We introduce a banking sector and heterogeneous agents in the dynamic overlapping generations model of Matsuyama et al. (2016). Our model captures the benefits and costs of an advanced banking system. While it allocates resources to productive activities, it can also hinder progress if it invests in projects that do not contribute to capital formation, and potentially triggering instabilities due to the emergence of cycles. Our intergenerational dynamic framework enables us to show that income inequality between agents increases during recessions, confirming empirical observations. Moreover, we identify both changes in production factor prices and the reallocation of agents across occupations as driving factors behind the increased inequality.

I show that the defining features of the Great Moderation were a shift in output volatility toward medium-term fluctuations and a shift in the origin of those fluctuations from the real to the financial sector. I uncover a Granger-causal relationship whereby financial cycles attenuate short-term business cycle fluctuations while simultaneously amplifying longer-term fluctuations. As a result, financial shocks systematically drive medium-term output fluctuations, whereas real shocks drive short-term output fluctuations. I use these results to argue that the Great Moderation and Great Recession both resulted from the same economic forces. On the theoretical front, I show that long-run risk is a critical ingredient of DSGE models with financial sectors that seek to replicate these shifts. Finally, I use this DSGE model to refine the “good luck” and “good policy” hypotheses of the Great Moderation.

This paper examines how credit constraints shape the transmission of uncertainty shocks in business cycles. Standard models struggle to capture the simultaneous declines in output, consumption, investment, and labor hours during uncertainty spikes. We introduce collateral-based credit constraints for impatient households and entrepreneurs, linking their borrowing capacity to asset values. As uncertainty rises, higher risk premia reduce the demand for collateral assets, prompting impatient households to cut labor supply, leading to an output decline. Our model generates macroeconomic co-movements without relying on nominal rigidities. Lowering the loan-to-value (LTV) ratio, particularly for households, helps mitigate these adverse effects.

This paper studies the dynamic relationship between economic growth, pollution, and government intervention. To do so, we develop a model that links pollution to the economy’s productive capacity, thereby capturing the feedback loops between economic activity, environmental degradation, and fiscal policy intervention. The model incorporates a pollution-sensitive damage function, taxes, and government spending while analyzing economic growth under different levels of government intervention. Therefore, the main paper’s contributions reveal that economies can achieve favorable outcomes with low or moderate government intervention, and that our results underscore the vital role of pollution mitigation policy in dynamically balancing economic growth with environmental sustainability.

Climate change, partly driven by rising emissions, has damaging and often irreversible impacts on entire economies. In this context, production processes play a crucial role, as they affect the level of pollution, causing environmental degradation, and affecting human health. Sustainable production methods and stricter environmental regulations can help mitigate these effects. However, their effectiveness depends on many factors as, for instance, the attitude towards greenery by firms and their convenience in breaking the rules. In the present work, we propose a dynamic framework to describe how and in which measure the production processes influence the environmental quality, considering the presence of non-compliant firms and the attitude toward greenery. We obtain a 3D piecewise-smooth dynamical system describing the evolution of the fraction of polluting firms, the monitoring level by the State, and the environmental quality over time. By analyzing the effects on environmental quality of the environmental regulation enforcement for different greenery propensities, we show that: (1) if the propensity for greenery is high, the system will converge towards a good equilibrium, that is, with high environmental quality and absence of dishonest companies; (2) if the propensity for greenery is at an intermediate level, the system may converge towards good or bad equilibria; (3) if the propensity for greenery is low, further internal attractors may emerge.

Our paper investigates the impact of the user cost of money, or the forgone interest associated with divisia monetary aggregates, on aggregate private investment in the U.S. We employ a mixed-frequency time-varying factor augmented vector autoregressive model with a large dataset spanning January 1972 to September 2023. Our impulse response function results show that the impact of the user cost of money is similar to that of interest rates, represented by the credit spread (the yield gap between Moody’s Baa corporate bond yield and the 10-year treasury bill yield). However, a shock to the user cost of M4 growth rate has a slightly stronger impact on disaggregated private investment growth than a credit spread shock. Hence, private investment is more responsive to the user cost of money than to interest rates in any economic environment. In this regard, when economic uncertainty is low, such as during the Great Moderation, shocks to interest rates or the M4 monetary aggregate growth rate have a significant positive impact on aggregate private investment growth. Our findings align with the literature on the relationship between interest rates and private investment (Bernanke, 1983b; Chetty, 2007).

This paper examines the effects of average inflation targeting (AIT) on social welfare and fiscal multipliers under varying averaging windows using a nonlinear New Keynesian model. While the existing literature highlights AIT’s advantages over Inflation Targeting(IT) and longer-window AIT over shorter-window AIT in terms of social welfare, these conclusions often rely on linearized models that fail to capture expectation effects arising from window lengths. By solving the model nonlinearly, we find that social welfare increases with AIT windows up to six years but declines for longer windows. The key driver is the differing expectation effects, where longer windows reduce the likelihood of the zero lower bound (ZLB) binding but may overshoot inflation targets, leading to lower output and welfare. Our results reveal that the optimal averaging window for AIT depends critically on the ZLB probability: higher ZLB risks favor longer windows, while lower risks make shorter windows sufficient. Moreover, we investigate the fiscal multiplier under AIT and show that it differs significantly from IT. In addition, the welfare-maximizing AIT window does not align with the window that maximizes fiscal multipliers, highlighting trade-offs between welfare and fiscal policy effectiveness. This study underscores the importance of nonlinear methods in evaluating AIT and provides practical insights into its calibration for modern monetary policy frameworks.

We propose a novel approach to classifying inflation-targeting (IT) economies using fractionally integrated processes. Motivated by the rising prevalence and diversity of IT, we leverage variation in the persistence of inflation rates to identify four de facto strategies, or “shades” of IT. Moving from negative orders of fractional integration, indicating anti-persistent behaviour, to more persistent long-memory processes, often associated with less credible policy frameworks, we classify countries into average, strict, flexible, and uncommitted IT. This framework sheds light on differences between declarative and actual strategies across 36 advanced and emerging economies. Most countries fall into the flexible IT category, though extreme cases, including uncommitted IT, occur quite frequently. Furthermore, we link our classification to institutional features of national frameworks using ordinal probit models. The results suggest differences across categories are related to variations in the maturity and stability of IT frameworks, with weaker connections to central bank independence and transparency.

We analyze the extent to which the prospects for economic development may relate to the environmental damages associated with economic activities. We consider an economic growth framework in which production activities generate polluting emissions which in turn negatively affect production capabilities, and publicly-funded abatement is pursued to mitigate such effects. Since the time preference is endogenously related to capital, abatement affects the size of the discount factor through its implications on capital accumulation. We show that the elasticity of environmental damages affects the optimal tax rate and thus the abatement level, which in turn determines whether the economy will end up in a stagnation or growth regime. This suggests that the cross-country heterogeneity in environmental damages may explain the different development patterns experienced by industrialized and developing economies. Our results are robust to the presence of productive public spending and two alternative forms of capital (clean and dirty capital).

This paper investigates the effect of taxation of polluting products and redistribution on pollution, income and welfare inequalities. We consider a two-sector Ramsey model with a green and a polluting good, two types of households and a subsistence level of consumption for the polluting good. The environmental tax is always effective in reducing pollution regardless of the level of subsistence consumption. However, this level, together with the redistribution rate, matters at the individual level as it shapes the impact of the environmental policy on individual consumption and welfare. Looking at the stability properties of the economy, a high subsistence level of polluting consumption leads to instability or indeterminacy of the steady state, while the environmental externality reduces the scope for indeterminacy. Increasing the tax rate and redistributing more to the worker affect the occurrence of indeterminacy and instability. Considering the subsistence level of consumption and the level of redistribution among households are of importance as it determines the effects of environmental tax policy in the long term and the stability of the economy in the short term.

Environmental issues have an international dimension, with causes and consequences that extend beyond national borders—including the effects of the policies designed to address them. This paper investigates how different levels of environmental regulation influence the long-term spatial distribution of firms and households. The results suggest that only highly asymmetric regulations align with the Pollution Haven Hypothesis, causing firms to cluster in areas with lax environmental standards. In contrast, moderate differences in regulation tend to improve environmental quality across regions and can generate positive spillovers for countries adopting greener policies, such as attracting new residents and stimulating investment. While this lends support to the Porter Hypothesis, it does so through a less conventional mechanism. Rather than fostering innovation, stringent regulations enhances regional attractiveness by expanding the market size.

This paper uses a dynamic general equilibrium approach that takes into account the macroeconomic implications of the green transition and its consequences for public finances. It shows that when the government relies too heavily on expenditure-based measures, it threatens the sustainability of public debt, by increasing the probability of sovereign default, leading to higher interest rates on government bonds. This higher public default risk has potentially significant repercussions on investment financing conditions for the private sector, and increases the cost of the transition to a net-zero economy. On the other hand, carbon pricing policies make the transition more viable for public finances, at the expenses of similarly high economic costs, while remaining effective in reducing greenhouse gas emissions. The welfare-maximizing optimal policy mix results in a balanced approach, with the public sector’s contribution to the total mitigation effort increasing gradually, ranging from 25% to 40% between 2030 and 2050.

Using a Bayesian Global VAR model as a methodological tool, we analyze how heightened geopolitical risk shocks propagate across advanced economies and quantify the economic effects of these events. The global VAR impulse response functions in response to the skyrocketing Russian geopolitical risk after Russia’s invasion of Ukraine revealed a contraction of GDP and an increase in inflation. Eastern European and Baltic countries are particularly affected by the Russian geopolitical risk shock. We also document a strong component of the Russian geopolitical risk shock that is not driven by fossil fuel prices.

This paper examines optimal fiscal and regulatory policies within a New Keynesian (NK) framework that incorporates household fairness concerns regarding firm pricing behavior. Households derive utility not only from consumption and leisure but also from their perception of price fairness, which is influenced by biased beliefs about the price markup. These misperceptions reduce the effective price markup, as firms adjust pricing to avoid a demand backlash. The planner faces a trade-off between addressing monopolistic distortions, traditionally managed through the labor subsidy, and mitigating fairness concerns amplified by behavioral biases as spending increases. When biases are mild, the optimal fiscal policy remains the labor subsidy, though smaller than in the standard NK model. As fairness dynamics strengthen, the optimal policy shifts to a labor tax aimed at alleviating perceived unfair pricing, albeit with additional welfare losses. Capping the price markup can replicate the labor subsidy under moderate biases but loses effectiveness as fairness intensifies. These findings provide theoretical insights into how fairness-related behavioral distortions shape policymakers’ trade-offs and inform the design of optimal fiscal and regulatory policies.

This paper analyzes the relationship between microfinance, competition, and growth in a sample of 119 countries over the period 1999–2018. Our results are fourfold. First, we show that microfinance increases economic growth. Second, we identify investment and consumption as the main channels explaining the positive effect of microfinance on growth. Third, our study highlights that the conventional financial sector and microfinance are substitutes and not complements in emerging and developing countries. Finally, we show that competitive microfinance markets allow increasing the positive effect of microfinance on growth.

This paper investigates the stability of the demand for money in the United States and provides a comparison among the simple-sum monetary aggregates, the original (non-credit-card-augmented) Divisia monetary aggregates, and the credit-augmented Divisia and credit-augmented Divisia inside aggregates. We use quarterly data from the Center for Financial Stability and the Pesaran et al. (2001) bounds test procedure to investigate the long-run relation between the monetary aggregates and their respective user costs. In doing so, we use three classic money demand functions—the log–log, the semi-log, and the Selden and Latané specifications. With quarterly data over the 1967:q1 through 2025:q1 period, for which the original Divisia monetary aggregates are available, we find evidence of a stable money demand function only with the Sum M4 aggregate under all money demand specifications, but not with any of the Divisia aggregates. With quarterly data over the post-2006 period, for which the credit-augmented Divisia monetary aggregates are also available, our findings show that the demand for money is stable across all money demand specifications with all of the original Divisia aggregates and the credit-augmented Divisia aggregates (but not with all of the credit-augmented Divisia inside aggregates). We also find evidence of cointegration with the Sum M3 and Sum M4 aggregates under all three money demand specifications, but not with the Fed’s Sum M2 aggregate.

This paper investigates the welfare implications of the rise of shadow banking in China, driven by regulatory arbitrage and implicit guarantees. Although shadow banking can improve social welfare by relaxing constraints on banks’ capacity to expand credit, it may also hurt social welfare due to the risk-taking behavior induced by implicit guarantees. We study the optimal level of guarantees and shadow banking in a model that balances these benefits and costs. Our findings suggest that reducing the existing degree of guarantees and shrinking the shadow banking sector could enhance social welfare in China.

Over recent decades, we find about $80\%$ of widening residual wage inequality to be within jobs (industry-occupation pairs). To explore the underlying drivers, we incorporate into a sorting equilibrium framework with two extensive margin channels (across-job sorting and within-job selection of a performance-pay position) and an intensive margin channel (quality of skill match), in addition to residual job productivity. We show that equilibrium sorting is positively assortative both within and across jobs. By calibrating the model to the United States in 1990 and 2000, we find the improved match quality and rising performance-pay incidence amplify each other, jointly accounting for about $90\%$ of the widening within-job wage inequality. Match quality and performance pay are particularly important in jobs with rising average wages and expansionary employment. Once performance pay and match quality channels are incorporated, job sorting becomes less important and residual job productivity becomes inconsequential throughout.

Extreme precipitation events have become more frequent and severe in recent years, leading to devastating natural disasters around the world. This paper investigates the impacts of extreme rainfall on corporate leverage dynamics. We find that the increase of extreme precipitation brings about a significant drop in firm’s leverage. The channel tests show that extreme rainfall would generate the recession of firm’s balance sheet and thus tighten the financing constraints, inducing firm to cut down leverage. On the other hand, intense rainfall would depress the land price and heighten local government’s debt risk, which crowds out the credit resources allocated to private sector, contributing to the deleveraging of firms. Simulations from the new Keynesian DSGE model with extreme rainfall shock and local government land finance system, lend further support to our empirical findings. Furthermore, our model shows that the welfare cost of extreme rainfall risk can amount to 2.2% of the agent’s lifetime utility. Lower welfare cost can be achieved by accommodating monetary policy and active fiscal policy.