Kim, Y. ., Zou, L., Weon, S.Y., & Sherraden, M. (2016). Asset-Based Policy in South Korea (CSD Publication No. No.15-48). Center for Social Development, Washington University in St. Louis.
Please see the link below:
posts and ripostes on poverty and development
Kim, Y. ., Zou, L., Weon, S.Y., & Sherraden, M. (2016). Asset-Based Policy in South Korea (CSD Publication No. No.15-48). Center for Social Development, Washington University in St. Louis.
Please see the link below:
I’ve developed a new way to visualize the results from one of our analyses from the perceived financial capability paper. In the previous post, I plotted the standardized score on the y axis and age groups across the x axis. Then perceived financial capability (a.k.a. subjective knowledge) and objective knowledge are plotted as separate lines. As an alternative we position the scores on x and y axes and plot the age groups as factors in the graph. The resulting display implies a correlation indicated with a 45-degree line. The deviation from the straight line – above or below – indicates the extent of over estimation and under estimation of financial knowledge by age group. By showing distance from the straight line we see clearly that individuals over 60 yrs of age overestimate their financial knowledge. I think the plot roughly meets the criteria established by Tufte (2001). I am curious what others think about the pros and cons of these two graphical displays.
Tufte, E. (2001). The visual display of quantitative information (2nd ed.). Cheshire, CT: Graphics press.
There is a growing interest in understanding the psychological and cognitive components that affect financial decisions. With factor analysis we produce a single measure of perceived financial capability from five items in the 2009 Canadian Survey of Financial Capability (N = 15,519). After adjusting the measure for the influence of income, we find through bivariate analysis and multiple regression that younger individuals and females have low levels of perceived financial capability. Results indicate that perceived financial capability is conceptually distinct from objective financial knowledge. Approximately 65% of the correlation between perceived financial capability and financial knowledge was unexplained by the covariates. This Figure shows how financial capability and financial knowledge scores (both standardized) vary across the life cycle. Between ages 25 and 55 there is a pattern of under-estimation. After age 60 people tend to overestimate their ability to manage finances. Understanding perceived financial capability is but one component of the broader concept of comprehensive financial capability that also includes objective knowledge and the opportunity to act.
by David W. Rothwell and Yunju Nam
The most common method of economic poverty measurement requires defining of a minimal level of basic needs and economic resources. Economic poverty can be measured using income, consumption or wealth; subjective or objective criteria; multiple or single dimensions; and, from relative and absolute perspectives. In advanced economies, the predominate method for understanding economic poverty relies on annual household income as an indicator of command over resources. There are disagreements over methods to understand income poverty (e.g., see the Institute for Research on Poverty’s overview here). The U.S. poverty line is an absolute measure. Relative measures are used for international comparison.
In the 1980s and early 1990s scholars began challenging the reliance on income to understand household well-being. They argued that saving and asset accumulation function as more than stored income to be used for future consumption (seminal works by Oliver and Shapiro; Sherraden). According to Sherraden, when people accumulate assets, they think and behave differently; and the world responds to them differently. Assets function not as a flow but as a stock and are more permanent. Following these ideas, economic deprivation, i.e., poverty, can be measured using assets instead of income. Studies of asset poverty complement and contrast our understanding of the poverty condition.
Economists Robert Haveman and Edward Wolff considered a household or person asset poor if their access to wealth-type resources is insufficient to meet basic needs for some predefined period of time. Wealth-type resources usually involves financial assets or net worth; basic needs can be approximated with the income poverty threshold; and, period of time has usually been set at three months. Therefore, a person or household is considered asset poor if their asset resources fall below one-fourth of the official income poverty line. Concretely, assuming the annual income poverty threshold for a family of four is $32,000, the household would be considered asset poor if owned assets were less than $8,000.
Recently, we estimated the first known asset poverty measures in Canada using the 1999 and 2005 Survey of Financial Security. We produced asset poverty rates based on (1) both financial assets and net worth, (2) the Canadian Low Income Cutoff as the threshold of basic needs and (3) three months as the period time. In the paper we reported the national asset poverty rates to be 53% based on financial assets and 34% based on net worth. Below we highlight key findings and contextualize them with US asset poverty findings.
Asset poverty is closely related to age. Figure 1 shows how the rate of financial asset poverty decreases with age. The line represents the rate of asset poverty across the life course. The shaded area reveals the uncertainty around the given asset poverty estimate. It is well known that younger people have struggled in the recovery from the Recession. This finding suggests a need for social policy targetted at younger households.
When the joint distribution of poverty based on income and assets is considered we were able to identify three sub-populations: (1) 14% of households were joint income and asset poor, (2) 3% of households were income poor but asset non-poor, and (3) 40% of households were income non-poor but asset poor. The third group reveals that a large segment of the Canadian population has sufficient income to be non-poor but lacks access to assets to survive for three months at the low income threshold. Future policy efforts will play a role in reducing or reinforcing this economic vulnerability.
Differences in measurements and survey design make cross-country comparisons difficult. (For example, using 2001 data, Haveman and Wolff reported that 25% of U.S. households were poor based on net worth compared to the Canadian estimate of 34%. Using financial assets, the disparity was greater: 53% in Canada compared to 38% in the U.S.) It is better to examine systematic cross-country data. Brandolini and colleagues used data from the Luxembourg Wealth Study (years 1999-2002) to compare the asset poverty rates in several OECD countries. Using 50 percent of the median income as the income threshold, they reported that Canada had the highest financial asset poverty rates at 56.5 followed by the US (52.6).
It is perhaps more useful to examine over representation among the asset poor. The most recent CFED scorecard, showed the 2011 liquid asset poverty in the US was 43.5% and these rates were analyzed separately based on race and family structure. The rate of white households compared to households of color was 34.7 to 60.6. The rate of asset poverty among single parent households is nearly double that of 2 parent households (1.94). The analysis showed that 17% of Americans are in extreme asset poverty, i.e., they have negative or zero net worth. In the Canadian study, we decomposed asset poverty rates to understand over-representation. We created a disproportionate index where 1 is perfectly representative of the population rate.
|Variable||Population||Asset poor||Disproportionate index|
|Female lone parents||3.91||6.01||1.54|
|Age under 25||6.26||9.65||1.54|
Although not perfectly comparable with the CFED and Haveman results (e.g., race and ethnicity is not measured in the Canadian survey), there are some parallels between Canada and the U.S. Asset poverty is disproportionately experienced by female single parents, younger people, and renters.
Our recent study reinforces the importance of asset poverty measurement to understand dimensions of poverty and economic vulnerability that go unnoticed when using an income based measure of poverty.
Importantly, the method of asset poverty measurement used in the U.S. and Canadian studies assumes that households need a certain amount of asset to meet consumption needs at the poverty threshold. In addition to asset poverty measures described above, new and more comprehensive asset-based economic well-being measures have been recently developed in the United States. These measures incorporate ‘asset for development’ perspective in that they recognize assets’ roles in promoting long-term economic development as well as assets’ roles in protecting families from unexpected economic emergencies (Nam, Huang, & Sherraden, 2008). For example, the Asset Security and Opportunity Index produced by the Institute on Assets and Social Policy at Brandies University includes asset opportunity as well asset security. The asset security index measures economic stability and a type of precautionary savings. While asset security is similar to asset poverty (i.e., assets needed for the period of unemployment), asset opportunity is a fundamentally different concept: it is based on the amount of economic resources needed for a family’s investment for the future (i.e. assets for college education, homeownership, and business start-up). Using this concept, over 50% of U.S. households have insufficient assets to promote social development (Shapiro, Oliver, and Meschede 2009).
In addition to precautionary savings for the time of unemployment, the US Department of Commerce (2010) highlighted the importance of two asset measures: savings for college education and retirement. College savings amounts are estimated from zero to $6,800 per year depending on family type and income while retirement savings is assessed as 1.2% to 3.3% of annual family income (U.S. Department of Commerce, 2010). The most comprehensive asset measure is included in a new framework called the Basic Economic Security Table (BEST): precautionary, retirement, homeownership and college education (McMahon, Nam, & Lee, 2011). Using the BEST, we estimated that monthly savings required to meet all four saving needs ranged from $155 to $572 depending on family size and conditions.
Brandolini, A., Magri, S., & Smeeding, T. M. (2010). Asset-based measurement of poverty. Journal of Policy Analysis and Management, 29(2), 267-284. doi:10.1002/pam.20491
1) Logistic regression and causality (look at page 316 of Hilgert and Hogarth, 2003).
2) Important idea to look at: “hierarchy” of financial practices. Hilgert and Hogarth discuss a hierarchy that goes from cash flow management, to credit, to savings, to investment. Buckland et al., in their literature review, discuss Lusardi’s concept of “basic” versus “advanced” literacies – she says that people with low income do not need advanced literacy. How does this inform policy/interventions for low income people? (This is more of a rhetorical question – an idea that we can return to later on).
3) Look at concept of statistical significance.
Independent Study Project, Financial behaviour among Canadians.
Simpson & Buckland: Examining evidence of financial and credit exclusion in Canada from 1999 to 2005
Am struggling to understand the method they developed: what, for example, is probit regression? The model used seems to have been developed by Jappelli (is also used in the Lalime & Michaud article) and used the life cycle as model of consumption. See article for formula used.
Lalime & Michaud: Litteratie financiere et preparation a la retraite au Quebec et dans le reste du Canada. Financial literacy and preparing for retirement, a comparison between QC and the ROC.
Methods (Questions): also using the life cycle model of consumption and Jappelli’s model. Shows how financial literacy and savings habits depend on the same fundamental elements…which are?
The model is developed to show financial literacy and savings are dependant on revenue. How? I have no idea. See page 7 for the formula.
Page 8: Indicates that investment in retirement increases with revenue, but goes down with increased financial literacy. This seem counterintuitive to me.
Refers to two periods of revenue/savings that are unclear to me.
*Didn’t quite understand if the variables measured to try to explain the difference in QC were then the reason, in the end, or if they were ‘measured out’. Other variables measured:
-Socio economic status
-Fewer people finishing post secondary
-Lower levels of family income
-Highest level of immigrants in Canada (different education systems?)
*In the conclusion, I still want to ask why…
I’ve recently come across innovative interventions in different contexts to address poverty. The title of the first paper is quite descriptive Labor Market Returns to Early Childhood Stimulation: a 20-year Followup to an Experimental Intervention in Jamaica. Overall, the authors find large positive effects from experimental conditions. From the abstract:
We find large effects on the earnings of participants from a randomized intervention that gave psychosocial stimulation to stunted Jamaican toddlers living in poverty. The intervention consisted of one-hour weekly visits from community Jamaican health workers over a 2-year period that taught parenting skills and encouraged mothers to interact and play with their children in ways that would develop their children’s cognitive and personality skills. We re-interviewed the study participants 20 years after the intervention. Stimulation increased the average earnings of participants by 42 percent. Treatment group earnings caught up to the earnings of a matched non-stunted comparison group. These findings show that psychosocial stimulation early in childhood in disadvantaged settings can have substantial effects on labor market outcomes and reduce later life inequality.
And a second family-level intervention focusing on childhood stimulation recently won a $5 million dollar grant from Bloomberg Philanthropies. The excellent Emily Badger reported it here Can We Disrupt Poverty by Changing How Poor Parents Talk to Their Kids?
Apparently the idea proposes a way to measure the quality and quantity of parent-child interaction. From the article:
The device, a 2-ounce specialized recorder about the size of a deck of cards, maps the intensity of communication between parents and children. The infants and toddlers in Providence Talks will wear it twice a month, tucked into a custom-made vest, for 12 to 16 hours at a time. The recorder then plugs into a computer, where software automatically converts the audio files into charts that can be used by Meeting Street to coach the parents on how and when they might speak to their children more often.
The Globe and Mail has created the Wealth Paradox series to educate Canadians about the enormous impact of income inequality in our nation today. The piece is extremely readable and filled with edifying examples of how inequality is negatively affecting Canadians’ access to education, health care, and even recreation. Further, it looks at solutions. While the simplicity and directness of the series may be criticized by some who expect more nuance in such discussions, I believe that its strength lies in its accessibility (to those who can afford to subscribe to the Globe and Mail, but that’s a conversation for another time). This is something that we need to be talking about.
In the course of the last couple weeks I’ve presented findings on asset poverty in Canada. The findings usually evoke a number of responses. One of the most troubling is that asset building policy caused the foreclosure housing crisis in the US. Most recently, on day 2 of the 2013 ABLE, Calgary Mayor Naheed Nenshi said (paraphrasing):
We need to be introspective and self-critical. We have interventions that don’t work. The home and foreclosure crisis showed us the limitations of home ownership and asset building for low income families.
The mayor is absolutely correct about the need to be self-critical. Only through understanding our failures can we develop more effective interventions to reduce financial exclusion and vulnerability. A major problem is that our failures are rarely documented and published. Understanding what goes wrong is probably more important than understanding our successes. (see the excellent Admitting Failure site). Few would disagree with this part of his speech. However, we also need to get the facts correct about the extent to which asset building policies influenced the foreclosure and housing crisis in the US. Consider the following points.
1. To date asset building policies have not reached massive scale in the US. There is no single asset building policy that could cause the scale of the foreclosure crisis (12.5 million foreclosure starts from 2007 to 2012) .
2. Little innovation in mortgage markets was observed in the 2000s and government policy toward the mortgage market did not change much in the 1990s and 2000s. The major mortgage innovations happened in the 1990s and the major government asset building policies of Federal Housing Administration and GI Bill expansions occured in the post-war era 1940’s and 50’s. (See Atlanta Federal Reserve Working Paper)
3. Research has shown that Individual Development Account (IDA) homebuyers were much less likely to experience foreclosure (1/2 to 1/3 lower) than a comparison group of low-income homeowners constructed from government data gathered via the Home Mortgage Disclosure Act. Over a period of 1999 – 2007 3.1% of IDA homes in the sample entered foreclosure compared to 6 – 9% for the comparison group. Importantly, only .2% of IDA homeowners secured subprime loans compared to 10% in the comparison group. Additionally, IDA homeowners were much less likely to have high interest rates.
4. Evidence from an experimental design longitudinal IDA study[gated] (1999 to 2009) showed that home ownership rates for the treatment and control group both increased through the Recession. If asset building policy has provided incentives for otherwise unqualified people to buy homes then we would have seen different ownership trends in the treatment group and not the control group. This did not happen.
5. From the same study the IDA program had no statistically significant effect on likelihood that a homeowner was late on a mortgage payment or went into foreclosure.
Overall, it’s dangerous and counter-factual to blame asset building policy for the home foreclosure crisis. The evidence suggests far more expansive and complex social and economic forces were at play.
It’s another year of discussions of poverty in SWRK 626 and so that means it’s time to (again) discuss the merits and drawbacks of the Gauranteed Annual Income or sometimes called Basic Income Guarantee. This year the topic came up when we started discussing possible anti-poverty interventions. Student K. Heyde mentioned the following article in the Globe and Mail. It reminded me of last year’s class when we debated the subject in-depth. I am realizing more and more that when a topic keeps appearing it’s time to write blog post.
This summer at the IRP I asked the question to Tim Smeeding. We went back and forth and he sent me a few resources (see below) and put me in touch with a graduate student working on a similar topic.
The most relevant to the Canadian context is a report Possibilities and Prospects: The Debate over a Gauranteed Income from the Canadian Center for Policy Alternatives (h/t David Calnitsky). The report succinctly describes the three main concerns with the GAI: (1) work disincentives, (2) reciprocity, (3) and cost.
The idea of unconditional cash transfers has garnered considerable attention lately.
Anne Blumenthal picked up on the NPR story that I previously posted about here. On Anne’s post, she links to the study “Cash Transfers and Child Schooling: Evidence from a Randomized Evaluation of the Role of Conditionality”. Development economist Chris Blattman has also been writing on the subject of giving cash to the poor.
In a previous post on this blog, I raised the two concerns about cost and political feasibility. I still have those concerns. In class, I argued that the GAI represents a radical shift in the conceptualization of the welfare state. Not to mention, the idea would put a lot of social workers out of job. I suspect McKnight would favor such a proposal because it would eliminate the iatrogenic social welfare system. Lots to digest here and touching on many of the key elements of social intervention (conditionality, costs, efficiency, implementation, tradeoffs, etc). Surely more to follow on this subject.
02 December update:
CBC the current ran a story (Switzerland considers a mandatory basic minimum income for everyone) this morning on their Project Money project. The story features the 1970s Canada min-come study from Manitoba.
Nicholas-James Clavet, Jean-Yves Duclos, Guy Lacroix (2013) Fighting Poverty: Assessing the Eﬀect of a Guaranteed
Minimum Income Proposal in Québec.
Steensland, B. (2008). The failed welfare revolution: America’s struggle over guaranteed income policy. Princeton University Press.
Anqi Zhang piece in the McGill Daily (2014). Enough money to survive
Hanushek, E. A. 1987. “Non-Labor-Supply Responses to the Income Maintenance Experiments.” In Lessons
from the Income Maintenance Experiments, ed. A. Munnell. Boston:Federal Reserve Bank of Boston.
Burtless, G. 1987. “The Work Response to a Guaranteed Income: A Survey of Experimental Evidence.” In
Lessons from the Income Maintenance Experiments, ed. A. Munnell. Boston: Federal Reserve Bank of Boston
Ben-Shalom, Y., Moffit, R., & Scholz, J.K. (forthcoming). As assessment of the effectiveness of anti-poverty
programs in the United States. In Oxford Handbook of Economics of Poverty, P. Jefferson, ed. New York:
Oxford University Press. Currently available as NBER working paper No. w17042, available at: http://www.nber.org/papers/w17042.
Moffitt, R. A. (2003). The Negative Income Tax and the Evolution of U.S. Welfare Policy. The Journal of
Economic Perspectives, 17 (3), 119-140.