This paper studies the impact of the COVID-19 epidemic on economic and health outcomes in China from January 20 to September 28, 2020. We first document China’s containment policies and present empirical evidence on the role of the online economy. We then use a SIR-macro model to study the macroeconomic and health outcomes of the epidemic. The model can generate infection and death dynamics broadly consistent with the data and the U-shaped recovery of the Chinese economy at the weekly frequency. The analysis reveals that, in addition to the containment policies, the development of the online economy (both online consumption and remote work) plays a critical role in fighting an epidemic.

We augment an overlapping generations endogenous credit cycle model with environmental externalities and two regulatory authorities to study how fiscal and financial environmental regulation together shape environmental quality, macroeconomic stability, and income distribution. Environmental quality depends on pollution from the brown sector, regulated either through environmental haircuts on collateral or via tax-financed abatement and environmental improvements. We find that haircuts and taxes affect emissions, income distribution, and system stability in distinct ways, with interaction effects that create trade-offs between environmental outcomes and macroeconomic stability. Compared to scenarios with only financial regulation, introducing an environmental tax maintains similar environmental quality but achieves higher aggregate income and capital per worker. However, we uncover intergenerational trade-offs as environmental regulation improves environmental quality and raises incomes for younger agents and investors but lowers and destabilizes the returns of older generations reliant on capital income.

This study analyses the dynamics of the global rare earth element market, with a focus on China’s dominant role as the primary supplier, which is crucial for the energy transition and digitalization. Using a game-theoretic approach, the research examines a potential duopoly market structure that may emerge over time, as well as potential shifts in supply from China to other countries in this scenario. It considers China’s low marginal costs and factors such as resource extraction and discoveries. Additionally, the study examines the strategic market interactions, the role of technological advancements, and policy support in shaping market outcomes. The methodology assumes that agents have limited foresight and use a learned value function to strategically assess outcomes based on their own and others’ actions, while accounting for environmental constraints.

We explore the effects of fiscal policy shocks on aggregate output and inflation. We use the Bayesian econometric methodology of Baumeister and Hamilton applied to the fiscal structural vector autoregressive model to evaluate key elasticities and fiscal multipliers using U.S. data. In our baseline specification that ends before Covid pandemic, the government spending multiplier is equal to approximately $0.57$ and tax multiplier is approximately $-0.35$ after one year. The short-term output elasticity of government spending is statistically insignificant and the output elasticity of taxes is approximately equal to $2.26$.

We investigate the impact of the academic environment on directed technical change and economic growth. We develop a heterogeneous Schumpeterian growth model in which innovation is categorized into radical and incremental types. A supportive environment for academic exploration enhances scientists’ autonomy utility in basic research, thereby motivating basic research and reducing the R&D difficulty of radical innovations through knowledge spillovers. We identify two major effects of the academic environment on economic growth: a positive directed technical change effect fostering growth through radical innovation, and a negative applied research crowding-out effect. Numerical analysis based on Chinese data reveals a negative autonomy utility (−0.37), indicating insufficient autonomy in basic research exploration. Promoting economic growth necessitates institutional reforms. The optimal autonomy utility for maximizing growth is 0.80. Welfare analysis further shows that the optimal autonomy utility is 0.87 for basic research labor and 0.75 for non-basic research labor.

The pandemic crisis introduced an unprecedented supply-side shock that was global in scope. Despite historically high levels of prior sovereign debt and low bond yields, macroeconomic policy responses included monetised fiscal expansions of extraordinary magnitude. Conventional theory suggests that the combination of supply contractions with such expansions is inflationary, yet central bank discourse during the pandemic expressed little concern about inflation. Our theoretical analysis suggests the presence of strong inflation forces at the time, likely offset by continuing pessimism shocks, consumption constraints and expectations management. In prominent advanced countries over more than a century, monetised fiscal expansions are shown to have preceded inflation surges, most strongly following signature episodes like WWII.

This paper introduces an overlapping generations model to explore the interplay between economic growth, the environment, and endogenous technology adoption. Considering an economy with physical capital and publicly funded human capital, the analytical framework extends Prieur and Bréchet (2013, Macroeconomic Dynamics 17, 1135–1157) by incorporating the endogenous technology choice mechanism from Umezuki and Yokoo (2019, Journal of Economic Dynamics & Control 100, 164–175). The analysis focuses on how the choice of capital-intensive technologies impacts environmental dynamics. The model reveals complex equilibrium dynamics, driven by a core trade-off between individuals’ resource allocation on consumption versus environmental protection and firms’ technology decisions.

This study utilizes a Bayesian Dynamic Stochastic General Equilibrium model, calibrated with Chinese data, to assess the impact of public investments, which account for about 16.2% of China’s GDP. Despite an expected public capital stock of 256% of GDP, based on a 4.6% depreciation rate and a 0.73 efficiency rate of public investment (emerging-economy estimate), the actual figure stands at 152%. This significant discrepancy underscores the inefficiencies in public investments, with 43% of public investment expenditures enhancing the capital stock. The output elasticity (productivity) of public capital is estimated at just 3%, substantially lower than the previously estimated 8% for emerging economies, and has declined to 2% in the post-2008 period. Simulations based on these efficiency and productivity metrics reveal that the output multiplier of public investment is 0.7. China’s public investments reduce TFP, crowd out private investment, and raise the public debt-to-GDP ratio in the medium term.

This paper applies Structure-Preserving Doubling Algorithms (SDAs) to solve the matrix quadratic that underlies linear DSGE models. We present and compare two SDAs to other competing methods—the QZ method, a Newton algorithm, and an iterative Bernoulli approach—as well as linking them to the cyclic and logarithmic reduction algorithms included in Dynare. Our evaluation, conducted across 142 models from the Macroeconomic Model Data Base and multiple parameterizations of the Smets and Wouters (2007) model, demonstrates that SDAs generally provide more accurate solutions in less time than QZ. We also establish their theoretical convergence properties and robustness to initialization issues. The SDAs perform particularly well in refining solutions provided by other methods and for large models.

The consensus view in the growth literature is that R&D scale effects are absent in mature industrialized economies but may be present in emerging economies undergoing transition. Scale effects imply a proportional relationship between a stationary $I(0)$ regressand (growth rates of real per capita GDP and/or TFP) and a non-stationary $I(1)$ regressor (the scale of R&D), which gives rise to the problem of unbalanced regression and spurious parameter estimates. This issue has not been adequately addressed in the existing literature. Furthermore, emerging economies have received relatively little attention in this context. We address these issues by (i) accurately measuring R&D scale and (ii) adopting an appropriate econometric specification and estimator. We find significant scale effects in a panel of emerging countries, but not in developed countries. We propose an endogenous growth model that captures these properties—presence of scale effects during growth transitions, but not at the long-run equilibrium—thereby reconciling our results. Our model predicts that the long-run growth rates of per capita real GDP and TFP are driven by the growth rates of technological innovation and aggregate employment—although, in the case of emerging economies, only technological innovation significantly contributes to TFP growth.

We analyse the monetary-fiscal policy mix in post-war Europe, focusing on France and Italy, to trace the historical dynamics of debt and inflation. Using a Markov-switching DSGE model, we identify distinct policy regimes: a Passive Monetary-Active Fiscal (PM/AF) regime before the late 1980s/early 1990s, an Active Monetary-Passive Fiscal (AM/PF) regime associated with central bank independence and EMU convergence, and a third regime marked by the ELB and active fiscal measures aimed at recovery. Simulations reveal that the PM/AF regime in France led to price volatility but stabilised debt, while AM/PF curbed inflation at the cost of rising debt. In contrast, Italy’s procyclical fiscal policy in downturns exacerbated imbalances, aggregate volatility, and low growth. We further assess the implications of policy credibility and uncertainty.

This paper studies the stabilization properties of time-varying capital requirements in an environment dominated by an oligopolistic banking sector, where banks accumulate capital subject to a leverage adequacy cost. The results indicate that macroprudential policy can stabilize fluctuations in business and credit cycles by controlling the loan rate, thereby influencing the spread within the banking system. A welfare analysis shows that the welfare gains from macroprudential policy depend on the type of shock hitting the economy, and that higher banking competition can amplify these benefits. The findings also highlight that time-varying capital requirements should not substitute for monetary policy, but rather complement it in addressing financial imbalances and adverse sectoral shocks.

This paper studies the price-setting behaviour in food products, using the microdata underlying the Portuguese Consumer Price Index (CPI). We document that, in each month, about 1 in 4 food items changed prices compared to the previous month, including promotions and sales. If these temporary price changes are excluded, the frequency drops to 1 out of 5, on average. Positive price changes were more frequent but had lower magnitudes than negative ones. There were strong heterogeneities in price-setting not only across products but also across industries and outlets. We find that, from 2009 to 2019, food inflation was primarily driven by the relative frequency of positive versus negative price changes, rather than changes in their size, consistent with standard New Keynesian calibrations of price rigidity. Finally, we report that price changes were more frequent at the producer than at the consumer level, but with a lower magnitude. Taken together, these results highlight that the frequency margin is the key driver of inflation dynamics and provide micro evidence supporting widely used macroeconomic calibrations of price rigidity.

This paper studies the transition to high inflation during the COVID-19 pandemic, using a behavioral version of the New Keynesian model, which replaces the conventional assumption of rational expectations with subjective and heterogeneous expectations. Different shares of agents in the economy form expectations based on alternative views regarding future economic variables: (1) a share of agents forecasts that inflation and output will rapidly revert to steady state; (2) another share forms forecasts based on a model resembling the MSV solution under rational expectations; (3) a third share of agents uses an under-specified model that captures trend-following, adaptive, or extrapolative behavior. Agents learn over time the parameters of their perceived model and they can also shift across different views based on past forecasting performance. The macroeconomic model is estimated using Bayesian methods to fit realized macroeconomic variables and data on expectations from surveys. The results document an additional channel that operates through switches in agents’ perceptions and amplifies the impact of the original inflationary shocks. In response to rising inflation after COVID, agents begin shifting from the mean reversion model to the trend-following specification (with a belief about perceived inflation persistence that is simultaneously revised upward). Consequently, the impact of inflationary shocks is magnified and the effects of monetary policy attenuated.

We explore international reserve accumulation in Emerging Market Economies (EMEs), rationalizing policymakers’ belief that it counteracts the negative effects of capital inflows. Empirical evidence reveals that EMEs accumulate reserves in response to capital inflows driven by global push factors, especially when there are limitations on residents’ investments abroad. We elucidate these findings with a three-period model of a small open economy. In the first period, a large direct investment inflow occurs, prompting an EME to save abroad for consumption smoothing. If frictions hinder private overseas investments, the government can accumulate reserves to supplement insufficient private outflows. The theory highlights the role of reserves in managing capital inflows, as substantiated by our empirical findings.

We provide new evidence on U.S. monetary policy spillovers to Australia using an integrated time–frequency connectedness framework. Spillovers primarily transmit through the interest rate (policy rate) channel, followed by the asset price (with the consumer discretionary sector as the main conduit) channel and the exchange rate channel. Spillovers are highly time-varying, peaking at the onset of COVID-19 and again during the global financial crisis and the European sovereign debt crisis. Linking these spillovers to the real economy, we show that an identified U.S. tightening is followed by a tightening in Australia’s monetary policy stance and generates contractionary and disinflationary effects on Australian output and inflation, consistent with transmission via imported financial conditions and the domestic policy reaction. Finally, we show that ignoring spillovers yields a price puzzle under recursive VAR identification, while using spillover-based surprises as external instruments removes the puzzle and recovers theory-consistent responses.

This study investigates the relationship between consumers’ fiscal and inflation expectations using granular survey data. After applying various methods to reduce endogeneity bias and providing several robustness checks, we show that consumers’ fiscal expectations positively affect their inflation expectations. Moreover, we demonstrate that this link is nonlinear and becomes stronger with the deterioration of the fiscal stance, particularly in response to increases in consumer expectations regarding future fiscal expansions. This novel empirical finding is especially relevant from both fiscal and monetary policy perspectives.

Sovereigns issue debt on both domestic and foreign markets and when they default, they default mostly selectively. We propose a theory to rationalize these observations. A government chooses the optimal combination of two debts to smooth consumption, which is subject to output shock and volatile tax distortions. In equilibrium, it mostly relies on domestic debt to smooth the tax wedge and on foreign debt to smooth the output shock. Issuing either debt is less costly than raising taxes, but it is subject to default risk due to the government’s limited commitment. A quantitative, calibrated model with two shocks and two debts replicates well debt-to-GDP ratios, default frequencies, cyclical properties of emerging economies and behavior of aggregates around default episodes.

We study the effect of time-varying disagreement of professional forecasters on the transmission of monetary policy in Korea, which has transitioned from an emerging to an advanced economy. We find that high levels of disagreement interfere with the transmission of monetary policy and, hence, weaken monetary policy effects. However, under low levels of disagreement, a monetary policy shock elicits textbook-like responses of inflation, expected inflation, and real activity. The findings are consistent with the view that disagreement affects the role of the signaling channel of monetary transmission relative to the conventional transmission channel. We also show that the dependance of the transmission on the level of disagreement remains intact even after controlling for time-varying monetary policy uncertainty and considering the shifts in the Bank of Korea’s inflation target type.