding of the likely effects of the NIT and UBI in the discussions following the release of the results of the experiments in the 1970s.[vi]

Whatever the causes for it, an environment with a low understanding of complexity is highly vulnerable to spin with simplistic if nearly vacuous interpretation. All sides spin, but in the late 1970s NIT debate, only one side showed up. The guaranteed income movement that had been so active in the United States at the beginning of the decade had declined to the point that it was able to provide little or no counter-spin to the enormously negative discussion of the experimental results in the popular media.

Whether the low information content of the discussion in the media resulted more from spin, sensationalism, or honest misunderstanding is hard to determine. But whatever the reasons, the low-information discussion of the experimental results put the NIT (and, in hindsight, UBI by proxy) in an extremely unfavorable light, when the scientific results were mixed-to-favorable.

The scientists who presented the data are not entirely to blame for this misunderstanding. Neither can all of it be blamed on spin, sound bites, sensationalism, conscious desire to make an oversimplified judgment, or the failure of reports to do their homework. Nor can all of it be blamed on the people involved in political debates not paying sufficient attention. It is inherently easier to understand an oversimplification than it is to understand the genuine complexity that scientific research usually involves no matter how painstakingly it is presented. It may be impossible to communicate the complexities to most nonspecialists readers in the time a reasonable person to devote to the issue.

Nevertheless, everyone needs to try to do better next time. And we can do better. Results from experiments in conducted in Namibia and India in the early 2010s and late ’00s were much better understood, as resulted from Canada’s Mincome experiment that sadly did not come out until more than two decades after that experiment was concluded.

The book I’m working on is an effort to help reduce misunderstandings with future experiments. It is aimed at a wide audience because it focuses the problem of communication from specialists to non-specialists. I hope to help researchers involved in current and future experiments design and report their findings in ways that are more likely to raise the level of debate; to help researchers not involved in the experiments raise the level of discussion when they write about the findings of the experiment, to help journalists understand and report experimental findings more accurately; and to help interested citizens of all political predispositions see beyond any possible spin and media misinterpretations to the complexities of the results of this next round of experiments—whatever they turn out to be.

[i] Widerquist, 2005.

[ii] Widerquist, 2005.

[iii] Widerquist, 2005.

[iv] Widerquist, 2005.

[v] Burtless, 1986.

[vi] Widerquist, 2005.

Basic Income Experiments—The Devil’s in the Caveats

Basic Income Experiments—The Devil’s in the Caveats

The devil’s in the details is a common saying about policy proposals. Perhaps we need a similar saying for policy research, something like the devil’s in the caveats. By this, I mean that the evidence any particular piece of research can provide is only a small part of the evidence people need to fully evaluate policy proposals. Non-specialists involved in the debate over that policy are often unable to translate caveats about the limits of research into a firm grasp of what that research does and does not imply about the policies they want evaluated. Therefore, even the best scientific policy research can leave nonspecialists with an oversimplified, or simply wrong, impression of its implications for policy.

For example, popular media reports about medical research often leave people in the United States today with the impression that the medical professionals make widely swinging recommendations about prevention and treatment of diseases, when medical consensus is actually slow to change and even slower to reverse a change once made. It is possible that the misperception of an erratic medical consensus exists because nonspecialists don’t have the background to understand the difference between a medical consensus and an oversimplified or sensationalized report of one study.

Whatever the problems of this type are with medical research, they are likely to be much greater with social science research in general and Universal Basic Income (UBI) experiments in particular. At least some medical research is fairly straightforward. Many medicines affect people only on an individual basis, and all we might want to know about a medicine is whether it is safe and effective. In many cases, medical research can address that question directly in a controlled experiment, and hopefully, it’s not too difficult to communicate the results to nonspecialists.

Although medical experiments might not always be this straightforward, UBI experiments can never be straightforward. I believe this problem is so big that I’m working on a book, provisionally titled Basic Income Experiments—The Devil’s in the Details, to discuss the enormous difficulty of conducting a UBI experiment that successfully raises the level of political debate over UBI.

UBI has complex economic, political, social, and cultural effects that cannot be observed in a controlled experiment. Researchers conducting experiments know that experimental evidence alone cannot fully answer the big questions about UBI: does it work? Is it cost-effective? Should we introduce it on a national level? They have to be content with making a small contribution to a large body of knowledge about UBI. When research is conducted of, by, and for specialists, mutual understanding of the limits of research usually requires no more a simple list of caveats, many of which can go without mention in a group with a great deal of shared, specialized knowledge.

The same is not true when policymakers and citizens make up part of the audience of research—as they do for research on major policy issues such as UBI. Citizens and policymakers want answers to the big questions mentioned above; they understandably try to interpret experimental results in light of those questions. But as I will argue throughout the book, they have great difficulty understanding what UBI experiments do and do not imply about those big questions. The devil is in the caveats.

Most academic specialists are professionals at writing for other academics within the same specialty but amateurs at communicating with nonspecialists. The book argues that these communications barriers affect not only how specialists report their research to nonspecialists but also how they design and conduct it.

It is no coincidence that UBI experiments are getting underway just after an enormous growth in the discussion of UBI in many countries around the world. In that environment, one of the goals of UBI experiments is—or ought to be—to raise the level of debate over UBI. The book will argue that past experiments have a mixed record in raising the level of debate over UBI: although all of them have provided valuable evidence, some have succeeded in raising the level of debate, and some have been so misunderstood that they might well have had an overall negative affect on the level of debate. This effort to raise the level of political debate (like the UBI debate) requires knowledge and skills that researchers have no special training to do and creates risks that research aimed purely at other researchers does not have, including the vulnerability to spin, misuse, sensationalism, or oversimplification.

The goal of the book is help researchers, policymakers, citizens, journalists, and anyone else interested in UBI experiments bridge gaps in understanding between them to help the experiments succeed in the goal of raising the level of debate. I hope that this effort will be valuable to researchers designing, conducting, and writing about UBI experiments, to policymakers commissioning and reacting to experiments, to journalists reporting on experiments, and to citizens involved in the debate or simply interested in the topic of UBI.

To help people bridge these gaps, the book has to explain how many significant barriers there are to conducting experiments that successfully raisr the level of debate. So, I will have a lot of negative things to say, but that should not distract readers from my overall enthusiasm for UBI experiments. They are worth doing, and worth doing well in all relevant ways. And to readers who are unenthusiastic about UBI experiments, I say, they are coming; it’s important to make the best of them.

A meeting during the Indian pilot project, c. 2011-2013

A meeting during the Indian pilot project, c. 2011-2013