Digital currencies store balances in anonymous electronic addresses. We analyze the trade-offs between safety and convenience of aggregating balances in addresses, electronic wallets and banks. In our model agents balance the risk of theft of a large account with the cost to safeguarding a large number of passwords of many small accounts. Account custodians (banks, wallets and other payment service providers) have different objectives and tradeoffs on these dimensions; we analyze the welfare effects of differing industry structures and interdependencies, and in particular the consequences of "password aggregation" programs which in effect consolidate risks across accounts.
We construct a real-time dataset (FRED-SD) with vintage data for the U.S. states that can be used to forecast both state-level and national-level variables. Our dataset includes approximately 28 variables per state, including labor market, production, and housing variables. We conduct two sets of real-time forecasting exercises. The first forecasts state-level labor-market variables using five different models and different levels of industrially-disaggregated data. The second forecasts a national-level variable exploiting the cross-section of state data. The state-forecasting experiments suggest that large models with industrially-disaggregated data tend to have higher predictive ability for industrially-diversified states. For national-level data, we find that forecasting and aggregating state-level data can outperform a random walk but not an autoregression.
This paper studies the impact of collaboration on research output. First, we build a micro founded model for scientific knowledge production, where collaboration between researchers is represented by a bipartite network. The equilibrium of the game incorporates both the complementarity effect between collaborating researchers and the substitutability effect between concurrent projects of the same researcher. Next, we develop a Bayesian MCMC procedure to estimate the structural parameters, taking into account the endogenous matching of researchers and projects. Finally, we illustrate the empirical relevance of the model by analyzing the coauthorship network of economists registered in the RePEc Author Service.
Both large establishments and large cities are known to offer workers an earnings premium. In this paper, we show that these two premia are closely linked by documenting a new fact: when workers move to a large city, they also move to larger establishments. We then ask how much of the city- size earnings premium can be attributed to transitions to larger and better-paying establishments. Using administrative data from Spain, we find that 38 percent of the city-size earnings premium can be explained by establishment-size composition. Most of the gains from the transition to larger establishments realize in the short-term upon moving to the large city. Establishment size explains 29 percent of the short-term gains, but only 5 percent of the medium-term gains that accrue as workers gain experience in the large city. The small contribution to the medium-term gains is due to two facts: first, within large cities workers transition to large establishments only slightly faster than in smaller cities; second, the relationship between earnings and establishment size is weaker in large cities.
High-frequency financial and economic activity indicators are usually time aggregated before forecasts of low-frequency macroeconomic events, such as recessions, are computed. We propose a mixed-frequency modelling alternative that delivers high-frequency probability forecasts (including their confidence bands) for these low-frequency events. The new approach is compared with single-frequency alternatives using loss functions adequate to rare event forecasting. We provide evidence that: (i) weekly-sampled spread improves over monthly-sampled to predict NBER recessions, (ii) the predictive content of the spread and the Chicago Fed Financial Condition Index (NFCI) is supplementary to economic activity for one-year-ahead forecasts of contractions, and (iii) a weekly activity index can date the 2020 business cycle peak two months in advance using a mixed-frequency filtering.
This paper illustrates a challenge in analyzing the learning algorithms resulting in second-order difference equations. We show in a simple monetary model that the learning dynamics do not converge to the rational expectations monetary steady state. We then show that to guarantee convergence, the gain parameter used in the learning rule has to be restricted based on economic fundamentals in the monetary model.
The analysis in this paper was presented to the Federal Open Market Committee as background for its discussion of the Federal Reserve’s review of monetary policy strategy, tools, and communication practices. The Committee discussed issues related to the review at five consecutive meetings from July 2019 to January 2020. References to the FOMC’s current framework for monetary policy refer to the framework articulated in the Statement on Longer-Run Goals and Monetary Policy Strategy first issued in January 2012 and reaffirmed each January, most recently in January 2019.
Between the months of February and April of 2020, average weekly market hours dropped by 6.25, meanwhile 35% of commuting workers reported switching to remote work arrangements. In this paper, we examine implications of these changes for the time allocation of different households, and on aggregate. We estimate that home production activity increased by 2.1 hours a week, or 34% of lost market hours, whereas leisure activity increased by 3.8 hours a week. The monthly value of home production increased by $30.83 billion – that is 10.5% of the concurrent $292.61 billion drop in monthly GDP. Although market hours declined the most for single, less educated individuals, the lost market hours were absorbed into home production the most by married individuals with children.
We study the positive and normative implications of labor market policies that counteract the economic fallout from containment measures during an epidemic. We incorporate a standard epidemiological model into an equilibrium search model of the labor market to compare unemployment insurance (UI) expansions and payroll subsidies. In isolation, payroll subsidies that preserve match capital and enable a swift economic recovery are preferred over a cost-equivalent UI expansion. When considered jointly, however, a cost-equivalent optimal mix allocates 20 percent of the budget to payroll subsidies and 80 percent to UI. The two policies are complementary, catering to different rungs of the productivity ladder. The small share of payroll subsidies is sufficient to preserve high-productivity jobs, but it leaves room for social assistance to workers who face inevitable job loss.
Unemployment inflows have declined sharply since the 1980s while unemployment outflows have remained mostly steady despite a rise in workers' applications over time. Using a random search model of multiple applications with costly information, we show how rising applications incentivize more firms to acquire information, improving the realized distribution of match qualities. Higher concentrations of high productivity matches reduce the incidence of endogenous separations, causing unemployment inflow rates to fall. Quantitatively, our model replicates the relative change in inflow and outflow rates as well as the decline in acceptance rates, job offers and the rise in reservation wages.
In October 1979, Federal Reserve Chairman Paul Volcker persuaded his FOMC colleagues to adopt a new policy framework that i) accepted responsibility for controlling inflation and ii) implemented new operating procedures to control the growth of monetary aggregates in an effort to restore price stability. These moves were strongly supported by monetarist-oriented economists, including the leadership and staff of the Federal Reserve Bank of St. Louis. The next three years saw inflation peak and then fall sharply, but also two recessions and considerable volatility in interest rates and money supply growth rates. This article reviews the episode through the lens of speeches and FOMC meeting statements of Volcker and St. Louis Fed president Lawrence Roos, and articles by Roos’ staff. The FOMC adopted monetarist principles to establish the Fed’s anti-inflation credibility but Volcker was willing to accept deviations of money growth from the FOMC’s targets, unlike Roos, who viewed the targets as sacrosanct. The FOMC abandoned monetary aggregates in October 1982, but preserved the Fed’s commitment to price stability. The episode illustrates how Volcker used a change in operating procedures to alter policy fundamentally, and later adapt the procedures to changed circumstances without abandoning the foundational features of the policy.
We use an incomplete markets economy to quantify the distribution of welfare gains and losses of the US "Volcker" disinflation. In the long run households prefer low inflation, but disinflation requires a transition period and a redistribution from net nominal borrowers to net nominal savers. Even with perfectly flexible prices, welfare costs may be significant for households with nominal liabilities. When calibrated to match the micro and macro moments of the early 1980s high inflation environment, almost half of all borrowers (14 percent of all households) would prefer to avoid the redistribution and equilibrium effects of the disinflation. This share depends negatively on the liquidity value of money and positively on the average duration of nominal borrowing.
This paper seeks to explain three key components of the growing regional disparities in the U.S. since 1980, referred to as the Great Divergence by Moretti (2012). Namely, big cities saw a larger increase in the relative wages of skilled workers, a larger increase in the relative supply of skilled workers, and a smaller decline in business dynamism. These trends can be explained by differences across cities in the extent to which firms adopt new skill-biased technologies. In response to the introduction of a new skill-biased, high fixed cost but low marginal cost technology, firms endogenously adopt more in big cities, in cities that offer abundant amenities for high-skilled workers and in cities that are more productive in using high-skilled labor. The differences in adoption can account for the increasing relationship between skill intensity and city size, the divergence of the city size wage premium by skill group and the changing cross sectional patterns of business dynamism. I document a new fact that firms in big cities invest more in Information and Communication Technology per employee than firms in small cities,consistent with patterns of technology adoption in the model.
What is the theoretical justification for taxing unspent money transfers in a recession? To examine this question, I study a model economy where fiat money is necessary as a medium of exchange and, incidentally, serves as a store of value. This latter property is shown to open the door to business cycles and depressions driven entirely by speculation. Unconditional money transfers do not guarantee escape from a psychologically-induced depression. I demonstrate how money transfers subject to a short expiration date do eliminate speculative equilibria. This hot money policy compares favorably to negative interest rate policy because the latter taxes all money savings whereas the former only threatens to tax gifted money.
We investigate the essentiality of credit and banking in a microfounded monetary model in which agents face heterogeneous idiosyncratic time preference shocks. Three main results arise from our analysis. First, the constrained-efficient allocation is unattainable without banks. Second, financial intermediation can improve the equilibrium allocation even at the Friedman rule because it relaxes the liquidity constraints of impatient borrowers. Third, changes in credit conditions are not necessarily neutral in a monetary equilibrium at the Friedman rule. If the debt limit is sufficiently low, money and credit are perfect substitutes and tightening the debt limit is neutral. As the debt limit increases, however, patient agents always hold money but impatient agents prefer not to since it is costly for them to do so given they are facing a positive shadow rate. Borrowing instead is costless when interest rates are zero and increasing the debt limit improves the allocation.
Monetary policy affects the tradeoffs faced by governments in sovereign default models. In the absence of lump-sum taxation, governments rely on both distortionary taxes and seigniorage to finance expenditure. Furthermore, monetary policy adds a time-consistency problem in debt choice, which may mitigate or exacerbate the incentives to accumulate debt. A deterioration of the terms-of-trade leads to an increase in sovereign-default risk and inflation, and a reduction in growth, which are consistent with the empirical evidence for emerging economies. An unanticipated shock resembling the COVID-19 pandemic generates a significant currency depreciation, increased inflation, and distress in government finances.
This article describes the origins and development of the federal funds market from its inception in the 1920s to the early 1950s. We present a newly digitized daily data series on the federal funds rate from April 1928 through June 1954. We compare the behavior of the funds rate with other money market interest rates and the Federal Reserve discount rate. Our federal funds rate series will enhance the ability of researchers to study an eventful period in U.S. financial history and to better understand how monetary policy was transmitted to banking and financial markets. For the 1920s and 1930s, our series is the best available measure of the overnight risk-free interest rate, better than the call money rate which many studies have used for that purpose. For the 1940s-1950s, our series provides new information about the transition away from wartime interest-rate pegs culminating in the 1951 Treasury-Federal Reserve Accord.
This paper takes a unique approach to the scenario where a resident terrorist group in a (fragile) developing nation poses a terrorism threat at home and abroad. The host developing nation’s proactive countermeasures against the resident terrorist group not only limits terrorism at home and abroad, but also bolsters regime stability at home. A two-stage game is presented in which the developed country takes a leadership role to institute a tax-subsidy combination to discourage (encourage) proactive measures at home (abroad) in stage 1. Stage 2 involves both nations’ counterterrorism choices under alternative stage-1 public-policy packages. Unlike the extant literature, we explore corner and interior solutions in both stages based on the terrorists’ targeting preferences and the host nation’s regime-stability preferences. Surprisingly, the developed nation may profit from policy packages that reduce global counterterrorism while raising global terrorism. This outcome and others involve engineered counterterrorism burden shifting.
This paper decomposes the causal effect of government defense spending into: (i) a local (or direct) effect, and (ii) a spillover (or indirect) effect. Using state-level defense spending data, we show that a negative cross-state spillover effect explains the existing simultaneous findings of a low aggregate multiplier and a high local multiplier. We show that enlisting disaggregate data improves the precision of aggregate effect estimates, relative to using aggregate time series alone. Moreover, we compare two-step efficient GMM with two alternative moment weighting approaches used in existing research.
I present a model where work implies social interactions and the spread of a disease is described by an SIR-type framework where both susceptible and infectious are asymptomatic. Upon the outbreak of a disease a lower contact rate can be achieved at the cost of lower consumption. Individuals do not internalize the effects of their decisions on the evolution of the epidemic while the planner does. Specifically, the planner internalizes that a low contact rate early in the epidemic implies a low stock of infectious in the future; and a low stock of infectious in the future permits an increase in the contact rate without risking additional infections. Since a low contact rate is associated with low consumption, the planner effectively substitutes consumption early in the epidemic for consumption later. The individual's response does not, hence the planner obtains a flatter infection curve than that generated by the individual's' response, even though the planner's objective is not to ``flatten the curve.''
Short-term debt is commonly used to fund illiquid assets. A conventional view asserts that such arrangements are run-prone in part because redemptions must be processed on a first-come, first-served basis. This sequential service protocol, however, appears absent in the wholesale banking sector---and yet, shadow banks appear vulnerable to runs. We explain how banking arrangements that fund fixed-cost operations using short-term debt can be run-prone even in the absence of sequential service. Interventions designed to eliminate run risk may or may not improve depositor welfare. We describe how optimal policies vary under different conditions and compare these to recent policy interventions by the Security and Exchange Commission and the Federal Reserve. We conclude that the conventional view concerning the societal benefits of liquidity transformation and its recommendations for prudential policy extend far beyond their application to depository institutions.
We measure labor demand and supply shocks at the sector level around the COVID-19 outbreak by estimating a Bayesian structural vector autoregression on monthly statistics of hours worked and real wages. Most sectors were subject to historically large negative labor supply and demand shocks in March and April, with substantial heterogeneity in the size of shocks across sectors. Our estimates suggest that two-thirds of the drop in the aggregate growth rate of hours in March and April 2020 are attributable to labor supply. We validate our estimates of supply shocks by showing that they are correlated with sectoral measures of telework.
This paper studies the role of international trade of essential goods during a pandemic. We consider a multi-country, multi-sector model with essential and non-essential goods. Essential goods provide utility relative to a reference consumption level, and a pandemic consists of an increase in this reference level. Each country produces domestic varieties of both types of goods using capital and labor subject to sectoral adjustment costs, and all varieties are traded internationally subject to trade barriers. We study the role of international trade of essential goods in mitigating or amplifying the impact of a pandemic. We find that the effects depend crucially on the countries' trade imbalances in essential goods. Net importers of these goods are relatively worse off during a pandemic than net exporters. The welfare losses of net importers are lower in a world with high trade barriers, while the reverse is the case for net exporters. Yet, once a pandemic arrives, net exporters of essential goods benefit from an increase in trade barriers, while net importers benefit from a decrease in them. These findings are consistent with preliminary evidence on changes in trade barriers across countries during the COVID-19 pandemic.
The largest economic cost of the COVID-19 pandemic could arise if it changed behavior long after the immediate health crisis is resolved. A common explanation for such a long-lived effect is the scarring of beliefs. We show how to quantify the extent of such belief changes and determine their impact on future economic outcomes. We find that the long-run effect of the COVID crisis depends crucially on whether bankruptcies and changes in habit make existing capital obsolete. A policy that avoided most permanent separation of workers from capital could generate a much larger benefit than originally thought, that could easily be 180% of annual GDP, in present value.
This paper studies the optimal maturity structure for government debt when markets for liquidity insurance are incomplete or non-competitive. There is no fiscal risk. Government debt in the model solves a dynamic inefficiency. Issuing debt in short and long maturities solves a liquidity insurance problem, but optimal yield curve policy is only possible if long-duration debt is rendered illiquid. Optimal policy is implementable through treasury operations only--adjustments in the primary deficit are not necessary.
The rapidly growing national debt in the U.S. since the 1970s has alarmed and intrigued the academic world. Consequently, the concept of dynamic (in)efficiency in an overlapping generations (OLG) world and the importance of the heterogeneous-agents and incomplete markets (HAIM) hypothesis to justify a high debt-to-GDP ratio have been extensively studied. Two important consensus emerge from this literature: (i) The optimal quantity of public debt is positive—due to insufficient private liquidity to support private saving and investment (see, e.g., Barro (1974), Woodford (1990), and Aiyagari and McGrattan (1998)); (ii) the optimal capital tax is positive—because of precautionary saving and the consequent failure of the modified golden rule (see, e.g., Aiyagari (1995)). But these two consensus views are seldom derived jointly in the same model, so the dynamic relationship between optimal debt and optimal taxation remains unclear in HAIM models, especially considering that the optimal quantity of debt must be judged by the golden-rule saving rate and any debt must be financed by future taxes. We use a primal Ramsey approach to analytically characterize optimal debt and tax policy in an OLG-HAIM model. We show that since precautionary saving and oversaving are not necessarily the same thing, they have different policy implications—the Ramsey planner opts to issue bonds to crowd out private savings if and only if a competitive equilibrium is dynamically inefficient regardless of precautionary savings. In other words, optimal debt can be negative even if households cannot insure themselves against idiosyncratic risk under borrowing constraints. The sign and magnitude of the optimal quantity of debt in turn dictate the sign and magnitude of optimal taxes as well as the priority order of tax tools such as a labor tax vs. a capital tax.
I study the effects of the 2019-20 coronavirus outbreak in the United States and subsequent fiscal policy response in a nonlinear DSGE model. The pandemic is a shock to the utility of contact-intensive services that propagates to other sectors via general equilibrium, triggering a deep recession. I use a calibrated version of the model to analyze different types of fiscal policies. I find that UI benefits are the most effective tool to stabilize income for borrowers, who are the hardest hit, while savers may favor unconditional transfers. Liquidity assistance programs are effective if the policy objective is to stabilize employment in the affected sector. I also study the effects of the $2 trillion CARES Act of 2020.
In this paper we present and describe a large quarterly frequency, macroeconomic database. The data provided are closely modeled to that used in Stock and Watson (2012a). As in our previous work on FRED-MD, our goal is simply to provide a publicly available source of macroeconomic “big data” that is updated in real time using the FRED database. We show that factors extracted from this data set exhibit similar behavior to those extracted from the original Stock and Watson data set. The dominant factors are shown to be insensitive to outliers, but outliers do affect the relative influence of the series as indicated by leverage scores. We then investigate the role unit root tests play in the choice of transformation codes with an emphasis on identifying instances in which the unit root-based codes differ from those already used in the literature. Finally, we show that factors extracted from our data set are useful for forecasting a range of macroeconomic series and that the choice of transformation codes can contribute substantially to the accuracy of these forecasts.
New vehicle sales in the U.S. fell nearly 40 percent during the past recession, causing significant job losses and unprecedented government interventions in the auto industry. This paper explores three potential explanations for this decline: increasing oil prices, falling home values, and falling household income expectations. First, we use the historical macroeconomic relationship between oil prices and vehicle sales to show that the oil price spike explains roughly 15 percent of the auto sales decline between 2007 and 2009. Second, we establish that declining home values explain only a small portion of the observed reduction in household new vehicle sales. Using a county-level panel from the episode, we find (1) a one-dollar fall in home values reduced household new vehicle spending by 0.5 to 0.7 cents and overall new vehicle spending by 0.9 to 1.2 cents and (2) falling home values explain between 16 and 19 percent of the overall new vehicle spending decline. Next, examining state-level data for 1997-2016, we find (3) the short-run responses of new vehicle consumption to home value changes are larger in the 2005-2011 period relative to other years, but at longer horizons (e.g. 5 years), the responses are similar across the two sub-periods and (4) the service flow from vehicles, as measured by miles traveled, responds very little to house price shocks. We also detail the sources of the differences between our findings (1) and (2) from existing research. Third, we establish that declining current and expected future income expectations potentially played an important role in the auto market's collapse. We build a permanent income model augmented to include infrequent repeated car buying. Our calibrated model matches the pre-recession distribution of auto vintages and the liquid-wealth-to-income ratio, and exhibits a large vehicle sales decline in response to a mild decline in expected permanent income due to a transitory slowdown in income growth. In response to the shock, households delay replacing existing vehicles, allowing them to smooth the effects of the income shock without significantly adjusting the service flow from their vehicles. Augmenting our model with a richer set of household expectations allows us to match 65 percent of the overall new vehicle spending decline (i.e. roughly the portion of the decline not explained by oil prices and falling home values). Combining our negative results regarding housing wealth and oil prices with our positive model-based findings, we interpret the auto market collapse as consistent with existing permanent income based approaches to durable goods purchases (e.g., Leahy and Zeira (2005)).
Deciding to undertake a series of tightening actions present unique challenges for Federal Reserve policymakers. These challenges are both political and economic. Using a variety of economic and financial market metrics, this article examines how the economy and financial markets evolved in response to the five tightening episodes enacted by the FOMC since 1983. The primary aim is to compare the most-recent episode, from December 2015 to December 2018, with the previous four episodes. The findings in this article indicate that the current episode bears some resemblance to previous Fed tightening episodes, but also differs in several key dimensions. For example, in the first four episodes, the data show the FOMC was generally tightening into a strengthening economy with building price pressures. In contrast, in the fifth episode the FOMC began its tightening regime during a deceleration in economic activity and with headline and core inflation remaining well below the FOMC’s 2 percent inflation target. Moreover, both short- and long-term inflation expectations were drifting lower. These developments helped explain why there was a one-year gap between the first and second increases in the federal funds target rate in the most-recent episode. Another key difference is that in three of the first four episodes, the FOMC continued to tighten after the yield curve inverted; a recession then followed shortly thereafter. However, in the final episode, the FOMC ended its tightening policy about eight months before the yield curve inverted. It remains to be seen if a recession follows this inversion.