We examine the response of the exchange rate to monetary policy shocks using structural vector autoregression (SVAR). The SVAR approach in this study differs from previous studies by incorporating uncertainty measures and employing shock-restricted identification constraints. Using structural shocks that are in accordance with the event and external variable constraints, we demonstrate that the US exchange rate appreciates immediately in response to contractionary monetary policy shocks, with the maximum appreciation occurring within one to two months. Our finding highlights the importance of allowing contemporaneous interaction between interest rate and exchange rate, as facilitated by the shock-restricted SVAR, and accounting for uncertainties to address the puzzle of the exchange rate response.

Specialised AI hardware becomes economically obsolete much faster than conventional capital, so maintaining a given stock of compute requires high replacement investment. This paper studies the implications for growth, adjustment dynamics, and policy in a two-asset growth model in which AI capacity both raises productivity and produces digital services at low marginal cost. Calibrated to advanced economies, the model delivers two distinct adjustment speeds. AI capacity reverts relatively quickly, with a half-life of about seven quarters, while conventional capital adjusts over roughly a decade. When hardware is short-lived, even modest changes in gross spending can produce large swings in measured AI investment, despite only limited movements in the underlying stock. This helps explain the volatility often seen in specialised AI hardware investment cycles. Hardware durability also has first-order welfare effects. In the baseline calibration, a two-percentage-point fall in quarterly depreciation raises welfare by 0.36% in consumption-equivalent terms, while an equal-sized compute tax reduces the steady-state AI stock by around one-fifth.

Climate-related transition risks are expected to escalate in the coming years, posing potentially significant threats to the banking system. This paper employs a DSGE model that incorporates heterogeneous firms and financial frictions to demonstrate the need to explicitly address climate-related risks in the prudential framework. Our findings indicate that failing to acknowledge transition risk can lead to excessive risk-taking by banks, thereby increasing the volatility of lending and output. With the introduction of climate-related prudential policies, banks are less exposed to transition risk and more efficient in allocating capital.

This paper examines how structural reforms can boost long-term growth and welfare in the U.S. economy. Using a model calibrated to historical data, we compare three reforms: reducing regulatory costs, increasing public investment, and eliminating rent-seeking. Our results show that all three improve welfare, but through different channels. Cutting regulatory burdens delivers quick efficiency gains with minimal adjustment costs. Raising public investment has the most substantial impact on growth and welfare, though it requires short-term trade-offs. Eliminating rent-seeking improves efficiency and leisure, but its growth effect is smaller. Overall, public investment emerges as the most powerful lever for growth, while regulatory simplification and institutional reform provide complementary benefits by reducing distortions, improving resource allocation, and reinforcing the efficiency gains from fiscal policy.

In this paper, we examine the role of state-owned enterprises (SOEs) in the transmission of fiscal policy shocks in China, combining a structural VAR with macroeconomic data and a panel model with firm-level data. We first identify two types of structural fiscal shocks using a Bayesian SVAR with sign restrictions and informative priors on structural elasticities: (1) stimulus shocks, defined as deviations from a policy rule for the budget deficit, and (2) government size shocks, which reflect changes in taxes not necessarily affecting the deficit. These shocks are then incorporated into a local projections framework using firm-level data. Our analysis reveals that SOEs respond fundamentally differently from non-SOEs to fiscal shocks. The results suggest that SOEs are not in strict competition with non-SOEs for government resources: both types of firms benefit from fiscal stimulus, yet SOEs are the ones predominantly subject to crowding out when the size of the government sector expands. At the same time, SOEs in strategic industries consistently receive government support under both government size shocks and tax-cut-led stimulus shocks. Moreover, in nonstrategic sectors, SOE investment exhibits a leading effect over non-SOE investment under tax-cut-led stimulus—an effect that vanishes under spending-led stimulus.

Do low-income households systematically face higher inflation than high-income households? Contrary to prevailing narratives based on the consumer price index (CPI), our analysis using personal consumption expenditure (PCE) price indices demonstrates that inflation inequality has been moderating. Using income-stratified PCE price indices consistent with national accounts, we find substantially smaller inflation gaps than CPI-based studies suggest. This convergence is driven by significant inflation in financial services, primarily impacting higher-income households. Recalculating real disposable personal income (DPI) growth using corresponding PCE price indices yields significantly flatter income growth gradients than previously found using the CPI.

The European Union has placed the Circular Economy (CE) as a central strategy to advance fair and sustainable GDP growth. Yet, the mechanisms through which CE could decouple growth from social and environmental harms remain underexplored. This study assesses the macroeconomic, social, and ecological implications of CE policies in France by applying an extended version of the EUROGREEN model. The model is grounded in Ecological Macroeconomics, calibrated on historical data, and simulated over the period 2014–2050 under a business-as-usual (BAU) baseline. A “sequential scenario” methodology is adopted to evaluate alternative CE pathways: (i) a Techno-Optimistic Circularity (TOC) scenario featuring substantial improvements in material efficiency and recycling; (ii) two socially-oriented circularity scenarios that combine moderate technological progress with innovative social policies like reduced working time (C2C) and a Job Guarantee(JG) financed through a wealth tax (SEC); and (iii) a Post-Growth scenario (SCD) characterised by lower consumption and material throughput, supported by a Piketty-style financial wealth tax. Simulation results reveal persistent trade-offs between economic growth, social equity, and environmental sustainability. Growth-centred technological and social circularity scenarios do not achieve sufficient levels of decoupling between economic activity and material use, whereas post-growth pathways deliver balanced outcomes across material extraction, employment, and inequality. Overall, simulation outcomes reveal that growth-oriented circularity strategies cannot combine social equity and long-term sustainability goals. Instead, it seems that integrated policy packages combining technological innovation, social policies, and consumption reduction can reconcile CE ambitions with the pursuit of well-being within planetary boundaries.

This paper examines the vulnerability of variance-maximizing identification, specifically the Max-Share estimator, to biases arising from confounding shocks. We show analytically that Max-Share tends to recover a hybrid of structural disturbances rather than the dominant long-run shock of interest, even when the target shock clearly drives low-frequency variation. To address this weakness, we propose a band-limited frequency-domain estimator – the Limited-Spectral approach – which isolates low-frequency dynamics and reduces contamination from higher-frequency shocks. Using a transparent two-shock model, we characterize the confounding mechanism and document its implications through Monte Carlo experiments. We further show that, while Limited-Spectral improves identification of low-frequency shocks, variance maximization in the spectral domain can still face difficulties at business-cycle frequencies when multiple structural shocks overlap.

I evaluate differences in the response of the U.S. economy to productivity shocks around the effective lower bound (ELB) using post-WWII data. My empirical results indicate that positive productivity shocks are more expansionary when monetary policy operates away from the ELB, in line with a basic New Keynesian model, compared to the ELB regime. The interest-sensitive component of GDP, i.e., private investment, is the main driver of this nonlinear response. I find evidence of regime thresholds beyond the standard 0.25% Federal Funds Rate definition of the ELB that could influence the state-dependent shock response of the economy. My work highlights the role played by the monetary policy channel in changing the propagation of productivity shocks to the U.S. economy.

This article investigates the dynamics of a parsimonious extension of the standard neo-classical growth model introduced by Solow (1956) and Swan (1956) to a two-sector growth model in discrete time. We identify the economy’s propensity to invest as a market mechanism that may cause endogenous business cycles and complex dynamics, provided that the elasticity of factor substitution in producing consumption goods is sufficiently small. The theoretical results are supported by numerical evidence for topological chaos and strange attractors.

The macroeconomic literature assumes that sectoral labor income shares and output per person are uncorrelated across countries. This paper shows that the data reject this assumption for a large set of countries. The labor shares of the manufacturing and market services sectors systematically increase with output per person relative to those of other sectors, leading to a shift of labor income across sectors with economic development. The empirical evidence suggests that capital deepening and cross-sector differences in the degree of capital-labor substitutability may be important for understanding these patterns. Researchers can directly use the provided dataset of labor shares to calibrate macroeconomic models.