by Kate McFarland | Feb 4, 2018 | Opinion
My interest in basic income stemmed from the conjecture that such a policy could help to ignite a progression away from the culture of total work. However, there are many open empirical questions regarding the exact way in which a basic income would (or would not) influence work-related attitudes and behaviors.
One might hope that current and planned experiments will shed some light on this topic. My claim in this article is that this is not likely to be the case: the impact of basic income on work-related attitudes and behaviors is not readily amenable to experimentation.
1. Fixing the Viewpoint: Opposition to the Culture of Work
When I began casually following the basic income movement in 2015, and when I began volunteering for Basic Income News in November of that year, I was tentatively attracted to the policy as a means to subsidize lifestyles like downshifting and what I’d come to call anti-careerism – the rejection of idea that one’s life course should be structured and defined by a career path.
At that time, I was unaware of the movement’s budding interest in experimentation. I did not realize that the center-right federal government of Finland was about to declare its intention to fund an experimental trial of basic income, or that the provincial government of Ontario was also preparing to design and implement a trial of guaranteed minimum income.
I did not foresee the global surge of interest in experiments and pilot studies that would happen soon after the commencement of my volunteership. But happen it did, and thus, as a writer for Basic Income News, I was committed to expend considerable effort covering the current basic income implementation trials. Moreover, as a “just the facts” news reporter, it was my duty to report on them without allowing my own personal misgivings to show through (although I did have occasion to leak my skepticism in the Op-Ed section). As a result, I was often mistaken for someone with a genuine and favorable interest in basic income experiments.
Through it all, my main interest in basic income remained the conjecture that the policy might act as a subsidy for downshifting, anti-careerism, and working without pay, and thereby help to displace society’s overvaluing of selling labor for money. While such an “anti-work” approach to basic income is highly controversial, I will assume this perspective throughout the present article. (Those who do not share it may either accept it for the sake of argument or stop reading.)
Such an approach to basic income rests on untested empirical conjectures. In fact, however, many questions remain open. Would individuals living in a society with basic income come to hold different views about the role and importance of jobs? Would they fail to view an occupation or career as integral to self-identity? Would they deny that a high salary or professional advancement is essential for personal success? Would they ascribe greater value to self-development and social contributions that occur outside of paid work? Would they tend to prioritize activities that are rewarding in themselves over activities that contribute to professionalization and employability? To what extent would basic income actually enable people to lead lives without full-time or continuous jobs? It is sufficient to empower individuals to work fewer hours? (Probably not.) Would it permit some to withdraw from the labor market completely?
Some proponents take for granted that basic income would usher in a society in which the pursuit of passions is more important than paid work. Such optimistic predictions, however, must be moderated against the reality that the culture of work is deeply entrenched. When critics contend that it’s premature to “give up” on the goal of full employment, the normative assumptions behind their rhetoric should not be ignored: secure full-time jobs and careers remain central to the identity and self-worth of many who have them, and central to the goals and aspirations of many who don’t. Even more unsettlingly (in my view), many supporters enthusiastically maintain that basic income would not result in lower rates of employment–and might even increase work effort (as is the hypothesis behind Finland’s experiment, which is designed primarily to assess whether unemployed individuals would be more likely to accept work if their benefits were made unconditional). Some argue that it would act as a stimulus to business and grow the economy, never pausing to question the ethos of paid work and productivity.
We simply don’t know the long-term effects of basic income on work-related attitudes and behaviors. Given the myriad of unanswered empirical questions, one might guess that I would have been heartened to witness the unexpected onslaught of experiments that occurred during my volunteership with Basic Income News. But I was not: unfortunately, it is unlikely that the present wave of experiments will yield insight into the empirical concerns that interest me and others who approach basic income from the “anti-work” perspective.
2. Five Limitations of Experiments
I believe it’s possible that basic income could precipitate a mass transformation of work-related behavior and attitudes but, if so, it most likely occur through long-term, society-wide processes. Experiments, in contrast, are necessarily (1) limited in duration and (2) restricted to a subset of the population (rather than “universal”).
And experiments have other shortcomings. For instance, they must be (3) designed to prevent subjects from being financially worse off as a result of participation, whereas any “real-world” UBI would almost certainly be introduced in tandem with a funding mechanism that causes some individuals to be net payees. Finally, as existing experiments have been designed, the target populations (4) consist of low-income individuals, the unemployed, and/or welfare recipients, and (5) consist mainly of adults who have already been acculturated into the present society and its ethos of work and consumption.
2.1 Experiments are limited in duration.
Most of the current BI-related experiments are two or three years in length. In the United States, the non-profit YC Research plans to launch an experiment in which some participants receive cash transfers for five years. The only projects of longer duration are taking place in developing nations: GiveDirectly is providing a 12-year basic income to 40 villages in its major experiment in Kenya, and the Brazilian non-profit organization ReCivitas has introduced a “lifetime basic income” in the village Quatinga Velho (note that the latter is not an “experiment” in the scientific sense). Even if longer term experiments were affordable, the pressure to obtain results would generally militate against them.
The short-term nature of experiments poses at least two major shortcomings vis-à-vis our present interests:
First, the payments’ limited duration disincentivizes financially risky behavior, such as abandoning a job or career. We should expect that few individuals would choose to make radical changes to their work and life if they are guaranteed unconditional cash payments for only two or three years. A two- or three-year gap in employment might jeopardize not only one’s ability to return to one’s former job or career path but also one’s general future prospects in the labor market.
Secondly, let’s assume that some participants do radically alter their workforce participation despite the short-term nature of the experiment (e.g. they might use the money to help provide financial security during the process of downshifting from a lucrative full-time job, with the confidence that the experiment’s timeframe is long enough to permit them to settle into stable part-time employment or freelance work). Under a society-wide and permanent basic income, such “first movers” might inspire others also to seek alternatives to the norm of full-time permanent employment, initiating a sort of ripple effect whereby downshifting and other such alternative lifestyles gain in practice and acceptance. A two- or three-year experiment, however, is unlikely to be long enough to observe these more slowly accruing effects on social attitudes toward work.
Stated otherwise: a basic income might enable some individuals to voluntarily accept less money pay through work, reduce their time in the labor market, or even cease employment entirely (especially in the many non-USA nations in which benefits such as healthcare are not dependent on full-time employment). It might, for example, liberate those who had already been keen to adopt such a lifestyle (say, downshifting) but were restrained by, and only by, the lack of a stable financial safety net. Meanwhile, however, other would-be downshifters might remain hesitant. The latter group might include, for instance, those who have been held back by not only financial anxiety but also fear of social marginalization. Over time, however, an increased prevalence and visibility of downshifting could increase the lifestyle’s social acceptability, thereby reducing its stigmatization and rendering more attractive to more people (which would further increase its visibility and social acceptance, and so on).
Of course, this is purely speculative. Even if a basic income were to bring about increase in the number and visibility of downshifters (which itself is uncertain), this might lead not to social acceptance but to angry complaints about “parasitism” and further stigmatization. But the point is just that experiments are unlikely to reveal which outcome would transpire.
Indeed, moreover, some of the effects basic income on social attitudes toward work might develop over generations. Perhaps children and teens would develop less material-driven aspirations if they were to grow up in a society in which basic material security is taken for granted; perhaps they would place less weight on monetary considerations when choosing work or other projects and pursuits. Perhaps they would not internalize the moral imperative that one must “earn a living” through paid labor. Perhaps it would merely seem intuitive to them to conceptualize work and income as independent. Perhaps, in turn, they would conceive of the value of work in terms other than income, such as the good it brings to the world and the satisfaction it provides to the worker. Views that are counternormative in our own society might come naturally to those raised in world with universal basic income…
But we certainly can’t be confident about any of that, and experiments will not help.
2.2 Experiments are not “universal” in scope.
As I have written elsewhere, a bigger question than “What would you do if your income were taken care of?” is “What would you do if everyone’s income were taken care of?” What a financially self-sufficient individual would choose to do in a society of full-time workers is not necessarily identical to what that same financially self-sufficient individual would choose to do in a society in which everyone could afford to live without a job.
Experiments require a control group. This effectively prevents an experimental test of a truly universal basic income. Now, to be sure, some experiments do aim to include universality in their design. In GiveDirectly’s experiment, for example, the experimental units are not individual people but entire villages. In this major study, the treatment groups are each composed of communities in which all individuals are receiving unconditional cash transfers. An earlier experiment in the Indian state of Madhya Pradesh also implemented a basic income in several villages, using similar villages as controls. There is even precedent in the developed world: the much-discussed “Mincome” experiment, a negative income tax experiment conducted in Manitoba in the 1970s, used the town of Dauphin as a saturation site; every resident of Dauphin was unconditionally guaranteed a minimum income from 1974 to 1979, when the experiment was terminated.
No current experiment in the developed world, however, includes the use of a saturation site (even though Hugh Segal, the adviser to the Ontario pilot study, initially recommended it). In Finland, the experimental group consists of a random sample of 2,000 individuals who had previously been receiving federal unemployment benefits. Similarly, in the Dutch municipal experiments, participants have been randomly selected from current welfare beneficiaries residing in the respective cities, and Barcelona’s experiment involves a stratified sample of welfare recipients within one of the city’s most impoverished neighborhoods. In Ontario, experimental groups will be randomly selected from self-selected applicants, where eligible applicants are restricted to low-income individuals from three specific regions of the province. And YC Research has designed its experiment as a randomized controlled trial with a target population of low-income young adults in two regions of the US. (See this summary for more information on the design of the experiments.)
A consequence of these design decisions is that all of the above experiments will fail to capture social multiplier effects. For an example of social multiplier effects in the context of minimum income experiments, consider one of the most striking results from Dauphin: an increase in high school graduation rates. Last year, I attended a talk by Evelyn Forget, the scholar responsible for the analysis of the experiment, wherein she described survey data that revealed that the decisions of Dauphin teens to remain in school were due not only to the financial security of their individual families but also to the fact that their peers were able to stay in school as well.
We should expect that work-related behavior could also be susceptible to social multiplier effects. Like teenagers’ decisions to stay in school, adults’ decisions to withdraw from full-time employment might depend not only on their personal financial status but also on the actions of their peers. An individual with a personal source of passive income might be financially able to quit her job, and even desire to do so, but nonetheless choose to remain employed if – and because – her friends and coworkers stay in their jobs. She might, for example, believe that she would become socially isolated if she were to opt out of work while her peers remained in full-time employment. She might think about her lack of friends available before 5 pm on weekdays, or she might feel pressure to continue to earn enough money to continue to engage in costly dining, entertainment, and other activities with friends who remain lucratively employed. She might fear a lack of sympathy or understanding, even ostracism, if she were to become the only person within her peer group to abandon traditional employment.
Furthermore, as discussed above, the potential impact of basic income is not limited to the liberation of those who already desire to downshift; another possibility is that, through social multiplier effects, a basic income could generate this desire in those who had not previously considered the option. Our attitudes and aspirations are also influenced not only by our private circumstances but also by our observations of others’ choices lifestyles, and by our perception of what is socially acceptable. Some who now lack any interest in downshifting might develop one in the face of social or structural changes that legitimate or popularize the lifestyle.
Even experiments with saturation sites would be insufficient to permit us to assess all of these potential effects; the social, cultural, and economic forces that impinge on work-related attitudes and behavior vastly exceed the local scale.
2.3 Experiments exclude net contributors.
A “real world” basic income would almost certainly be introduced in conjunction with tax increases to help to finance the program, which would likely include higher income taxes on top earners. But researchers cannot ethically introduce manipulations that leave some subjects worse off as a result of the experiment. Consequently, tax increases cannot be part of experimental trials. This limits the ability to test how the full policy package would affect work-related behaviors. Even those that have studied taxes and come from financial education backgrounds such as through Northeastern University wouldn’t be able to test how different experiments could affect society and financial systems.
For one, it’s not basic income per se but redistribution – reduction of inequality – that carries the greater potential to curb the demand for positional goods. As mentioned above, a worker might hesitate to downshift if the maintenance of social relationships requires engagement in costly dining, drinking, entertainment, or luxury holidays. In a society with high inequality, a mere basic income might do little to reduce the demand for positional goods, limiting the temptation to downshift or opt out of paid work to live on a subsistence income. Many might continue to feel the need to wear nice clothing, drive a new car, and live in an affluent neighborhood to be taken seriously in society, and thus might continue to prefer greater earnings to greater leisure, despite the possibilities opened by the introduction of a basic income. Conversely, the less that one perceives one’s social status to depend on spending and consumption, the more one might be inclined to trade higher earnings for more leisure time. Policies that mitigate financial inequality, such as progressive taxes on wealth and income, help to address this barrier to downshifting.
Additionally, policies that stymie the ability to become “filthy rich” might discourage those who would otherwise be inclined to choose jobs and careers based primarily on their prospects for financial gain. Sufficiently high income taxes could reduce the role of monetary incentives in selecting work. Limitations on wealth acquisition might push some would-be profiteers to instead seek work that they could find non-monetarily rewarding.
Such effects could enhance the ability of a “basic income plus tax reform” package to transform work-related attitudes and behavior; however, they are bound to be missed in experiments.
2.4 Existing experiments are restricted to low-income populations.
So far, we have focused on limitations that are destined to afflict all basic income experiments, merely in virtue of the nature of experiments. Let’s now turn to a contingent design decision that constrains all current experiments in developed nations: in each experiment, as mentioned above, the target population contains only individuals who are low-income and/or receiving social assistance or unemployment benefits or other benefits or with incomes falling below a certain level.
To be fair, none of the existing experiments have been inspired by questions like “Can basic income provide a subsidy for downshifting?” or “Would basic income promote the acceptance and desirability of lifestyles outside of full-time employment?” On the contrary, most are motivated by the desire to determine whether unconditional cash transfers would be more effective than existing programs in addressing poverty or unemployment. In this light, these choices of target populations seem reasonable. But these choices make the experiments less congenial to the questions of those who are interested in the ability of basic income to facilitate a reduction in paid work.
A test of a policy’s potential to foster downshifting only makes sense if experimental subjects are drawn from a population of people who have the potential to downshift, and “downshifting” typically implies a reasonably well-paying position from which one shifts down. Thus, for an experiment to address our key interests, the target population should encompass individuals who are currently employed in relatively well-paying jobs. An experiment limited to the unemployed will tell us little about a policy’s ability to promote voluntary reduction of working hours. An experiment limited to the poor will tell us little about a policy’s ability to promote voluntary reduction of earnings and consumption.
The inclusion of “successful” workers among test subject is also important with respect to the question of whether basic income would reduce the stigma associated with the receipt of public benefits or, more precisely, voluntary “benefit scrounging” (which is, in essence, just a pejorative term for what I’ve been politely describing as “using a basic income to subsidize downshifting”). Quite likely, the “scrounging stigma” is too strong to disappear during the course of a short-term experiment in any case. If a basic income were to play a role in reducing the stigma, however, it would almost certainly not be by allowing poor and unemployed individuals to live upon government subsidies while they voluntarily opt out of the search for full-time jobs. Unfortunately, such an outcome (however desirable) seems much more likely to feed existing stigmas and stereotypes than to combat them.
In contrast, basic income might have a greater and more favorable cultural impact if it subsidized downshifting among individuals in relatively well-paying jobs and promising career paths – among those, that is, who embody conventional images of success. Society accords respect and admiration to those in lucrative careers, which makes such individuals uniquely well-positioned to attract curiosity, perhaps even sympathy, if they were to spurn the life of traditional employment and choose to rely upon government monies to meet their basic expenses (which is not to say that they would not also elicit the scorn or many others). Admittedly, the idea that basic income could lessen the stigma of “benefits scrounging” is far-fetched. The point at hand, however, is simply that existing experiments are not designed in a way that can adequately illuminate how far-fetched.
2.5 Experimental subjects have already “come of age” in the culture of work.
Each of the existing experiments is focused on effects on adults who have already been acculturated into the dominant work ethic. It is possible, however, that some of the social and cultural effects about basic income would result from its influence on younger generations. Perhaps teenagers would internalize different attitudes toward work if they were to come of age under an unconditional guarantee of financial security – not necessarily taking for granted that a core defining features of “adulting” is to find employment at a full-time job in order to earn a living. Perhaps young adults would formulate different personal goals and ideals of success if they did not face an immediate need to earn money through a job.
In a past feature article for Basic Income News, I speculated that entering adulthood with a work-independent college stipend – which shared some commonalities to a five-year “basic income” – could have played a large role in solidifying my own rejection of the ethic of (paid) work. For example, by allowing me to continue to dedicate myself to schoolwork without worrying about paid work, it might have helped to “prevent me from unlearning” that the fact that an activity is unpaid does not imply that the activity is not worthwhile, rewarding, or hard work – or that it’s not the best use of one’s time.
To some extent, this is just to repeat the point that experiments are too limited in duration to capture multi-generational effects of a policy. In principle, though, one could design a short-term study to test the effects of a guaranteed income on a cohort of young adults at critical transitional phases, such as leaving home for college or leaving college for “the real world” (i.e., usually, either a job or the search for one). But existing experiments are not this.
3. Concluding Remarks
In conclusion, then, I expect the current wave of experiments to shed little light on the question of whether, or to what extent, basic income would promote a cultural shift towards a decreased valuation of paid work. Any apparent evidence that basic income would not have such an effect (e.g. a lack of observed change in workforce participation or self-reported attitudes toward work) could be explained as an artifact of the limitations of experimental design.
Arguably, however, the biggest problem with experiments is not that they most likely won’t show considerable reduction in workforce participation (and yet for reasons that are inconclusive) but that many of the policy’s own proponents don’t want them to. When committed supporters of basic income demand more experiments, as often happens these days, they aren’t doing so because they want to decide for themselves whether to endorse the policy; they already have. The hope, generally, is that experiments would produce results that allay the fears of skeptical policymakers, such as the commonplace “fear” that basic income would cause a decrease in workforce participation. As many supporters are fond of pointing out, previous experiments have not shown a marked decrease in workforce participation, or have shown a decrease only within population segments where reducing work hours is socially acceptable (e.g. school-age teenagers or mothers of young children). This attitude toward basic income experiments only recapitulates society’s overvaluation of paid work.
The policymakers who assess experiments for “failure” or “success” will do so relative to the norms and values of the status quo. Political speeches and media reports are likely to portray any observed decrease in labor force participation as evidence of the failure of the policy, as happened when a negative income tax was tested in several cities in the United States in the late 1960s and 70s. My impression, based on two years of intense work in the basic income movement, is that many supporters realize this but call for experiments nonetheless, believing that the trials will in fact yield outcomes that are “successful” relative to the norms and values of the status quo.
Hence, in addition to being unlikely to produce interesting or useful results, basic income experiments may also threaten to reinforce these norms and values in the minds of advocates and other readers. And, from the standpoint as critic of the culture of work, this is not only unhelpful but dangerous.
Photo: banned :: The Golden Book of Chemistry Experiments CC BY-NC 2.0
by Donald Brown | Dec 20, 2017 | News
GiveDirectly, a nonprofit organization currently most known for unconditional cash transfers in East Africa, has decided to distribute cash among Hurricane Harvey victims, starting with those afflicted in Rose City, Texas with a population of about 500 people considered for the project. However, depending on the occupancy of the affected areas, the estimation is to cover at least 3000 people with cash aid. This aid should help go towards matters similar to Roof repair by 99roofers as well as food and supplies. This kind of help would allow people to regain some sense of normalcy in the midst of this disaster. There would be so many families whose houses have sustained significant water damage and would be in need of Water Damage Restoration Services from expert professionals. Hopefully, the people of Rose City will be able to recover from this disaster and be able to restore their lives back to a sense of normality.
As with their other initiatives in Kenya, Uganda, and Rwanda, GiveDirectly is proposing to transfer money to hurricane victims in Texas as an unconditional payment. Unlike the projects in East Africa however, where the transfers were via payments to phones through methods like mobile banking, the transfer for Harvey victims is being delivered via prepaid debit cards containing US$1,500. This initiative also differs from the African experiments in the sense that it is not designed as a basic income pilot: beneficiaries are targeted by applying “a range of criteria to select locations: degree of damage sustained, income levels, access to other aid resources, and size”, as transmitted by Piali Mukhopadhyay from GiveDirectly. Moreover, Hurricane Harvey cash transfer will not be monitored via a control group, so there is no comparison between treated and non-treated groups. Clarifying the “unconditional” reference above, it applies only to the way beneficiaries spend the money, which is completely free from control / conditions.
Disaster victim assistance is changing, from an in-kind-based approach to cash-based programming. Cash transfers were used after the Pakistan floods in 2010, and useful lessons were learnt about cash distribution systems, and in 2016 the method was discussed in a United Nations report. GiveDirectly’s project is therefore part of a trend. Experience so far suggests that providing cash rather than services is an efficient way to provide disaster relief because it supports the local economy at the same time as providing the goods and services that disaster victims know that they need. Homes may take huge hits resulting in different requirements to get them fixed so it is safe for a family to live in again. This will include not only the exterior of the home, wherein you might need an expert gutter cleaning company similar to a Clean Pro Gutter Cleaning Ann Arbor agency, or maybe a water damage restoration company who can look at the problems caused by the excess water in your house! The money given to the needy will come handy when these restorative and repair works will take place, as the latter is imperative to proper living standards for a community. Multiple companies are needed, from roof repairs by a reputable company (you can look on the Florida Southern Roofing info page if you are in this area) to stocking up on provisions after all food is lost. There are many ways in which an injection of cash can help those affected.
Whilst these experiments are not Basic Income pilot projects, the results are useful indicators of how different methods for distributing cash might work, and therefore of what the best methods for distributing Basic Incomes might be in different contexts; and the results might also inform a longer-term debate about how Basic Incomes might be preferable to longer term development aid.
More information at:
Ben Paynter, “This experiment will test if giving cash to victims is the best disaster relief“, Fast Company, November 7th 2017
by Karl Widerquist | Dec 3, 2017 | Opinion, The Indepentarian
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.
by Karl Widerquist | Nov 26, 2017 | Opinion, The Indepentarian
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.
by Hilde Latour | Nov 26, 2017 | News
On November 14th 2017, Antoinette Hertsenberg (from the Dutch television program Radar) handed over a petition to the Dutch Parliament (signed by 113.344 people), asking for an experiment with a basic income for people over 55 years old who are unemployed.
The petition was started after Radar called attention to the fact that only 3% of the unemployed 55+ have a chance to find a paid job in the Netherlands, 6 months ago.
The handing over of the petition was a large event; many members of Parliament were present, representing almost all political parties. In reaction to the petition, the Socialist Party (SP) asked for a debate in Parliament on the topic, in contrast to what happened in the preceding year, in which a debate about another petition on basic income was refused.
A lot of media attention was given to the petition, reigniting discussion on basic income in the Netherlands.
More info:
Pedro Alves, “Netherlands: Basic Income petition in the Netherlands for people over 55 years old was signed more than 50000 times“, Basic Income News, July 6th 2017