1-10 of 365 Results


Demystifying Electronic Payment Systems and Digital Currencies  

Lin William Cong, David Easley, and Eswar Prasad

Digital payments have transformed how consumers and businesses transact. New technologies such as mobile wallets and buy-now-pay-later financing offer additional convenience and expand access. However, the proliferation of private platforms raises concerns about market power, privacy, and stability. Since 2008, fast payment systems and decentralized cryptocurrencies have enabled direct transactions with fewer or no intermediaries, but they face challenges such as the lack of value stability and scalability. Central banks are responding by designing digital versions of fiat currencies. Retail central bank digital currencies (CBDCs) could promote financial inclusion and provide a central bank–backed alternative to private platforms. CBDCs raise complex policy trade-offs around disintermediating banks, enabling negative interest rates, preserving privacy, and coexistence with cash. International CBDCs may facilitate cheaper cross-border payments. While digital payments offer efficiency, key design choices around transaction fees and governance determine accessibility. High or unpredictable fees on blockchain platforms disproportionately affect smaller users. Initiatives that broaden token ownership help democratize networks. Tensions persist between decentralization, security, scalability, and privacy. Further research can improve digital payment technologies and clarify policy implications.


The Economics of Abortion Policy  

Damian Clarke

The economic literature on abortion policy broadly is broad, studying abortion reforms that have occurred over the past two centuries, with a concentration of studies examining policy reform over the 20th and 21st centuries. The literature has examined a range of policies: both those which restrict access and those which legalize elective abortion; but within these two broad classes, the precise nature of policy reform can vary greatly. Policy reforms studied range from specific types of limits or financial barriers restricting access for particular age groups to policies which entirely criminalize or legalize elective abortion. Policies have been studied that restrict or relax individual access as well as impose regulations on abortion providers. The economic literature on abortion reform has illuminated a number of clear links, showing that increased availability of abortion decreases rates of unintended births, and vice versa when access to abortion is limited. These effects have been shown to have downstream impacts in many domains such as family formation, educational attainment, and labor market attachment, as well as impacts on health, empowerment, and broader measures of well-being such as life satisfaction and exposure to intimate partner violence. There is mixed evidence when examining the impact that abortion reform has on cohorts of children exposed to reform variation. Across contexts abortion reforms have been shown to affect the composition of cohorts of children via differential rates of access to abortion, though this compositional effect is context-dependent, and as such a number of different patterns have been documented. Compositional effects of policies often also have been shown to have a geographic component, given that certain types of individuals are more easily able to travel to access abortion where restrictions are in place in one area but not in another. Much of what is known in the economic literature on abortion is gleaned from country-level case studies and cohort variation in access, with this evidence generated from a relatively small number of countries in which reforms have occurred and data is available. In general, much of the literature available covers low fertility and industrialized settings. Additional evidence from other settings would allow for a broader understanding of how abortion reform affects well-being.


The Multiple Missions of Community College  

Christopher Jepsen and Adela Soliz

U.S. community colleges are extremely diverse; these public schools provide vocational awards, the first 2 years of a 4-year university degree, adult basic education, specialized training for companies, coursework for industry credentials, and many offerings in between. In other words, community colleges have many different missions. They serve students who, on average, have less advantaged educational and socioeconomic backgrounds than students attending 4-year institutions, yet community colleges receive less funding per student, on average. Regarding remedial or developmental education, many studies estimating the effect of participating in traditional developmental education courses use regression discontinuity models to look at the population of students who barely fail placement exams, compared to those who barely pass. These studies find mixed results. Results are more promising for corequisite models where students take remedial classes alongside college-level classes. Many community college students state that their goal is to transfer to a 4-year school and complete a bachelor’s degree, but only roughly one quarter achieve this goal. Although state articulation agreements aim to simplify the process of transferring, descriptive analyses of these programs suggest that they have at best modest effects on transferring and completing a bachelor’s degree. Associate Degree for Transfer (ADT) programs aim to reduce the number of choices students face as they work through their community college courses. In the early 21st century, evaluations of these programs suggest that they raise bachelor’s degree receipt relative to students in majors or schools that do not offer ADTs, but more research is needed. Despite low persistence rates, particularly in academic programs at community colleges, nearly all the awards offered by these institutions lead to increases, often sizable, in labor-market outcomes. Broadly speaking, the biggest gains are for the program with the most coursework, an associate’s degree, which typically requires 2 years of full-time coursework. At the same time, stackable credentials and non-credit credentials, awards that can sometimes be completed in under a year, often lead to increases of more than 10% in earnings and over 4 percentage points in employment. In contrast, certificates have mixed impacts on labor-market outcomes, although the results for employment are more promising than those for earnings.


Macroeconomic Announcement Premium  

Hengjie Ai, Ravi Bansal, and Hongye Guo

The macroeconomic announcement premium refers to the fact that a large fraction of the equity market risk premium is realized on a small number of trading days with significant macroeconomic announcements. Examples include monetary policy announcements by the Federal Open Market Committee, unemployment/non-farm payroll reports, the Producer Price Index published by the U.S. Bureau of Labor Statistics, and the gross domestic product reported by the U.S. Bureau of Economic Analysis. During the period 1961–2023, roughly 44 days per year with macroeconomic announcements account for more than 71% of the aggregate equity market risk compensation. The existence of the macroeconomic announcement premium has important implications for modeling risk preferences in economics and finance. It provides strong support for non-expected utility analysis. The study of Ai and Bansal demonstrates that the existence of the macroeconomic announcement premium implies that investors’ preferences cannot have an expected utility representation and must satisfy generalized risk sensitivity, a property shared by many non-expected utility models such as the maxmin expected utility of Gilboa and Schmeidler, the recursive utility of Epstein and Zin, and the robust control preference of Hansen and Sargent. Because the amount of risk compensation is proportional to the magnitude of variations in marginal utility, the macroeconomic announcement premium highlights information as the most important driver of marginal utility. This observation has profound implications for many economic analyses that rely on modeling either time-series variation or cross-sectional heterogeneity in marginal utility across agents, such as consumption risk sharing, the trade-off between equality and efficiency, exchange rate variations, and so on. The link between macroeconomic policy announcements and financial market risk compensation is an important direction for future research.


The Hong Kong Housing Market  

Lok Sang Ho and Yonglin Wang

The Hong Kong Special Administrative Region (SAR) government made a tremendous effort to raise the homeownership rate, starting with Mr. Tung Chee-hwa, the first Chief Executive, who, in his Policy Address in 1997, vowed to raise the homeownership rate from below 50% to 70% in 10 years. The figures showed, however, that while the total homeownership rate had gone up by 18 percentage points in 15 years prior to 1997, from 1997 to Q3 2022, in the space of 25 years, the total homeownership rose from 46.7% to 52.6%, or a mere 5.9 percentage points in 25 years. The nonsubsidized private homeownership rate rose from 30% in 1985 to 36.2% in 1997 (6.2 percentage points in 12 years), yet it rose only from 36.2% in 1997 to 37.2% in 2022Q3, amounting to only 1 percentage point in 25 years. The puzzle may lie in the SAR government’s mistaken strategy of providing increasing opportunities for public housing tenants and subsidized flat owners to profit from the housing benefits. These benefits turn out to be at the expense of the middle-class people who provide much impetus to economic growth and who bear the brunt of the tax burden. The various transaction taxes meant to curb speculation turn out to impede the trading-up process. By significantly reducing the supply of existing homes, and especially that of starter homes, an unintended consequence is much sharper price increases for starter homes than for larger homes. This leads to the proliferation of so-called nanoflats that are tiny yet very expensive.


Labor Market Returns to Higher Education  

Ghazala Azmat and Jack Britton

The persistent high wage premium associated with college education, despite increasing participation rates, continues to generate a great deal of academic and policy interest. While it is widely agreed that the financial benefits associated with college completion outweigh the costs, modeling and empirically estimating the returns are complicated. A simple theoretical framework on educational investment illustrates the decision-making processes and key factors, such as expected returns, that guide the choice of an individual to engage in higher education and to achieve an optimal level of educational investment. Broadening the investment model, however, is instrumental to account for potential heterogeneous returns to higher education—the variation in returns by institution, field of study, and students’ background characteristics, among others—and to recognize the wider societal benefits of higher education, beyond private returns. The challenges involved in estimating the returns to higher education and the heterogeneity in returns are central in the discussion. Interpreting a naive correlation between education and wages is complicated by the nonrandom selection of individuals into higher education, such that individuals who are most likely to benefit from higher education are also those most likely to attend. Advancements in data collection, the ability to track individuals from compulsory education to the labor market, and improvements in econometric methodologies have enabled researchers to causally estimate the impact of higher education on earnings and allow for an improved insight into the disparities in returns to higher education. Recognizing the links between students’ characteristics (or backgrounds) and associated constraints helps to understand differences in higher education choices. Similarly, identifying differences in labor market returns associated with attending certain colleges or pursuing particular academic disciplines is as important in shedding light on the complex nature of human capital disparities and the signaling effect of higher education. As the costs of higher education provision constitute an increasingly large share of government spending all over the world, the high returns to college raise questions associated with who should pay for attending college and the role of the state. Internalizing the social returns to education and their broader implications on the growth and the persistence of inequality complicates this discussion. Higher education funding is one potential policy instrument to influence college attendance and returns. It is not, however, the only one. Better information on returns to education or access to policies that target members of certain social groups might be other potential tools to overcome constraints.


Leverage Cycle Theory of Economic Crises and Booms  

John Geanakoplos

Traditionally, booms and busts have been attributed to investors’ excessive or insufficient demand, irrational exuberance and panics, or fraud. The leverage cycle begins with the observation that much of demand is facilitated by borrowing and that crashes often occur simultaneously with the withdrawal of lending. Uncertainty scares lenders before investors. Lenders are worried about default and therefore attach credit terms like collateral or minimum credit ratings to their contracts. The credit surface, depicting interest rates as a function of the credit terms, emerges in leverage cycle equilibrium. The leverage cycle is about booms when credit terms, especially collateral, are chosen to be loose, and busts when they suddenly become tight, in contrast to the traditional fixation on the (riskless) interest rate. Leverage cycle crashes are triggered at the top of the cycle by scary bad news, which has three effects. The bad news reduces every agent’s valuation of the asset. The increased uncertainty steepens the credit surface, causing leverage to plummet on new loans, explaining the withdrawal of credit. The high valuation leveraged investors holding the asset lose wealth when the price falls; if their debts are due, they lose liquid wealth and face margin calls. Each effect feeds back and exacerbates the others and increases the uncertainty. The credit surface is steeper for long loans than short loans because uncertainty is higher. Investors respond by borrowing short, creating a maturity mismatch and voluntarily exposing themselves to margin calls. When uncertainty rises, the credit surface steepens more for low credit rating agents than for high rated agents, leading to more inequality.. The leverage cycle also applies to banks, leading to a theory of insolvency runs rather than panic runs. The leverage cycle policy implication for banks is that there should be transparency, which will induce depositors or regulators to hold down bank leverage before insolvency is reached. This is contrary to the view that opaqueness is a virtue of banks because it lessens panic.


Unintended Fertility: Trends, Causes, Consequences  

Christine Piette Durrance and Melanie Guldi

Unintended fertility occurs when an individual, who did not intend to, becomes pregnant or gives birth. Most measures of unintended fertility account for whether the pregnancy (birth) was wanted and whether it occurred at a desired time. Economic models of fertility provide a framework for understanding an individual’s desire to have children (or not), the number of children to have alongside the quality of each child, and the timing of childbirth. To study fertility intendedness, researchers often classify pregnancies or births as unintended using self-reported retrospective (or prospective) survey responses. However, since survey information on the intendedness of pregnancies and births is not always available, the research on unintended fertility using survey data is necessarily limited to the population surveyed. Consequently, to broaden the population studied, researchers also often rely on reported births, abortions, and miscarriages (fetal deaths) to estimate intendedness. However, other factors (such as laws restricting access or financial hurdles to overcome) may restrict access to the methods used to control reproduction, and these restrictions in turn may influence realized (observed) pregnancies, births, and abortions. Furthermore, abortion and miscarriages are not consistently reported and, when reported, they exhibit more measurement error than births. Despite these research challenges, the available data have allowed researchers to glean information on trends in unintendedness and to study the relationship between fertility-related policies and unintendedness. Over the last 2 decades, unintended fertility has declined in many countries and fewer births are happening “too soon.” There are multiple factors underlying these changes, but changes in access to and quality of reproductive technologies, changes in macroeconomic conditions, and socioeconomic characteristics of fertility-aged individuals appear to be crucial drivers of these changes.


Asset Pricing: Cross-Section Predictability  

Paolo Zaffaroni and Guofu Zhou

A fundamental question in finance is the study of why different assets have different expected returns, which is intricately linked to the issue of cross-section prediction in the sense of addressing the question “What explains the cross section of expected returns?” There is vast literature on this topic. There are state-of-the-art methods used to forecast the cross section of stock returns with firm characteristics predictors, and the same methods can be applied to other asset classes, such as corporate bonds and foreign exchange rates, and to managed portfolios such mutual and hedge funds. First, there are the traditional ordinary least squares and weighted least squares methods, as well as the recently developed various machine learning approaches such as neutral networks and genetic programming. These are the main methods used today in applications. There are three measures that assess how the various methods perform. The first is the Sharpe ratio of a long–short portfolio that longs the assets with the highest predicted return and shorts those with the lowest. This measure provides the economic value for one method versus another. The second measure is an out-of-sample R 2 that evaluates how the forecasts perform relative to a natural benchmark that is the cross-section mean. This is important as any method that fails to outperform the benchmark is questionable. The third measure is how well the predicted returns explain the realized ones. This provides an overall error assessment cross all the stocks. Factor models are another tool used to understand cross-section predictability. This sheds light on whether the predictability is due to mispricing or risk exposure. There are three ways to consider these models: First, we can consider how to test traditional factor models and estimate the associated risk premia, where the factors are specified ex ante. Second, we can analyze similar problems for latent factor models. Finally, going beyond the traditional setup, we can consider recent studies on asset-specific risks. This analysis provides the framework to understand the economic driving forces of predictability.


COVID-19 and Mental Health: Natural Experiments of the Costs of Lockdowns  

Climent Quintana-Domeque and Jingya Zeng

The global impact of the COVID-19 pandemic has been profound, leaving a significant imprint on physical health, the economy, and mental well-being. Researchers have undertaken empirical investigations across different countries, with a primary focus on understanding the association between lockdown measures—an essential public health intervention—and mental health. These studies aim to discern the causal effect of lockdowns on mental well-being. Three notable studies have adopted natural experiments to explore the causal effect of lockdowns on mental health in diverse countries. Despite variations in their research methodologies, these studies collectively support the conclusion that lockdowns have had detrimental consequences on mental health. Furthermore, they reveal that the intensity of these negative effects varies among distinct population groups. Certain segments of the population, such as women, have borne a more profound burden of the mental health costs associated with lockdown measures. In light of these findings, it becomes imperative to consider the implications for mental health when implementing public health interventions, especially during crises like the COVID-19 pandemic. While rigorous measures like lockdowns are essential for safeguarding public health, striking a balance with robust mental health support policies becomes crucial to mitigating the adverse impacts on mental well-being.