This paper sets up a small open economy two-agent model and addresses the size of output multiplier of government spending associated with taxation either on constrained households or on unconstrained households. The paper shows that the tax financing rule matters to real resource allocations in the small open economy with flexible prices and equal tax burden at the steady state, contrasting to the finding of Monacelli and Perotti (2011) in closed economies. The output multiplier in open economies is larger than the multiplier in closed economies when taxes are levied on constrained households, while the reverse holds under taxations on unconstrained households.

We explore the international transmission of monetary policy and central bank information shocks originating from the United States and the euro area. Employing a panel vector autoregression, we use macroeconomic and financial variables across several major economies to address both static and dynamic spillovers. To identify structural shocks, we introduce a novel approach that combines external instruments with heteroskedasticity-based identification and sign restrictions. Our results suggest significant spillovers from European Central Bank and Federal Reserve policies to each other’s economies, global aggregates, and other countries. These effects are more pronounced for central bank information shocks than for pure monetary policy shocks, and the dominance of the US in the global economy is reflected in our findings.

In this paper, we adopt an evolutionary model to describe the coevolution of technological transition and pollution in a country, where the choice of technology does not only give firms access to cleaner (but more expensive) or dirtier (cheaper and illegal) forms of production, but also access to social groups and information. Firms’ activity may be harmful to the environment and, due to the existence of ambient pollution charges, economic activity is affected by the level of pollution in the country. Our analysis describes how the evolution of the transition to clean technology and pollution generates a rich set of possible equilibria, which include stable pure strategies (where all firms choose the same technology) and inner equilibria (where both technologies could be adopted in the long run). We also observe more complex behavior and coexistence of different attractors as well as highlight the importance of initial conditions and uncover how the regulator may face possible pollution traps.

We in this paper employ a penalized moment selection procedure to identify valid and relevant moments for estimating and testing forecast rationality within the flexible loss framework proposed by Elliott et al. (2005). We motivate the selection of moments in a high-dimensional setting, outlining the fundamental mechanism of the penalized moment selection procedure and demonstrating its implementation in the context of forecast rationality, particularly in the presence of potentially invalid moment conditions. The selection consistency and asymptotic normality are established under conditions specifically tailored to economic forecasting. Through a series of Monte Carlo simulations, we evaluate the finite sample performance of penalized moment estimation in utilizing available instrument information effectively within both estimation and testing procedures. Additionally, we present an empirical analysis using data from the Survey of Professional Forecasters issued by the Federal Reserve Bank of Philadelphia to illustrate the practical utility of the suggested methodology. The results indicate that the proposed post-selection estimator for forecaster’s attitude performs comparably to the oracle estimator by efficiently incorporating available information. The power of rationality and symmetry tests leveraging penalized moment estimation is substantially enhanced by minimizing the impact of uninformative instruments. For practitioners assessing the rationality of externally generated forecasts, such as those in the Greenbook, the proposed penalized moment selection procedure could offer a robust approach to achieve more efficient estimation outcomes.

This paper investigates the nature of financial market fluctuations by empirically testing three competing models of instability. We contrast a linear state-space model and a nonlinear Markov-switching model – both rooted in heterogeneous behavioral heuristics and capable of generating endogenous dynamics – with a benchmark linear random walk model that assumes exogenous shocks. Using monthly S&P 500 data from 1990 to 2019, we find strong evidence supporting endogenous sources of instability. In particular, models incorporating behavioral nonlinearities significantly outperform both the linear behavioral model and the random walk in short-, medium-, and long-term forecasting. Our findings underscore the importance of accounting for heterogeneous expectations and regime-switching behavior in explaining asset price dynamics.

Climate change can have significant consequences on the world economy, a possibility explored in this paper. We simulate the world economy using data from 20 economies spanning from 1999 to 2023 in a Global Vector Autoregression (GVAR) framework. Our hypothesis posits that temperature anomaly shocks impact economies through financial markets, which then transmit the shock to production. We model financial markets using four key indicators: currency markets, stock markets, short-term credit markets, and long-term credit markets. Our findings reveal that temperature anomaly shocks: i) trigger a global recession, ii) induce fluctuations across all financial markets, iii) lead to depreciation of domestic currencies, declines in stock markets, and decreases in long-term interest rates, and iv) elicit a minor response in short-term interest rates. These results highlight the presence of spillover effects from temperature anomalies. We validated our findings using alternative configurations (time-varying and fixed bilateral trade), with the main conclusions remaining consistent. Our study suggests that financial markets, particularly the stock market, serve as transmission channels for the consequences of climate change.

The “demographic dividend” refers to the boost to GDP per capita growth countries experience during the part of the demographic transition when age dependency ratios plummet. The size and the source of the dividend are debated in the literature. Using newly constructed age-specific population data by country from the beginning of the demographic transition to the present day, this paper estimates the contribution of changing age structure to GDP per capita growth during the demographic transition. A quantitative overlapping-generations model is used to produce country-specific estimates of the dividend and to disentangle its drivers. Model simulations for 101 countries suggest a global average boost of 0.40 percentage points per annum to GDP per capita growth during the dividend period. Changing age structure explains 9.5% of total growth during the period of the demographic dividend on average. Countries with more rapid and more extreme changes in age structure experience larger dividends.

This paper examines optimal policy for foreign exchange (FX) reserve management without commitment. The stylized linear-quadratic model incorporates three key elements: (i) fear of floating, (ii) forward-looking exchange rates, and (iii) the cost of reserve management. The paper first analyzes two benchmark optimal policies: the Ramsey policy (with commitment) and the Markov-Perfect policy (without commitment). It then proposes a sustainable plan that addresses the time inconsistency in reserve management. By following this plan, the government without commitment achieves the Ramsey outcome in equilibrium.

Using a dynamic stochastic general equilibrium model (DSGE) model with households’, firms’, and banks’ default calibrated for Portugal, we assess the impact of some prudential policy measures adopted to mitigate COVID-19 economic effects: the flexibility measure and the dividends pay-out restriction. The joint use of the measures reinforces the support for credit achieved using the flexibility measure only and reduces the effort of banks to rebuild capital buffers once the pandemic crisis is over. Given the recovery and the measures’ withdrawal, we also consider distinct paths for replenishing capital buffers. Shorter transitions strengthen banks’ resilience, but longer transitions may be more suitable to ensure a smooth flow of lending to the economy.

Within a new Keynesian model of monetary policy with both backward- and forward-looking variables, we investigate the impact of risk aversion by assuming that the central bank is endowed with recursive preferences à la Hansen and Sargent (Hansen and Sargent, 1995). We establish that, since in this model inflation and output are forward-looking, under discretion the optimal policy is found by solving two distinct fixed-point problems: the former pertains to the central bank’s optimization exercise, the latter to the identification of the equilibrium expectations of the forward-looking variables. We show that, in the presence of forward-looking variables, the optimal policy differs from the robust policy chosen by a central bank endowed with quadratic preferences and subject to Knightian uncertainty, confuting the equivalence established by Hansen and Sargent (2008) when only backward-looking variables enter into the laws of motion regulating the dynamics of the economic system. Through our analysis we show: i) how a risk-averse central bank selects a more aggressive policy than one furnished with the standard preferences of a canonical DSGE model; ii) that the “divine coincidence” established within traditional linear-quadratic formulations between inflation and output stabilization no longer holds.

This study proposes a novel time-varying, endogenous fiscal reaction function, and investigates whether and how the US government responded to the rising debt to assess the sustainability of its debt over 1916 to 2022. The reaction function is estimated via a state space model using Bayesian methods by treating its coefficient as an unobservable stochastic process. Although there is evidence that the government considered long-term projections of the interest rate in its fiscal decisions, the response to debt was largely driven by unobservable non-economic factors and by large and persistent shocks. We find that the government was more proactive about constraining debt increases during the 20th century than previously thought (such as in Bohn, 1998), but it has become less aggressive ever since. The debt-GDP ratio was sustainable for almost the entire sample period, but its steady state value has been rising consistently in recent years. The government’s response to debt contributed 6.0 percentage points to the surplus-GDP ratio in the postwar 20th century, but only 3.6 percentage points afterward.

This paper investigates the dynamic effects of environmental and fiscal policy shocks in a New Keynesian dynamic stochastic general equilibrium model featuring price and wage rigidity and a polluting intermediate goods sector. I compare carbon taxes and cap-and-trade systems under abatement cost and government spending shocks, considering three revenue-recycling schemes: lump-sum transfers, labor tax cuts, and consumption tax cuts. Abatement cost shocks reduce output and consumption, with stronger effects under cap-and-trade due to rising permit prices. These effects are mitigated when revenues are used to reduce distortionary taxes, especially consumption taxes. Government spending shocks stimulate output and labor, particularly under lump-sum financing, but their expansionary effects are dampened under cap-and-trade. Nominal rigidities amplify these dynamics. The findings support the double dividend hypothesis and highlight the importance of fiscal design and policy coordination. Carbon taxes, combined with targeted tax reductions, offer superior macroeconomic stabilization in the face of environmental and fiscal shocks.

The rise of U.S. inflation in 2021 and 2022 and its partial subsiding have sparked debates about the relative role of supply and demand factors. The initial surge surprised many macroeconomists despite the unprecedented jump in money growth in 2020–21. We find that the relationship between consumption and the theoretically based Divisia M3 measure of money (velocity) can be well modeled both in the short- and long-runs. We use the estimated long-run relationship to calculate the deviation of actual velocity from its long-run equilibrium and incorporate it into a P-Star framework. Our model of velocity significantly improves the performance of the P-Star model relative to using a one-sided HP filter to calculate trend velocity as used by other researchers. We also include a global supply pressures index in the model and find that recent movements in U.S. inflation largely owed to aggregate demand driven macroeconomic factors that are tracked by Divisia money with a smaller role played by supply factors.

During the global recession of 2020 food insecurity increased substantially in many countries around the world. Fortunately, the surge in food insecurity quickly came to a halt as the world economy returned to its positive growth path, despite double-digit domestic food inflation in most countries. To shed light on the relative importance of income growth and food inflation in driving food insecurity, we employ a heterogeneous-agent model with income inequality, complemented by novel cross-country data for the period 2001–2021. We use external instruments (changes in commodity terms-of-trade, external economic growth, and harvest shocks) to isolate exogenous variation in domestic income growth and food inflation. Our findings suggest that income growth is the dominant driver of annual variations in food insecurity, while food price inflation plays a somewhat smaller role, aligning with our model predictions.

In this paper, we provide a detailed analytical treatment of the behavioral macroeconomic model by De Grauwe and Ji (2020 Structural reforms, animal spirits, and monetary policies. European Economic Review 124, 103395). Although the model’s dynamics is governed by a high-dimensional nonlinear law of motion, we are able to derive necessary and sufficient conditions for the local asymptotic stability of its fundamental steady state. Specifically, we find that under the authors’ baseline parameter setting, the fundamental steady state is locally asymptotically stable, implying that the dynamics of booms and busts only arise when exogenous shocks hit the system. However, we also identify conditions under which boom-bust dynamics emerge temporarily endogenously from within the model. By doing so, we may contribute to a deeper understanding of how booms and busts can arise in such a framework – insights that central banks can use to design more effective monetary policies.

This paper investigates the impact of environmental regulations on inward foreign direct investment (FDI) using a novel index that distinguishes between the implementation and enforcement of environmental policy across 111 countries from 2001 to 2018. Leveraging bilateral FDI data and a structural gravity model, we find robust evidence of a Pollution Haven Effect: weaker environmental regulations in host countries are associated with higher levels of inward FDI. The effect is more pronounced in emerging markets and in environments with higher corruption. Importantly, we show that FDI responds more strongly to policy implementation, capturing formal regulatory commitment, than to enforcement, measured as deviations between predicted and actual emissions. In addition, bilateral FDI patterns are shaped by the environmental stringency gap between source and host countries, consistent with regulatory arbitrage behavior.

The green transition to reduce greenhouse gas emissions requires substantial investments in a narrow time window to avoid climate-related disruptions, adding two new dimensions for monetary policy and exacerbating the trade-offs that central banks face. First, climate-related physical disruptions lead to higher inflation (i.e., Climateflation). Second, the rush to green technology may result in inflation due to supply bottlenecks (i.e., Greenflation). As a consequence, central banks implement restrictive monetary policy that have a detrimental effect on the high up-front costs of renewable energy projects. This slows down the dynamics of green technologies adoption. We build a dynamic non-linear model to study these interactions under reasonable parameterizations. Both Climateflation and Greenflation are quantitatively significant, creating a dilemma for central banks between raising interest rates to counteract inflation and easing them to facilitate renewable investment. We further show that, under specific stochastic scenarios, the trade-off between inflation control and green transition can improve when structural costs for green technologies decrease or when supply-side constraints relax.

Banking supervisors rely on a set of indicators, such as the credit-to-Gross Domestic Product (GDP) gap, to evaluate the macro-financial environment and implement the countercyclical capital buffer. This paper proposes two supplementary indicators, based on forecast-based measures of the credit-to-GDP gap: forecast-augmented credit-to-GDP gaps and predicted credit-to-GDP gaps. While the former has already attracted attention from some banking supervisors, the latter represents a novel metric introduced here. These gaps are generated using singular spectrum analysis. We show that forecasting performance varies between countries and depends on credit market conditions. Furthermore, our results indicate that forecast-based credit-to-GDP gaps are effective in predicting the early stages of a credit boom.

This study revisits the relationship between household consumption and its economic (income, wealth, and interest rates) and behavioural drivers. We specify this relationship while allowing for a threshold effect and a switching regime, which help capture further asymmetry, time-variation, and nonlinearity in this relationship. To this end, we specify a vector logistic smooth transition regression (VLSTR) model, which allows modelling the consumption–income relationship in a nonlinear system and provides more concise estimators. We obtain two interesting results. First, the consumption–income relationship is time-varying, regime-dependent, and it exhibits asymmetry and nonlinearity. Second, while household consumption remains driven by usual factors (income, financial wealth, interest rate, and exchange rate), it is also statistically sensitive to factors (consumer sentiment), and this sensitivity is regime-dependent.

With the increasing demand for sustainable products, greenwashing has become more prevalent and sophisticated over the past decade. To better understand the incentives for firms to greenwash, we develop an evolutionary game-theoretic model in which firms may choose to mimic green behavior without having to bear the cost linked to green investment and production. We provide the conditions for the different evolutionarily stable equilibria. In a second step, we extend the model using agent-based simulations to incorporate path-dependent investment/production costs, history-dependent mimicry effectiveness, peer effects, and localized firm interactions. We show that the simpler model with random matching offers good approximations of the equilibrium conditions in more complex setups, but market segmentation supports green investment and production in contrast to higher penalties. While curtailing opportunities to pretend green behavior boosts green production, we also find that increasing cost efficiencies encourage firms to engage in green production, even in the face of increasingly sophisticated deceptive strategies. Based on our results, we suggest trio-targeted policies that reduce the (initial) costs of green investment/production, curtail opportunities to mimic green behavior, and support segmentation.