Applying Big Data Solutions to Big Social Problems

| Posted: May 6th, 2013

Los Angeles has now synchronized all 4,500 traffic signals across the city’s 469 square miles. It’s the first major city worldwide to achieve this feat, using magnetic sensors at every intersection; cameras; and a central computer system that monitors cars, buses, bicycles, and pedestrians. These innovations have increased the average speed of traffic by 16 percent and reduced delays at major intersections by 12 percent. Coupled with other initiatives that alert drivers to congestion, synchronization has brought an estimated annual savings in fuel and time of $1.3 billion.

Can we not apply the same “big data” solutions to major social policy problems?

One opportunity may be found in the Supplemental Nutrition Assistance Program (SNAP), formerly the Food Stamp Program, which serves about 47 million individuals per month, providing about $75 billion annually in nutritional support. Program participants redeem their benefits at authorized retailers using an electronic benefit transfer (EBT) card. Can the data generated by participants through card swipes be used to help serve these households better?

Many participants continue to have unmet nutritional needs; about one-quarter of SNAP households still experience very low food security, coping with their constrained resources by eating less and/or relying on lower quality foods. Can we better target such households for other forms of assistance—in particular, other federal benefits for which they may already qualify? Can real-time data be used to provide early warning signals of household distress?

A recent USDA study involving in-depth interviews with 90 SNAP participants in Boston, Houston, Indianapolis, and Riverside said: “One of the most striking observations in the current research is how many households fail to budget money with which to buy food during the time at the ‘end of the month’ when SNAP benefits typically run out.” Indeed, the absence of a plan for stretching resources to the next month—or for accessing additional resources from families, friends, or other networks—was a distinguishing feature among those who were food insecure.

Here’s an idea that builds on USDA’s current use of EBT transaction data nationally to analyze SNAP benefit redemption patterns. Such data could be used to identify SNAP households that redeem more than 90 percent of their monthly benefit within the first week (as 20 percent do nationally) or those who exhaust their benefit within the first week (as 17 percent do nationally). These households very likely will have a hard time affording food at the end of the month. But that impending hardship could be alleviated by ensuring that these households receive other benefits that they qualify for (such as Medicaid, Supplemental Security Income, or the Earned Income Tax Credit) or that they get priority in receiving discretionary program support (such as energy assistance or child care subsidies).

This kind of targeted outreach would require information systems that can capture EBT transactions data in real time and can generate early warning signals to the appropriate program office with adequate protection of client privacy.

It may seem fanciful, but if Los Angeles can synchronize the city’s traffic signals, is it that far-fetched for Los Angeles County—with more than one million SNAP participants among its residents—to institute such an early warning system?

Grocery Store image from Shutterstock

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Let the Borrower Beware: Facing the Facts about Payday Loans and Pawnshops

| Posted: March 11th, 2013

Photo by Flickr user Eddie~S, used under a Creative Commons License (cc-by-sa 2.0)

Payday loans are making headlines again.

A new study by the Pew Charitable Trusts mentions the plight of payday borrowers whose repayments lead to checking account overdrafts and a compounding of fees and charges. A New York Times article has noted that major banks have played a role in the growth of internet payday lending by enabling lenders to make automatic withdrawals from borrowers’ accounts. Bank of America, Wells Fargo, and JP Morgan Chase are among those involved, reaping overdraft charges even in states where payday lending is banned and even after borrowers—wanting to repay their loans to avoid an automatic rollover—have requested that withdrawals be stopped.

While payday loans are a particularly egregious form of predatory lending, with APRs exceeding 500 percent, they’re not the most widely used form of nonbank credit. That distinction falls to pawnshop loans. According to FDIC’s June 2011 survey, 3.5 million U.S. households used pawnshop loans within the past 12 months. In comparison, an estimated 2.1 million households took out payday loans. The number of American households that have ever used a pawnshop loan is 9.0 million, compared with 5.6 million for payday loans. Both of these numbers are increasing by about 15–20 percent annually.

Payday lenders have increasingly shifted their marketing to web-based products, as states have imposed outright bans and other restrictions. Although this has boosted the growth in payday lending, the take-up of these loans is limited by the requirement that borrowers be employed and have a bank account.

In contrast, even the unbanked (those without bank accounts) can use pawnshop loans for small-dollar credit. These are short-term loans for which property items such as jewelry or home electronics equipment serve as collateral. The loan term is usually one month and the amount normally less than $100. The customer who repays the loan (including interest and fees) reclaims their pawned item. Those unable to repay must forfeit their item, which the pawnbroker can then sell. The customer also has the option of renewing the loan.

Storefront pawnbrokers have been popularized by television series such as “Pawn Stars” and “Hardcore Pawn.” As with payday lending, pawnshop loans are increasingly transacted through the internet, including through eBay.

What we’re learning from recent surveys of nonbank credit users is that these consumers engage in the serial, myopic use of multiple credit sources—all too often, in a stressed-out search to meet recurring basic spending needs, not isolated emergency expenses. This is the picture that emerges from No Slack: The Financial Lives of Low-Income Americans (by Michael Barr, based on the 938 interviews conducted under the 2005–2006 Detroit Area Household Financial Services study) and A Complex Portrait: An Examination of Small-Dollar Credit Consumers (by Rob Levy and Joshua Sledge, based on 1,112 interviews conducted nationally in 2012).

In thinking about the policy and regulatory issues of the alternative financial services sector, we should focus not on any particular type of loan product, but on the array of credit sources tapped by consumers as they try to avert hardship while unable to borrow in the financial mainstream. Their credit sources include not only pawnshop loans, payday loans, and account overcharges, but also auto title loans, tax refund anticipation loans, and rent-to-own contracts. These sources tend to be used interchangeably in a de facto, high-risk portfolio choice, motivated by perceptions of financial cost that are often ill-informed. These poor decisions have lasting consequences through damaged credit scores. Among the many reasons for the slowness of our recovery from the Great Recession may be the increasing reliance on high-cost, high-risk, nonbank borrowing, with its adverse effects on the near-term creditworthiness of low- and middle-income working families.

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Tax-Time Savings Initiatives: Rethinking Program Design

| Posted: February 6th, 2013

As we plunge headlong into tax filing season, let’s pause to reflect on tax-time savings initiatives—a major focus of asset-building efforts over the past decade. Through a growing number of innovative programs, low-income tax filers are encouraged to save part of their lump-sum tax refund, which they derive primarily from the earned income tax credit (EITC).

New York City’s SaveNYC pilot program offers a 50 percent match on refund dollars if the money is held in a savings account for a full 12 months. The program has been expanded to more Volunteer Income Tax Assistance sites throughout the city and has now been adopted in Newark, Tulsa, and San Antonio, under the name SaveUSA. The nonprofit organization Doorways to Dreams Fund just launched a nationwide SaveYourRefund Sweepstakes, offering cash prizes to those using IRS Form 8888 to commit their refund dollars to US savings bonds or other savings products.

As with any concerted effort to encourage workers to save, we should ask: Do these programs generate new savings? Or do they largely reward participants for doing what they would have done anyhow?

We’ll be better able to answer these questions after MDRC’s evaluation of SaveUSA underway in New York and Tulsa. In the interim, insightful evidence comes from a study by Kathryn Edin at Harvard University and Ruby Mendenhall at the University of Illinois about how low-income families use their EITC refunds. Edin and Mendenhall’s team conducted 194 in-depth interviews in Boston and Champaign-Urbana in 2007. Fully two-thirds (67 percent) used their refund to pay off back debt or overdue bills. More than one-third (39 percent) initially saved a portion of their refund, but only 21 percent still retained some of that savings after six months. Other uses included car-related expenses (27 percent) and home-related expenses (8 percent). Virtually all households used at least some of their refund for current spending needs.

What’s striking about this evidence is how many of these low-income families used their tax refund to pay down debt. We should not be surprised if the upcoming SaveUSA impact study shows that participants hold more in savings but also face higher debt (than those not in the program), with little or no effect on net worth (in other words, no net increase in savings).

We should also ask: How do we want low-income tax filers to use their refunds? For purchasing assets, for emergency spending needs, for paying off debt, or for some combination of these? Tax-time programs are explicitly structured for asset building. The 12-month SaveUSA rule or the encouraged use of savings bond products makes it difficult to access funds for emergency expenses or for squaring one’s balance sheet. This seems needlessly restrictive. The upward mobility of low-income households rests on their ability to buffer themselves against financial shocks, avoid high-cost borrowing, and maintain their creditworthiness. Unless program rules are relaxed, tax-time savings initiatives will tend to benefit those with incomes at the upper end of the qualifying range, not those whose economic security is most at risk.

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Urban-Rural Trends in SNAP Participation: What's Going On?

| Posted: January 7th, 2013

The average monthly number of recipients in the Supplemental Nutrition Assistance Program (SNAP, formerly food stamps) reached 46.6 million, or about one in every six Americans, in FY 2012, according to the most recent USDA data. The weak economy was principally responsible, as the 2007-2009 downturn and slow recovery increased the pool of eligible recipients from an average of 38.9 million a month in 2007 to 50.7 million a month in 2010. At the same time, the program’s participation rate—the percentage of eligibles receiving benefits—went up from 65.8 percent to 75.2 percent. (The basic pattern here is more noteworthy than the specific estimates, given some recent changes in USDA’s method of calculating participation rates.)

Underlying these numbers is a little-noticed trend: a large and growing gap between the participation rates for urban and rural Americans. Individuals living in urban areas participate at lower rates: in 2010, they had a participation rate of 72.9 percent versus 85.6 percent for those in rural areas. This differential—now, more than 12 percentage points—has grown in recent years. It was less than 5 percentage points during 2003 and 2004. Going back to 1997 and earlier, eligibles in urban areas actually participated at higher rates than eligibles in rural areas. In 1995, for instance, the urban participation rate was 77.8 percent, compared with a rural rate of 65.5 percent.

What’s going on here? Three possible explanations deserve attention: benefit size, ease of program access, and preferences about receiving public benefits.

First, if urban cases tend now to receive smaller benefits, relative to rural cases, we might expect households in urban areas to be less likely to participate. The available data back to 1997 don’t support this, however. The average benefit for urban cases has consistently been slightly higher than rural cases—proportionally, by 2 to 7 percent—since 1997, without any discernible shift in this pattern.

Second, if access to SNAP benefits has become relatively easier for rural cases than for urban cases, we might expect the observed flip-flop in participation rates. Indeed, the availability of online, mail-in, or phone-in options for program application and renewal have likely benefitted rural cases more than urban cases. Prior to such administrative improvements, people in rural areas needed to travel greater distances to visit a local welfare office than people in cities did. One would not expect, however, these developments by themselves to raise rural participation rates above urban rates. We need to look further.

Third, if people living in urban areas have become less inclined to receive public benefits, it would support the urban-rural trend in SNAP participation rates. This indeed appears to be a contributing factor, reflecting the shifting racial-ethnic composition of the urban poor. Specifically, Hispanic households now represent a much larger percentage of urban households with incomes below 200 percent of the poverty level. Studies of both SNAP and Medicaid indicate lower rates of participation among eligible Hispanics.

This latter explanation has implications for future growth in SNAP caseloads. Against the backdrop of an improving economy, which will bring down the number of people eligible for the program, the long-term upward trend in program participation rates is likely to be moderated by a continued urban-rural imbalance in SNAP participation rates.

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Taking a Closer Look at the Census Poverty Numbers: Trends Among Hispanics

| Posted: September 20th, 2012

One bright spot in the Census Bureau’s recent poverty report was the significant reduction in the poverty rate for Hispanics, down from 26.5 percent in 2010 to 25.3 percent in 2011. Despite this progress, the 2011 Hispanic poverty rate still far exceeded the overall U.S. rate of 15.0 percent.

The decline in the Hispanic poverty rate appears related to substantial year-over-year growth in the number of Hispanic workers employed year-round and full time. Fully 40 percent of Hispanics 15 and older were employed 50 or more weeks during 2011 at 35 or more hours a week, just slightly below the national average. Nonetheless, low wages have stifled income growth for Hispanic households. Their inflation-adjusted median income actually dropped slightly between 2010 and 2011 to $38,624, remaining well below its peak of $43,319 in 2000. Over the past 40 years, household incomes among Hispanics have declined relative to those of non-Hispanic whites. The ratio of median income between the two groups fell from 0.74 to 0.70 between 1972 and 2011.

Underlying these national trends for Hispanics are substantial geographic differences in their economic circumstances. Hispanic households in the South are faring better than elsewhere, contributing in part to the significant 2010–2011 drop in the poverty rate for that region. Hispanics in the West (including the Mountain and Far West states) have not fared as well.   Indicative of this is that New Mexico, the state with the highest share of Hispanic residents (46.3 percent), now has the nation’s highest poverty rate (22.2 percent).

Against this backdrop, the Urban Institute has recently undertaken a study that will shed light on the dynamics of income and wealth for low-income workers in two major southwestern cities with large Hispanic populations: Albuquerque and Los Angeles. Under contract to the U.S. Department of Health and Human Services, we have selected program sites in these cities for an evaluation of the impact of individual development accounts (IDAs), matched savings accounts that encourage low-income individuals to save for homeownership, small business development, or postsecondary education. A combined sample of 1,100 low-income households, all with incomes below 200 percent of the poverty level and more than half expected to be Hispanic, will be randomly assigned to equal-sized treatment and control groups. Treatment cases will be allowed to enter a local IDA program funded federally under the Assets for Independence Act; the control cases will serve as a benchmark for comparison. Program impacts will be measured for outcomes related to saving, asset ownership, and hardship avoidance.

In light of the recent Census report, this upcoming evaluation will develop important further evidence on the factors influencing the economic mobility of low-income households, with a particular focus on the Hispanic population and the impact of programs to promote saving, asset ownership, and self-investment.

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Potential Effects of the Affordable Care Act on SNAP Participation

| Posted: August 22nd, 2012

As states decide whether to adopt the Medicaid expansions now allowed—but not required—under the Affordable Care Act, it is useful to consider the potential consequences of these choices beyond the immediate sphere of health insurance. One likely result is greater participation in the Supplemental Nutrition Assistance Program (SNAP, formerly the Food Stamp Program) among low-income adults who are nonelderly and nondisabled.

Recent Urban Institute analysis indicates that nationally 15.1 million such adults lack health insurance but could become covered under Medicaid if all states adopt the expanded income eligibility limit of 138 percent of the federal poverty level. These adults are typically young (52 percent are under 35), male (53 percent), and without children in the household (82 percent).

Virtually all adults in this group are currently eligible for SNAP based on their income, but nearly half do not receive SNAP. In 2009 the SNAP participation rate was only 56 percent among SNAP-eligible, 19-to-49-year-old, able-bodied adults without dependents. This suggests that approximately 7 million of these 15.1 million uninsured adults are not taking advantage of nutritional support they are entitled to receive. Important to states, these benefits are fully federally funded.

The avenue through which these adults may come to receive both Medicaid and SNAP is the increasing cross-program coordination states have implemented in their application procedures. As of 2010, 40 states had integrated their eligibility and intake processes between Medicaid and SNAP.

To see the potential increases in SNAP participation, let’s look at states that (a) have more than 500,000 uninsured adults with incomes below 138 percent of FPL, (b) appear open to a Medicaid expansion, and (c) have integrated their Medicaid and SNAP application procedures. We find six such states: California, Georgia, Illinois, Michigan, Ohio, and Pennsylvania. Collectively they account for 4.7 million of the estimated 15.1 million adults who might become newly Medicaid-eligible. If one assumes that 56 percent already receive SNAP, approximately 2 million adults in these states will become new SNAP participants.

At a time when recession-related growth in the SNAP caseload has drawn criticism, we should look favorably upon this increased take-up of nutritional assistance among working-age adults. This income support, in combination with newly acquired health insurance, will measurably improve low-income workers’ chances to achieve greater stability in their economic lives.

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Providing Affordable Credit to Underbanked Consumers

| Posted: June 27th, 2012

The availability of small-dollar credit to low- and moderate-income (LMI) households was a major focus of the 7th Annual Underbanked Forum, hosted on June 13-15 by the Center for Financial Services Innovation (CFSI). Small-dollar credit refers to consumer loans under $2,500 (and are typically less than $500). The forum’s discussions highlighted two opposing business models for offering small dollar credit—one focused primarily on profit and one focused on customers.

The first model, normally associated with “alternative financial services” providers (payday lenders, pawnshops, rent-to-own stores, etc.) but also distressingly evident among mainstream institutions, is to extract fees and charges from LMI consumers who have difficulty managing credit. Intentional choices in product design and targeting stack the deck against borrowers, making timely repayment an unlikely prospect and resulting in lender profits. A prominent example is Internet payday lending, the most rapidly growing segment of the small-dollar credit market. Recent CFSI survey data indicate that fully 40 percent of borrowers do not make timely repayment on “very short” term loans—products with repayment periods of one month or less, such as payday loans, pawn loans, and deposit advance loans (taken out against an upcoming direct deposit to one’s bank account).

A contrasting model works off the premise that loan products can be designed to enable repayment and thus avoid the debilitating cycle of loan rollover and borrower dependency. With such products, repayment is rewarded, as the borrower’s record of payment is reported to credit agencies. Structural safeguards prevent misuse, and loan terms are transparent to the borrower. Lender risk is reduced to an extent that APRs of 36 percent or lower—less than one-tenth the effective rates for payday loans—become viable. These innovative products are offered by firms such as Tandem Money, ZestCash, BillFloat, Lending Club, and Progreso Financiero. The Tandem Money product, for example, is a creatively structured line of credit, with the loan amount conditioned on a borrower using their own savings to meet a portion of their financial need.

The emergence of this customer-focused small-dollar credit paradigm is an important market development, given the large number of newly underbanked consumers. Most underbanked households (81 percent) can be found in metropolitan areas. A legacy of the Great Recession has been the number of previously banked consumers who ended up making late payments or defaulting on loans, bringing down their credit scores and shutting them out of mainstream credit products. Many of these consumers are creditworthy, as evidenced by a recent Equifax analysis showing that more than one-quarter of the underbanked consistently make on-time bill payments. Add in their consistent payment history on utility and rent bills and 18 percent of those conventionally regarded as high risk are reclassified into a lower-risk category. Many of these consumers spend less than they earn every month, but they are vulnerable to unexpected financial shocks, such as car repairs or medical expenses.

Whether the consumer-empowering business model can make headway against its predatory counterpart remains to be seen. One encouraging sign is the extent to which mobile technology may enable the emerging lenders to reduce their marketing, underwriting, and servicing costs. Equifax has found that, among the underbanked, 29 percent have used mobile banking in the past year for deposits, payments, remittances, and other fund transfers. As evidenced by the growth of Internet payday loans, however, technology is also increasingly exploited by predatory lenders. A key question is whether innovative customer-centered product development in this market can keep pace.

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Can the Poor Save? Yes, But...

| Posted: May 22nd, 2012

A recent two-day conference in Washington, DC, celebrated the 21st anniversary of Michael Sherraden’s Assets and the Poor, which first proposed individual development accounts (IDAs, savings accounts offering match funds for specified uses) and other asset-based antipoverty strategies. The Assets@21 convening brought together policy researchers and advocates to assess progress and look ahead.

A mixed story emerged. Yes, there have been legislative victories (the Assets for Independence Act, providing federal grant funding for state and local IDA projects) and behaviorally informed innovations (such as the IRS’s Form 8888, enabling low-income tax filers to precommit a portion of their federal tax refund to the purchase of US savings bonds). But research to date has yielded limited supportive evidence—enough to sustain asset­-building as a field of policy development, but not enough to convince skeptics. And efforts to further advance asset-building are now more difficult in an increasingly partisan, deficit-constrained environment.

The question posed by Sherraden and others two decades ago was, “Can the poor save?” The answer depends on how poor a target population one has in mind. Those with annual incomes chronically below the poverty level have little capacity to save, as their incomes never rise enough to provide the necessary budget slack. Fortunately, among those who become income-poor, only a small fraction remains so chronically. An analysis of 1968-89 data from the Panel Study of Income Dynamics concluded that only 5 percent of those who enter a poverty spell then remain chronically poor throughout the ensuring ten years.  The typical experience is episodic poverty, with 30 percent never having another below-poverty year within the ten-year horizon and another 26 percent experiencing poverty again in only one or two of the following years. For the episodically poor, the opportunity to save comes when they have above-poverty income. If they manage to avoid major emergencies, the savings accumulated in their less-poor years can offset their dissaving (asset drawdown) in other years.

So the poor can save, as long as they are not always poor. Asset-building programs use this dynamic by extending their income eligibility thresholds (measured at program intake) to 150 or 200 percent of the poverty level. The favorable evidence on homeownership among IDA participants (including a randomized control trial under an early Tulsa program) suggests that program effects are concentrated among those in the higher ranges of income eligibility. Only a subset (30 to 40 percent) of IDA participants makes any matched withdrawals. This tends to be the near-poor, in keeping with the notion that a consistent savings habit is possible only during times when a household’s annual income exceeds the poverty level.

Asset-building programs should thus be viewed not as approaches to lift people out of chronic poverty, but as ways to promote upward mobility for the episodically poor and to prevent the near-poor from falling back into poverty. The latter role for asset-building—to provide emergency savings as protection against unplanned spending needs or income drops, and to avoid the high cost of credit from predatory lenders—was prominently mentioned at the Assets@21 meeting. Assets are thus important for both self-investment and self-insurance: for both offense and defense.

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Helping Low-Income Families Save: Lessons from Tax-Time Savings Accounts

| Posted: April 20th, 2012

With the tax season now over, it’s a good time to point out that tax-time matched savings programs are among the more promising approaches to boost low-income savings. In these programs, tax filers are encouraged to deposit some of their tax refund—primarily from the earned income tax credit (EITC)—into a savings account. Those deposits are then supplemented with match funds. One successful example is New York City’s $aveNYC Program, run through participating Volunteer Income Tax Assistance (VITA) sites. The program pays a 50 percent match on amounts up to $1,000 held in a $aveNYC account for a full year. In 2008-2009, the initial years of the program, 79 percent of participants received match funds. Of these accountholders, 71 percent re-upped the following year.

A just-released report by UNC-Chapel Hill’s Center for Community Capital provides insights on low-income savings behavior based on in-depth interviews with 48 $aveNYC participants—mostly African-American and Hispanic women between 25 and 50 years old. Consistent with other research, the study highlights the fact that children provide the strongest motivation for low-income workers to save because of the obligation to meet kids’ basic living needs, the instinct to serve as a role model for them, and the desire to provide them a better environment for growing up. To be realized, these impulses to save must be combined with confidence in one’s ability to save and a sense of trust in the financial institutions that hold one’s savings. And low-income households often lack that confidence and trust.

The basic message from this recent research—and the emerging body of work in behavioral economics—is that savings interventions need to nurture the intention to save and also make the act of saving easier. Whether someone is able to save (given that they can afford to) depends on a complex tug-of-war between their current impulses and their future plans. Savings tools such as precommitment, default-in/opt-out decision framing, and envelope budgeting are ways to enable our better selves to prevail.

Community-based savings collaboratives, such as savings circles where people pool their savings, have had some success helping the very poor save in developing countries. Is there a scalable way to do something similar in urban America? Can the motivational influence of one’s children be more effectively harnessed?

One possible untested approach is setting up a virtual savers’ club comprised of parents whose children share the same birthday. Parents could create a savings account on their child’s behalf and set a savings goal to be reached by the child’s next birthday. Members would receive periodic savings reminders and could compare their progress with the progress of other club members. This kind of self-induced competition has worked in energy conservation initiatives.

As with $aveNYC, the financial incentive to save could be strengthened by match funds—in this case, funds directed to a child’s account through donations from other family members or friends (or even a noncustodial parent). If this virtual savers’ club were widely marketed, other people who share the same birthday might be interested in making charitable donations of match funds to a child’s account.

In each of these cases, the necessary focus for savings interventions is clear: nurture the intention to save and enable the act of saving.

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To Save or Spend: Meeting the Short-Term and Long-Term Consumption Needs of U.S. Households

| Posted: March 16th, 2012

Two just-published reports provide useful insights on patterns of household saving in the United States. The analyses highlight the policy dilemma that comes during and after recessions. As American consumers, we tend to save more than we should during recessionary periods, when more spending would stimulate economic expansion. We then tend to fall back into myopic spending habits, when more saving would promote the economy’s long-run growth potential and help provide for our own long-term needs.

Amidst the statistical avalanche of the 2012 Economic Report of the President are the most recent numbers on personal saving (as a percent of disposable personal income) before, during, and after the Great Recession. From a pre-recession level of 2.4 percent in 2007, the saving rate more than doubled to above 5 percent in 2008–2010, exceeding 6 percent in some quarters during the recession. This reflects the collective reaction to the enormous drop in household wealth that was a result of plunging stock market values and housing prices. The total wealth decline was the equivalent of 1.8 years of income for the average household, the steepest drop since such data were first collected in the early 1950s.

During 2011 the saving rate then fell to below 4 percent as pent-up demand for consumer durables (especially cars) buoyed consumption. This has been welcome news for the economic recovery, but it suggests a return to a historical path of not saving, a matter of concern for our long-term economic health.

Barry Bosworth of the Brookings Institution focuses on this long-run horizon in his book The Decline in Saving. As Bosworth points out, our personal saving rate has declined over the past three decades. From an average of 7.7 percent in the 1970s, it dropped to 7.2 percent in the 1980s, 4.7 percent in the 1990s, and then 2.4 percent during 2000–2007. As explanations for this decline, Bosworth points to easier credit availability and financial innovations that enabled households to extract equity from homes and other assets, fueling a more consumption-oriented economy. He notes that Canada is an instructive comparison, observing that “the mortgage market innovations that led to the growth of the subprime mortgage market in the United States were largely absent from Canada.”

Whether American households under-save or over-save is a complex question from a macroeconomic perspective; it hinges importantly on the level of saving or dis-saving in the corporate and public sectors.  The evidence suggesting a return to long-term trends of under-saving in the household sector is discomforting, with discernible risks apparent as one moves down the income distribution. Do households have sufficient assets to weather financial emergencies, to withstand national economic downturns, and to meet their retirement needs? If upcoming data show continued low rates of personal saving, in a world where low interest rates do little to encourage thrift, we should heighten our focus on savings initiatives, especially targeted to low- and middle-income consumers, to break the pattern of saving too little.

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