essay on poverty is just a state of mind

Why poverty is not a personal choice, but a reflection of society

Research Investigator of Psychiatry, Public Health, and Poverty Solutions, University of Michigan

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Shervin Assari does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

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As the Senate prepares to modify its version of the health care bill, now is a good time to back up and examine why we as a nation are so divided about providing health care, especially to the poor.

I believe one reason the United States is cutting spending on health insurance and safety nets that protect poor and marginalized people is because of American culture, which overemphasizes individual responsibility. Our culture does this to the point that it ignores the effect of root causes shaped by society and beyond the control of the individual. How laypeople define and attribute poverty may not be that much different from the way U.S. policymakers in the Senate see poverty.

As someone who studies poverty solutions and social and health inequalities, I am convinced by the academic literature that the biggest reason for poverty is how a society is structured. Without structural changes, it may be very difficult if not impossible to eliminate disparities and poverty.

Social structure

About 13.5 percent of Americans are living in poverty. Many of these people do not have insurance, and efforts to help them gain insurance, be it through Medicaid or private insurance, have been stymied. Medicaid provides insurance for the disabled, people in nursing homes and the poor.

Four states recently asked the Centers for Medicare and Medicaid Services for permission to require Medicaid recipients in their states who are not disabled or elderly to work.

This request is reflective of the fact that many Americans believe that poverty is, by and large, the result of laziness , immorality and irresponsibility.

In fact, poverty and other social miseries are in large part due to social structure , which is how society functions at a macro level. Some societal issues, such as racism, sexism and segregation, constantly cause disparities in education, employment and income for marginalized groups. The majority group naturally has a head start, relative to groups that deal with a wide range of societal barriers on a daily basis. This is what I mean by structural causes of poverty and inequality.

Poverty: Not just a state of mind

We have all heard that the poor and minorities need only make better choices – work hard, stay in school, get married, do not have children before they can afford them. If they did all this, they wouldn’t be poor.

Just a few weeks ago, Housing Secretary Ben Carson called poverty “ a state of mind .” At the same time, his budget to help low-income households could be cut by more than US$6 billion next year.

This is an example of a simplistic view toward the complex social phenomenon. It is minimizing the impact of a societal issue caused by structure – macro‐level labor market and societal conditions – on individuals’ behavior. Such claims also ignore a large body of sociological science.

American independence

Americans have one of the most independent cultures on Earth. A majority of Americans deﬁne people in terms of internal attributes such as choices , abilities, values, preferences, decisions and traits.

This is very different from interdependent cultures , such as eastern Asian countries where people are seen mainly in terms of their environment, context and relationships with others.

A direct consequence of independent mindsets and cognitive models is that one may ignore all the historical and environmental conditions, such as slavery, segregation and discrimination against women, that contribute to certain outcomes. When we ignore the historical context, it is easier to instead attribute an unfavorable outcome, such as poverty, to the person.

Views shaped by politics

Many Americans view poverty as an individual phenomenon and say that it’s primarily their own fault that people are poor. The alternative view is that poverty is a structural phenomenon. From this viewpoint, people are in poverty because they find themselves in holes in the economic system that deliver them inadequate income.

The fact is that people move in and out of poverty. Research has shown that 45 percent of poverty spells last no more than a year, 70 percent last no more than three years and only 12 percent stretch beyond a decade.

The Panel Study of Income Dynamics ( PSID ), a 50-year longitudinal study of 18,000 Americans, has shown that around four in 10 adults experience an entire year of poverty from the ages of 25 to 60. The last Survey of Income and Program Participation ( SIPP ), a longitudinal survey conducted by the U.S. Census, had about one-third of Americans in episodic poverty at some point in a three-year period, but just 3.5 percent in episodic poverty for all three years.

Why calling the poor ‘lazy’ is victim blaming

If one believes that poverty is related to historical and environmental events and not just to an individual, we should be careful about blaming the poor for their fates.

Victim blaming occurs when the victim of a crime or any wrongful act is held entirely or partially responsible for the harm that befell them. It is a common psychological and societal phenomenon. Victimology has shown that humans have a tendency to perceive victims at least partially responsible . This is true even in rape cases, where there is a considerable tendency to blame victims and is true particularly if the victim and perpetrator know each other.

I believe all our lives could be improved if we considered the structural influences as root causes of social problems such as poverty and inequality. Perhaps then, we could more easily agree on solutions.

Social mobility
Homelessness
Health disparities
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Why poverty is not a personal choice, but a reflection of society

A homeless camp in Los Angeles, where homelessness has risen 23 percent in the past year, in May 2017.

AP Photo/Richard Vogel

Shervin Assari , University of Michigan

As the Senate prepares to modify its version of the health care bill, now is a good time to back up and examine why we as a nation are so divided about providing health care, especially to the poor.

Social structure

Four states recently asked the Centers for Medicare and Medicaid Services for permission to require Medicaid recipients in their states who are not disabled or elderly to work.

This request is reflective of the fact that many Americans believe that poverty is, by and large, the result of laziness , immorality and irresponsibility.

Poverty: Not just a state of mind

Just a few weeks ago, Housing Secretary Ben Carson called poverty “ a state of mind .” At the same time, his budget to help low-income households could be cut by more than US$6 billion next year.

American independence

This is very different from interdependent cultures , such as eastern Asian countries where people are seen mainly in terms of their environment, context and relationships with others.

Views shaped by politics

Why calling the poor ‘lazy’ is victim blaming

If one believes that poverty is related to historical and environmental events and not just to an individual, we should be careful about blaming the poor for their fates.

Shervin Assari , Research Investigator of Psychiatry, Public Health, and Poverty Solutions, University of Michigan

This article was originally published on The Conversation . Read the original article .

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Root causes of poverty, impact on individuals and society, potential solutions.

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Poverty Is Just a State of Mind

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Elizabeth A. Throop

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American dominant culture understands poverty as a defect of character, not a result of a structurally unjust economic system. People who are poor are not poor because they lack money. They are poor because, in America’s dominant culture, there is something wrong with them emotionally, morally, subculturally, or behaviorally. People in poverty in the United States are largely viewed as individually responsible for their own economic circumstances, and they must be punished in this view (see Ryan 1976 and Schneider 1999 for representative takes on the issue). This appallingly cruel perspective has a long history in the United States despite its patent falsity, going far beyond the “blaming the victim” nonsense furthered by allegedly liberal social scientists and providers of social services (including social workers, psychotherapists, counselors, and other purveyors of the “helping” professions).

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Throop, E.A. (2009). Poverty Is Just a State of Mind. In: Psychotherapy, American Culture, and Social Policy. Culture, Mind, and Society. Palgrave Macmillan, New York. https://doi.org/10.1057/9780230618350_3

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Thought Experiment

Does ‘Wrong Mind-Set’ Cause Poverty or Vice Versa?

By Emily Badger

May 30, 2017

Ben Carson has proposed, in effect, a human experiment.

Consider someone with the right “mind-set.” Take away everything he owns, drop him onto the street, and he will soon lift himself out of poverty.

“And you take somebody with the wrong mind-set,” Mr. Carson, the head of the Department of Housing and Urban Development, continued last week in a SiriusXM radio interview with his longtime friend Armstrong Williams. “You can give them everything in the world. They’ll work their way right back down to the bottom.”

Poverty, Mr. Carson is saying, is in part a state of mind. But while that idea holds truth, researchers who study poverty say Mr. Carson has greatly confused cause and effect.

Poverty is in some ways a state of mind, their studies show, in that it can cause people to think less clearly, to sleep less well, to contend with distraction and to internalize shame. But it’s the experience of deprivation that leads to the mind-set, researchers say. It’s not the mind-set that leads people into poverty, or that explains why many never escape it.

“There’s definitely evidence that poverty — particularly childhood poverty — does affect things like persistence, your executive functioning, your ability to control attention, to inhibit emotions,” said Gary Evans, a professor of human ecology at Cornell. “He’s correct in identifying that there’s this link. But I think he’s got the relationships backwards.”

The best evidence for Mr. Carson’s argument comes from his own life. He grew up poor in Detroit and went on to become a renowned neurosurgeon, a trajectory he attributes to his childhood outlook. “I had to will myself to see the opportunities that existed on the horizon,” he explained in a note emailed to HUD staff today, following up on his public comments last week.

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Search Utah State University:

A rolling perspective: poverty is a state of mind.

During a conversation with Kim, the Costco/Ameriprise lady who was helping me save money, I shared that I was writing a book, The Art of Poverty. “Poverty is a state of mind,” I said. She agreed and added: “You may be broke, but you’re never poor.”

Wise words. But how to stop feeling poor when even able-bodied people feel that way these days? Disabled persons in particular face a frightening state of perpetual poverty. During the shaming process of getting SSDI, I succumbed to hopelessness and depression. It was only when I learned that poverty is a state of mind, and institutions do not define me, that I escaped that pit of despair. I’ve broken up my long journey—from feeling poor to feeling wealthy—into steps that I can share with you via this column.

People often tell me how poor they are; I can see they suffer from believing that untrue thought. They don’t realize that we wheelie folk already live with and in poverty. You see, I don’t look poor (thank you, Savers!). I have a fancy-schmancy wheelchair (thank you, Utah Assistive Technology Program !). Most important, I don’t act poor, which throws people off guard. People assume if you’re really poor, you must be miserable, and I’m too happy.

I sit in my wheelchair with a little smile on my face as they speak. I notice their new clothes, or new car. I see them drink their third Starbuck’s concoction of the day while they hold the fifth bag of take-out food they’ve had that week. Some of these unhappy people spend more in a day than I spend on food in a month. Sometimes I catch myself thinking, They have no idea what it means to be really poor.

And then I stop in my wheel-tracks: Jen, you’re not poor. I then remember with compassion how it was to feel poor, and how no one in the world could tell me I wasn’t. If we believe we’re poor, we’re right, for our perceptions create our reality. Allowing ourselves to believe we’re poor keeps us from true happiness. That’s real disability.

Ready to change your perspective? Let your Mind ponder these:

Do you need it, or just want it? Humans need food, water, and air: that’s it. (Sorry, Maslow.) Okay, shelter if they don’t live in Hawaii. Even in that hospitable clime, they don’t need an eight-bedroomed mansion on the beach.
You’ll get more of what you’re grateful for. No matter how teeny it might be, show gratitude and you’ll get more of it. I look at a bright green kale leaf and say, “Thanks for this kale, Kevin.” Kevin, my son-in-law, now gives me his amazing organic produce because they stopped the SNAP “Double Up” program this year.
What you see is what you get (more of). On what do you focus? Lack? Or abundance? What we focus on most becomes all we can see; it’s all we’ll look for. Change your focus: physically or mentally stand across from a situation and find its other side(s). Absolutely nothing has only one side. Upsides are just as valid as downsides; besides, they’re more fun, and they create within you a feeling of wealth.
Right here, right now, you don’t need more money. BUT…BUT…BUT! you stutter. Sorry, it’s true. Unless a masked gunman stands before you demanding it right now, you don’t need more money. (Reality check: you’re reading this, so no masked gunman is present in this moment, no matter where he may be later.)
Finally, you will either (a) find a new source of income; or (b) find ways of trimming or removing budget items so what you have pays the bills. Effortlessly. I know. It sounds crazy, but I have experienced it time and again. The car insurance is a great example. I now save $39 a month: precisely my June rent increase. Look back honestly at your life, and notice how every single time you thought you weren’t going to make it, you did. A way opened up. This phenomenon will happen regardless, but if you want to agonize about it, that’s your choice.

There are so many ways to live richly on a small fixed income that I’m writing a book about it, but here’s one tip: the Smith’s grocery store app. My daughter and I share pics of our receipts in a sort of “Savings Showdown.” Recently, she was elated when she saved a whopping $47. While I saved a “mere” $27, I’m on food stamps. For me, that’s ten days’ worth of groceries. I felt RICH.

And that’s the whole point: you can feel rich any time you choose. Sure, maybe you are broke, but you’re not broken. And you sure don’t have to feel poor. The choice is yours.

Jennifer Holland taught herself to read and write at age four and has been doing both ever since. Minnesota-born and Wisconsin-bred, she nonetheless inherited the Irish perchant for travel. Despite the shoestring budget, she visited a dozen countries before her diff-ablement, and even lived in Ireland for nearly fifteen years. Her encounters with other cultures inform the quirky insights into human behavior that find their expression in her poetry, novels, and non-fiction works. When she's not reading or writing, she enjoys chair yoga, video chats with her children and gradchildren, and living happily with MS on a tiny fixed income.

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Housing Secretary Ben Carson Clarifies Comment That Poverty Is A 'State Of Mind'

Pam Fessler

Housing and Urban Development Secretary Ben Carson drew controversy last month when he said in a radio interview that "poverty to a large extent is also a state of mind." Chris Carlson/AP hide caption

Housing and Urban Development Secretary Ben Carson drew controversy last month when he said in a radio interview that "poverty to a large extent is also a state of mind."

Housing and Urban Development Secretary Ben Carson is standing by his controversial comment that poverty is a "state of mind," but he says that "how a person thinks" is only one component that contributes to being poor.

"What I said is that it is a factor. A part of poverty can be the state of mind," he told NPR in an interview. "People tend to approach things differently, based on their frame of mind."

His agency, he says, wants "to find ways to make sure that people understand that the person who has the most to do with what happens to you, is you."

Carson, who grew up in poverty, said in a Sirius XM radio interview last month that "poverty to a large extent is also a state of mind." The comment drew widespread criticism from anti-poverty advocates who say it implies that poor Americans are at fault for their poverty and that they're better off without government aid.

Carson is scheduled to appear before a House appropriations subcommittee Thursday to defend President Trump's 2018 budget request for his agency.

Carson will likely face tough questions about his comments on poverty as well as the administration's proposal to cut more than $6 billion — or 13 percent — from HUD's budget. Among the programs targeted: public housing, housing vouchers, community development block grants, and other aid for low-income Americans.

The administration argues that much of this spending is ineffective and inefficient and that the money would be better spent elsewhere. And Carson tells NPR his agency's approach is aimed at breaking cycles of poverty long term. Housing advocates say the cuts would be devastating for millions of Americans who can't afford a place to live without assistance.

Carson sat down with NPR's Pam Fessler at his HUD office last week to talk about some of these issues. Here are some highlights:

Interview Highlights

You made these comments about poverty largely being a state of mind. Can you explain how much you think a "state of mind" accounts for somebody being poor?

What I said is that it is a factor. A part of poverty can be the state of mind. Poor in spirit. And people tend to approach things differently, based on their frame of mind.

A good example would be, if you were a minor league baseball player, and you were brought up to the majors and you look up on the mound and you say, "Nolan Ryan! Oh no, he's a legend. He's got a 100 mile per hour fastball. I'll probably not even see the ball." You're probably not going to get a hit. If you come up and say, "Nolan Ryan. He's an old man. I'm going to knock the cover off the ball," you are probably going to have a much better chance.

So one of the things I think government can do very well is to help create the right kinds of mindset, frame of mind, by providing ladders of opportunity so that people can really see what's going on around them. A lot of times if you go to a disadvantaged neighborhood, you ask the kids, "What do you want to do when you grow up?" You get about five different answers. But there's a thousand. We need to show people the other 995 and how you get there. And those are the kinds of things that create that can-do attitude that is so important, and that for such a long time was a part of the American mindset. And there are those now who want people to think that somebody else is in control of you and that you're a victim. We want to find ways to make sure that people understand that the person who has the most to do with what happens to you, is you.

I want to make sure I'm clear. You're saying it's only one component of people being poor, or the main component?

Of course [state of mind is] just a component [but] it is an important component, how a person thinks. And I know there was a recent article that says, no, the state of mind is caused by poverty. I totally disagree with that. I think you can have a lot of people who are in poverty who are not adversely affected by that at all, who have a winning attitude and who will do whatever they need to do to be successful. And I would encourage people to go to the Horatio Alger Society website, and read those hundreds of biographies there of Americans who rose through incredible odds and severe poverty to become leaders in our society

So what are you going to do at HUD to give people what you say is the right state of mind to get out of poverty?

A number of things, but one of the interesting concepts we're working on are centers that will be put into neighborhoods, repurposing some of the old buildings, and exposing people to what those many opportunities are, exposing people to some basic skills that people used to get, for instance in high school, creating mentorship programs.

There are a lot of people out there who would be delighted to take people under their wings but they don't have a good mechanism for doing that. (And) to provide day care for so many of the young ladies who end up getting pregnant and then their education stops. Provide them a mechanism so that they can go back and get their GED, get their associate's degree, their bachelor's degree, their master's degree, take care of themselves and teach their children to take care of themselves, so that you break the cycles. The systems that we have been using for decades don't seem to be breaking the cycles. They seem to be adding to them, so we have to start thinking a little bit differently about these things.

But these centers aren't included in the president's budget. So how are they going to come about? Is this something HUD is going to do?

Yeah, these are things that we're working on. We're working on concepts, on how do we break these cycles, not how do we continue them. So many people just are focused on, but if we change this, then it won't go on like it always has, but maybe we don't want it to go on like it always has. We have three to four times as many people in need of affordable housing as we can provide. The more we can move out the more others we can help. Success is not how many people we can put into public housing, it's how many we can get out of it.

The president's budget, though, calls for tremendous cuts in the HUD budget. You told the National Low Income Housing Coalition that nobody would be thrown out on the street under your watch. But many analysts look at those numbers and say that people will be thrown out on the street under this budget. Are they wrong?

I think [analysts are] wrong, absolutely. We're paying very close attention to the vulnerable population and making that a very important part of how things are executed. Bear in mind, there are a lot efficiencies that will save us a lot of money. And there's also a new model that we're really concentrating on. The old model was the federal government rides in on the white horse and plops down millions of dollars and says, "Build this place for all these people." And then goes on to the next project. The new model is the federal government seeds the project, and oversees and facilitates, along with the housing authorities, ... bringing in those private partners, bringing in the nonprofits, bringing in the faith community.

And there's a lot more money there than there ever could be in the federal government. And you also get those people vested in the project, so now their income stream is dependent upon that project being successful. And having that done at the local level is going to be so much better.

So you don't think anybody's going to be thrown out on the street?

I don't think anybody's going to be thrown out on the streets. We're paying very careful attention to that.

Los Angeles County [has] reported that its homeless population went up 23 percent last year, which is an amazing number. But this budget calls for cuts in homeless assistance. Do you think we're going to be seeing increases in homelessness in lots of other places?

I don't think so. Of course, the other part of that story is a number of places, like Bergen County [N.J.], have reported there's no homelessness there. It's been eradicated. We're going to continue to make that a high priority, fully recognizing that it actually costs more to leave people homeless. That person sleeping under the bridge who's going to wind up in the emergency room, sometimes getting admitted for a week in the hospital? That week hospital stay costs more than it costs to put them in a place for a year. But putting them in a place is not enough. That's only Part 1. Part 2, we have to diagnose why they're in that condition. And Part 3 is we have to treat it.

There are a number of things in the president's budget to encourage home ownership, but we have many millions of people in this country who aren't even close to that point. What's in the budget to help them?

For one thing, people are closer to it than you might think, but it's a matter of making sure they're educated properly. A lot of times people maybe bite off more than they can chew. And that's one of the reasons, for instance, that we are now looking at being able to guarantee mortgages on individual condominium units. Because that can frequently be the first step. You buy that kind of home, you build up equity, you save, and then you move to the next step. In 2008, there were so many people who deceived individuals and simply said you've got an ever expanding price here. It's going to be your piggy bank for the rest of your life. And you can always count on that. And look what the results of that were. So we're working to make sure that the education of the people is such that they understand how you go about building that equity, and how you go about making your first, second, third steps to acquiring a home. Because, quite frankly, in America ... the primary source of wealth is home ownership.

How are you going to educate people?

We have multiple places around the country, more than 1,200, of individuals who are trained ... and we're working with them. We're also looking at some uses of social media and the Internet to help keep people well-informed on how to do things. Giving them little quizzes that they can take, and things of that nature. It's really just a matter of making sure people are well-informed. You know Americans are industrious people. That's how America got to be a great place. We're not a little feeble people who have to be spoon-fed. But we do have to recognize where we are right now and utilize what we have in order to help facilitate the use of the tremendous intellect and energies that exist within our society.

But there are some people who you would say are poor, who might want to try but they can't get out for other reasons besides their state of mind?

Of course, there are people of all types. But our duty in government and in HUD is to provide the avenues, the mechanisms, to allow anyone who can get out to get out, and I think that's going to be most people.

This transcript has been edited for length and clarity.

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Article Contents

1. introduction, 2. the malawi social cash transfer program, 3. measures, 4. malawi sctp, 7. discussion and conclusion, supplementary material, the psychology of poverty: evidence from the field.

Article contents
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Supplementary Data

Adria Molotsky, Sudhanshu Handa, The Psychology of Poverty: Evidence from the Field, Journal of African Economies , Volume 30, Issue 3, June 2021, Pages 207–224, https://doi.org/10.1093/jae/ejaa010

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Individuals living in poverty are less likely to save and plan for the future, behaviour traditionally attributed to liquidity constraints and the associated need to address immediate consumption. Recent work on the behavioural consequences of poverty suggests that poverty induces stress and negative affect, which themselves directly influence economic decisions. We test this hypothesis using evaluation data from a national cash transfer program in Malawi in which some eligible households were randomly assigned to receive the transfer before others. We find that cash transfer reduces stress and improves positive affect, and positive affect has a direct effect on economic decisions.

Standard economic explanations of shortsightedness displayed by individuals living in poverty include liquidity constraints and the urgency to meet immediate needs. The consequences of this myopia and their related behaviours help explain the persistence of poverty among individuals over time and across generations. However, insights from the psychology of poverty could further our understanding about why those living under severe material deprivation make decisions that effectively perpetuate their economic condition. This line of reasoning proposes that poverty affects economic choices through its influence on psychological states—stress and affect—as well as through the psychological toll of scarcity ( Mullainathan & Shafir, 2013 ; Haushofer & Fehr, 2014 ). Material deprivation and its immediate correlates such as exposure to disease, crime and violence cause negative affect and chronic or ‘toxic’ stress, and these psychological states then exert an additional and separate effect on forward looking behaviour and time discounting.

Economists as far back as the 19th century recognised the idea that economic decisions, particularly those involving intertemporal choice, may be influenced by psychological factors. John Rae (1834), among others, described the factors inhibiting the ‘effective desire of accumulation’ to include impulse control, visceral influences and emotion, as well as the habit of prudence and reflection. More recent reviews of intertemporal choice have continued to highlight the importance of emotion and current psychological states on behaviour, citing evidence on these relationships from laboratory studies conducted by psychologists (Frederick et al ., 2002; Lowenstein, 2000). A key pathway for these effects is thought to be attention and self-control, whereby stress and emotion lead people to make choices that are habitual rather than goal-oriented ( Haushofer & Fehr, 2014 ), that respond to salient cues ( Shah, 2012 ) or that resolve the immediate emotion ( Loewenstein, 1996 ). The psychological consequence of poverty is further manifested through the phenomenon of scarcity, which creates a mindset that draws attention to the immediate shortage and away from long-term considerations ( Mullainathan & Shafir, 2013 ). For those in extreme poverty for whom food or water is scarce, all available resources, mental and physical, are devoted to addressing this immediate need to the neglect of other concerns. This extreme focus or ‘tunnelling’ is not a behaviour that only affects the poor, but for those living in poverty tunnelling can represent a near perpetual state of mind with profound consequences.

A few studies have used exogenous variation in income to study the link between poverty and psychological states such as affect and subjective well-being (SWB). Recipients of the Government of Zambia’s unconditional cash transfer program displayed a significant increase in subjective future well-being relative to an experimental control group ( Handa, Seidenfeld & Tembo, 2020 ). Similarly, a lump-sum cash transfer to poor individuals provided by the non-governmental organisation Give Directly in Kenya increased SWB and happiness relative to a randomly assigned control group, though the stress hormone, cortisol, was only affected in the group receiving larger transfers ( Haushofer & Shapiro, 2016 ). Qualitative evidence from four cash transfer programs in Sub-Saharan Africa also report positive effects of the programs on the psychosocial well-being of beneficiaries ( Attah et al ., 2016 ). A review of 25 quantitative studies that report on the effect of poverty on psychological well-being revealed that 18 demonstrated positive and significant associations between poverty alleviation and aspects of psychological well-being or stress ( Haushofer & Fehr, 2014 ).

While there is growing evidence on the causal link between poverty and psychological states, the evidence on the causal link between psychological states and economic decisions is limited to laboratory settings. Pharmacological elevation of the stress hormone cortisol increased time discounting among males aged 18–35 in a study in Amsterdam ( Cornelisse et al ., 2013 ). Negative affect (induced through film clips) also reduced patience among individuals aged 18–63 in the USA ( Lerner, Li & Weber, 2013 ), while positive affect (also induced through film clips) increased patience ( Ifcher & Zarghamee, 2011 ). There is no evidence outside the lab setting on these relationships due to the challenge of finding exogenous variation in psychological states that can be used to establish a causal link to economic decisions. Indeed, the question we address in this paper—whether emotional and psychological states affect economic decisions at the population level—can only be answered through non-experimental methods, since the random assignment to psychological states on a large scale is not possible.

In this study, we use secondary data from a longitudinal randomised control trial (RCT) to evaluate the impact of a national cash transfer program in Malawi—a program that reaches a large number of extremely poor beneficiaries and is implemented by the Ministry of Gender, Children, Disability and Social Welfare. We use the random assignment to the cash transfer to identify the causal effect of income on psychological states and on two inter-temporal decisions, a hypothetical choice task and actual savings. We then exploit our three-wave panel to build a first-difference instrumental variable (FDIV) estimator to identify the causal effect of psychological states on inter-temporal decisions. This approach purges our main regression of both time-invariant and time-varying sources of endogeneity that potentially confound the observed relationship between psychological states and economic decisions. The results show that psychological states predict the decision to wait for future money. For example, happiness leads to an increase of about 11.2 percentage points in the likelihood of waiting for a future value of MWK13,000, an increase of 36% over the baseline mean. An index based on our five different measures of psychological states increases the likelihood of waiting for MWK13,000 by 24%. These results are the first from a field setting to demonstrate that psychological and emotional states have a causal effect on economic decisions. We also show that the cash transfer program significantly improves all five measures of psychological states. The positive effects on stress are particularly novel since stress is viewed as an important mechanism linking poverty to a host of health and behavioral outcomes.

2.1. Program design

The Malawi Social Cash Transfer Program (SCTP), an unconditional cash transfer program targeted to ultra-poor, labour-constrained households in Malawi, is administered by the Ministry of Gender, Children, Disability and Social Welfare. 1 The program began as a pilot in the Mchinji district in 2006, was expanded to an additional eight districts by 2009 and was further expanded starting in 2014. Beneficiary households receive bimonthly payments of varying amounts depending on household size and the number of primary and secondary school-aged children in the home. By endline, the average monthly per capita transfer amount received by beneficiary households was equivalent to US$1.25 a month or about US$60 per household annually. Payments are made in cash every other month through a local pay-point manager to the main beneficiary, and there are no conditions to receive the money. Payments represent approximately 20% of pre-program consumption for beneficiary households and are therefore sizeable. The overarching objective of the SCTP is to reduce extreme poverty and hunger, and to increase school enrolment among the ultra-poor.

2.2. Study design

A cluster-randomised, longitudinal study consisting of a baseline and two follow-up surveys was designed to assess the impact of the SCTP. 2 Our present study uses data from the baseline survey conducted in mid-2013, the first follow-up survey conducted in late 2014 through early 2015 and the final follow-up survey conducted in late 2015. The SCTP study consisted of both quantitative and qualitative components. The household questionnaire, the main survey instrument, covered a comprehensive list of topics including household composition, consumption, health, education, economic activity, time and SWB, among others. The study was designed around the Government of Malawi’s plans to extend and expand coverage of the SCTP starting in 2014. Two districts, Salima and Mangochi, were chosen for the impact study to align the evaluation with the expansion plans. Randomisation took place at multiple levels within these two districts starting with Traditional Authorities (TAs) down to Village Clusters (VCs). Two TAs were randomly selected in each district to participate in the study. Based on the program’s targeting procedure set by the government, eligibility lists in each VC in the study sites were created by program staff and provided to the study team. The study team randomly assigned numbers to the VCs in each TA using the random number generator in Excel. Once baseline data collection was complete, the District Commissioner’s Office in each district conducted a public coin toss to determine whether the top or bottom half of the randomly ordered list would enter the program first, with the rest comprising a delayed-entry group. The coin toss thus determined the treatment group and resulted in 14 VCs being assigned to treatment with the remaining 15 assigned to the delayed-entry control arm. 3

Power for the study was calculated based on the three key program objectives—consumption, school enrolment and child nutritional status—using intra-class correlation estimates from the most recent Malawi Demographic and Health Survey for nutrition, and the Malawi Integrated Household Survey for consumption and schooling. Per these calculations, a sample size of 3,500 households in 29 VCs was necessitated, or an average of 121 households per VC. The final sample size was 3,531 households—1,678 in treatment VCs. Since limited financial resources prevented the inclusion of all households in program districts at once, the final ethically feasible study sample represents approximately 47% of all eligible households from the four TAs. For additional details on the sampling procedure and power calculations to determine optimal sample size, see the publicly available study baseline report ( Handa et al . 2014 ).

We estimate the impact of the cash transfer on two economic decisions that involve self-control and long-term planning. The first is whether the respondent saved any cash in the last 30 days for an emergency or to buy something special in the future. The second is a hypothetical intertemporal choice task where the respondent was asked if they would wait 1 month and take a future (higher) amount if they were to receive MWK10,000 today. The higher amounts ranged from one to four times the value of the current amount. The lowest future value for which we observe a significant treatment effect is MWK13,000, and this is also the value at which the largest proportion of respondents who ever waited for a future value switched from not waiting to waiting, so we use a dichotomous indicator of whether the respondent chose to wait for this future amount of money as our other indicator of economic decision making. 4 As mentioned, this subset of questions was hypothetical in nature meaning respondents were not incentivised and no monetary rewards were exchanged. While there is a debate in the literature over the merit of hypothetical versus incentivised choice modules, studies have found both types lead to similar responses, and hypothetical questions afford researchers the additional advantage of testing a broader range of values across a larger, more diverse sample (Camerer & Hogarth, 1999; Delavande et al ., 2011; Harrison et al ., 2002; Harrison et al ., 2007; Holt & Laury, 2002; Johnson & Bickel, 2002; Kirby, 1997). Researchers must remain within their budget constraint, so incentivising such tasks necessitates smaller sample sizes and lower future value ranges as the costs associated with paying out the rewards can quickly add up. Conversely, with hypothetical tasks, researchers can sample more individuals and use a much larger spread of future values, as we do here.

The psychological variables we use are broken down into those that measure the respondent’s stress and those that measure their affect and SWB. The former group consists of a stress index created using a variation of the Cohen’s Perceived Stress Scale (PSS) ( Cohen, Kamarck and Mermelstein 1983 ) (4-item scale 5 ) and a dichotomous variable denoting whether or not the respondent reported worrying about having enough food for their family over the past 7 days. To ascertain respondents’ affect and general feelings of well-being, we look at whether they believe their life will be better 1 year from the date of the interview, whether they reported generally feeling happy and their score on a quality-of-life scale. The quality-of-life scale is an eight-item module in which respondents were asked how strongly they agreed or disagreed with eight positive statements about their life. We also create an index based on all five of the psychological variables for each main respondent. 6 Full details and the definition of all variables used in the analysis are provided in Appendix 2.

Self-reporting of psychological variables may be subject to response bias. The happiness question would be most susceptible to a concern that treatment households might be over-stating their happiness because of desirability bias or that control households might be upset about not receiving the cash transfer. Our study design, by randomising at the VC level, reduces the potential interaction between treatment and control households and for associated feelings of envy. Two measures (quality of life and stress) are derived from complex multi-item scales that include reverse codes and so would be hard to manipulate in a way that would seem obvious to the respondent. A fourth measure is on future well-being rather than current well-being, and the fifth measure refers specifically to food. Table 3 presents means of the five psychological variables (plus the overall index) by study arm and wave. There is, in fact, an increasing trend in four of the five measures including the happiness measure.

The SCTP baseline evaluation report tested for balance across all primary indicators plus variables that were thought to be important determinants of the primary indicators such as age, education and marital status of the main beneficiary. Of the 350 indicators tested, 10 were statistically different at baseline (including the main respondent being currently separated/divorced, per capita food-specific expenditures and percent of children who suffered from a fever in the past 2 weeks), though the magnitude of all differences was small. The analytical sample for this article is restricted to the panel of respondents who responded to the questions on intertemporal choice, affect and savings in each round. Across the three survey waves, 2,659 households had the same respondent for the individual module on preferences and affect. Table 1 Panel A shows baseline balance tests for seven key variables for this restricted panel that are likely to be important determinants of the outcomes considered in this article. None of the means of these seven variables are statistically different across study arms. Similarly, Table 1 Panel B shows baseline balance tests on the analytical sample for the six outcomes analyzed in this article for which we have baseline data. Again, none of the means for these outcomes are statistically different across study arms at baseline among the analytical sample.

Malawi SCTP Baseline Balance Tests for Key Individual and Household Characteristics

.	.	All .	Control .	Treatment .	value of difference .

Respondent female	2,659	0.88	0.89	0.87	0.33
Respondent age	2,659	56.89	56.08	57.77	0.46
Respondent any school	2,659	0.31	0.30	0.31	0.77
Widow	2,659	0.45	0.44	0.46	0.52
Household size	2,659	4.53	4.55	4.50	0.81
Per capita expenditures (Kwacha)	2,659	44,052.97	42,452.05	45,785.53	0.39
Number of livestock owned	2,659	1.18	1.20	1.15	0.82

Waits for 13,000 Kwacha	2,659	0.31	0.32	0.30	0.26
Generally feel happy	2,659	0.18	0.18	0.17	0.72
Life better in 1 year	2,659	0.53	0.53	0.53	0.95
Quality-of-life scale (out of 8)	2,659	2.23	2.26	2.19	0.58
Low stress index (out of 20)	2,659	6.00	5.89	6.12	0.67
Not worried about food	2,659	0.15	0.15	0.14	0.73
Overall psychological state index	2,659	−0.00	0.01	−0.01	0.49

.	.	All .	Control .	Treatment .	value of difference .

Respondent female	2,659	0.88	0.89	0.87	0.33
Respondent age	2,659	56.89	56.08	57.77	0.46
Respondent any school	2,659	0.31	0.30	0.31	0.77
Widow	2,659	0.45	0.44	0.46	0.52
Household size	2,659	4.53	4.55	4.50	0.81
Per capita expenditures (Kwacha)	2,659	44,052.97	42,452.05	45,785.53	0.39
Number of livestock owned	2,659	1.18	1.20	1.15	0.82

Waits for 13,000 Kwacha	2,659	0.31	0.32	0.30	0.26
Generally feel happy	2,659	0.18	0.18	0.17	0.72
Life better in 1 year	2,659	0.53	0.53	0.53	0.95
Quality-of-life scale (out of 8)	2,659	2.23	2.26	2.19	0.58
Low stress index (out of 20)	2,659	6.00	5.89	6.12	0.67
Not worried about food	2,659	0.15	0.15	0.14	0.73
Overall psychological state index	2,659	−0.00	0.01	−0.01	0.49

Notes: P values are reported from Wald tests on the equality of means of Treatment and Control for each variable. Standard errors are clustered at the village cluster level.

4.1. Attrition

Overall attrition in the SCTP over the three rounds was about 6.5%. The publicly available endline evaluation report investigates attrition by testing for similarities at baseline between (i) treatment and control groups for panel households only (differential attrition) and (ii) all households at baseline and the remaining households at follow-up (overall attrition) ( Handa et al ., 2016 ). These results show that there was no differential attrition (so balance was preserved across the two arms), but there was a small difference in the composition of households remaining in the sample over time. Panel A of Table 2 shows results from attrition analyses of the same set of seven key indicators reported earlier for the analytical sample. Column (8) of this table shows that there is no differential attrition. Panel B reports the same analysis for the seven outcomes that we measured at baseline, including the index, and confirms that there is no differential attrition for these outcomes.

Malawi Attrition Analysis of Selected Indicators at Baseline

.	Control .			Treatment .			Difference .
Attritors (1) .	Non-attritors (2) .	value (3) .	Attritors (4) .	Non-attritors (5) .	value (6) .	Col(1)–Col(4) (7) .	value (8) .

Respondent female	0.70	0.85		0.79	0.83	0.41	−0.09	0.20
Respondent age	54.50	56.30	0.58	61.19	58.17	0.42	−6.69	0.26
Respondent any school	0.35	0.32	0.66	0.30	0.34	0.64	0.05	0.66
Widow	0.42	0.41	0.83	0.50	0.44	0.48	−0.08	0.54
Household size	4.00	4.64		3.29	4.59		0.71	0.16
Per capita expenditures (Kwacha)	51,533.84	43,020.33	0.23	65,148.46	45,520.79		−13,614.6	0.17
No. of livestock owned	0.76	1.35		1.47	1.38	0.89	−0.71	0.25

Generally feel happy	0.23	0.19	0.55	0.11	0.17	0.13	0.11	0.15
Life better in 1 year	0.58	0.53	0.32	0.56	0.53	0.60	0.02	0.83
Quality-of-life scale (out of 8)	2.37	2.26	0.42	1.98	2.19	0.06	0.39	0.08
Low stress scale (out of 20) 1 = most stressed/20 = least stressed	6.62	6.00	0.23	5.57	6.16	0.15	1.05	0.21
Not worried about food	0.18	0.15	0.39	0.14	0.15	0.84	0.04	0.51
Overall psychological states index	0.13	0.01	0.25	−0.12	−0.01	0.06	0.25	0.09
Waits for 13,000 Kwacha	0.27	0.31	0.47	0.23	0.29	0.25	0.04	0.58
Observations

.	Control .			Treatment .			Difference .
Attritors (1) .	Non-attritors (2) .	value (3) .	Attritors (4) .	Non-attritors (5) .	value (6) .	Col(1)–Col(4) (7) .	value (8) .

Respondent female	0.70	0.85		0.79	0.83	0.41	−0.09	0.20
Respondent age	54.50	56.30	0.58	61.19	58.17	0.42	−6.69	0.26
Respondent any school	0.35	0.32	0.66	0.30	0.34	0.64	0.05	0.66
Widow	0.42	0.41	0.83	0.50	0.44	0.48	−0.08	0.54
Household size	4.00	4.64		3.29	4.59		0.71	0.16
Per capita expenditures (Kwacha)	51,533.84	43,020.33	0.23	65,148.46	45,520.79		−13,614.6	0.17
No. of livestock owned	0.76	1.35		1.47	1.38	0.89	−0.71	0.25

Generally feel happy	0.23	0.19	0.55	0.11	0.17	0.13	0.11	0.15
Life better in 1 year	0.58	0.53	0.32	0.56	0.53	0.60	0.02	0.83
Quality-of-life scale (out of 8)	2.37	2.26	0.42	1.98	2.19	0.06	0.39	0.08
Low stress scale (out of 20) 1 = most stressed/20 = least stressed	6.62	6.00	0.23	5.57	6.16	0.15	1.05	0.21
Not worried about food	0.18	0.15	0.39	0.14	0.15	0.84	0.04	0.51
Overall psychological states index	0.13	0.01	0.25	−0.12	−0.01	0.06	0.25	0.09
Waits for 13,000 Kwacha	0.27	0.31	0.47	0.23	0.29	0.25	0.04	0.58
Observations

Notes: Bold denotes differences that alpha = 0.05 level. P values are reported from Wald tests on the equality of means of Treatment and Control for each variable. Standard errors are clustered at the village cluster level

Equation (1) shows our basic empirical specification where |${Y}_{i\mathrm{t}}$| denotes the individual, time-specific outcome of interest and |${\beta}_1$| —the coefficient on the indicator for receiving the transfer ( T i ) in the post periods ( P t )—signifies the average effect of the cash transfer. These effects can be interpreted as causal due to the random assignment to treatment or control status. |${X}_{it}$| is a vector of controls measured at baseline including the main respondent’s age, gender and education and the stratification variable. 7 We then looked at whether the treatment effect on savings and time discounting operated through the psychological states by adding each psychological variable to the models. All standard errors are clustered at the VC level, and we also implement the wild bootstrap ( Cameron, Gelbach & Miller, 2008 ) to account for the fact that we only have 29 clusters.

5.1. Identification of the causal effect of psychological states on economic decisions

The main question we address in this paper is the effect of emotional and psychological states on economic decisions at the population level. The empirical challenge is the joint determination of psychological states and economic decisions, and since purposeful randomisation to psychological states on a large scale (outside a lab setting) is infeasible and likely to be unethical, we require a credible non-experimental approach. In this section, we present our alternative identification strategies and their associated assumptions.

We address this problem using an individual fixed-effects (FE) model, where the key assumption for the FE model to provide consistent estimates is that the joint determination of psychological states and economic decisions emanate from an individual characteristic that is fixed over time. In the FE estimation, when there is baseline information we use data from all three waves; when there is no baseline information we use the two post-treatment periods only. Note that the research question and associated identification strategy do not involve using cash transfer receipt status.

The second and potentially more important source of endogeneity stems from time-varying factors that affect both psychological states and economic decisions in the same period, denoted by u t in equation ( 2 ). The myopia displayed by the poor is typically attributed to liquidity constraints and resulting inability to borrow to overcome shocks and smooth consumption. Shocks and liquidity constraints vary across time, will affect inter-temporal choices and also affect psychological outcomes such as stress or emotion.

The fixed effect ( v i t ) is no longer in equation ( 3 ) due to the differencing, and the instrument and error term in equation ( 4 ) is from period (t−2), and no (t−2) factors enter into equation ( 3 ) ( Arellano & Bond, 1991 ). In equation ( 4 ), we exclude assignment to treatment as an instrument, since this would require that assignment to treatment at (t−2) is independent of ∆ u t , the change in the future value of the time-varying endogenous component of equation ( 3 ). Participation in the program (receiving the cash transfer) may allow households to minimise exposure to future shocks and thus reduce the variance in ∆ u t as well as its mean. In addition, we explicitly control for covariate shocks (floods, drought), which can reasonably be treated as exogenous and which are consequential in this setting. Across all waves, about two-thirds of households report experiencing a covariate shock. We also perform robustness checks by explicitly controlling for both idiosyncratic shocks and credit constraints directly in the regressions, though these are not our preferred estimates because they are plausibly endogenous.

First, we identify the average effect of treatment (the cash transfer) on individuals’ time discounting, propensity to have any cash savings and psychological indicators. For outcomes with baseline information, we estimate DD models, pooling all follow-up waves to generate an average treatment effect over the two follow-up periods. For savings, which was only collected at wave 3, we present single difference estimates only. We find that the respondents in the treatment group are 7.1 pp more likely to be willing to wait for a future payout of MWK13,000 compared to those in the control group ( Table 4 , column 2), and treatment leads to a 16-pp increase in the probability that an individual had any savings at endline ( Table 4 , column 1). Furthermore, we see highly significant treatment effects for all of the psychological variables ( Table 4 , columns 3–8). Program beneficiaries are less stressed and more optimistic about their lives currently and projected in the following year. Specifically, receipt of the transfer, on average, increases individuals’ score on the four-item PSS (where 1 is the most stressed and 20 is the least stressed) by a little over one point, increases their likelihood of not worrying about having enough food by 20 pp, increases the likelihood of generally feeling happy as well as believing life will be better in 1 year by 19 pp and increases the score on the quality-of-life scale by about half a point. We also find that treatment is highly predictive of the overall psychological state index as well. Thus, the induction of an exogenous variation in income has noted improvements in respondents’ levels of stress, affect and savings. The results on stress are particularly worth highlighting as there is no prior evidence that a national cash transfer program reduces stress. Stress is seen as an important channel through which poverty affects a wide range of health and anti-social behaviours including violence, alcohol use, suicide and weight gain ( Lupien et al ., 2001 ; Glaser & Kiecolt-Glaser, 2005 ; Peterman et al ., 2017 ).

Means or Psychological Variables by Treatment Status and Wave

.	Control .		Treatment .
Outcome .	Baseline .	Combined follow-up .	Baseline .	Combined follow-up .
Low stress index	5.89	6.62	6.12	8.08
Not worried about food	0.15	0.10	0.14	0.29
Generally feels happy	0.18	0.20	0.17	0.36
Life better in 1 year	0.53	0.55	0.53	0.75
Quality-of-life scale	2.26	2.44	2.19	2.83
Overall psychological index	0.01	−0.21	−0.01	0.23

.	Control .		Treatment .
Outcome .	Baseline .	Combined follow-up .	Baseline .	Combined follow-up .
Low stress index	5.89	6.62	6.12	8.08
Not worried about food	0.15	0.10	0.14	0.29
Generally feels happy	0.18	0.20	0.17	0.36
Life better in 1 year	0.53	0.55	0.53	0.75
Quality-of-life scale	2.26	2.44	2.19	2.83
Overall psychological index	0.01	−0.21	−0.01	0.23

Notes : 7551 observations, of which 2517 are from the baseline (2013) and 5034 are from the combined follow-up waves (2014, 2015).

Next, we looked at whether the treatment effect on savings and time discounting operates through the psychological states by adding each psychological variable to the models in columns (1) and (2) of Table 4 —these are shown in Table 5 . For savings in Panel A, the treatment effect from Table 3 diminishes slightly but is still statistically significant and large in all specifications. The largest drop occurs when the overall index is added to the regression (Panel A, column 6) where the treatment effect decreases from 16.6 to 12.1 pp, or about 27%. All the individual psychological variables have a statistically significant association with savings, with ‘never worrying about food’ producing the greatest mediation of the treatment effect as evidenced by the decrease in the estimated effect by 17% from 16.6 pp to 13.7 pp.

Effects of the Malawi SCTP on Savings, Intertemporal Choice and Psychological States

Dependent variable: .	Any savings .	Waits for 13,000 Kwacha .	Low stress index (four-item) .	Not worried about food .	Generally feels happy .	Life better in 1 year .	Quality-of-life scale .	Overall psychological state index .
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
Treatment effect	0.166 (0.03)	0.071 (0.03)	1.22 (0.54)	0.203 (0.04)	0.186 (0.04)	0.198 (0.07)	0.462 (0.11)	0.467 (0.09)
Wild bootstrap value	0.000	0.046	0.031	0.000	0.000	0.006	0.000	0.000
Estimation	Single Difference	Double Difference	Double Difference	Double Difference	Double Difference	Double Difference	Double Difference	Double Difference
Observations	2,517	7,551	7,551	7,550	7,551	7,331	7,551	7,551
R-squared	0.082	0.010	0.093	0.058	0.049	0.072	0.117	0.099
Mean of dep.var. vvar.	0.03	0.30	6.00	0.15	0.18	0.53	2.23	−0.001
-stat.	12.84	6.26	15.97	20.08	14.61	50.59	23.37	54.34

Dependent variable: .	Any savings .	Waits for 13,000 Kwacha .	Low stress index (four-item) .	Not worried about food .	Generally feels happy .	Life better in 1 year .	Quality-of-life scale .	Overall psychological state index .
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
Treatment effect	0.166 (0.03)	0.071 (0.03)	1.22 (0.54)	0.203 (0.04)	0.186 (0.04)	0.198 (0.07)	0.462 (0.11)	0.467 (0.09)
Wild bootstrap value	0.000	0.046	0.031	0.000	0.000	0.006	0.000	0.000
Estimation	Single Difference	Double Difference	Double Difference	Double Difference	Double Difference	Double Difference	Double Difference	Double Difference
Observations	2,517	7,551	7,551	7,550	7,551	7,331	7,551	7,551
R-squared	0.082	0.010	0.093	0.058	0.049	0.072	0.117	0.099
Mean of dep.var. vvar.	0.03	0.30	6.00	0.15	0.18	0.53	2.23	−0.001
-stat.	12.84	6.26	15.97	20.08	14.61	50.59	23.37	54.34

Notes: Each column represents a separate regression. All regressions control for a household experiencing a covariate shock and a set of baseline characteristics including age and schooling of the respondent, and the stratification variable. Standard errors, clustered at the village cluster level, are shown in parentheses below the coefficient. Wild bootstrapping P values for the impact coefficient (1000 reps, H 0 = 0) are shown in Row 2. Dependent variable means are averaged across Treatment and Control at baseline except for any savings which uses endline control means. *** P < 0.01, ** P < 0.05, * P < 0.1.

Results in Panel B are qualitatively similar; all psychological variables have a statistically significant direct association with time discounting, and point estimates are generally the same except for ‘not worried about food’, where the point estimate is reduced by half. We find that with the exception of stress and never worrying about food, the treatment effect is no longer significant in these estimates, indicating that the psychological variables tend to absorb the treatment effect for time discounting. As in Panel A, the largest drop in the estimated treatment effect occurs when we assess the influence of the overall psychological index (Column 12). Robustness checks show that results are consistent when controlling for idiosyncratic shocks and credit constraints, suggesting these are not additional pathways through which the cash transfer influences economic behaviours. See Appendix 3 for these estimates.

We now turn to the causal estimates of stress and affect on the economic decisions using our alternative identification strategies—this analysis is limited to time discounting because savings were only captured in wave three. The first column of Table 6 shows the FE estimates, and these are generally consistent with the results in Table 5 , with three of the five psychological indicators plus the index displaying a significant relationship with time discounting, the exception being stress and ‘not worrying about food’.

Results from the FDIV model are shown in column (2), where the reduced sample size reflects the fact that we only use the last two waves of data in the estimation since the wave 1 value is used as the instrument. The predictive power of the instrument is very strong, and the stage 1 regressions all have highly significant F statistics well above the common benchmark of 10 (complete first-stage regression results are provided in Appendix 4). In this column, only three effects are statistically significant—feeling happy, the quality-of-life scale and the overall psychological index. Point estimates are large; generally feeling happy increases the likelihood of waiting for future money by 11.2 pp, a 36% increase over the baseline mean of 62%. A one standard deviation increase in the psychological index increases the propensity to wait for a future value of MWK13,000 by 24%. Table 4 shows that receiving the cash transfer itself directly affects time discounting. As a robustness check, we limit our sample to just households in the control group in Column 3 to ensure that our results are not driven by the effect of the cash transfer on time-varying unobservables. The results in Column 3 are identical to those on the full sample. The robustness of our results to the exclusion of the transfer recipients also implies that our results are not subject to possible response bias driven by receipt of the transfer, as discussed earlier.

We noted earlier that a shortage of cash due to credit constraints is an important confounder in the relationship between psychological states and economic decisions. In Appendix 3, we have repeated all our analyses with both idiosyncratic shocks and credit constraints as additional covariates with no change in results. 8 These two variables may themselves be endogenous so we do not show them as our preferred estimates, but the fact that they do not affect the main results suggests that the estimates in Table 5 do not reflect access to credit but rather the true causal effect of the psychological variables on economic decisions.

The Effects of Psychological States on Savings and Intertemporal Choice

.					.
(1) .	(2) .	(3) .	(4) .	(5) .	(6) .
Treatment effect	0.147	0.137	0.157	0.152	0.148	0.121
	(0.026)	(0.023)	(0.028)	(0.028)	(0.027)	(0.025)
Wild bootstrap value	0.000	0.000	0.000	0.000	0.000	0.000
Low stress index (4-item)	0.011 (0.002)
Not worried about food		0.124 (0.027)
Generally feels happy			0.042 (0.013)
Life better in 1 year				0.060 (0.015)
Quality-of-life scale					0.041 (0.011)
Overall psychological state index						0.077 (0.012)
Estimation	Single difference	Single difference	Single difference	Single difference	Single difference	Single difference
Observations	2,517	2,517	2,517	2,464	2,517	2,517
R-squared	0.090	0.102	0.084	0.088	0.090	0.101

	(7)	(8)	(9)	(10)	(11)	(12)
Treatment effect	0.062	0.0591	0.052	0.053	0.033	0.026
	(0.033)	(0.033)	(0.033)	(0.032)	(0.032)	(0.03)
Wild bootstrap value	0.065	0.083	0.124	0.109	0.312	0.396
Low stress index (four-item)	0.007 (0.003)
Not worried about food		0.056 (0.018)
Generally feels happy			0.099 (0.018)
Life better in 1 year				0.098 (0.017)
Quality-of-life scale					0.081 (0.009)
Overall psychological state index						0.096 (0.012)
Estimation	Double difference	Double difference	Double difference	Double difference	Double difference	Doubled difference
Observations	7,551	7,550	7,551	7,331	7,551	7,551
R-squared	0.012	0.012	0.018	0.019	0.028	0.026

.					.
(1) .	(2) .	(3) .	(4) .	(5) .	(6) .
Treatment effect	0.147	0.137	0.157	0.152	0.148	0.121
	(0.026)	(0.023)	(0.028)	(0.028)	(0.027)	(0.025)
Wild bootstrap value	0.000	0.000	0.000	0.000	0.000	0.000
Low stress index (4-item)	0.011 (0.002)
Not worried about food		0.124 (0.027)
Generally feels happy			0.042 (0.013)
Life better in 1 year				0.060 (0.015)
Quality-of-life scale					0.041 (0.011)
Overall psychological state index						0.077 (0.012)
Estimation	Single difference	Single difference	Single difference	Single difference	Single difference	Single difference
Observations	2,517	2,517	2,517	2,464	2,517	2,517
R-squared	0.090	0.102	0.084	0.088	0.090	0.101

	(7)	(8)	(9)	(10)	(11)	(12)
Treatment effect	0.062	0.0591	0.052	0.053	0.033	0.026
	(0.033)	(0.033)	(0.033)	(0.032)	(0.032)	(0.03)
Wild bootstrap value	0.065	0.083	0.124	0.109	0.312	0.396
Low stress index (four-item)	0.007 (0.003)
Not worried about food		0.056 (0.018)
Generally feels happy			0.099 (0.018)
Life better in 1 year				0.098 (0.017)
Quality-of-life scale					0.081 (0.009)
Overall psychological state index						0.096 (0.012)
Estimation	Double difference	Double difference	Double difference	Double difference	Double difference	Doubled difference
Observations	7,551	7,550	7,551	7,331	7,551	7,551
R-squared	0.012	0.012	0.018	0.019	0.028	0.026

Notes: Each column represents a separate regression. All regressions control for whether the household experienced a covariate shock as well as a set of baseline characteristics including age and schooling of the respondent, and the stratification variable. Standard errors, clustered at the village cluster level, are shown in parentheses below the coefficient. Wild bootstrapping P values for the impact coefficient (1000 reps, H 0 = 0) are shown in Row 2. *** P < 0.01, ** P < 0.05, * P < 0.1.

The Effects of Psychological States on Intertemporal Choice: FE and FDIV Estimates

Variables .	FE .	.	Wild bootstrap value .	FDIV .	.	Wild bootstrap value .	FDIV (control only) .	.	Wild bootstrap value .
	(1)			(2)			(3)
Low stress index (four-item)	0.005 (0.003)	7,551	0.1071	0.0002 (0.007)	5,034	0.7287	−0.000 (0.010)	2,618	0.9910
Not worried about food	0.045 (0.025)	7,550	0.0941	0.021 (0.055)	5,032	0.7087	0.033 (0.083)	2,616	0.7137
Generally feels happy	0.096 (0.021)	7,551	0.0000	0.112 (0.038)	5,034	0.0050	0.095 (0.040)	2,618	0.0490
Life better in 1 year	0.088 (0.021)	7,331	0.0000	0.054 (0.032)	4,648	0.1031	0.052 (0.046)	2,387	0.2983
Quality-of-life scale	0.073 (0.009)	7,551	0.0000	0.069 (0.023)	5,034	0.0040	0.079 (0.033)	2,618	0.0480
Overall psychological state index	0.082 (0.015)	7,551	0.0000	0.074 (0.034)	5,034	0.0410	0.067 (0.049)	2,618	0.2833

Variables .	FE .	.	Wild bootstrap value .	FDIV .	.	Wild bootstrap value .	FDIV (control only) .	.	Wild bootstrap value .
	(1)			(2)			(3)
Low stress index (four-item)	0.005 (0.003)	7,551	0.1071	0.0002 (0.007)	5,034	0.7287	−0.000 (0.010)	2,618	0.9910
Not worried about food	0.045 (0.025)	7,550	0.0941	0.021 (0.055)	5,032	0.7087	0.033 (0.083)	2,616	0.7137
Generally feels happy	0.096 (0.021)	7,551	0.0000	0.112 (0.038)	5,034	0.0050	0.095 (0.040)	2,618	0.0490
Life better in 1 year	0.088 (0.021)	7,331	0.0000	0.054 (0.032)	4,648	0.1031	0.052 (0.046)	2,387	0.2983
Quality-of-life scale	0.073 (0.009)	7,551	0.0000	0.069 (0.023)	5,034	0.0040	0.079 (0.033)	2,618	0.0480
Overall psychological state index	0.082 (0.015)	7,551	0.0000	0.074 (0.034)	5,034	0.0410	0.067 (0.049)	2,618	0.2833

Notes: The outcome equals 1 if respondent waits 1 month for MWK13,000 instead of taking MWK10,000 now (and 0 otherwise). Each column and row pair present coefficients from a separate regression. Standard errors, clustered at the village cluster level, are shown below the coefficients in parentheses. The identifying instrument in the FDIV regressions is the baseline value of the variable indicated in the first column. Wild bootstrapping P values for the coefficient (1000 reps, H 0 = 0) are shown in for all regressions. Column (3) uses just the control group. *** P < 0.01, ** P < 0.05, * P < 0.1

Insights on the psychology of poverty propose a feedback loop whereby poverty leads to negative emotion and stress, which in turn influence economic behaviours, leading to sub-optimal decisions that effectively perpetuate poverty. Our results from a large sample of ultra-poor households in Malawi support this theory and are consistent with results from laboratory settings demonstrating that psychological well-being directly influences intertemporal choice ( Shah, Mullainathan & Shafir, 2012 ; Mani et al ., 2013 ; Gennetian & Shafir, 2015 ).

The Malawi SCTP, an unconditional cash transfer program, had an impact on all five measures of psychological well-being: happiness, SWB, worrying about food, quality of life and stress. Moreover, these psychological states are predictive of the decision to save money or to wait for money in the future. For example, results show that feeling happy leads to an 11.2-pp increase in waiting for a future value of MWK13,000. Similarly, a unit increase in the Quality of Life scale leads to a 6.9-pp increase in waiting for a future value of MWK13,000, a 23% increase off a mean of 30%, while a standard deviation increase in an overall psychological index increases the likelihood of waiting for a future value of MWK13,000 by 24%. Our findings also suggest that psychological states are not necessarily mediators between the cash transfer and economic decisions. After controlling for the psychological states, the direct treatment effect on time discounting dissipates, but the direct treatment effect on savings persists. Handa, Seidenfeld & Tembo (2020) report effects of a similar unconditional cash transfer administered by the Government of Zambia. In that program, the cash transfer also had a direct effect on both time discounting and SWB, but the direct treatment effect of the cash transfer persisted after controlling for SWB. Together, results from these two countries suggest that the relationship between income support programs, psychological states and economic decisions is complex. While our results support the psychology of poverty hypothesis (by showing that psychological states directly affect economic decisions), the fact that these psychological states do not necessarily mediate the effect of the cash transfer indicates that income support programs alter other features of the lives of beneficiaries that promote positive affect and reduce stress and lead to forward looking economic behaviour.

An important feature of our results is that they derive from a population of ultra-poor cash transfer beneficiaries that are similar in their demographic structure to beneficiaries in other large, national cash transfer programs across sub-Saharan Africa, such as Zambia, Mozambique, Kenya, Ghana and Liberia. For example, the typical beneficiary in the Malawi program has an average age of 58, and the majority are women as the grant is targeted towards labour-constrained households. This is similar to the percent of women beneficiaries in the Kenya Cash Transfer for Orphans & Vulnerable Children (85), the Ghana Livelihood Empowerment against Poverty Program (65), the Zambia Social Cash Transfer (75) and the Mozambique Food Security Program (56) ( Handa et al . 2012 ). 9 Other features of the target population are that just half of beneficiaries are married, the average household size is about 4.5 people and the average consumption level is less than 40 cents per person per day. Another noteworthy feature of our data is that we have multiple measures of psychological states, which is important because not all measures show significant causal effects on time discounting. There is likely to be substantial measurement error in these variables, making it important to capture the underlying concept of emotion and stress through multiple measures in a field setting. In our data, all five measures are statistically correlated with each other. The Quality of Life scale shows the strongest correlation with all other measures, suggesting it might be the preferred scale to use in field settings, as it captures both subjective well-being and life satisfaction dimensions of psychological states. However, the most promising option is to combine the distinct measures into an overall index as we have done to capture the different components of an individual’s psychological state, but this increases the length of the interview.

Research on the causal effect of psychological states on economic decisions in a field setting or at the population level is still in its infancy. Obviously, the random assignment to psychological states on a large scale is not possible. Additional evidence on causal effects could come from natural experiments or exogenous shocks that result in a change in affect or stress, provided the shock does not directly influence economic decisions around inter-temporal choice. Such events, even if they can be identified, are likely to be quite particular and/or affect a unique sub-sample of the population, making it hard to generalise to society as a whole. The strongest evidence, which addresses both internal and external validity, is likely to come from observational studies that exploit panel data techniques coupled with naturally occurring exogenous variation or randomisation in income (as we have in this study) to build a case for causality.

The precise mechanism through which stress and negative affect influence intertemporal behaviours such as saving and time discounting in a field setting is still not clear. Results from the laboratory suggest that stress may weaken cognitive function and lead to bad decisions ( Gennetian & Shafir, 2015 ). Poverty-related stress may also weaken the immune system through increased exposure to latent viral infection, which itself can impede cognitive capacity and inhibit forward-looking behaviour ( Aiello et al ., 2006 ). Negative affect can also have a direct impact on impulse control and the ability to delay gratification ( Loewenstein, 1996 ). Understanding the underlying mechanisms in a field setting remains a key issue on the research agenda. This in turn can improve the design of poverty interventions, including cash transfer programs, to address both the financial and behavioural consequences of poverty that lead to poverty traps. This study provides promising evidence that if programs can relieve stress, worry and negative affect, they may also alter economic decision-making towards more future-oriented and safeguarding behaviours.

Supplementary material is available at Journal of African Economies online.

The Operations Manual of the SCTP defines ultra-poor as a household that is unable to meet the most basic urgent needs, including food and essential non-food items such as soap and clothing, while labour constrained refers to a household with a dependency ratio (ratio of ‘fit to work’ to ‘not fit to work’) of more than three or with no individuals who are fit to work. An individual who is considered not fit to work is someone under the age of 18, over the age of 64 or within the age range 18 to 64 but suffering from a chronic illness or disability or is otherwise unable to work ( Handa et al ., 2014 ).

Survey instruments were reviewed for ethical considerations and approved by the UNC-CH Institutional Review Board and Malawi’s National Commission for Science and Technology, National Committee for Research in Social Sciences and Humanities (UNC IRB Study No. 12-2496; Malawi NCST Study No. RTT/2/20).

Control households were not aware they were receiving the transfer at a later date. The study team additionally checked for anticipation effects in the control group at endline right before those households were scheduled to start receiving payments and found no effects.

Table A.1 in Appendix 1 presents the treatment effect of the cash transfer on all future values in our survey instruments and several other constructed time discounting measures. We find large, statistically significant effects of receipt of the cash transfer on all future values except the largest (MWK40,000). In general we expect, and find, that the cash transfer induces waiting at lower future values.

Of the full 10-item Cohen’s PSS, only four items were included in all three waves of the Malawi SCTP survey. Even though all 10 items were administered in both follow-up rounds, we only use the 4-item scale for study so as to compare the same items over time.

To build the index we first convert each individual indicator to a wave specific z -score, then take the average of the five z -scores.

Our results are robust to the exclusion of these control variables, but we keep them in our models to increase the precision of our estimates.

Credit constraints are measured through a sequence of questions that ask whether the household borrowed money or received items on credit, and if not, whether they could have borrowed if they wanted to. For those who did borrow, we asked whether they would have liked to borrow more at the same price.

The average age of beneficiaries in these four major programs is also similar to the Malawi program. The average age of recipients is 61, 53, 59 and 67 years, respectively, in Ghana, Kenya, Zambia and Mozambique. This information is taken from Handa et al . (2012) and publicly available evaluation reports at the website https://transfer.cpc.unc.edu/ .

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In the courtyard where Hersh Goldberg-Polin danced on Oct. 6, grief and anger reign after his death

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Shira Ben-Sasson, a founder of the Hakhel synagogue in Jerusalem, lights a candle in memory of Hersh Goldberg-Polin, Sept. 1, 2024. (Deborah Danan)

By Deborah Danan September 1, 2024

( JTA ) — JERUSALEM — Three hundred and thirty-two days after Hersh Goldberg-Polin danced in the courtyard next to his Jerusalem synagogue on the holiday of Simchat Torah, more than a thousand people gathered there in grief and prayer to mourn his murder by Hamas terrorists in Gaza.

During the Sunday night vigil, the courtyard railings were lined with oversized yellow ribbons to symbolize advocacy for the hostages, Hapoel Jerusalem soccer flags — the 23-year-old’s favorite team — and posters that read, “We love you, stay strong, survive,” a mantra coined by his mother, Rachel Goldberg-Polin.

Just hours earlier, one of the posters had been hanging over the balcony of the home of Shira Ben-Sasson, a leader of Hakhel, the Goldberg-Polins’ egalitarian congregation in the Baka neighborhood of Jerusalem.

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“We were sure we would take it down when he came home,” Ben Sasson said.

The community wanted to unite while respecting the Goldberg-Polins’ desire for privacy, she said, prompting them to organize the prayer gathering.

“But it’s like a Band-Aid or giving first aid, it’s what you do in an emergency. I don’t know how we go on after this,” she said.

She added that the community, which has a large contingent of English-speaking immigrants, was not prepared for the High Holidays, which begin in about a month. She said, “Seeing his empty seat is hard.”

For Ben-Sasson, who wore a T-shirt bearing the Talmudic dictum “There is no greater mitzvah than the redeeming of captives,” the tragedy is especially painful because, she said, it could have been avoided with a ceasefire agreement that freed hostages.

“Hersh was alive 48 hours ago. We think a deal could have saved him. There is no military solution to this,” she said.

That feeling of bereavement, often mixed with betrayal, pervaded gatherings across Israel on Sunday, as the country struggled with the news that six hostages who may have been freed in an agreement were now dead as negotiations continue to stall. Speakers at protests in Tel Aviv blamed Israeli Prime Minister Benjamin Netanyahu, who himself apologized for not getting the hostages out alive but blamed Hamas for obstructing a deal. The country’s labor union, the Histadrut, has called a national strike on Monday to demand a deal.

Some at the Jerusalem gathering, including the relative of another former hostage, said Netanyahu had chosen defeating Hamas over freeing the captives.

Josef Avi Yair Engel, whose grandson Ofir was released from Hamas captivity in November during that month’s ceasefire deal, expressed shock over Hersh’s murder but said he was not surprised, given the wartime policies of Netanyahu’s government.

“We knew months ago this was going to happen. Bibi’s formula, to dismantle Hamas and return the hostages, wasn’t logical. It’s an either/or situation,” Engel said, referring to Netanyahu by his nickname. “He’s tearing the country apart. I’m afraid that in the coming months there won’t be a state at all.”

Engel said he felt a close bond with Hersh’s father Jon Polin, not only because of their joint activism in the hostage families’ tent outside the Prime Minister’s Residence, but also because of their shared identity as Jerusalemites.

“There aren’t many of us in the hostage circle,” he said. “We’re like family.”

Sarah Mann, who did not know the family personally, said the weekend’s tragedy reminded her of Oct. 7.

“This day has sparks of the seventh, which created numbness and an inability to talk. Just complete shock,” she said.

Part of the reason for that, Mann said, was Rachel, who she described as a “force of faith.” Goldberg-Polin’s mother emerged as the most prominent advocate for the hostages globally and became a symbol in her own right as she crisscrossed the world calling for her son’s freedom.

“Millions of people around the world held onto her. Once that was cut, people’s ability to hold onto faith was knocked out today. But even though this has shattered us, we need to keep holding onto God,” Mann said.

For Susi Döring Preston, the day called to mind was not Oct. 7 but Yom Kippur, and its communal solemnity.

She said she usually steers clear of similar war-related events because they are too overwhelming for her.

“Before I avoided stuff like this because I guess I still had hope. But now is the time to just give in to needing to be around people because you can’t hold your own self up any more,” she said, tears rolling down her face. “You need to feel the humanity and hang onto that.”

Like so many others, Döring Preston paid tribute to the Goldberg-Polins’ tireless activism. “They needed everyone else’s strength but we drew so much strength from them and their efforts, “she said. “You felt it could change the outcome. But war is more evil than good. I think that’s the crushing thing. You can do everything right, but the outcome is still devastating.”

Guy Gordon, a member of Hakhel who moved to Israel from Dublin, Ireland, in the mid-1990s, said the efforts towards ensuring Hersh’s safe return have been an anchor for the community during the war.

“It gave us something to hope for, and pray for and to demonstrate for,” he said. “We had no choice but to be unreasonably optimistic. Tragically it transpired that he survived until the very end.”

Gordon, like many others in the crowd, wore a piece of duct tape marked with the number of days since Oct. 7 — a gesture initiated by Goldberg-Polin’s mother. Unlike on previous days, though, his tape also featured a broken red heart beside the number.

Nadia Levene, a family friend, also reflected on the improbability of Hersh’s survival.

“He did exactly what his parents begged him to do. He was strong. He did survive. And look what happened,” Levene said.

She hailed Rachel Goldberg-Polin’s “unwavering strength and belief in God,” adding, “There were times I lost faith. I suppose I was angry with God. But she just kept inspiring us all to pray, pray, pray.”

Jerusalem resident Leah Silver rejected politicizing the hostages’ deaths.

“Everything turns political so quickly. I came here because I felt that before all the protests, we need to just mourn for a moment and to pray. And show respect for each other,” she said. “We’ve become confused about who the enemy is. It’s very sad.”

But not everyone at the gathering joined in to sing Israel’s national anthem at the closing of the prayer gathering.

“I’m sorry, I can’t sing ‘Hatikvah,’” Reza Green, a Baka resident who did not know the Goldberg-Polins personally, said. “I’m too angry. We shouldn’t be here.”

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A protester holds a poster with a photo of 23-year-old U.S.-Israeli Hersh Goldberg-Polin as people gather with signs calling for the release of hostages held by Hamas since Oct. 7, during a rally in Tel Aviv Oct. 28.

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COMMENTS

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We should extend the conversation about tackling poverty, but that conversation should not be governed by the belief that poverty in resources is synonymous with poverty of values.
Poverty really is the result of a state of mind
Recently, Housing and Urban Development Secretary Ben Carson said that poverty is a state of mind, and having the right mind-set will let people escape poverty. He was both right and wrong.
PDF Poverty Is Just a State of Mind
Poverty Is Just a State of Mind American dominant culture understands poverty as a defect of character, not a result of a structurally unjust economic system. People who are poor are not poor because they lack money. They are poor because, in America's dominant culture, there is something wrong with them emotionally, morally, subculturally, or behavior-ally. People in poverty in the United ...
Causes And Effects Of Poverty: [Essay Example], 736 words
Understanding the causes and effects of poverty is crucial in developing effective strategies to combat it. This essay delves into the intricate causes and far-reaching effects of poverty, highlighting the interconnectedness of various factors that perpetuate this global issue.
Why poverty is not a personal choice, but a reflection of society
Just a few weeks ago, Housing Secretary Ben Carson called poverty "a state of mind." At the same time, his budget to help low-income households could be cut by more than US$6 billion next year. This is an example of a simplistic view toward the complex social phenomenon.
Argumentative Paper: Poverty in The United States
Poverty in the United States is a pervasive issue that continues to impact millions of individuals and families across the country. Despite being one of the wealthiest nations in the world, a significant portion of the population struggles to make ends meet, facing challenges such as inadequate access to education, healthcare, and affordable housing. This essay will explore the root causes of ...
Poverty Is A State Of Mind
The essay focuses on Hare's past, from when he grew up poor in Leeds to adult whose angry and bitter, to eventually letting go of his anger and "spirit of poverty ". The theme in the text is poverty and Hare is trying to emphasize that poverty is a state of mind, by telling about his own past. The essay is written from the authors point ...
Poverty Is A State Of Mind Essay
Poverty is defined as the state of being unable to fulfill basic needs of human beings. Poverty is the lack of resources leading to physical deprivation. Poor people are unable to fulfill basic survival needs such as food, clothing, shelter. These are the needs of lowest order and assume top priority.
Poverty Is A State Of Mind Essay
The central problem with Hare's essay and his statements, that poverty is only a state of mind, is that it is psychological. Poverty is big part of humanity, and being physically poor means that your possibilities are restricted. Those people who are stuck in poverty and can't get out, it becomes difficult to reflect on the riches such as ...
Poverty Is Just a State of Mind
People in poverty in the United States are largely viewed as individually responsible for their own economic circumstances, and they must be punished in this view (see Ryan 1976 and Schneider 1999 for representative takes on the issue). This appallingly cruel perspective has a long history in the United States despite its patent falsity, going ...
PDF A Rolling Perspective: Poverty Is A State Of Mind
A Rolling Perspective: Poverty Is A State Of Mind | CPD Blog. During a conversation with Kim, the Costco/Ameriprise lady who was helping me save money, I shared that I was writing a book, The Art of Poverty. "Poverty is a state of mind," I said. She agreed and added: "You may be broke, but you're never poor.".
Does 'Wrong Mind-Set' Cause Poverty or Vice Versa?
The HUD secretary Ben Carson said that the "wrong mind-set" leads to poverty. But research suggests cause and effect go the opposite way.
Poverty Is a State of Mind
Many people lives in poverty. An example of a man who lived in poverty is Bernard Hare in the text "Poverty is a state of mind " from 2012. The main claim in the text "Poverty is a state of mind" is "Poverty is a state of mind" (l. 320). The ground is "As far as I was concerned, we had warmth, love, shelter, enough to eat ...
A Rolling Perspective: Poverty Is A State Of Mind
During a conversation with Kim, the Costco/Ameriprise lady who was helping me save money, I shared that I was writing a book, The Art of Poverty. "Poverty is a state of mind," I said. She agreed and added: "You may be broke, but you're never poor.". Wise words. But how to stop feeling poor when even able-bodied people feel that way ...
Ben Carson Says Poverty Is A 'State of Mind" : NPR
People with the "right mind set" can pull themselves up, Carson said. Many conservatives and the Trump administration say cuts to government benefits could incentivize people to find work.
Bernard Hare's Personal Odyssey and the Complexity Within Free Essay
In conclusion, Bernard Hare's exploration of poverty challenges the simplistic notion of it being merely a state of mind. His life journey becomes a powerful illustration of the intricate interplay between personal choices, external circumstances, and societal factors in shaping one's economic status.
Housing Secretary Ben Carson Clarifies Comment That Poverty Is A 'State
Housing and Urban Development Secretary Ben Carson is standing by his controversial comment that poverty is a "state of mind," but he says that "how a person thinks" is only one component that ...
Psychology of Poverty: Evidence from the Field
1. Introduction Standard economic explanations of shortsightedness displayed by individuals living in poverty include liquidity constraints and the urgency to meet immediate needs. The consequences of this myopia and their related behaviours help explain the persistence of poverty among individuals over time and across generations. However, insights from the psychology of poverty could further ...
Poverty is a State of Mind: English Cases Free Essay Example
The central problem with Hare's essay and his statements, that poverty is only a state of mind, is that it is psychological. Poverty is big part of humanity, and being physically poor means that your possibilities are restricted.
In the courtyard where Hersh Goldberg-Polin danced on Oct. 6, grief and
JERUSALEM — Three hundred and thirty-two days after Hersh Goldberg-Polin danced in the courtyard next to his Jerusalem synagogue on the holiday of Simchat Torah, more than a thousand people ...

Why poverty is not a personal choice, but a reflection of society

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Why poverty is not a personal choice, but a reflection of society

Social structure

Poverty: Not just a state of mind

American independence

Views shaped by politics

Why calling the poor ‘lazy’ is victim blaming

Argumentative Paper: Poverty in The United States

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