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We attempt to replicate 67 papers published in 13 well-regarded economics journals using author-provided replication files that include both data and code. Some journals in our sample require data and code replication files, and other journals do not require such files. Aside from 6 papers that use confidential data, we obtain data and code replication files for 29 of 35 papers (83%) that are required to provide such files as a condition of publication, compared to 11 of 26 papers (42%) that are not required to provide data and code replication files. We successfully replicate the key qualitative result of 22 of 67 papers (33%) without contacting the authors. Excluding the 6 papers that use confidential data and the 2 papers that use software we do not possess, we replicate 29 of 59 papers (49%) with assistance from the authors. Because we are able to replicate less than half of the papers in our sample even with help from the authors, we assert that economics research is usually not replicable. We conclude with recommendations on improving replication of economics research.

Time is a significant cost of conducting transactions, and theoretical models predict that transactions costs significantly affect the type of media of exchange buyers use. However, there is little empirical work documenting the magnitude of this effect. This paper uses grocery store scanner data to examine how time affects consumer choices of checks and debit cards. On average, check transactions take thirty percent longer than debit card transactions. This time difference is a significant factor in the choice to use a debit card over a check and offers empirical evidence for transactions costs affecting the use of media of exchange.

This paper offers a fresh perspective on fundamental issues in using official incorporation records to corroborate the identity of corporate entities by comparing two publicly-available sets of information, namely, business registry incorporation records and reference data from the Legal Entity Identifier (LEI) system, with some focus on the monitoring function performed by LEI issuers as agents for LEI data users. Three modes of analysis are used to consider these issues, high-level analysis of LEI system data about U.S. entities with LEIs, interviews conducted with U.S. business registries, and entity-level comparisons of business registry and LEI records for entities with LEIs incorporated in the states of Ohio and Massachusetts. The fresh perspective provided here includes attention to key comparison issues such as truncation of Legal Names in official records; significant state-level variation in requirements to provide business address information in incorporation records or periodic reports; recognition that some key business register data may not be readily available or available only at a cost; whether in this context enhancements can be made to the expectations for, and disclosures by, LEI issuers in their monitoring role; and to what extent the high incidence of non-renewal of LEIs might play a role in the quality of LEI reference data. The paper develops measures of scope and degree for many key issues that can arise in using business registry information within an identity-corroboration context. The exceptional transparency of the LEI system allows for detailed comparisons that connect its data quality and value proposition with its sources and methods.

This paper examines estimates of, and drivers for, the sacrifice ratio in the United States. Three approaches are employed. The first reviews the literature on what sacrifice ratio might be expected. The second studies a generic disinflation experiment using 40 estimated macro models of the U.S. economy, calculating a distribution of sacrifice ratios. Those sacrifice ratios are high by historical standards and the paper discusses some stories for why this is so. The role of expectations formation and the credibility of policy is emphasized. The third approach gets under the hood of drivers of the output cost of disinflation by carrying out a selection of disinflation experiments using the FRB/US model, varying certain characteristics of the model’s expectations formation mechanism. Pinning down a precise measure for the output cost of disinflation is challenging. But the literature and policy experiments do offer some guidance on how the sacrifice ratio can be reduced.

This paper presents a stylized framework of bank risk‐taking to help clarify the concept of “double materiality,” the idea that supervisory authorities should consider both the risks that banks face from climate change and the impact of a bank’s actions on climate change. The paper shows that the concept of double materiality can be coherently embedded in a microprudential framework, but the practical implications could be quite similar to the implications of a single materiality perspective. The importance of a double materiality perspective becomes larger when one considers macroprudential objectives driven by financial sector externalities. The framework illustrates the critical importance of being clear on the supervisory mandate and objectives when assessing policy alternatives.

The value of assets in the digital ecosystem has grown rapidly, amid periods of high volatility. Does the digital financial system create new potential challenges to financial stability? This paper explores this question using the Federal Reserve’s framework for analyzing vulnerabilities in the traditional financial system. The digital asset ecosystem has recently proven itself highly fragile. However adverse digital asset markets shocks have had limited spillovers to the traditional financial system. Currently, the digital asset ecosystem does not provide significant financial services outside the ecosystem, and it exhibits limited interconnections with the traditional financial system. The paper describes emerging vulnerabilities that could present risks to financial stability in the future if the digital asset ecosystem becomes more systemic, including: run risks among large stablecoins, valuation pressures in crypto-assets, fragilities of DeFi platforms, growing interconnectedness, and a general lack of regulation.

This paper studies the impact of unanticipated monetary policy news around FOMC announcements on secondary market corporate loan spreads. I find that the reaction of loan spreads to monetary policy news is weaker than that of bond spreads: following an unanticipated monetary policy tightening (easing) shock, loan spreads do not increase (decrease) as much as bond spreads do. Decomposition of the spreads into compensations for expected defaults and risk premiums shows that differential reactions of loan and bond risk premiums are the main driver of the differential spread reactions. This paper further finds that the weaker loan spread reactions to monetary policy shocks are more pronounced for riskier loans. Lastly, reactions of primary market loan spreads to monetary policy shocks are also muted. These findings highlight heterogeneous impacts of monetary policy across different types of corporate credit markets, possibly reflecting heterogeneous investor demand responses to monetary policy in those markets.

This paper investigates how corporate tax changes affect workers’ earnings. We use a dataset of U.S. worker-level W-2 filings matched with corporate tax returns and study the implementation of the Domestic Production Activities Deduction (DPAD). We find the DPAD tax rate reduction has a substantial effect on the distribution of annual wage earnings within a firm. Earnings of workers at the top of their firm’s earnings distribution rise relative to those at the bottom of the distribution. We estimate a semi-elasticity of average earnings of 1.1 with respect to the DPAD marginal tax rate reduction, while the semi-elasticity of median earnings is notably smaller—0.5. Furthermore, we estimate a semi-elasticity of 1.3 at the 95th percentile of workers’ earnings and 2.7 at the 99th percentile. This trend of larger semi-elasticities at the top of the earnings distribution is especially pronounced for small firms. Looking at overall employment effects, we see no change overall, but the number of employees rises at small firms and declines at large firms. In contrast, we find that capital investment rises for large firms, suggesting that the DPAD also resulted in domestic capitallabor substitution for large corporations. Our paper has significant implications for assessing the progressivity of the U.S. tax code and for analyzing the effect of corporate tax policy changes on the U.S. income distribution.

This paper provides a brief history of the U.S. financial regulatory perimeter, a legal cordon comprised of "positive" and "negative" restrictions on the conduct of banking organizations. Today's regulatory perimeter faces a wide range of challenges, from disaggregation, to new commercial entrants, to new varieties of charters (and new uses of legacy charters). We situate these challenges in the longer history of American banking, identifying a pattern in debates about the nature, shape, and position of the perimeter: outside-in pressure, inside-out pressure, and reform and expansion. We also observe a shift in this pattern, beginning roughly three decades ago, which gradually made the perimeter broader, more complex, and arguably more permeable. We show this trend graphically in an animation accompanying this paper.

This paper examines whether banks strategically incorporate their competitors’ liquidity mismatch policies when determining their own and the impact of these collective decisions on financial stability. Using a novel identification strategy exploiting the presence of partially overlapping peer groups, I show that banks’ liquidity transformation activity is driven by that of their peers. These correlated decisions are concentrated on the asset side of riskier banks and are asymmetric, with mimicking occurring only when competitors take more risk. Accordingly, this strategic behavior increases banks’ default risk and overall systemic risk, highlighting the importance of regulating liquidity risk from a macroprudential perspective. ReceivedMay 4, 2016; editorial decision January 1, 2019 by Editor Philip Strahan. Author has furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Standard achievement scales aggregate test questions without considering their relationship to economic outcomes. This paper uses question-level data to improve the measurement of achievement in two ways. First, the paper constructs alternative achievement scales by relating individual questions directly to school completion and labor market outcomes. Second, the paper leverages the question data to construct multiple such scales in order to correct for biases stemming from measurement error. These new achievement scales rank students differently than standard scales and typically yield achievement gaps by race, gender, and household income that are larger by 0.1 to 0.5 standard deviations. Differential performance on test questions can fully explain black-white differences in both wages and lifetime earnings and can explain roughly half of the difference in these outcomes between youth from high- versus low-income households. By contrast, test questions do not explain gender differences in labor market outcomes.

Empirical analysis of U.S. income, saving and wealth dynamics is constrained by a lack of high-quality and comprehensive household-level panel data. This paper uses a pseudo-panel approach, tracking types of agents by birth cohort and across time through a series of cross-section snapshots synthesized with macro aggregates. The key micro source data is the Survey of Consumer Finances (SCF), which captures the top of the wealth distribution by sampling from administrative records. The SCF has the detailed balance sheet components, incomes, and interfamily transfers needed to use both sides of the intertemporal budget constraint and thus solve for saving and consumption. The results here are consistent with recent papers based on individual panel data from countries with administrative registries, and highlights the different roles of saving, capital gains, and interfamily transfers in wealth change over the lifecycle and across permanent income groups.

This paper examines two candidate hypotheses explaining the stabilization of U.S. inflation since the 1970s and 1980s. The first explanation credits the stabilization of inflation expectations, and assumes those expectations have a strong positive causal effect on actual subsequent inflation, while the second explanation credits the disappearance of such a strong positive causal effect. The paper reports statistical tests favorable to both a stabilization of inflation expectations and a marked decline in the effect of the general public’s inflation expectations on subsequent inflation.

This paper considers the impact of how human capital is accumulated on optimal capital tax policy in a life cycle model. In particular, it compares the optimal capital tax when human capital is accumulated exogenously, endogenously through learning-by-doing, and endogenously through learning-or-doing. Previous work demonstrates that in a simple two generation life cycle model with exogenous human capital accumulation, if the utility function is separable and homothetic in each consumption and labor, then the government has no motive to condition taxes on age or tax capital. In contrast, this paper demonstrates analytically that adding either form of endogenous human capital accumulation creates a motive for the government to use age-dependent labor income taxes. Moreover, if the government cannot condition taxes on age, then a capital tax can be optimal in order to mimic such taxes. This paper quantitatively explores the strength of this channel and finds that, includ ing human capital accumulation with learning-by-doing, as opposed to exogenously, causes the optimal capital tax to increase by between 7.3 and 14.5 percentage points. In contrast, introducing learning-or-doing causes a much smaller increase in the optimal capital tax of between 0.7 and 3.7 percentage points. Taken as a whole, this paper finds that the specific formulation by which human capital is accumulated can have notable implications on the optimal capital tax.

This paper provides a new technique for representing discrete time nonlinear dynamic stochastic time invariant maps. Using this new series representation, the paper augments the usual solution strategy with an additional set of constraints thereby enhancing algorithm reliability. The paper also provides general formulas for evaluating the accuracy of proposed solutions. The technique can readily accommodate models with occasionally binding constraints and regime switching. The algorithm uses Smolyak polynomial function approximation in a way which makes it possible to exploit a high degree of parallelism.

Arkansas has been a popular place to study the effects of rate ceilings because of its exceptionally low interest rate ceiling. This paper examines the effects of the Arkansas rate ceiling on credit use by nonprime consumers in Arkansas, who are especially vulnerable to credit rationing because of the low ceiling. We compare the level and composition of consumer debt of nonprime consumers in Arkansas with that of prime Arkansas consumers and also non-prime consumers in the neighboring states. We find that nonprime consumers in Arkansas are less likely to have consumer debt and, conditional on having debt, have slightly lower levels of consumer debt than prime Arkansas consumers and nonprime consumers in neighboring states. Types of credit used by nonprime consumers in Arkansas tend to differ from those of the comparison groups. Notable is much lower use of consumer finance loans, traditionally an important source of credit for higher risk consumers. This finding suggests rate-based rationing of risky consumers. Also notable is lower use of bank credit despite federal preemption of the rate ceiling for banks. This result is consistent with banks’ traditional avoidance of risky lending.

This paper explores an under-studied channel for school finance inequality: property assessment. School districts have historically relied on local tax revenues (typically property taxes) to fund schools, which can generate disparities in funding across districts. Many states passed school finance reforms that give more state funding to poorer districts. These formulas typically discourage school districts from offsetting state funding by reducing local tax rates (“crowd out”). However, many reforms have not adequately addressed another source of inequality: property assessment accuracy and equity. Moreover, state reform can unintentionally subsidize property underassessment. We analyze a state government intervention to address property assessment inequities within and across school districts. We use difference-in-differences and county- and school district-level administrative data to find the intervention boosted assessments by 32 percent. Assessment equity improved substantially and local property revenues temporarily increased by 17 percent. Local fiscal and institutional capacity played a role in assessment inequity pre-reform. Our results suggest that underassessment can compound funding inequality across districts in states that rely on property wealth to fund schools. Therefore, effective state oversight in property assessments is needed to ensure the integrity of funding systems that distribute state funding to districts on the basis of their assessed property wealth.

This paper investigates how bank supervisors’ enforcement decisions and orders (EDOs) influence the allocation of mortgage lending across demographic groups underlying a banks’ borrower base. Specifically, we investigate how banks’ mortgage lending to minority borrowers relative to white borrowers changes following the resolution of severe EDOs. We hypothesize that improvements in management control systems imposed by EDOs serve as channels through which EDOs affect a bank’s borrower base generally, and minority lending specifically. We empirically examine how changes in loan policies and internal governance mechanisms specified in EDOs influence banks’ mortgage lending decisions. We find that relative to white borrowers, mortgage lending to minority borrowers significantly increases following the resolution of EDOs, where this positive effect increases with the strictness of bank supervisors and severity of the EDO. Consistent with management controls serving as channels for this change, there is a more pronounced effect on minority lending when an EDO mandates improvements in lending policies and stronger internal governance over lending decisions.

This paper examines whether the measurement of trend inflation can be improved by using wage data in a dynamic factor model of disaggregated prices and wages for the United States. The model features time-varying coefficients and stochastic volatility. An estimate of trend inflation is a time-varying distributed lag of prices and wages, where the weight on a series depends on its time-varying volatility, persistence, and comovement with other series. The results show that wages inform estimates of trend inflation. The weight on wages was highest around 1980, drifted down through the 2000s, and returned to its 1980s value by 2022. In addition, inflation in the 2020s appears to have unmoored moderately from the 2 percent range that prevailed for decades, as the role of the persistent component of inflation increased in recent year. However, accounting for wages lowers the model's view of the increase in the volatility of trend inflation.

This paper investigates contagion in financial networks through both debt and collateral markets. We find that the role of collateral is mitigating counterparty exposures and reducing contagion but has a phase transition property. Contagion can change dramatically depending on the amount of collateral relative to the debt exposures. When there is an abundance of collateral (leverage is low), then collateral can fully cover debt exposures, and the network structure does not matter. When there is an adequate amount of collateral (leverage is moderate), then collateral can mitigate counterparty contagion, and having more links in the network reduces contagion, as interlinkages act as a diversifying mechanism. When collateral is not enough (leverage is high) and agents in the network are too interconnected, then the collateral price can plummet to zero and the whole network can collapse. Therefore, we show the importance of the interaction between the level of collateral and interconnectedness across agents. The model also provides the minimum collateral-to-debt ratio (haircut) to attain a robust macroprudential state for a given network structure and aggregate state.

We analyze the effect of measurement error in macroeconomic data on economics research using two features of the estimates of latent US output produced by the Bureau of Economic Analysis (BEA). First, we use the fact that the BEA publishes two theoretically identical estimates of latent US output that only differ due to measurement error: the more well-known gross domestic product (GDP), which the BEA constructs using expenditure data, and gross domestic income (GDI), which the BEA constructs using income data. Second, we use BEA revisions to previously published releases of GDP and GDI. Using a sample of 23 published economics papers from top economics journals that utilize GDP as a key component of an estimated model, we assess whether using either revised GDP or GDI instead of GDP in the published paper would change reported results. We find that estimating models using revised GDP generates the same qualitative result as the original paper in all 23 cases. Estimating models using GDI, both with the GDI data originally available to the authors and with revised GDI, instead of GDP generates larger differences in results than those obtained with revised GDP. For 3 of 23 papers (13%), the results we obtain with GDI are qualitatively different than the original published results.

This paper constructs regime-switching models for estimating the probability of inflation returning to its relatively high levels of variability and persistence in the 1970s and 1980s. Forecasts and probabilities of extreme events from the models are evaluated against comparable estimates from other statistical models, from surveys, and from financial markets. The paper then uses the models to construct prediction intervals around Federal Reserve Board staff forecasts of PCE price inflation, combining the recent non-parametric forecast error distribution with parametric information from the model. The outer tails of the prediction intervals depend importantly on the probability inflation is in its high-variance, high-persistence regime.

Detractors have warned that Private Equity (PE) funds tend to over-lever their portfolio companies because of an option-like payoff, building up default risk and debt overhang. This paper argues PE-ownership leads to substantially higher levels of optimal (value-maximizing) leverage, by reducing the expected cost of financial distress. Using data from a large sample of PE buyouts, I estimate a dynamic trade-off model where leverage is chosen by the PE investor. The model is able to explain both the level and change in leverage documented empirically following buyouts. The increase in optimal leverage is driven primarily by a reduction in the portfolio company's asset volatility and, to a lesser extent, an increase in asset return. Counterfactual analysis shows significant loss in firmvalue if PE sub-optimally chose lower leverage. Consistent with lower asset volatility, additional tests show PE-backed firms experience lower volatility of sales and receive greater equity injections for distress resolution, compared to non PE-backed firms. Overall, my findings broaden our understanding of factors that drive buyout leverage.

This paper is a companion to our recent paper, "ICT Prices and ICT Services: What do they tell us about Productivity and Technology?" It provides the sources and methods used to construct national accounts-style price deflators for the major components of ICT investment--communications equipment, computer equipment, and software--that were presented and analyzed in that paper. The ICT equipment measures described herein were also used in Byrne, Fernald, and Reinsdorf (2016). This paper is a companion to our recent paper, "ICT Services and their Prices: What do they tell us about Productivity and Technology?" It provides the sources and methods used to construct national accounts-style price deflators for the major components of ICT investment--communications equipment, computer equipment, and software--that were analyzed and used in that paper. The ICT equipment measures described herein were also used in Byrne, Fernald, and Reinsdorf (2016).

This paper reassesses the link between ICT prices, technology, and productivity. To understand how the ICT sector could come to the rescue of a whole economy, we extend a multi-sector model due to Oulton (2012) to include ICT services (e.g., cloud services) and use it to calibrate the steady-state contribution of the ICT sector to growth in aggregate U.S. labor productivity. Because ICT technologies diffuse through the economy increasingly via purchases of cloud and data analytic services that are not fully accounted for in the standard narrative on ICT's contribution to economic growth, the contribution of ICT to growth in output per hour going forward is found to be substantially larger than generally thought--1.4 percentage points per year. One reason why the estimated contribution is so large is that official ICT asset prices are found to substantially understate the productivity of the sector. The model developed in this paper also has implications for the relationship between prices for ICT services and prices for the capital stocks (i.e., ICT assets) used to supply them. In particular, ICT service prices may diverge from asset prices and capture productivity gains from ICT asset management by the sector.

This paper finds a significant influence of Milton Friedman on U.K. economic policy from the 1970s onward, and especially during the period of the Thatcher Government. The finding is based on a consideration of statements by policymakers and key economic advisers, as well as an analysis of Friedman’s commentary in the 1970s, 1980s, and 1990s on U.K. economic developments. Explicit, public acknowledgments of Friedman's influence were given by Margaret Thatcher, Chancellor of the Exchequer Geoffrey Howe, Bank of England officials, and others in policy circles. Examples of Friedman's influence include the absorption into U.K. policy doctrine of the permanent income hypothesis and the natural rate hypothesis, the rejection from 1979 onward of incomes policy as a weapon against inflation, and U.K. officials' repeated appeals to monetary sovereignty when arguing against monetary union or a sterling peg. Evidence of influence by Friedman on privatization policy and on the official perspective on the current account deficit can also be discerned. Although he had only limited interaction with U.K. policymakers, Friedman had a major influence, reflected in the adoption into actual U.K. policymaking of recommendations made in his writings and in the fact that those writings-which were studied closely by a number of senior U.K. economic advisers-helped alter U.K. economists' conceptual framework and thereby fostered doctrinal changes in U.K. economic policy. This paper's analysis also shows that two prominent critics of the Thatcher economic policy-Labour's Harold Wilson and the Conservatives' Edward Heath-saw this policy as partly due to the influence of Friedman, whom each of them had met before the Thatcher era.

This paper answers two questions that help those analyzing FinTech understand its origins, growth, and potential to affect financial stability. First, it answers the question of why "FinTech" is happening right now. Many of the technologies that support FinTech innovations are not new, but financial institutions and entrepreneurs are only now applying them to financial products and services. Analysis of the supply and demand factors that drive "traditional" financial innovation reveals a confluence of factors driving a large quantity of innovation. Second, this paper answers the question of why FinTech is getting so much more attention than traditional innovation normally does. The answer to this question has to do with the 'depth' of innovation, a concept introduced in this paper. The deeper an innovation, the greater the ability of that innovation to transform financial services. The paper shows that many FinTech innovations are deep innovations and hence have a greater potential to change financial services. A greater potential to transform can also lead to a greater chance of affecting financial stability.

This paper is a companion to our recent paper, "ICT Prices and ICT Services: What do they tell us about Productivity and Technology?" It provides the sources and methods used to construct national accounts-style price deflators for the major components of ICT investment--communications equipment, computer equipment, and software--that were presented and analyzed in that paper. The ICT equipment measures described herein were also used in Byrne, Fernald, and Reinsdorf (2016).

This paper studies measurement errors that subtract signal from true variables of interest, labeled lack of signal errors (LoSE). The effect on OLS regression of LoSE is opposite the conventional wisdom about classical measurement errors, with LoSE in the dependent variable, not the explanatory variables, causing attenuation bias under some conditions. The paper provides evidence of LoSE in US GDP growth during the period known as the Great Moderation (roughly the mid-1980s to the mid-2000s), illustrating attenuation bias in regressions of GDP growth on asset prices. These biases may have contributed to conventional macroeconomic analysis missing the severity of the adverse shocks hitting the economy in the Great Recession.

A number of researchers have recently argued that the growth of the shadow banking system in the years preceding the recent U.S. financial crisis was driven by rising demand for "money-like" claims—short-term, safe instruments (STSI)—from institutional investors and nonfinancial firms. These instruments carry a money premium that lowers their yields. While government securities are an important part of the supply of STSI, financial intermediaries also take advantage of this money premium when they issue certain types of low-risk, short-term debt, such as asset-backed commercial paper or repo. In this paper, we take the demand for STSI as given and consider the extent to which central banks can improve financial stability and manage maturity transformation by the private sector through their ability to affect the public supply of STSI. The first part of the paper provides new evidence that complements the existing literature on two key ingredients that are necessary for there to be a role for policy: the extent to which public short-term debt and private short-term debt might be substitutes, and the relationship between the money premium and the supply of STSI. The second part of the paper then builds on this evidence and discusses potential ways a central bank could use its balance sheet and monetary policy implementation framework to affect the quantity and mix of short-term liquid assets that will be available to financial market participants.

This paper outlines a model of demand segmentation in the federal funds market with two types of borrowers - the "interest on reserves (IOR) arbitrage'' type and the "regulatory'' type - which have different reservation prices and cannot always be separated. When fed funds trade above IOR, the "regulatory" type is revealed and consequently pays an interest rate closer to its real reservation price, pushing the fed funds rate further up. When fed funds trade below IOR, a decrease in the fed funds rate encourages entry in the market for IOR arbitrage purposes thus counteracting the downward pressure on the fed funds rate. We use probit regression models and daily data for the period April 2018 to February 2020 to provide empirical support for this model. We find the following: 1) When fed funds trade above IOR, there is, on average, a 10 percentage points increase in the probability that the fed funds rate increases the following period. Furthermore, analysis using confidential bank-level data shows that this increase in the probability is higher for banks that report their liquidity profile daily and that were present all trading days during this period. 2) When the fed funds trade below IOR, the probability of a decrease in the fed funds rate decreases with the widening of the spread between the fed funds rate and IOR.

The stringency of bank liquidity and capital requirements should depend on their social costs and benefits. This paper investigates their welfare effects and quantifies their welfare costs using sufficient statistics. The special role of banks as liquidity providers is embedded in an otherwise standard general equilibrium growth model. Capital and liquidity requirements mitigate moral hazard from deposit insurance, which, if unchecked, can lead to excessive credit and liquidity risk at banks. However, these regulations are also costly because they reduce the ability of banks to create net liquidity and can distort investment. Equilibrium asset returns reveal the strength of demand for liquidity, yielding two simple sufficient statistics that express the welfare cost of each requirement as a function of observable variables only. Based on U.S. data, the welfare cost of a 10 percent liquidity requirement is equivalent to a permanent loss in consumption of about 0.02%, a modest impact. Even using a conservative estimate, the cost of a similarly-sized increase in the capital requirement is roughly ten times as large. Even so, optimal policy relies on both requirements, as the financial stability benefits of capital requirements are found to be broader.

This paper provides an overview of the literature examining how the introduction of a CBDC would affect the banking sector, financial stability, and the implementation and transmission of monetary policy in a developed economy such as the United States. A CBDC has the potential to improve welfare by reducing financial frictions in deposit markets, by boosting financial inclusion, and by improving the transmission of monetary policy. However, a CBDC also entails noteworthy risks, including the possibility of bank disintermediation and associated contraction in bank credit, as well as potential adverse effects on financial stability. A CBDC also raise important questions regarding monetary policy implementation and the footprint of central banks in the financial system. Ultimately, the effects of a CBDC depend critically on its design features, particularly remuneration.

As of October 2022, the retired share of the U.S. population was nearly 1½ percentage points above its pre-pandemic level (after adjusting for updated population controls to the Current Population Survey), accounting for nearly all of the shortfall in the labor force participation rate. In this paper, we analyze the pandemic-era rise in retirements using a model that accounts for pre-pandemic trends in retirement, the cyclicality of retirement, and other factors. We show that: more than half of the increase in the retired share are “excess retirements” that would likely not have occurred in the absence of the pandemic; excess retirements have been concentrated among cohorts age 65 and older at the start of the pandemic; excess retirements have been largest among the college-educated and whites; and excess retirements reflect in part that worker transitions from the labor force to retirement remain elevated. We also show that failing to account for updated population controls to the Current Population Survey leads to an underestimate of the rise in the retired share over the last few years. We use a cohort-based framework to argue that looking forward, unless the pandemic has permanently affected retirement behavior, excess retirements should eventually fade as those who retired early during the pandemic reach ages when they would have normally retired. Even as excess retirements fade, the retired share will remain well above its pre-pandemic level, reflecting population aging.

Does going public affect the amount and type of corporate tax planning? Using a panel of U.S. corporate tax return data from 1994 to 2018, we show that IPO completion is associated with the implementation of multinational income shifting strategies central to the current international tax policy debate. Specifically, firms (i) expand their foreign tax haven presence, (ii) enter into cross-border agreements that accompany intangible asset transfers to foreign subsidiaries, and (iii) increase their level of foreign related-party payments around the time that they go public. The effects are strongest among firms that switch to more sophisticated tax advisors in the years preceding the IPO. In contrast, we observe little domestic tax planning because large stock option deductions, which increase as a consequence of the IPO, provide large domestic tax shields. The paper contributes to the nascent literature studying IPOs by documenting the types and timing of specific tax strategies that enable public firms to remain lightly taxed in the post-IPO period. Furthermore, the findings imply that U.S. tax policies targeted at early-stage innovative firms are critical for retaining domestically developed IP – and the income earned on such assets – for the U.S. tax base.

It is difficult to assess the effectiveness of investment strategies that screen companies based on environmental criteria to hedge climate change risk because physical risks have not yet fully materialized and policies to combat climate change are usually widely anticipated. This paper sidesteps these limitations by analyzing the stock market response to plausibly exogenous changes in expectations about the level of a carbon tax in Germany. The risk-adjusted return on two sustainable investment approaches---screening companies based on environmental scores and on firms' carbon footprint---around the carbon tax news reveals that firms with a high environmental score did not perform any better than those with a low environmental score. In contrast, the stock price of firms with low carbon emissions increased in value relative to those with a high carbon footprint. Carbon intensity explains the cross-sectional reaction to the carbon tax news because it predicts revisions in expected profitability.

This paper builds a micro-founded general equilibrium model of hysteresis in which changing composition of firms with heterogeneous qualities in response to demand shocks alter the total factor productivity of the economy through a process of "creative destruction". Hysteresis fundamentally challenges existing consensus on stabilization policies: the complete stabilization of demand shocks becomes suboptimal as demand creates its own supply; fiscal multiplier can be substantially larger than 1; an opportunistic monetary policymaker, who adopts a lenient policy reaction to positive demand shocks, but provides decisive monetary stimulus in response to negative demand shocks, can bring large welfare gains.

This paper presents a stylized framework to assess conceptually how the financial risks of climate change could interact with a regulatory capital regime. We summarize core features of a capital regime such as expected and unexpected losses, regulatory ratios and risk-weighted assets, and minimum requirements and buffers, and then consider where climate-related risk drivers may be relevant. We show that when considering policy implications, it is critically important to be precise about how climate change may impact the loss-generating process for banks and to be clear about the specific policy objective. While climate change could potentially impact the regulatory capital regime in several ways, an internally coherent approach requires a strong link between specific assumptions and beliefs about how these financial risks may manifest as bank losses and what objectives regulators are pursuing. We conclude by identifying several potential research opportunities to better understand these complex issues and inform policy development.

This paper considers the use of the Federal Reserve’s ability to provide loans to depository institutions under its discount window lending authority in support of achieving its monetary policy objectives through a funding for lending program. Broadly, a funding for lending program could be structured as one in which the Federal Reserve makes ample low-cost funding available to banks or a program in which the Federal Reserve only provides low-cost funding conditional on the banks meeting certain lending targets. We provide a general description of how a funding for lending program could be structured along each of these lines and review important considerations, costs, and benefits of any such program. We also review the literature regarding various lending programs implemented previously in the United States by a variety of agencies and abroad by foreign central banks that shed light on the potential effectiveness of funding for lending programs.

This paper develops a method to approximate arbitrage-free bond yields within a term structure model in which the short rate follows a Gaussian process censored at zero (a shadow-rate model as proposed by Black, 1995). The censoring ensures that model-implied yields are constrained to be positive, but it also introduces non-linearity that renders standard bond pricing formulas inapplicable. In particular, yields are not linear functions of the underlying state vector as they are in affine term structure models (see Piazzesi, 2010). Existing approaches towards computing yields in shadow-rate models suffer from high computational burden or low accuracy. In contrast, I show that the technique proposed in this paper is sufficiently fast for single-step estimation of a three-factor shadow-rate term structure model, and sufficiently accurate to evaluate yields to within approximately half a basis point.

In this paper, we formulate and solve a New Keynesian model with monetary and fiscal policy rules whose coefficients are time-varying and interdependent. We implement time variation in the policy rules by specifying coefficients that are logistic functions of correlated latent factors and propose a solution method that allows for these characteristics. The paper uses Bayesian methods to estimate the policy rules with time-varying coefficients, endogeneity, and stochastic volatility in a limited-information framework. Results show that monetary policy switches regime more frequently than fiscal policy, and that there is a non-negligible degree of interdependence between policies. Policy experiments reveal that contractionary monetary policy lowers inflation in the short run and increases it in the long run. Also, lump-sum taxes affect output and inflation, as the literature on the fiscal theory of the price level suggests, but the effects are attenuated with respect to a pure fiscal regime.

This paper examines the geographic variation in Medicare and non-Medicare health spending and finds little support for the view that most of the variation is attributable to differences in practice styles. Instead, I find that socioeconomic factors that affect the need for medical care, as well as interactions between the Medicare system, Medicaid, and private health spending, can account for most of the variation in Medicare spending. Furthermore, I find that the health spending of the non-Medicare population is not well correlated with Medicare spending, suggesting that Medicare spending is not a good proxy for average health spending by state. Finally, there is a negative correlation between the level and growth of Medicare spending: Low-spending states are not low-growth states and are thus unlikely to provide the key to curbing excess cost growth in Medicare. The paper also explores the econometric differences between controlling for health attributes at the state level vs the individual level. I show that a state-level approach is better at controlling for health attributes and argue that this econometric difference likely explains most of the difference between my results and those of the Dartmouth group. More broadly, the paper shows that the geographic variation in health spending does not provide a useful measure of the inefficiencies of our health system. States where Medicare spending is high are very different in multiple dimensions from states where Medicare spending is low, and thus it is difficult to isolate the effects of differences in health spending intensity from the effects of the differences in the underlying state characteristics. I show, for example, that the relationships between health spending, physician composition and quality are likely the result of omitted factors rather than the result of causal relationships.

There are large differences between the microeconometric estimates of the Frisch labor supply elasticity (0-0.5) and the values used by macroeconomists to calibrate general equilibrium models (2-4). The microeconometric estimates of the Frisch are typically estimated by regressing changes in hours on changes in wages conditional on the individual being a married male head of household, working some minimum number of hours and being of prime working age. In contrast macroeconomic calibration values are typically set such that fluctuations in a general equilibrium model match the observed changes in the aggregate hours and wages from the whole population over time. This paper aims to explain the gap by estimating an aggregate Frisch elasticity which is consistent with the concept of macro calibration values using the microeconometric techniques. In order to estimate the Frisch consistent with the macro concept, this paper alters the typical microeconometric approach in order to incorporate fluctuations on the extensive margin and also broadens the scope of the sample to include single males, females, secondary earners, young individuals, and old individuals. This paper finds that estimates of the aggregate macro Frisch elasticity are in the middle of the range of macroeconomic calibration values (around 3.0). Furthermore, it finds that the key to explaining the difference are the fluctuations on the extensive margin of single males, females, secondary earners, older individuals, and younger individuals.

This paper uses US state panel data to explore the relationship between the share of income received by affluent households and the level of income and earnings received by low and middle-income families. A rising top share of income can potentially lead to increases in the incomes of low and middle-income families if economic growth is sufficiently responsive to increases in inequality. A substantial literature on the impacts of inequality on economic growth exists, but has failed to achieve consensus, with various studies finding positive impacts, negative impacts, and no impacts on growth from increased levels of income inequality. This paper departs from that literature by exploring the effect of inequality on the standard of living of middle-income and low-income families. In the context of rising inequality, increased overall growth is not necessarily a suitable proxy for overall standard of living, since growth patterns are not always uniform for the entire income distribution. The results of this study indicate that increases in the top share of income (particularly the top one percent) are associated with declines in the actual incomes (and earnings) of middle income families, but have no clear impact on families at the bottom of the income distribution.

The financial industry, like many others, is powered by information and data. A number of government agencies, quasi-government agencies, and private companies collect, process, use, and distribute information about a variety of players in the financial world. While the subjects of the data (balance sheet items or counterparty information, for example) may vary dramatically by agency and use, they all describe a particular financial institution or legal entity. Yet a standard way to uniquely identify one financial entity from another does not currently exist. A Social Security number distinguishes one John Smith from another John Smith, but at present no single identifier distinguishes one First National Bank from another. Several private companies have developed proprietary identifiers created for their own purposes but none of those identifiers are industry-wide, universal, or strictly focused on identifying a specific institution. A diverse group of analysts from the Board of Governors of the Federal Reserve System, Federal Reserve Bank of New York, Commodity Futures Trading Commission (CFTC), Federal Deposit Insurance Corporation (FDIC), Financial Industry Regulatory Authority (FINRA), Securities and Exchange Commission (SEC), and Treasury have developed guidelines detailing the best way the industry might create, develop, and maintain such a crucial identifier. The paper summarizes the current environment of entity identification and the problems that are currently encountered in both the private and public sectors by the lack of an industry-wide identifier. The paper identifies the key components that should be incorporated into the LEI such as uniqueness, persistence, and public availability. The paper identifies possible alternative approaches to solving the LEI problem and supports a collaborative public and private sector approach. The paper also considers the need for an international solution, as financial markets grow ever more interconnected across the globe.

This paper describes the E-Newton and E-QNewton algorithms for solving rational expectations (RE) models. Both algorithms treat a model's RE terms as exogenous variables whose values are iteratively updated until they (hopefully) satisfy the RE requirement. In E-Newton, the updates are based on Newton's method E-QNewton uses an efficient form of Broyden's quasi-Newton method. The paper shows that the algorithms are reliable, fast enough for practical use on a mid-range PC, and simple enough that their implementation does not require highly specialized software. The evaluation of the algorithms is based on experiments with three well-known macro models--the Smets-Wouters (SW) model, EDO, and FRB/US--using code written in EViews, a general-purpose, easy-to-use software package. The models are either linear (SW and EDO) or mildly nonlinear (FRB/US). A test of the robustness of the algorithms in the presence of substantial nonlinearity is based on modified versions of each model that include a smoothed form of the constraint that the short-term rate of interest cannot fall below zero. In two single-simulation experiments with the standard and modified versions of the models, E-QNewton is found to be faster than E-Newton, except for solutions of small-to-medium sized linear models. In a multi-simulation experiment using the standard versions of the models, E-Newton dominates E-QNewton.

FRB/US, a large-scale, nonlinear macroeconomic model of the U.S., has been in use at the Federal Reserve Board for 25 years. For nearly as long, the FRB/US “project” has included a linear version of the model known as LINVER. A key reason that LINVER exists is the vast reduction in the computational costs that linearity confers when running experiments requiring large numbers of simulations under the assumption that expectations are model-consistent (MC). The public has been able to download FRB/US simulation code, documentation, and data from the Federal Reserve Board’s website since 2014. To further expand access to and understanding of the FRB/US project, a package devoted to LINVER is now available on the website. In this paper, we provide both a general introduction to LINVER and an overview of the contents and capabilities of its package. We review the ways that LINVER has been used in past research to study key policy issues; describe the package’s comprehensive set of programs for running simulations with MC expectations, with or without imposing the effective lower bound (ELB) on the federal funds rate and other nonlinear constraints; and illustrate how LINVER deterministic and stochastic simulations can be used to gauge the implications of the ELB for macroeconomic performance and to assess different strategies for mitigating its adverse effects.

The Federal Reserve Board has published extensive statistical information on the U.S. economy and banking industry since 1914. This information has been published in various formats, usually referred to as “statistical releases.” The titles and release numbers of the publications have changed frequently. Federal Reserve Board Statistical Releases: A Publications History describes these changes; it is a convenient tool that lightens the burden of tracing the titles and release numbers by providing their history in a single location. This revision updates a previous paper published in 2016. It contains content changes for various statistical releases from 2016 to 2022.