We extend the growth-at-risk (GaR) literature by examining US growth risks over 130 years using a time-varying parameter stochastic volatility regression model. This model effectively captures the distribution of GDP growth over long samples, accommodating changing relationships across variables and structural breaks. Our analysis offers several key insights for policymakers. We identify significant temporal variation in both the level and determinants of GaR. The stability of upside risks to GDP growth, as seen in previous research, is largely confined to the Great Moderation period, with a more balanced risk distribution prior to the 1970s. Additionally, the distribution of GDP growth has narrowed significantly since the end of the Bretton Woods system. Financial stress is consistently associated with higher downside risks, without affecting upside risks. Moreover, indicators such as credit growth and house prices influence both downside and upside risks during economic booms. Our findings also contribute to the financial cycle literature by providing a comprehensive view of the drivers and risks associated with economic booms and recessions over time.

This article studies how sudden changes in bank credit supply impact economic activity. I identify shocks to bank credit supply based on firms’ aggregate debt composition. I use a model where firms fund production with bonds and loans. In the model, bank shocks are the only type of shock that imply opposite movements in the two types of debt as firms adjust their debt composition to new credit conditions. Bank shocks account for a third of output fluctuations and are predictive of the bond spread.

The paper looks at the question of measuring the importance of shocks to cycles. We consider two types of cycles - oscillations and those summarized by the NBER that require a study of growth in activity to establish turning points in the level of activity. The latter demarcate expansions and contractions. We establish a connection between these two concepts of cycles that shows shocks may have very different effects on each. As an application we look at a question that has often been asked over how important technology shocks are to cycles in activity? Some recent research concludes that total factor productivity (TFP) shocks are not important for oscillations and therefore models should be designed to reflect that. Using the same data we show that TFP shocks are very important to both types of cycles.

An article published in 2018 by J.D. Hamilton gained significant attention due to its provocative title, “Why you should never use the Hodrick-Prescott filter.” Additionally, an alternative method for detrending, the Hamilton regression filter (HRF), was introduced. His work was frequently interpreted as a proposal to substitute the Hodrick–Prescott (HP) filter with HRF, therefore utilizing and understanding it similarly as HP detrending. This research disputes this perspective, particularly in relation to quarterly business cycle data on aggregate output. Focusing on economic fluctuations in the United States, this study generates a large amount of artificial data that follow a known pattern and include both a trend and cyclical component. The objective is to assess the effectiveness of a certain detrending approach in accurately identifying the real decomposition of the data. In addition to the standard HP smoothing parameter of $\lambda = 1600$, the study also examines values of $\lambda ^{\star }$ from earlier research that are seven to twelve times greater. Based on three unique statistical measures of the discrepancy between the estimated and real trends, it is evident that both versions of HP significantly surpass those of HRF. Additionally, HP with $\lambda ^{\star }$ consistently outperforms HP-1600.

We investigate the causes underlying the decline in the government expenditure multiplier after the Korean War, through the lens of a structural dynamic stochastic general equilibrium model. We estimate the model using Bayesian methods and annual frequency data from 1939 to 2017. The model replicates the observed fall in the expenditure multiplier. We find that the decline is accounted for by changes in two of the model’s structural parameters, namely a decline in consumption habit persistence and a higher autocorrelation of the public expenditure processes. These changes imply a stronger negative wealth effect, a lower discretion of US fiscal policy and, consequently, a multiplier of smaller magnitude. The model identifies the news shocks to military spending, yet fiscal news plays little role in the decline of the multiplier. Rather, the news shocks account for an important fraction of medium-term variances of debt and military expenditures, which justifies their inclusion in the model.

Emissions are directly linked to economic output and consequently subject to business cycle fluctuations. The present study analyses the interactions between climate policies and business cycles through the lens of a New Keynesian dynamic stochastic general equilibrium model. We compare a static cap-and-trade policy with a dynamically adjusting policy in terms of macroeconomic stabilisation, welfare and emissions price dynamics. The results of the quantitative evaluation suggest that a constant policy leads to lower aggregate volatility but is associated with larger welfare costs. In contrast, under the dynamic policy emissions prices and labour markets display less variations.

We estimate a smooth-transition vector autoregression model (ST-VAR) using panel data from 14 OECD countries to study the cross-country spillover effects of economic policy uncertainty (EPU) shocks. An unexpected elevation of EPU originating abroad has an overall contractionary real effect, and the spillover effects depend on the state of the business cycle of the recipient country. EPU spillover shocks during recessions have stronger but less persistent effects on a number of economic indicators. We also find that the interconnectedness of EPU, financial markets, and business confidence are important channels for the EPU shocks to propagate across countries, while the trade channel has limited effects, especially during expansions.

This paper investigates the relationship between credits and sector-level output dynamics in a sample of 41 advanced and developing countries. The existing literature shows that household credits are associated with boom-bust cycles in aggregate output, whereas business loans do not cause such output dynamics. The present paper expands these findings in terms of advanced versus developing countries and manufacturing versus services sectors. The new findings indicate that the resulting boom-bust cycles in the aggregate output in response to household credits are generally observed in the sample of developing countries, with no similar dynamics in the advanced countries. Another significant conclusion is that the boom-bust cycles are generated mostly in the services sector. No equivalent boom-bust dynamics are observed in the manufacturing sector, but the negative medium-run effects of household credits are larger in this sector. These findings indicate that credit mechanisms and consequences can significantly vary across countries and sectors.

This paper explores the effect of fiscal policy on the welfare of heterogeneous agents with different income sources over the business cycle. Policy experiments allow the government to choose the cyclical properties of fiscal policy instruments conditional on long-run levels to separately maximize the welfare of entrepreneurs and workers. This policy choice creates welfare conflicts between the two groups, which is confirmed by empirical evidence. The government maximizes workers’ welfare by choosing procyclical capital income tax rates and countercyclical labor income tax rates while it optimizes entrepreneurs’ welfare with countercyclical capital income tax rates and strongly countercyclical labor income tax rates. The socially optimal policy is a tradeoff between the welfare of entrepreneurs and workers. The welfare conflict holds when the government modifies the cyclical behavior of policy in a crisis, or it adjusts the long-run level and cyclical behavior at the same time.

This paper applies the common stochastic trends representation approach to the time series of total factor productivity (TFP) and the relative price of investment (RPI) to investigate the modeling of neutral technology (NT) and investment-specific technology (IST) and its econometric ramifications on the analysis of general equilibrium model. The permanent and transitory movements in both series are estimated efficiently via Markov chain Monte Carlo methods using band matrix algorithms. The results indicate that TFP and the RPI are, each, well represented by a differenced first-order autoregressive process. In addition, their time series share a common trend component that we interpret as reflecting changes in general purpose technology. These results are consistent with studies that suggest that (1) the traditional view of assuming that NT and IST follow independent processes is not supported by the features of the time series and (2) improper specification of secular trends may distort estimation and inference. Notably, the findings provide some guidance to minimize the effect of idiosyncratic and common trend misspecifications on the analysis of impulse dynamics and propagation mechanisms in macroeconomic models.

The existing output gap measures for the US economy rely on aggregate data and assume a constant output gap over sectors (see Coibion et al. [(2018) Brookings Papers on Economic Activity, 333–441] and Owyang et al. [(2018) Federal Reserve Bank of St. Louis Review, 297–316]); however, each sector has its cycle, which does not necessarily match the business cycle (Burns and Mitchell [(1946) National Bureau of Economic Research]). By modeling sectoral cycles based on their investment cycles with a nonparametric method, I estimate output gaps of 20 US sectors over 1948–2020. The weighted mean output gap indicates a persistent spare capacity in the last business cycle, pointing to insufficient stabilization policies behind secular stagnation. Phillips curve estimations with the weighted quartiles of sectoral output gaps show that the output gap of bottleneck sectors (weighted Q3) is correlated strongly with inflation over 1950–2020. Policymakers can track bottleneck sectors to mitigate inflationary pressures while supporting the sectors with negative output gaps to stabilize the output at its potential. My findings show that it is possible to produce more output by sector-level demand supporting policies without generating inflation.

We examine the start date of the Great Recession across OECD countries. The Sahm Rule identifies the start of recession in the US to the beginning of 2008 but in most other OECD countries it identifies the start after that identified by two successive falls in quarterly GDP. We establish our own rule for predicting recession using the fear of unemployment series to predict recession. We show a 10-point rise in the series compared to its previous 12 month low predicted the onset of the Great Recession in both the United States and Europe.

This study revisits the relationship between economic variables and alcohol consumption from a macro perspective. Focusing explicitly on the asymmetries of the responsiveness of alcohol consumption during the expansion and contraction phases of the business cycle, asymmetric panel estimators are employed. We employ a nonlinear autoregressive distributed lag model for a panel of 24 countries for the period 1961 to 2014. Findings show that expansion leads to a long-term increase in average alcohol consumption, while during contraction, the level of average alcohol consumption persists. Expansion, together with a pronounced reduction in the unemployment rate could, however, lead to a net reduction of gross alcohol and wine consumption. Nonetheless, if the recession corresponds with a surge in unemployment, this leads to a long-run increase in the level of total gross alcohol consumption but a decrease in wine and beer consumption. Reduction in unemployment does not lead to a reduction in beer consumption, as pre-expansion levels of beer consumption persist. (JEL Classifications: E32, I19, L66)