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Many ocean economic activities are not readily visible in official statistics, hindering policymakers' access to crucial information for decision making. The OECD ocean economy measurement project aims to address this by aligning ocean economy statistics with broader economic data and ensuring international consistency. This paper compares the measurement strategies of eight OECD member countries using principles from the system of national accounts. It also highlights the ocean economy thematic accounts of four countries and summarises their methods. The paper concludes with recommendations for integrating ocean economy measurements with national accounting standards, a vital step for improving the evidence base for ocean policymaking. [ABSTRACT FROM AUTHOR]

This paper provides evidence and insights on the main demographic trends and challenges in cities across OECD countries, with a focus on G7 cities. The paper also draws implications for urban policy and city-specific examples to address the negative effects of demographic change, with a view to building more inclusive, sustainable, and resilient cities. Preliminary findings from the paper served as input to the G7 Ministerial Meeting on Sustainable Urban Development (7-9 July 2023, Takamatsu, Japan) under the G7 Japanese Presidency. [ABSTRACT FROM AUTHOR]

This paper examines the role of uncertainty on elasticities of trade flows with respect to variable trade costs in a canonical model of trade with monopolistic competition and heterogeneous firms. We identify two channels through which uncertainty impacts trade: through export participation thresholds (the selection effect) and the distribution of shocks governing export selection (the dispersion effect). While the selection effect dampens trade elasticities under uncertainty, the dispersion effect is ambiguous. We develop a methodology for using customs firm-level data to quantify trade elasticities under uncertainty, and the magnitude of each of the two channels through which uncertainty impacts trade. We find that uncertainty amplifies trade elasticities, on average, indicating that the dispersion effect of idiosyncratic firm-level shocks dominates - though the effect is heterogeneous across industries. The overall magnitude of the endogenous selection mechanism on trade elasticities is small, indicating that the main drivers of trade in this class of trade models are overwhelmingly incumbent firms. [ABSTRACT FROM AUTHOR]

It is common in applied work to estimate responses of macroeconomic aggregates to news shocks derived from surprise changes in daily futures prices around the date of policy announcements. This requires mapping the daily surprises into a monthly shock that may be used as an external instrument in a monthly VAR model or local projection. The standard approach has been to sum these daily surprises over the course of a given month when constructing the monthly proxy variable, ignoring the accounting relationship between daily and average monthly price data. In this paper, I provide a new approach to constructing monthly proxies from daily surprises that takes account of this link and revisit the question of how to use OPEC announcements to identify news shocks in VAR models of the global oil market. The proposed approach calls into question the interpretation of the identified shock as oil supply news and implies quantitatively and qualitatively different estimates of the macroeconomic impact of OPEC announcements. [ABSTRACT FROM AUTHOR]

The past 15 years have been eventful. The Global Financial Crisis (GFC) reminded us of the importance of a stable financial system to a well-functioning economy, one with low and stable inflation and maximum employment. Given the recent banking stress, we ponder this issue again. The pandemic was a huge shock surrounded by much uncertainty, making precise forecasts within traditional models difficult. And more recently, there has been continuous talk of a soft landing and recession risks. In this paper, I focus on some of the lessons we have learned over the years: (i) uncertainty and tail risk have cyclical variation; (ii) financial shocks can have a significant effect on macroeconomic outcomes; (iii) the impact of shocks is stronger in periods of high volatility. These lessons have important implications for policymakers in today's environment. [ABSTRACT FROM AUTHOR]

This paper reviews literature on the empirical relationship between vulnerabilities in the financial system and the macroeconomy, and how monetary policy affects that connection. Financial vulnerabilities build up over time, with both risk appetite and risk taking rising during economic expansions. To some extent, financial crises are predictable and have severe real economic consequences when they occur. Empirically it is difficult to link monetary policy to financial vulnerabilities, in part because financial cycles have long durations, making it difficult to separate effects of changes in monetary policy from other business cycle effects. [ABSTRACT FROM AUTHOR]

In a simple New Keynesian open economy setting, we analyze how local input shortages influence policy transmission and equilibrium determinacy. Shortages increase the elasticity of the local price of the scarce factor to domestic economic activity, affecting the cyclicality of marginal costs and incomes. As a result, the slope of both the Phillips and the IS curve is altered, crucially influencing monetary and fiscal policy transmission. These changes are affected by factor ownership and propensities to consume. Theoretically, shortages can also raise the risk of self-fulfilling fluctuations if a rising price of the constrained factor boosts incomes for agents with high propensities to consume. We illustrate these channels for the 2022 German energy crisis. [ABSTRACT FROM AUTHOR]

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In this paper, we revisit the scope for macroprudential policy in production economies with pecuniary externalities and collateral constraints. We study competitive equilibria and constrained-efficient equilibria and examine the extent to which the gap between the two depends on the production structure and the policy instruments available to the planner. We argue that macroprudential policy is desirable regardless of whether the competitive equilibrium features more or less borrowing than the constrained-efficient equilibrium. In our quantitative analysis, macroprudential taxes on borrowing turn out to be larger when the government has access to ex-post stabilization policies. [ABSTRACT FROM AUTHOR]

Congressional districts are political entities with heterogeneous trade policy preferences due to their diverse economic structures. Representation of these interests in Congress is a crucial aspect of trade policymaking that is missing in canonical political economy models of trade. In this paper, we underscore the influence of districts by developing a political economy model of trade with region-specific factors. Using 2002 data from U.S. Congressional Districts, we first characterize the unobserved district-level demand for protection. Extending the model beyond the small country assumption to account for export interests as a force countering protection, we develop a model of national tariff-setting. The model predictions are used to estimate the welfare weights implied by tariff and non-tariff measures enacted nationally. Our supply-side explanation for trade policy, while complementing Grossman and Helpman (1994), reveals district and industry-level patterns of winners and losers, central to understanding the political consequences of trade and the backlash against globalization. [ABSTRACT FROM AUTHOR]

We show that inflation expectations are heterogeneous and depend on past individual experiences. We propose a diagnostic expectations-augmented Kalman filter to represent consumers' heterogeneous inflation expectations-formation process, where heterogeneity comes from an anchoring-to-the-past mechanism. We estimate the diagnosticity parameter that governs the inflation expectations-formation process and show that the model can replicate systematic differences in inflation expectations across cohorts in the US. We introduce this mechanism into a New Keynesian model and find that heterogeneous expectations anchor aggregate responses to the agents' memory, making shocks more persistent. Central banks should be more active to prevent agents from remembering current shocks far into the future. [ABSTRACT FROM AUTHOR]

Recent decades have seen advances in using econometric methods to produce more timely and higher-frequency estimates of economic activity at the national level, enabling better tracking of the economy in real time. These advances have not generally been replicated at the sub-national level, likely because of the empirical challenges that nowcasting at a regional level presents, notably, the short time series of available data, changes in data frequency over time, and the hierarchical structure of the data. This paper develops a mixed-frequency Bayesian VAR model to address common features of the regional nowcasting context, using an application to regional productivity in the UK. We evaluate the contribution that different features of our model provide to the accuracy of point and density nowcasts, in particular the role of hierarchical aggregation constraints. We show that these aggregation constraints, imposed in stochastic form, play a key role in delivering improved regional nowcasts; they prove to be more important than adding region-specific predictors when the equivalent national data are known, but not when this aggregate is unknown. [ABSTRACT FROM AUTHOR]

This paper reviews the theoretical literature at the intersection of macroeconomics and finance to draw lessons on the connection between vulnerabilities in the financial system and the macroeconomy, and on how monetary policy affects that connection. This literature finds that financial vulnerabilities are inherent to financial systems and tend to be procyclical. Moreover, financial vulnerabilities amplify the effects of adverse shocks to the economy, so that even a small shock to fundamentals or a small revision of beliefs can create a self-reinforcing feedback loop that impairs credit provision, lowers asset prices, and depresses economic activity and inflation. Finally, monetary policy may affect the buildup of vulnerabilities, but the sign of the impact along some of its transmission channels is theoretically ambiguous and may vary with the state of the economy. [ABSTRACT FROM AUTHOR]

This paper reviews the theoretical literature at the intersection of macroeconomics and finance to draw lessons on the connection between vulnerabilities in the financial system and the macroeconomy, and on how monetary policy affects that connection. This literature finds that financial vulnerabilities are inherent to financial systems and tend to be procyclical. Moreover, financial vulnerabilities amplify the effects of adverse shocks to the economy, so that even a small shock to fundamentals or a small revision of beliefs can create a self-reinforcing feedback loop that impairs credit provision, lowers asset prices, and depresses economic activity and inflation. Finally, monetary policy may affect the buildup of vulnerabilities, but the sign of the impact along some of its transmission channels is theoretically ambiguous and may vary with the state of the economy. [ABSTRACT FROM AUTHOR]

We document a sizable effect of oil price fluctuations on US banking variables by estimating an SVAR with sign restrictions as in Baumeister and Hamilton (2019). We find that oil market shocks that lead to a contraction in world economic activity unambiguously lower the amount of bank credit to the US economy, tend to decrease US banks' net worth, and tend to increase the US credit spread. The effects can be strong and long-lasting, or more modest and short-lived, depending on the source of the oil price fluctuations. The effects are stronger for smaller and lower leveraged banks. [ABSTRACT FROM AUTHOR]

This paper studies the effectiveness of government-backed credit guarantees to the infrastructure sector, a policy tool adopted by a range of countries during recessions. We propose a two-sector model with financial intermediary frictions so that infrastructure producers rely on bank loans to finance their risky production. Governments can intervene in the credit market by providing a partial guarantee on those bank loans. We find that a credit guarantee increases infrastructure production, leading to a high fiscal multiplier in the longer run. In the near term, however, higher wages in the infrastructure sector crowd out labor supply in the private sector, dampening economic activity. Importantly, the higher leverage associated with credit expansion raises non-performing loans, and this channel is particularly pronounced if the government-backed credit guarantee lingers for a long period of time. [ABSTRACT FROM AUTHOR]

The Texas Manufacturing Outlook Survey (TMOS) is a monthly survey of area manufacturers conducted by the Federal Reserve Bank of Dallas. TMOS indexes provide timely information on manufacturing activity in Texas, which is useful for understanding broader changes in regional economic conditions. This paper describes the survey methodology and analyzes the explanatory and predictive power of TMOS indexes with regard to other measures of state economic activity. Regression analysis shows that several TMOS indexes successfully track changes in Texas employment, gross domestic product and consumer price index. Forecasting exercises show that several TMOS indexes are also useful in predicting future changes in some of these regional economic indicators. [ABSTRACT FROM AUTHOR]

We assess the impacts from physical hazards (or severe weather events) on economic activity in a panel of 98 countries using local projection methods. Proxying the strength of an event by the monetary damages it caused, we find severe weather events to reduce the level of GDP. For most events in the EM-DAT data set the effects are small. The largest events in our sample (above the 90th percentile of damages) bring down the level of GDP by 0.5 percent for several years without recovery to trend. Smaller events (below the 90th percentile) see a less immediate decrease in initial years (0.1 percent) that progressively widens to become similar to the effect of larger disasters after 10 years. Climatological hazards (droughts and forest fires) appear to have the largest effects. These findings are robust across country groupings by development and alternative measures of the strength of the physical hazard. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of vaccine administration on three main dimensions of activity: spending, mobility, and employment. Our investigation combines two parts. First, we exploit the variation in vaccine administration across states. In panel regressions that include a large set of controls, we find that the rollout has a significant impact on spending, while the results on mobility and employment are mixed. Second, to address concerns of endogeneity, we look at the impact of vaccine lotteries on spending. Using a dynamic event design setting, we find that lotteries have significantly boosted vaccination rates about a week after announcement, with an effect that lasts over the next several days and increases new vaccinations between 3.5 and 5 percent. This boost in vaccination rates, in turn, translates into a significant increase in retail spending, which is larger and somewhat more persistent than what we document in our state-level panel regressions. All told, our findings imply that the vaccine rollout added, on average, 0.5 percentage point to GDP growth in 2021. [ABSTRACT FROM AUTHOR]

This paper clarifies the conditions under which the state-of-the-art approach to identifying TFP news shocks in Kurmann and Sims (2021, KS) identifies not only news shocks but also surprise shocks. We examine the ability of the KS procedure to recover responses to these shocks from data generated by a conventional New Keynesian DSGE model. Our analysis shows that the KS response estimator tends to be strongly biased even in the absence of measurement error. This bias worsens in realistically small samples, and the estimator becomes highly variable. Incorporating a direct measure of TFP news into the model and adapting the identification strategy accordingly removes this asymptotic bias and greatly reduces the RMSE when TFP news are correctly measured. However, the high variability of this alternative estimator in small samples suggests caution in interpreting empirical estimates. We examine to what extent empirical estimates of the responses to news and surprise shocks from a range of VAR models based on alternative measures of TFP news are economically plausible. [ABSTRACT FROM AUTHOR]

This paper shows how policy announcements can be used to manage expectations and have a role as a policy tool. Using regional variation in radio exposure, I evaluate the impact of President Franklin D. Roosevelt's 1935 Fireside Chat, in which he showcased the introduction of important social policies, establishing a new cycle of the New Deal. I document that cities with higher exposure to the announcement exhibited a significant increase in spending on durable goods. I provide evidence that this result is not driven by wealth or other potentially confounding variables. The estimated effect is consistent with changes in expectations toward the policies announced. This paper shows the power of communication as a policy tool in affecting economic activity. [ABSTRACT FROM AUTHOR]

We study the reaction of voters to shifts in local economic conditions. Using the departure from the gold standard of US trading partners in 1931 and the US in 1933, we exploit heterogeneity in export destinations, creating local differences in expenditure-switching in US counties by isolating the aggregate effects of the monetary shocks using time fixed effects. We find significant changes in local voting behavior in response to both shocks, one originating abroad, and another domestically. The response to both shocks have similar magnitude. We argue that voters punished and rewarded incumbents regardless of the shocks' origin, implying strong feedback from economic conditions to electoral outcomes. [ABSTRACT FROM AUTHOR]

There is substantial asymmetry in effective corporate income tax rates across firms. While tax asymmetries would reduce productivity in frictionless economies, they can improve efficiency in a distorted economy if taxes alleviate other economic frictions. We develop a framework to estimate to what extent tax asymmetries affect productivity in distorted economies. Using US firm-level balance sheet data alongside measures of effective marginal tax rates, we find a positive correlation between tax rates and factor productivity, suggesting that tax asymmetry exacerbates the distortions from other economic frictions. Eliminating tax rate asymmetries would raise aggregate productivity by 3 to 4 percent if taxes distort capital costs alone. Models where taxes also distort the marginal cost of labor predict potential gains as high as 9 percent. [ABSTRACT FROM AUTHOR]

Since the 1970s, exports and imports of manufactured goods have been the engine of international trade and much of that trade relies on container shipping. This paper introduces a new monthly index of the volume of container trade to and from North America. Incorporating this index into a structural macroeconomic VAR model facilitates the identification of shocks to domestic U.S. demand as well as foreign demand for U.S. manufactured goods. We show that, unlike in the Great Recession, the primary determinant of the U.S. economic contraction in early 2020 was a sharp drop in domestic demand. Although detrended data for personal consumption expenditures and manufacturing output suggest that the U.S. economy has recovered to near 90% of prepandemic levels as of March 2021, our structural VAR model shows that the component of manufacturing output driven by domestic demand had only recovered to 57% of prepandemic levels and that of real personal consumption only to 78%. The difference is mainly accounted for by unexpected reductions in frictions in the container shipping market. [ABSTRACT FROM AUTHOR]

This paper quantifies the relationship between local opioid prescription rates and labor market outcomes in the United States between 2006 and 2016. To understand this relationship at the national level, we assemble a data set that allows us both to include rural areas and to estimate the relationship at a disaggregated level. We control for geographic variation in both short-term and long-term economic conditions. In our preferred specification, a 10 percent higher local prescription rate is associated with a lower prime-age labor force participation rate of 0.53 percentage points for men and 0.10 percentage points for women. We focus on measuring the impact of opioid prescriptions on labor markets, so we evaluate the robustness of our estimates to an alternative causal path, unobserved selection, and an instrumental variable from the literature. [ABSTRACT FROM AUTHOR]

Widespread adoption of just-in-time (JIT) production has reduced inventory holdings. This paper finds that JIT creates a trade-off between firm profitability and vulnerability to large shocks. Empirically, JIT adopters experience higher sales and less volatility while also exhibiting heightened cyclicality and sensitivity to natural disasters. I explain these facts in a structurally estimated general equilibrium model where firms can adopt JIT. Relative to a no-JIT economy, the estimated model implies a 1.3% increase in firm value. At the same time, an unanticipated shock results in a roughly 15% deeper output contraction. This occurs because firms "stock out" or hoard materials. [ABSTRACT FROM AUTHOR]

This paper develops a quantitative life cycle model in which economic decisions impact the spread of COVID-19 and, conversely, the virus affects economic decisions. The calibrated model is used to measure the welfare costs of the pandemic across the age, income, and wealth distribution and to study the effectiveness of various mitigation policies. In the absence of mitigation, young workers engage in too much economic activity relative to the social optimum, leading to higher rates of infection and death in the aggregate. The paper considers a subsidy-and-tax policy that imposes a tax on consumption and subsidizes reduced work compared to a lockdown policy that caps work hours. Both policies are welfare improving and lead to less infections and deaths. Notably, almost all agents favor the subsidy-and-tax policy, suggesting that there need not be a tradeoff between saving lives and economic welfare. [ABSTRACT FROM AUTHOR]

Some key structural features of the U.S. economy appear to have changed in the recent decades, making the conduct of monetary policy more challenging. In particular, there is high uncertainty about the levels of the natural rate of interest and unemployment as well as about the effect of economic activity on inflation. At the same time, a prolonged period of below-target inflation has raised concerns about the unanchoring of inflation expectations at levels below the Federal Open Market Committee's inflation target. In addition, a low natural rate of interest increases the probability of hitting the effective lower bound during a downturn. This paper studies how these factors complicate the attainment of the objectives specified in the Federal Reserve's dual mandate in the context of a DSGE (dynamic stochastic general equilibrium) model, taking into account risk-management considerations. We find that these challenges may warrant pursuing more accommodative policy than would be desirable otherwise. However, such accommodative policy could be associated with concerns about risks to financial markets. [ABSTRACT FROM AUTHOR]

In the December 2022 Summary of Economic Projections (SEP), the median projection for four-quarter core PCE inflation in the fourth quarter of 2025 is 2.1 percent. This same SEP has unemployment rising by nine-tenths, to 4.6 percent, by the end of 2023. We assess the plausibility of this projection using a specific nonlinear model that embeds an empirically successful nonlinear Phillips curve specification into a structural model, identifying it via an underutilized data-dependent method. We model core PCE inflation using three components that align with those noted by Chair Powell in his December 14, 2022, press conference: housing, core goods, and core-services-less-housing. Our model projects that conditional on the SEP unemployment rate path and a rapid deceleration of core goods prices, core PCE inflation moderates to only 2.75 percent by the end of 2025: inflation will be higher for longer. A deep recession would be necessary to achieve the SEP's projected inflation path. A simple reduced-form welfare analysis, which abstracts from any danger of inflation expectations becoming unanchored, suggests that such a recession would not be optimal. [ABSTRACT FROM AUTHOR]

In this paper, I develop a systemic risk measure derived from investor sentiment that has predictive power over future economic activity and market returns. Unlike existing measures, it is not focused on flagging investors' heightened awareness of risk at the end of a boom episode but rather on capturing shifts in their trading behavior at the beginning of the episode. The method allows investors and regulators to observe industries in which risks could be building and provides regulators some lead time in deploying their macroprudential tools. [ABSTRACT FROM AUTHOR]

This paper looks at the evolution of U.S. stock prices from the time of the Presidential elections to the end of 2017. It concludes that a bit more than half of the increase in the aggregate U.S. stock prices from the presidential election to the end of 2017 can be attributed to higher actual and expected dividends. A general improvement in economic activity and a decrease in economic policy uncertainty around the world were the main factors behind the stock market increase. The prospect and the eventual passage of the corporate tax bill nevertheless played a role. And while part of the rise in stock returns came from a decrease in the equity risk premium, this decrease was relatively limited and returned the premium to the levels of the first half of the 2000s. [ABSTRACT FROM AUTHOR]

This paper reports on the development and analysis of a newly constructed dataset on the early stages of business formation. The data are based on applications for Employer Identification Numbers (EINs) submitted in the United States, known as IRS Form SS-4 filings. The goal of the research is to develop high-frequency indicators of business formation at the national, state and local levels. The analysis indicates that EIN applications provide forward-looking and very timely information on business formation. The signal of business formation provided by counts of applications is improved by using the characteristics of the applications to model the likelihood that applicants become employer businesses. The results also suggest that EIN applications are related to economic activity at the local level. For example, application activity is higher in counties that experienced higher employment growth since the end of the Great Recession and application counts grew more rapidly in counties engaged in shale oil and gas extraction. Finally, the paper provides a description of new publicuse dataset, the "Business Formation Statistics (BFS)," that contains new data series on business applications and formation. The initial release of the BFS shows that the number of business applications in the 3rd quarter of 2017 that have relatively high likelihood of becoming job creators is still far below pre-Great Recession levels. [ABSTRACT FROM AUTHOR]

The financial and economic crisis was preceded by an energy, food and climate crisis. Until 2008, prices for oil, food and various minerals were increasing due to accelerating scarcity in peak capitalism. With the outbreak of the financial turbulences, the environmental problems shifted somewhat to the background, but various academics and policy makers emphasized the multiple nature of the current crisis. A number or organizations, subsequently, called for the adoption of a Green New Deal to tackle ecological and economic problems. The idea was that investments in energy efficiency and renewable energy production would improve ecological sustainability, while at the same time generating growth and creating jobs. Some organizations saw the adoption of a Green New Deal as a first step in a transition towards a green economy. This paper critically examines the content of various Green New Deal proposals and analyzes the nature of a green economy with respect to their impact on equality. The major finding is that current concepts to not address the unequal distribution of environmental and economic assets and even tend to fortify gender inequality. [ABSTRACT FROM AUTHOR]

This paper focuses on nowcasts of tail risk to GDP growth, with a potentially wide array of monthly and weekly information. We consider different models (Bayesian mixed frequency regressions with stochastic volatility, as well as classical and Bayesian quantile regressions) and also different methods for data reduction (either forecasts from models that incorporate data reduction or the combination of forecasts from smaller models). Our results show that, within some limits, more information helps the accuracy of nowcasts of tail risk to GDP growth. Accuracy typically improves as time moves forward within a quarter, making additional data available, with monthly data more important to accuracy than weekly data. Accuracy also typically improves with the use of financial indicators in addition to a base set of macroeconomic indicators. The better-performing models or methods include the Bayesian regression model with stochastic volatility, Bayesian quantile regression, some approaches to data reduction that make use of factors, and forecast averaging. In contrast, simple quantile regression performs relatively poorly. [ABSTRACT FROM AUTHOR]

This paper focuses on nowcasts of tail risk to GDP growth, with a potentially wide array of monthly and weekly information. We consider different models (Bayesian mixed frequency regressions with stochastic volatility, classical and Bayesian quantile regressions, quantile MIDAS regressions) and also different methods for data reduction (either forecasts from models that incorporate data reduction or the combination of forecasts from smaller models). Our results show that, within some limits, more information helps the accuracy of nowcasts of tail risk to GDP growth. Accuracy typically improves as time moves forward within a quarter, making additional data available, with monthly data more important to accuracy than weekly data. Accuracy also typically improves with the use of financial indicators in addition to a base set of macroeconomic indicators. The better-performing models or methods include the Bayesian regression model with stochastic volatility, Bayesian quantile regression, some approaches to data reduction that make use of factors, and forecast averaging. In contrast, simple quantile regression and quantile MIDAS regression perform relatively poorly. [ABSTRACT FROM AUTHOR]

To slow the spread of COVID-19, many countries are shutting down non-essential sectors of the economy. Older individuals have the most to gain from slowing virus diffusion. Younger workers in sectors that are shuttered have the most to lose. In this paper, we build a model in which economic activity and disease progression are jointly determined. Individuals differ by age (young and retired), by sector (basic and luxury), and by health status. Disease transmission occurs in the workplace, in consumption activities, at home, and in hospitals. We study the optimal economic mitigation policy of a utilitarian government that can redistribute across individuals, but where such redistribution is costly. We show that optimal redistribution and mitigation policies interact, and reflect a compromise between the strongly diverging preferred policy paths of different subgroups of the population. We find that the shutdown in place on April 12 is too extensive, but that a partial shutdown should remain in place through the fall. People prefer deeper and longer shutdowns if a vaccine is imminent, especially the elderly. [ABSTRACT FROM AUTHOR]

This paper focuses on tail risk nowcasts of economic activity, measured by GDP growth, with a potentially wide array of monthly and weekly information. We consider different models (Bayesian mixed frequency regressions with stochastic volatility, classical and Bayesian quantile regressions, quantile MIDAS regressions) and also different methods for data reduction (either the combination of forecasts from smaller models or forecasts from models that incorporate data reduction). The results show that classical and MIDAS quantile regressions perform very well in-sample but not out-of-sample, where the Bayesian mixed frequency and quantile regressions are generally clearly superior. Such a ranking of methods appears to be driven by substantial variability over time in the recursively estimated parameters in classical quantile regressions, while the use of priors in the Bayesian approaches reduces sampling variability and its effects on forecast accuracy. From an economic point of view, we find that the weekly information flow is quite useful in improving tail nowcasts of economic activity, with initial claims for unemployment insurance, stock prices, a term spread, a credit spread, and the Chicago Fed's index of financial conditions emerging as particularly relevant indicators. Additional weekly indicators of economic activity do not improve historical forecast accuracy but do not harm it much, either. [ABSTRACT FROM AUTHOR]

This paper examines the relationship between high-skill immigration and multinational activity. I assemble a novel firm-level dataset on high-skill visa applications and show that there is a large home-bias effect. Foreign multinational enterprises (MNEs) in the US tend to hire more migrant workers from their home countries compared to US firms. To quantify the general equilibrium implications for production and welfare, I build and estimate a quantitative model that includes trade, MNE production, and the migration decisions of high-skill workers. I use an instrumental variables approach to show that the relationship between immigration and MNEs proposed by the model holds in the data. The model is then used to run two counterfactual exercises. The first, evaluates the im- plications of a more restrictive immigration policy in the US. I find that MNEs play a significant role in how immigration affects the location of production and welfare. In the second counterfactual exercise, I increase the barriers to MNE production to calculate the welfare gains generated by MNEs. I show that a model not incorporating migration would overestimate the MNE welfare gains for high-skill workers by 35% and underesti- mate welfare gains for low-skill workers by 8%. [ABSTRACT FROM AUTHOR]

This paper integrates a financial accelerator mechanism à la Bernanke et al. (1999) and timevarying uncertainty into a Dynamic New Keynesian model. We examine the extent to which uncertainty and credit conditions interact with one another. The idea is that uncertainty aggravates the information asymmetry between lenders and borrowers, and worsens credit conditions. Already poor credit conditions amplify the effect of shocks (to both the mean and variance) on the aggregate economy. In our model, uncertainty modelled as time-varying stochastic volatility emerges from monetary policy (policy uncertainty), financial risks (microuncertainty), and the aggregate state of the economy (macro-uncertainty). Using a third order approximation, we find that micro-uncertainty has first order effects on economic activity through its direct impact on credit conditions. We also find that if credit conditions (as measured by the endogenous risk spread) are already poor, then additional micro-uncertainty shocks have even larger real effects. In turn, shocks to aggregate uncertainty (macro- and policy-uncertainty) have relatively small direct effects on aggregate economic activity. [ABSTRACT FROM AUTHOR]

We measure the effects of the COVID-19 outbreak on uncertainty, and we assess the consequences of the uncertainty for key economic variables. We use a large, heteroskedastic vector autoregression (VAR) in which the error volatilities share two common factors, interpreted as macro and financial uncertainty. Macro and financial uncertainty are allowed to contemporaneously affect the macroeconomy and financial conditions, with changes in the common component of the volatilities providing contemporaneous identifying information on uncertainty. The model includes additional latent volatility states in order to accommodate outliers in volatility, to reduce the influence of extreme observations from the COVID period. Our estimates yield large increases in macroeconomic and financial uncertainty since the onset of the COVID-19 period. These increases have contributed to the downturn in economic and financial conditions, but the contributions of uncertainty are small compared to the overall movements in many macroeconomic and financial indicators. That implies that the downturn is driven more by other dimensions of the COVID crisis than shocks to aggregate uncertainty (as measured by our method). [ABSTRACT FROM AUTHOR]

This paper constructs a leading macroeconomic indicator from microeconomic data using recent machine learning techniques. Using tree-based methods, we estimate probabilities of default for publicly traded non-financial firms in the United States. We then use the cross-section of out-of-sample predicted default probabilities to construct a leading indicator of non-financial corporate health. The index predicts real economic outcomes such as GDP growth and employment up to eight quarters ahead. Impulse responses validate the interpretation of the index as a measure of financial stress. [ABSTRACT FROM AUTHOR]

This paper develops a theory of subjective beliefs that departs from rational expectations, and shows that biases in household beliefs have quantitatively large effects on macroeconomic aggregates. The departures are formalized using model-consistent notions of pessimism and optimism and are disciplined by data on household forecasts. The role of subjective beliefs is quantified in a business cycle model with goods and labor market frictions. Consistent with the survey evidence, an increase in pessimism generates upward biases in unemployment and inflation forecasts and lowers economic activity. The underlying belief distortions reduce aggregate demand and propagate through frictional goods and labor markets. As a by-product of the analysis, solution techniques that preserve the effects of time-varying belief distortions in the class of linear solutions are developed. [ABSTRACT FROM AUTHOR]

This paper constructs a leading macroeconomic indicator from microeconomic data using recent machine learning techniques. Using tree-based methods, we estimate probabilities of default for publicly traded non-financial firms in the United States. We then use the cross-section of out-of-sample predicted default probabilities to construct a leading indicator of non-financial corporate health. The index predicts real economic outcomes such as GDP growth and employment up to eight quarters ahead. Impulse responses validate the interpretation of the index as a measure of financial stress. [ABSTRACT FROM AUTHOR]

Business microdata have proven useful in a number of fields, but the main sources of comprehensive microdata are subject to significant confidentiality restrictions. A growing number of papers instead use a private data source seeking to cover the universe of U.S. business establishments, the National Establishment Time Series (NETS). Previous research documents the representativeness of NETS in terms of the distribution of employment and establishment counts across industry, geography, and establishment size. But there exists considerable need among researchers for microdata suitable for studying business dynamics--birth, growth, decline, and death. We evaluate NETS in terms of its ability to corroborate key insights from the business dynamics literature with a particular focus on the behavior of new and young firms. We find that NETS microdata exhibit patterns of business dynamics that are markedly different from official administrative sources, limiting the usefulness of NETS for studying these topics. [ABSTRACT FROM AUTHOR]

Considerable attention has been devoted to evaluating the macroeconomic effectiveness of the Federal Reserve's communications about future policy rates (forward guidance) in light of the U.S. economy's long spell at the zero lower bound (ZLB). In this paper, we study whether forward guidance represented a shift in the systematic description of monetary policy by estimating a New Keynesian model using Bayesian techniques. In doing so, we take into account the uncertainty that agents have about policy regimes using an incomplete information setup in which they update their beliefs using Bayes rule (Bayesian learning). We document a systematic change in U.S. policymakers' reaction function during the ZLB episode (2009-2016) that called for a persistently lower policy rate than in other regimes (we call this the forward guidance regime). Our estimates suggest that private sector agents were slow to learn about this change in real time, which limited the effectiveness of the forward guidance regime in stimulating economic activity and curbing disinationary pressure. We also show that the incomplete information specification of the model fits economic outcomes over the economy's long spell at the ZLB better than the full information specification. [ABSTRACT FROM AUTHOR]

A tailor-made survey documents consumer perceptions of the U.S. economy's response to a large shock: the advent of the COVID-19 pandemic. The survey ran at a daily frequency between March 2020 and July 2021. Consumer perceptions regarding output and inflation react rapidly. Uncertainty is pervasive. A business-cycle model calibrated to the consumer views provides an interpretation. The rise in household uncertainty amplifies the pandemic recession by a factor of three. Different perceptions about monetary policy can explain why consumers and professional forecasters agree on the recessionary impact, but have sharply divergent views about inflation. [ABSTRACT FROM AUTHOR]