Scarcity: Why Having Too Little Means So Much (32 page)

148
The ingredients of poverty create circumstances that are particularly hostile
:
For another original and highly engaging perspective on some ingredients behind poverty and its persistence, see Charles Karelis,
The Persistence of Poverty: Why the Economics of the Well-Off Can’t Help the Poor
(New Haven: Yale University Press, 2009).

150
285 million people worldwide
:
International Diabetes Federation,
Atlas.
http://www.diabetesatlas.org/content/some-285-million-peopleworldwide-will-live-diabetes-2010
.

151
take their medication only 50 to 75 percent of the time
:
This wide range of estimates is because adherence rates depend on the population under study. How adherence is measured—such as self-reports, drug refill rates, electronic monitoring—also affects the measure. As a starting point, see Eduardo Sabaté, ed.,
Adherence to Long-Term Therapies: Evidence for Action
(Geneva: World
Health Organization, 2003). This book also contains adherence data for a wide variety of diseases.

152
more than 28 percent of total yield
:
December 15, 2009. The benefits of weeding for any one farmer may be hard to generalize from these studies, which rely on model plots or on cross-sectional data. A careful randomized control trial of the benefits to farmers of weeding would be particularly useful in this area. For the current estimates in Africa, see L. P. Gianessi et al., “Solving Africa’s Weed Problem: Increasing Crop Production and Improving the Lives of Women,”
Proceedings of “Agriculture: Africa’s ‘engine for growth’—Plant Science and Biotechnology Hold the Key,” Rothamsted Research, Harpenden, UK, October 12–14, 2009
(Association of Applied Biologists, 2009).

152
up to 50 percent of total rice output
:
See D. E. Johnson, “Weed Management in Small Holder Rice Production in the Tropics,”
Natural Resources Institute, University of Greenwich Ghatham, Kent, UK
11 (1996), retrieved from
http://ipmworld.umn.edu/chapters/johnson.htm
.

152
harsher with their kids
:
J. Lexmond, L. Bazalgette, and J. Margo,
The Home Front
(London: Demos, 2011).

152
They are more likely to take out their own anger on the child
:
An early study is J. Garbarino, “A Preliminary Study of Some Ecological Correlates of Child Abuse: The Impact of Socioeconomic Stress on Mothers,”
Child Development
(1976): 178–85. A more recent study using larger data is in Christina Paxson and Jane Waldfogel, “Work, Welfare, and Child Maltreatment,”
Journal of Labor Economics
20, no. 3 (July 2002): 435–74.

153
they fail to engage with their children in substantive ways
:
J. S. Lee and N. K. Bowen, “Parent Involvement, Cultural Capital, and the Achievement Gap Among Elementary School Children,”
American Educational Research Journal
43, no. 2 (2006): 193–218.

153
they will have the kid watch television rather than read to her
:
A. T. Clarke and B. Kurtz-Costes, “Television Viewing, Educational Quality of the Home Environment, and School Readiness,”
Journal of Educational Research
(1997): 279–85.

153
The poor in the United States are more obese
:
A. Drewnowski and S. E. Specter, “Poverty and Obesity: The Role of Energy Density
and Energy Costs,”
The American Journal of Clinical Nutrition
79, no. 1 (2004): 6–16.

153
the poor are less likely to send their children to school
:
R. Tabberer, “Childhood Poverty and School Attainment, Causal Effect and Impact on Lifetime Inequality,” in
Persistent Poverty and Lifetime Inequality: The Evidence—Proceedings from a Workshop Held at HM Treasury, Chaired by Professor John Hills, Director of the ESRC Research Centre for Analysis of Social Exclusion
(1998).

153
The poor are less likely to get their children vaccinated
:
N. Adler, J. Stewart, S. Cohen, M. Cullen, A. D. Roux, W. Dow, and D. Williams, “Reaching for a Healthier Life: Facts on Socioeconomic Status and Health in the U.S.,”
The John D. and Catherine T. MacArthur Foundation Research Network on Socioeconomic Status and Health
43 (2007).

153
least likely to wash their hands
:
The correlation between income and hand washing or water treatment has been observed in many places. In Peru, one study looked at behavior of mothers or others taking care of children. It found that only 46 percent of caregivers washed their hands after using the toilet. Even within the data, there was a strong correlation with income: 56.5 percent of people in the top income quartile washed their hands after using the toilet whereas only 34 percent of the bottom quartile did. They reported similar differences for hand washing after cleaning children’s bottoms or prior to feeding children. See Sebastian Galiani and Alexandra Orsola-Vidal, “Scaling Up Handwashing Behavior,” Global Scaling Up Handwashing Project, Water and Sanitation Program (Washington, D.C., 2010).

153
less likely to eat properly or engage in prenatal care
:
Adler et al., “Reaching for a Healthier Life.”

154
a video of a young girl, Hannah, taking a test
:
John M. Darley and Paget H. Gross, “A Hypothesis-Confirming Bias in Labeling Effects,”
Journal of Personality and Social Psychology
44, no. 1 (1983): 20–33.

155
air traffic controllers
:
R. L. Repetti, “Short-Term and Long-Term Processes Linking Job Stressors to Father–Child Interaction,”
Social Development
3, no. 1 (2006): 1–15.

157
most likely to be acting out
:
L. A. Gennetian, G. Duncan, V. Knox,
W. Vargas, E. Clark-Kauffman, and A. S. London, “How Welfare Policies Affect Adolescents’ School Outcomes: A Synthesis of Evidence from Experimental Studies,”
Journal of Research on Adolescence
14, no. 4 (2004): 399–423.

159
smokers with financial stress
:
M. Siahpush, H. H. Yong, R. Borland, J. L. Reid, and D. Hammond, “Smokers with Financial Stress Are More Likely to Want to Quit but Less Likely to Try or Succeed: Findings from the International Tobacco Control (ITC) Four Country Survey,”
Addiction
104, no. 8 (2009): 1382–90.

159
rates of extreme obesity and diabetes dropped
:
Jens Ludwig, et al. “Neighborhoods, Obesity, and Diabetes—A Randomized Social Experiment,”
New England Journal of Medicine
365, no. 16 (2011): 1509–19.

159
thirty-eight good sleepers were instructed to go to sleep
:
R. T. Gross and T. D. Borkovec, “Effects of a Cognitive Intrusion Manipulation on the Sleep-Onset Latency of Good Sleepers,”
Behavior Therapy
13, no. 1 (1982): 112–16.

160
more likely to be worriers
:
F. N. Watts, K. Coyle, and M. P. East, “The Contribution of Worry to Insomnia,”
British Journal of Clinical Psychology
33 no. 2 (2011): 211–20.

160
they sleep less well and get fewer hours
:
J. T. Cacioppo, L. C. Hawkley, G. G. Berntson, J. M. Ernst, A. C. Gibbs, R. Stickgold, and J. A. Hobson, “Do Lonely Days Invade the Nights? Potential Social Modulation of Sleep Efficiency,”
Psychological Science
13, no. 4 (2002): 384–87.

160
lower-quality sleep
:
N. P. Patel, M. A. Grandner, D. Xie, C. C. Branas, and N. Gooneratne, “Sleep Disparity in the Population: Poor Sleep Quality Is Strongly Associated with Poverty and Ethnicity,”
BMC Public Health
10 (2010): 475–75.

160
can lead soldiers to fire on their own troops
:
G. Belenky, T. J. Balkin, D. P. Redmond, H. C. Sing, M. L. Thomas, D. R. Thorne, and N. J. Wesensten, “Sustaining Performance During Continuous Operations: The U.S. Army’s Sleep Management System,” in
Managing Fatigue in Transportation. Proceedings of the 3rd Fatigue in Transportation Conference
(1998).

160
The oil tanker
Exxon Valdez
:
See Alaska Oil Spill Commission,
Spill: The Wreck of the Exxon Valdez
, vol. 3 (State of Alaska, 1990). An approachable discussion of the sleep literature as a
whole can be found in William C. Dement and Christopher Vaughan,
The Promise of Sleep: A Pioneer in Sleep Medicine Explores the Vital Connection Between Health, Happiness, and a Good Night’s Sleep
(New York: Dell, 1999).

160
comparable to going without sleep for two nights in a row
:
See Hans PA van Dongen et al., “The Cumulative Cost of Additional Wakefulness: Dose-Response Effects on Neurobehavioral Functions and Sleep Physiology from Chronic Sleep Restriction and Total Sleep Deprivation,”
SLEEP
26, no. 2 (2003): 117–29. A nice overview of the literature on chronic sleep deprivation can be found in D. F. Dinges, N. L. Rogers, and M. D. Baynard, “Chronic Sleep Deprivation,”
Principles and Practice of Sleep Medicine
4 (2005): 67–76.

160
when income rises, so, too, does cognitive capacity
:
A growing literature has in fact argued that early childhood experience can affect brain development. See, most recently for example, Clancy Blair et al., “Salivary Cortisol Mediates Effects of Poverty and Parenting on Executive Functions in Early Childhood,”
Childhood Development
82, no. 6 (November/December 2011): 1970–84. Our results suggest that in addition to these kinds of effects, there is still a very large direct effect of poverty on cognitive function even in later life.

167
the recurrence of “wheels-up” crashes
:
A. Chapanis, “Psychology and the Instrument Panel,”
Scientific American
188 (1953): 74–82.

168
Low-income training programs in the United States
:
A nice collection of papers on training programs in the United States illustrates these challenges: Burt S. Barnow and Christopher T. King, eds.,
Improving the Odds: Increasing the Effectiveness of Publicly Funded Training
(Washington, D.C.: Urban Institute Press, 2000).

168
loans are used to pay off other debts
:
Two recent impact evaluations of microfinance illustrate the potential problems quantitatively: Dean Karlan and Jonathan Zinman, “Microcredit in Theory and Practice: Using Randomized Credit Scoring for Impact Evaluation,”
Science
332, no. 6035 (2011): 1278–84;
Abhijit Banerjee et al., “The Miracle of Microfinance? Evidence from a Randomized Evaluation” (MIT working paper, 2010).

171
do not undo hard work
:
Some of this argument can be made without resort to the psychology of scarcity. Much of policy design makes the presumption of rationality. Simply allowing for people to have natural psychological limitations already can improve policy making. This view has recently been wonderfully articulated by Richard H. Thaler and Cass R. Sunstein,
Nudge: Improving Decisions about Health, Wealth, and Happiness
(New Haven, Conn.: Yale University Press, 2008). See also Eldar Shafir, ed.,
The Behavioral Foundations of Public Policy
(Princeton, N.J.: Princeton University Press, 2012). We have previously used this logic to argue that we can better understand poverty just by understanding that the poor can have the same psychological quirks that affect everyone else: Marianne Bertrand, Sendhil Mullainathan, and Eldar Shafir, “A Behavioral-Economics View of Poverty,”
American Economic Review
(2004): 419–23. By compromising bandwidth, scarcity magnifies and expands on these arguments. Psychologically insightful policy is particularly important in the context of poverty.

172
for a total of five years over her lifetime
:
D. Ellwood and R. Haskins,
A Look Back at Welfare Reform
,
IPRNews
(Winter 2008), retrieved from
http://www.ipr.northwestern.edu/publications/newsletter/iprn0801/dppl.html
.

172
one study in rural Rajasthan, India
:
A. Cappelen, O. Mæstad, and B. Tungodden, “Demand for Childhood Vaccination—Insights from Behavioral Economics,” in
Forum for Development Studies
37, no. 3 (November 2010): 349–64.

173
depends on the good behaviors she exhibits
:
L. B. Rawlings and G. M. Rubio, “Evaluating the Impact of Conditional Cash Transfer Programs,”
The World Bank Research Observer
20, no. 1 (2005): 29–55.

174
a microfinance institution in the Dominican Republic called ADOPEM
:
A. Drexler, G. Fischer, and A. Schoar,
Keeping It Simple: Financial Literacy and Rules of Thumb
(London: Centre for Economic Policy Research, 2010).

178
the high demand for loans that averaged less than $10
:
See
Emergency Hand Loan: A Product Design Case Study
, Financial Access
Initiative, ideas42 and IFC. Discussion and document at
http://www.financialaccess.org/blog/2011/05/product-design-poor-emergency-hand-loan
.

179
One cash transfer program in Malawi
:
S. Baird, J. De Hoop, and B. Ozler, “Income Shocks and Adolescent Mental Health,”
World Bank Policy Research Working Paper Series
, no. 5644 (2011).

180
bound to return to it again and again
:
The return rates to welfare programs in the United States have been studied extensively. For example, see J. Cao, “Welfare Recipiency and Welfare Recidivism: An Analysis of the NLSY Data,”
Institute for Research on Poverty Discussion Papers
1081–96, University of Wisconsin Institute for Research on Poverty (March 1996).