This paper considers the impact of the coronavirus disease 2019 (COVID-19) pandemic on long-term individual lifetime consumption profiles. The framework for the analysis is a model that extends Strulik (2021) to include the government sector, where time preference is determined by individual health damage (deficit) distinct from normal aging. Thus, the health damage caused by COVID-19 changes the rate of time preference and consequently affects the Euler equation for consumption. Our theoretical contribution is the consistent incorporation of public health investment into the existing model to understand the effect of government measures against a pandemic. Numerical analysis based on this model is used to estimate changes in health status over time, trends in the rate of time preference, and individual lifetime consumption profiles, taking into account differences in age at the time of the pandemic and the nature of the government responses. Because the long-term negative economic impact would be enormous, we should avoid advocating for "living with COVID-19" without due consideration. The reopening of the economy must be accompanied by a commitment to the containment and elimination of infections with future novel coronaviruses.

Fiscal policy was more countercyclical during the Covid-19 crisis than in previous (crisis) episodes. This paper presents empirical evidence in favour of a "this time truly is different" moment based on analysing the cyclical behaviour of fiscal policy for 28 advanced economies over 1995-2021. Discretionary fiscal policy during the Covid-19 crisis (2020-2021) did more to counteract the downturn - especially in the Eurozone -, as we do not find comparable evidence for countercyclicality during the financial crisis or Euro crisis. Automatic fiscal stabilisers, the non-discretionary domain of fiscal policy, significantly contributed to countercyclical stabilisation during the pandemic.

The COVID-19 pandemic altered consumption patterns significantly in a short period of time. However, official inflation statistics take time to reflect changes in the weights of the CPI consumption basket. Using credit card data for the UK and Germany, we document how consumption patterns changed and quantify the resulting inflation bias. We find that consumers experienced a higher level of inflation at the beginning of the pandemic than what a fixed-weight inflation (or the official-weight) index suggests and lower inflation thereafter. We also show that weights can differ among age groups and in-person vs. online spenders. These differences affect the purchasing power of the population heterogeneously. We conclude that CPI inflation indexes based on frequently updated weights can provide useful inputs to assess changes in the cost of living, including across segments of the population. If shifts in consumption patterns prove persistent, these indexes can help determine the need to introduce new weights and inform monetary policy and the design of support policies for the more vulnerable.

We analyze the medium-term macroeconomic impact of the Covid-19 pandemic and associated lock-down measures on low-income countries. We focus on the impact of the degradation of health and human capital caused by the pandemic and its aftermath, exploring the trade-offs between rebuilding human capital and the recovery of livelihoods and macroeconomic sustainability. A dynamic general equilibrium model is calibrated to reflect the structural characteristics of vulnerable low-income countries and to replicate key dimensions of the Covid-19 shock. We show that absent significant and sustained external financing, the persistence of loss-of-learning effects on labor productivity is likely to make the post-Covid recovery more attenuated and more expensive than many contemporary analysis suggests.

The COVID-19 pandemic is an unprecedented worldwide event with a massive impact on the economic system. The first Western country that had to face the COVID-19 crisis was Italy, which therefore represents a natural "case study." By using the microdata and granular policy information available at the Italian Ministry of Economy and Finance, this paper provides a macroeconomic quantitative assessment of the initial emergency fiscal measures introduced in 2020 and an analysis of the impact of the COVID-19 shock during the lockdown. We find that emergency measures avoided an additional fall of GDP of about 4.4% in 2020. The impact of public interventions on the dynamics of investments is particularly significant.

Lags in official data releases have forced economists and policymakers to leverage "alternative" or "non-traditional" data to measure business exit resulting from the COVID-19 pandemic. We first review official data on business exit in recent decades to place the alternative measures of exit within historical context. For the U.S., business exit is fairly common, with about 7.5 percent of firms exiting annually in recent years. The high level of exit is driven by very small firms and establishments. We then explore a range of alternative measures of business exit, including novel measures based on paycheck issuance and phone-tracking data, which indicate exit was elevated in certain sectors during the first year of the pandemic. That said, we find many industries have likely seen lower-than-usual exit rates, and exiting businesses do not appear to represent a large share of U.S. employment. As a result, exit appears lower than widespread expectations from early in the pandemic.

In this paper we seek to make headway on the question of what recovery from Covid-19 recession may look like, focusing on the duration of the recovery - that is, how long it will take to re-attain the levels of output and employment reached at the prior business cycle peak. We start by categorizing all post-1960 recessions in advanced countries and emerging markets into supply-shock, demand-shock and both-shock induced recessions. We measure recovery duration as the number of years required to re-attain pre-recession levels of output or employment. We then rely on the earlier literature on business cycle dynamics to identify candidate variables that can help to account for variations in recovery duration following different kinds of shocks. By asking which of these variables are operative in the Covid-19 recession, we can then draw inferences about the duration of the recovery under different scenarios. A number of our statistical results point in the direction of lengthy recoveries.

I process credit-card consumption data through an input-output model of sectoral linkages to impute the sector-level output responses to the Covid-19 pandemic. The sector-level consumption responses are highly dispersed and even positive for some. Yet, all sectors suffer from output losses. Production of intermediate goods stabilises output. Consequently, the sectoral dispersion of final consumption is higher than the sectoral dispersion of output produced. Sectors that provide intermediate goods are affected less by the pandemic. Many service sectors face the largest losses in output since they depend the most on final consumption.

This paper examines the role of heterogeneity in a real business cycle model, which traditionally has not fully captured the relative volatility of hours to output. Men and women have different cyclical volatilities in hours worked, which is robust to different filtering methods. This empirical regularity is used to motivate a standard RBC model augmented to allow for two different agents following Jaimovich et al. (2013). These two agents have identical utility functions, but face different elasticities of labor demand due to their different complementarities with capital. These estimated elasticities find that women are more complementary to capital. The calibrated model generates the cyclical volatility of work hours by gender and for the total hours worked that matches the U.S. data better than the traditional representative agent model. I then explore other extensions to this model including investigating the stability of the estimated labor demand elasticities and allowing for various Frisch elasticities of labor supply. This paper demonstrates that allowing for even broad levels of heterogeneity in a simple framework can increase the model's tractability with the data. Since gender is important to explain U.S. business cycle dynamics, we need to carefully consider heterogeneity when analyzing counter-cyclical economic policy, as it may not have symmetric effects across assorted groups.

In this paper, we construct an extended SIR model with agents optimally choosing outdoor activities. We calibrate the model and match it to the data from the United States. The model predicts the epidemic in the United States very well. Without government intervention, our simulation shows that the epidemic peaks on 22 March, 2020 and ends on 29 August, 2022. By the end of the epidemic, more than 21 million people will be infected, and the death toll is close to 3.8 million. We further conduct counterfactual experiments to evaluate the effectiveness of different polices against this pandemic. We find that no single policy can effectively suppress the epidemic, and the most effective policy is a hybrid policy with lockdown and broadening testing. Lockdown policy alone is ineffective in controlling the epidemic as agents would have optimally stayed at home anyway if the infection risk is high even without a lockdown. Broadening testing solely will accelerate the return to normal life as there are fewer infected people hanging around. However, as people do not internalize the social costs of returning to normal life, the epidemic could get even worse. Increasing medical capacity without any other measures only has temporary effects on reducing the death toll. We also find that random testing is too inefficient unless a majority of population is infected.

"This paper analyzes the impact of the Baby Boom generation on macroeconomic relationships in the United States. Using quarterly postwar data, it finds that measures of population age composition influenced real interest rates, income, inflation, and unemployment. The demographic variables complement or dominate other economic variables in reduced-form macroeconomic specifications. The paper also projects how the aging of the generation may influence future macroeconomic activity."

"In this paper we incorporate the possibility of international migration into a monetary policy game played by governments in unionized interdependent economies. We show that contrary to usual presumptions, established by earlier studies that ignore the possibility of international migration, inter-government cooperation in the monetary field may well turn out to be advantageous. This has important implications for the European economies, since it suggests that measures taken towards encouraging international migration within EU [the European Union] will not only harmonize the European labor markets but will also make monetary policy cooperation within Europe, as required by the Maastrict Treaty, more advantageous."