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November 9, 2020
The Importance of Digital Payments to Financial Inclusion
Editor's note: In December, macroblog will become part of the Atlanta Fed's Policy Hub publication.
A recent Atlanta Fed white paper titled "Shifting the Focus: Digital Payments and the Path to Financial Inclusion" calls for a concerted effort to bring underbanked consumers into the digital payments economy. The paper—by Atlanta Fed president Raphael Bostic, payments experts Shari Bower and Jessica Washington, and economists Oz Shy and Larry Wall—acknowledges the importance of longstanding efforts to bring the full range of banking services to unbanked and underbanked consumers. (For another take on the white paper and its relationship to the Atlanta Fed's mission, you can read here.) However, the white paper observes, progress towards this goal has been slow. It further notes the growing importance of digital payments for a wide variety of economic activities. It concludes by highlighting a number of potential policies that could expand inclusion in the digital payments economy for policymakers to consider.
The 2017 Federal Deposit Insurance Corporation (FDIC) National Survey of Unbanked and Underbanked Households found that 6.5 percent of U.S. households are unbanked and an additional 18.7 percent underbanked. In this survey, a household is considered underbanked if it has a bank account but has obtained some financial services from higher-cost alternative service providers such as payday lenders. The proportions are even higher in some minority communities, with an unbanked rate for Black households at 16.9 percent. These figures were down modestly from earlier FDIC surveys, but progress remains inadequate.
The white paper retains full inclusion as the ultimate goal but argues we should not let the difficulties of achieving full inclusion deter us from moving aggressively to spread the benefits of digital payments. Such digital payments in the United States are typically made using (or funded by) a debit or credit card. Yet a recent paper by Oz Shy (one of the coauthors of this post) finds that over 4.8 percent of adults in a recent survey lack access to either card. Moreover, those lacking a card tend to be disproportionately concentrated in low-income households, with almost 20 percent of households earning under $10,000 annually and over 14 percent of those earning under $20,000 a year having neither card. These numbers also vary by ethnic groups: 4.8 percent of white and 10.2 percent of Black surveyed consumers.
The lack of access to digital payments has long been a costly inconvenience, but recent developments are moving digital payments from the "nice-to-have" category toward the "must-have" category. Card payments are increasing at an annual rate of 8.9 percent by number in recent years. While cash remains popular, debit cards have overtaken cash for the most popular in-person type of payments. Moreover, the use of cards in remote payments where cash is not an option nearly equals their use for in-person transactions. Most recently, COVID-19 has accelerated this move toward cards, with a 44.4 percent year-over-year increase in e-commerce sales in the second quarter of 2020.
These trends in card usage relative to cash usage pose several problems for consumers who lack access to digital payments. First, some retailers are starting to adopt a policy of refusing cash. Second, many governments are deploying no-cash parking meters, along with highway toll readers and mass transit fare machines that do not accept cash. Third, the growth of online shopping is being accompanied by a decrease in the number of physical stores, resulting in reduced access for those lacking cards.
The last part of the white paper discusses a number of not mutually exclusive ways of keeping the shift from paper-based payments (cash and checks) to digital payments from adversely affecting those lacking a bank account. A simple, short-term fix is to preserve an individual's ability to obtain cash and use it at physical stores. No federal law currently prevents businesses from going cashless, but some states and localities have mandated the acceptance of cash.
However, merely forcing businesses to accept cash does not solve the e-commerce problem, nor does it promote the development of faster, cheaper, safer, and more convenient payment systems, so considering alternatives takes on greater importance. One option the paper discusses is that of cash-in/cash-out networks that allow consumers to convert their physical cash to digital money (and vice versa). Examples of this in the United States include ATMs and prepaid debit cards, as well as prepaid services such as mass transit cards that can be purchased for cash in physical locations.
Another option is public banking. One version of this that has been proposed is a postal banking system like the ones operating in 51 countries outside the United States and the one that was once available here. Another public banking possibility would provide consumers with basic transaction accounts that allow digital payments services. The government or private firms (such as banks, credit unions, or some types of fintech firms) could administer such services.
The paper concludes with a discussion of some important challenges inherent in moving toward a completely cashless economy accessible to everyone. One such consideration is access to mobile and broadband. This issue has a financial dimension, that of being able to afford internet access. It also has a geographic dimension in that many rural areas lack both high-speed internet and fast cellphone networks. Another dimension is that of providing a faster payment service that would allow people to obtain earlier access to their incoming funds, and result in bank balances more accurately reflecting outgoing payments. Finally, the white paper raises the potential for central bank digital currency to expand access to digital payments. However, central bank digital currency raises a large number of issues that the federal government and Federal Reserve would need to work through before it could be a viable option.
May 28, 2020
Firms Expect Working from Home to Triple
The coronavirus and efforts to mitigate its impact are having a transformative impact on many aspects of economic life, intensifying trends like shopping online rather than visiting brick-and-mortar stores and increasing the incidence of working from home. Indeed, many tech giants have already made working from home a permanent option for employees.
Working from home, or telecommuting, is not a new phenomenon. According to a survey by the U.S. Bureau of Labor Statistics (BLS), around 8 percent of all employees worked from home at least one day a week before the arrival of COVID-19. However, only 2.5 percent worked from home full-time in the 2017–18 survey period.
Working from home has surged in the wake of social distancing and other efforts to contain the virus, and this surge brings up a good question: How many jobs can be done at home? Some careful research by Jonathan Dingel and Brent Neiman indicates that nearly 40 percent of U.S. jobs can be done at home.
While this provides an upper bound, can does not mean will, so a natural follow-up question is: How many jobs willbe done at home? To get a sense of how many jobs and how many working days will beperformedat home after the pandemic recedes, we turn to our Survey of Business Uncertainty (SBU). To preview our conclusion, the share of working days spent at home is expected to triple after the COVID-19 crisis ends compared to before the pandemic hit, but with considerable variation across industries.
In the May SBU, we asked two questions to gauge how firms anticipate working from home to change. To get a pre-pandemic starting point, we asked panelists, "What percentage of your full-time employees worked from home in 2019?" And to gauge how that's likely to change after the crisis ends, we asked, "What percentage of your full-time employees will work from home after the coronavirus pandemic?" We asked firms to sort the fraction of their full-time workforce into four categories, ranging from those employees working from home five full days per week to those who rarely or never work from home.
Chart 1 summarizes firms' responses to these two questions. It also summarizes the responses by workers to questions about working from home in the BLS's 2017–18 American Time Use Survey. For the period preceding COVID-19, SBU results and the Time Use Survey results are remarkably similar. Both surveys say 90 percent of employees rarely or never worked from home, and a very small fraction worked from home five full days per week. As reported in the chart's rightmost column, about 5 to 6 percent of all working days happened at home before the pandemic hit.
According to the SBU results, the anticipated share of working days at home is set to triple after the pandemic ends—rising from 5.5 percent to 16.6 percent of all working days. Perhaps even more striking, firms anticipate that 10 percent of their full-time workforce will be working from home five days a week.
Overall, firms say that about 10 percent of their full-time employees worked from home at least one day a week in 2019. That fraction is expected to jump to nearly 30 percent after the crisis ends (well below the upper bound estimated by Dingel and Neiman). Chart 2 gives a look at firm's working-from-home expectations for major industry groups.
The share of people working from home at least one day a week is expected to jump markedly in the construction, real estate, and mining and utilities sectors, presumably by granting front-office staff working-from-home status. It is also expected to jump markedly in health care, education, leisure and hospitality, and other services, possibly by relying more heavily on remote-delivery options (for example, online education and virtual doctor's visits). Firms in the business services sector anticipate that working from home will rise to nearly 45 percent.
For the industries we can match directly to American Time Use Survey statistics, the two data sources imply a similar incidence of working from home before COVID-19. For manufacturing, SBU data indicate that 9 percent of employees worked at home at least one day a week prior to COVID-19, and the American Time Use Survey indicates that 7.3 percent did so. For retail and wholesale trade, the corresponding figures are 4.1 percent and 4.0 percent, respectively.
To summarize, our survey indicates that, compared to before the pandemic, the share of working days spent at home by full-time workers will triple after the pandemic. Our results also say that this shift will happen across major industry sectors. These changes in the location of work are also likely to exert powerful effects on the future of cities and the demand for high-rise office space (more on that next month).
Regarding the long-run impact of the shift to working from home, there are grounds for optimism, including a potential boost to productivity—although if you're juggling kids at home and working from your couch or bedroom, we can understand if it's hard to imagine right now.
November 29, 2018
Cryptocurrency and Central Bank E-Money
The Atlanta Fed recently hosted a workshop, "Financial Stability Implications of New Technology," which was cosponsored by the Center for the Economic Analysis of Risk at Georgia State University. This macroblog post discusses the workshop's panel on cryptocurrency and central bank e-money. A companion Notes from the Vault post provides some highlights from the rest of the workshop.
The panel began with Douglas Elliot, a partner at Oliver Wyman, discussing some of the public policy issues associated with cryptoassets. Drawing on a recent paper he cowrote, Elliot observed that there are "at least four substantial market segments" that provide long-term support for cryptoassets:
- libertarians and techno-anarchists who, for ideological reasons, want a currency without a government;
- people who deeply distrust their government's economic management;
- seekers of anonymity, who don't want their names associated with transactions and investments; and
- technical users who find cryptoassets useful for some blockchain applications.
Besides these groups are the speculators and investors who hope to benefit from price appreciation of these assets.
Given the strong interest of these four groups, Elliot argues that cryptoassets are here to stay, but he also asserts that these assets raise public policy issues that regulation should address. Some issues, such as anti–money laundering, are being addressed, but all would benefit from a coordinated global approach. However, he observes that of the four long-term support groups, only the technical users are likely to favor such regulations.
Another paper, by University of Chicago professor Gina C. Pieters, analyzed the extent to which the cryptocurrency market is global using purchases of cryptocurrency by state-issued currencies. She finds that more than 90 percent of all cryptocurrency transactions occur using one of three currencies: the U.S. dollar, the South Korean won, and the Japanese yen. She further finds that the dominance of these three currencies cannot be explained by economic size, financial openness, or internet access. Pieters also observed that transactions involving bitcoin, the largest cryptocurrency by market value, do not necessarily represent a country's cryptomarket share.
Warren Weber, former Minneapolis Fed economist and a visiting scholar at the Atlanta Fed, discussed so-called "stable coins," one type of cryptocurrency. The value of many cryptocurrencies has fluctuated widely in recent years, with the price of one bitcoin soaring from under $6,000 to more than $19,000 and then plunging to just over $6,000—all within the period from October 2017 to October 2018. This extreme price volatility creates a significant impediment to Elliot's technical users who would like some method of buying blockchain services with a currency controlled by a blockchain. In an attempt to meet this demand, a number of "stable coins" have been issued or are under development.
Drawing on a preliminary paper, Weber discussed three types of stable coins. One type backs all of the currency it issues with holdings of a state-issued currency, such as the U.S. dollar. A potential weakness of these coins is that they incur operational costs that require payment. Weber observed that interest earnings might cover part of these expenses if the stable coin issuer holds the dollars in an interest-bearing asset. Additionally, charging redemption fees might offset some or all of the expense.
The other two alternatives involve the creation of cryptofinancial entities or crypto "central banks." Both of these approaches seek to adjust the quantity of the cryptocurrency outstanding to stabilize its price in another currency. However, Weber observed that both of these approaches are subject to the problem that the cryptocurrency could take on many values depending upon people's expectations. If people come to expect that a coin will lose its value, neither of these approaches can prevent the coin from becoming worthless.
The question of whether existing central banks should issue e-money was the topic of a presentation by Francisco Rivadeneyra of the Bank of Canada. Summarizing the results of his paper, Rivadeneyra observed that central banks could provide e-money that looks like a token or a more traditional account. The potential for central banks to offer widely available account-based services has long existed. However, after considering the tradeoffs, central banks have elected not to provide these accounts, and recent technological developments have not changed this calculus. However, new technologies may have changed the tradeoff for token-based systems. Many issues will need to be addressed first, though.
April 28, 2014
New Data Sources: A Conversation with Google's Hal Varian
New Data Sources: A Conversation with Google's Hal Varian
In recent years, there has been an explosion of new data coming from places like Google, Facebook, and Twitter. Economists and central bankers have begun to realize that these data may provide valuable insights into the economy that inform and improve the decisions made by policy makers.
As chief economist at Google and emeritus professor at UC Berkeley, Hal Varian is uniquely qualified to discuss the issues surrounding these new data sources. Last week he was kind enough to take some time out of his schedule to answer a few questions about these data, the benefits of using them, and their limitations.
Mark Curtis: You've argued that new data sources from Google can improve our ability to "nowcast." Can you describe what this means and how the exorbitant amount of data that Google collects can be used to better understand the present?
Hal Varian: The simplest definition of "nowcasting" is "contemporaneous forecasting," though I do agree with David Hendry that this definition is probably too simple. Over the past decade or so, firms have spent billions of dollars to set up real-time data warehouses that track business metrics on a daily level. These metrics could include retail sales (like Wal-Mart and Target), package delivery (UPS and FedEx), credit card expenditure (MasterCard's SpendingPulse), employment (Intuit's small business employment index), and many other economically relevant measures. We have worked primarily with Google data, because it's what we have available, but there are lots of other sources.
Curtis: The ability to "nowcast" is also crucially important to the Fed. In his December press conference, former Fed Chairman Ben Bernanke stated that the Fed may have been slow to acknowledge the crisis in part due to deficient real-time information. Do you believe that new data sources such as Google search data might be able to improve the Fed's understanding of where the economy is and where it is going?
Varian: Yes, I think that this is definitely a possibility. The real-time data sources mentioned above are a good starting point. Google data seems to be helpful in getting real-time estimates of initial claims for unemployment benefits, housing sales, and loan modification, among other things.
Curtis: Janet Yellen stated in her first press conference as Fed Chair that the Fed should use other labor market indicators beyond the unemployment rate when measuring the health of labor markets. (The Atlanta Fed publishes a labor market spider chart incorporating a variety of indicators.) Are there particular indicators that Google produces that could be useful in this regard?
Varian: Absolutely. Queries related to job search seem to be indicative of labor market activity. Interestingly, queries having to do with killing time also seem to be correlated with unemployment measures!
Curtis: What are the downsides or potential pitfalls of using these types of new data sources?
Varian: First, the real measures—like credit card spending—are probably more indicative of actual outcomes than search data. Search is about intention, and spending is about transactions. Second, there can be feedback from news media and the like that may distort the intention measures. A headline story about a jump in unemployment can stimulate a lot of "unemployment rate" searches, so you have to be careful about how you interpret the data. Third, we've only had one recession since Google has been available, and it was pretty clearly a financially driven recession. But there are other kinds of recessions having to do with supply shocks, like energy prices, or monetary policy, as in the early 1980s. So we need to be careful about generalizing too broadly from this one example.
Curtis: Given the predominance of new data coming from Google, Twitter, and Facebook, do you think that this will limit, or even make obsolete, the role of traditional government statistical agencies such as Census Bureau and the Bureau of Labor Statistics in the future? If not, do you believe there is the potential for collaboration between these agencies and companies such as Google?
Varian: The government statistical agencies are the gold standard for data collection. It is likely that real-time data can be helpful in providing leading indicators for the standard metrics, and supplementing them in various ways, but I think it is highly unlikely that they will replace them. I hope that the private and public sector can work together in fruitful ways to exploit new sources of real-time data in ways that are mutually beneficial.
Curtis: A few years ago, former Fed Chairman Bernanke challenged researchers when he said, "Do we need new measures of expectations or new surveys? Information on the price expectations of businesses—who are, after all, the price setters in the first instance—as well as information on nominal wage expectations is particularly scarce." Do data from Google have the potential to fill this need?
Varian: We have a new product called Google Consumer Surveys that can be used to survey a broad audience of consumers. We don't have ways to go after specific audiences such as business managers or workers looking for jobs. But I wouldn't rule that out in the future.
Curtis: MIT recently introduced a big-data measure of inflation called the Billion Prices Project. Can you see a big future in big data as a measure of inflation?
Varian: Yes, I think so. I know there are also projects looking at supermarket scanner data and the like. One difficulty with online data is that it leaves out gasoline, electricity, housing, large consumer durables, and other categories of consumption. On the other hand, it is quite good for discretionary consumer spending. So I think that online price surveys will enable inexpensive ways to gather certain sorts of price data, but it certainly won't replace existing methods.
By Mark Curtis, a visiting scholar in the Atlanta Fed's research department
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