In some classes of macroeconomic models with financial frictions, an adverse financial shock successfully explains a decrease in real activity but simultaneously induces a stock price boom. The latter theoretical result is not consistent with data from actual financial crises. This study aims to provide a theoretical explanation for both prolonged recessions and stock price declines. I develop a simple macroeconomic model featuring a banking sector, financial frictions, and R&D-based endogenous growth. Both the analytical and numerical investigations show that endogenous R&D investment and a shock hindering banks’ financial intermediary function can be key to generating both a prolonged recession and a drop in firms’ stock prices.

This study uses two large datasets to explore the output dynamics following economic disasters, one including 180 economic disasters across 38 countries over the last two centuries and the other including 204 disasters in 182 countries since World War II. Our results suggest that extreme economic crises are associated with huge and remarkably persistent loss. On average, output loss surges to above 26% in the first few years after the outbreak of a disaster and remains above 20% for as long as 20 years. It is only after more than 50 years that the loss is fully recovered.

This paper empirically investigates wage inequality within the group of skilled workers in the recent four decades in the USA using CPS data and finds evidence that the trend of wage growth of the top and bottom 10th percentile of skilled workers significantly diverged starting from 2000. Using a task-based framework of occupation, I find that the changing trend of wage inequality was entirely driven by one category of occupation, namely the nonroutine analytic occupation. Then, I consider in a model task reallocation between two broad task categories, namely the routine and abstract task, induced by an ongoing investment-specific technical change. In my model, the labor in the routine task is replaced by cheaper machines due to investment-specific technical change, then workers that are less productive in the abstract task enter abstract occupations. As a result, the wage inequality in the abstract task widens because of the reallocation of less productive workers from the routine task to the abstract task, that is, the “composition effect.” In addition, since economic agents tend to postpone the investment in machines after the ongoing investment-specific technical change takes place for a while, the expansion path of wage inequality is not linear but features an acceleration of wage dispersion in the middle of the technical change. The quantitative results suggest that the model is able to provide a well-matched timing and magnitude of the nonlinear expansion path in wage inequality that is observed in the data.

Homeownership rates differ widely across European countries. We document that part of this variation is driven by differences in the fraction of adults co-residing with their parents. Comparing Germany and Italy, we show that in contrast to homeownership rates per household, homeownership rates per individual are very similar during the first part of the life cycle. To understand these patterns, we build an overlapping-generations model where individuals face uninsurable income risk and make consumption-saving and housing tenure decisions. We embed an explicit intergenerational link between children and parents to capture the three-way trade-off between owning, renting, and co-residing. Calibrating the model to Germany we explore the role of income profiles, housing policies, and the taste for independence and show that a combination of these factors goes a long way in explaining the differential life-cycle patterns of living arrangements between the two countries.

Through the collateral channel for entrepreneurs, a positive housing demand shock in Liu et al. [(2013) Econometrica 81, 1147–1184.] increases land prices and business investment, but consumption decreases on impact and there is thus a comovement problem. This paper improves Liu et al. [(2013) Econometrica 81, 1147–1184.] by adding general household preferences with broader intratemporal and intertemporal substitutions Bayesian estimation of our structural model based on aggregate US data suggests that the intratemporal substitution is larger than unity and the intertemporal substitution is smaller than unity. Our impulse responses show that a positive housing demand shock increases land prices, business investment, and consumption, which resolves the comovement problem. Moreover, the strength of the collateral channel linking land prices and business investment in our Bayesian DSGE model is larger than that in Liu et al. [(2013) Econometrica 81, 1147–1184.]. Housing demand shocks explain 39−43% of the variance of output and 41−47% of the variance of investment in our model, but the same shocks explain only 17−31% of the variance of output and 30−41% of the variance of investment in Liu et al. [(2013) Econometrica 81, 1147–1184.]. Variance decomposition reveals that housing demand shocks account for a larger share of the fluctuations in land prices, investment, employment, and output than other shocks. Using the marginal data density as the measure of fit for models, we find that our model can better explain the same US aggregate data.

This paper proposes a dynamic model to capture the interaction among the environment, human capital accumulation, and economic growth. We emphasize the mechanism that pollution stock depresses human capital accumulation, which has received increasing support from empirical studies. The model predicts that the development of pollution-intensive industries can help an economy gear up a short-run prosperity, but it impairs the capability for long-run economic growth, trapping the economy at a low development level. The cost for a dirty economy to switch is expensive and even infeasible if the environmental degradation is irreversible. Policy interventions, such as tax on pollution and subsidy on human capital, can help alleviate but cannot eradicate the economic stagnation.

According to the real business cycle theory, business cycles mainly result from random exogenous shocks. In this paper, this argument is tested. I extend the Wald–Wolfowitz runs test under the assumption that a recession lasts for two periods at least and an expansion lasts for $k$ periods at least with k ≥ 2. I apply the extended runs test to the three two-valued data recession-expansion series generated by the National Bureau of Economic Research and the Center for Economic and Policy Research. The test results reject the null hypothesis that they are generated in a random way for any $k$ even at the 1% significance level.

Over the past decade, the most salient changes in macroeconomic conditions in developed economies have included rising government debt and population aging, which are strongly correlated with each other. This paper investigates fiscal multipliers by disentangling the effects of population aging from those of government debt. Our analysis, which uses heterogeneous panel data from 24 OECD economies, shows that while fiscal policy is ineffective for economies with high-debt levels, it is effective for economies with low-debt levels. Furthermore, the estimation results reveal that fiscal policy is ineffective for aged economies, regardless of the level of government debt. However, for nonaged economies, while fiscal policy leads to negative effects on output in times of high debt, its positive effects are more pronounced in times of low debt. Our results suggest that, for the effective implementation of fiscal stimulus policies, policy-based stimulation of employment in the labor market is essential.

Because economic outcomes depend on private-sector expectations, central banks might be tempted to guide these by publishing projections of key macroeconomic variables. We find that optimal projections require misleading the public. Optimal non-misleading projections are time-inconsistent. Non-misleading time-consistent projections can only improve policy outcomes if the public’s forecasts are noisier, or inconsistent with implemented policy. Since the public only has incentives to be guided by policymakers’ projections when most vulnerable to being mislead, these cannot be trusted blindly. Consistent with this, we find statistically significant systematic deviations between FOMC projections and professional forecasts for US inflation and GDP growth.

The rapid development of the digital economy has highlighted the crucial role of data in economic growth. This study investigates the impact of two types of innovation on long-term growth by incorporating data into a model of creative destruction and knowledge accumulation. Unlike traditional factors, data exhibit nonrivalry between the two research and development (R&D) sectors, thereby influencing the growth rate of economic outputs simultaneously without interference. Our findings reveal the existence of a balanced growth path (BGP) in both the decentralized economy and the social planner’s economy. In horizontal innovation, data can be transformed into digital knowledge to promote the economic growth [Cong et al. (2021)]. In addition to horizontal innovation, the utilization of data in vertical innovation also enhances the success rate of innovation, with a gradual decrease in per capita data usage on the BGP. Moreover, as agents accumulate human capital, the economy achieves higher output levels, effectively addressing consumer privacy concerns. However, along the transitional path, insufficient data provision by both R&D sectors leads to lower economic growth rates or more intense economic fluctuations, necessitating policy interventions.