In financial crises, a period of overheated credit markets turns into a credit crunch accompanied by a systemic breakdown in the financial intermediary sector. Without a deep understanding of their roots, designing policies to decrease the probability of suffering from them or to avoid the worst consequences is like flying blind. In this review, I survey the recent development of the theory of financial crises. I focus on the answers these theories provide to four fundamental questions. What makes the booming phase fragile, and what are the incentives and frictions leading to that fragility? What triggers the crisis? Why is the downturn persistent? Should policy intervene, and if so, how?

We assess the efficacy of market-based systemic risk measures that rely on US financial firms’ stock return comovements with market- or sector-wide returns under stress from 1895 to 2023. Stress episodes are identified using corporate bond spread widening and narrative dating, spanning from the Panic of 1907 to the Banking Stress of 2023. Measures observed prior to the onset of stress episodes predict market outcomes (realized volatility and returns), balance sheet outcomes (lending, profitability, and run risk), and bank failures. Specifically, the measures are: ( a ) particularly effective in capturing the cross-sectional ranking of institutions conditional on a stress episode, rather than aggregate outcomes; ( b ) more informative when stress episodes are severe; and ( c ) relevant for both banks and nonbank financial institutions, although measures incorporating market leverage are especially informative for banks. A comparative analysis shows that market-based indicators offer information that is distinct from, and complementary to, traditional balance sheet metrics used in supervisory and macroprudential risk assessment.

Fiscal dominance refers to situations in which monetary policy is constrained by the public sector's budget constraint. Large shifts in the dynamics of sovereign debts, surpluses, and central banks’ balance sheets since the great financial crisis have created the perception of a heightened risk of such fiscal dominance in major jurisdictions. This article reviews the theoretical and empirical literature on fiscal dominance. We offer a simple theory in which fiscal dominance arises as the outcome of strategic interactions between the government and the central bank.

Research is needed to quantify impacts and understand interactions with the broader economy.

ABSTRACT Around 50 years ago, the Netherlands decriminalized cannabis for recreational use. This article uses retrospective data on the ages at which individuals began and ceased cannabis use to reconstruct its prevalence in Amsterdam during the period surrounding the policy change. This approach enables a detailed analysis of the policy’s effects. The main conclusion is that the introduction of this policy did not lead to an increase in the prevalence of cannabis use.

Although climate change is expected to have a significant impact on the global population, little is known about how it will affect individual households in their daily lives. Based on food price increases caused by climate change, we analyze how climate-change-related damages distribute across households in 90 developing countries. In a microsimulation model, climate damages are quantified as losses in consumer surplus and are, on average, roughly 3% of total expenditure. We find evidence that climate damages are regressive, i.e., they disproportionately affect households with lower total consumption. Damages display regressivity when we compare (a) national averages across countries, (b) all households in our sample, and (c) households within countries. However, there are some — often more developed — countries, where damages are progressive, i.e., damages disproportionately affect more affluent households in those countries. At a sectoral level, damages tend to be more regressive in countries where, in relative terms, rice consumption contributes more to the welfare of households.

Meta-analysis assigns more weight to studies with smaller standard errors to maximize the precision of the overall estimate. In observational settings, however, standard errors are shaped by methodological decisions. These decisions can interact with publication bias and p-hacking, potentially leading to spuriously precise results reported by primary studies. Here we show that such spurious precision undermines standard meta-analytic techniques, including inverse-variance weighting and bias corrections based on the funnel plot. Through simulations and large-scale empirical applications, we find that selection models do not resolve the issue. In some cases, a simple unweighted mean of reported estimates outperforms widely used correction methods. We introduce MAIVE (Meta-Analysis Instrumental Variable Estimator), an approach that reduces bias by using sample size as an instrument for reported precision. MAIVE offers a simple and robust solution for improving the reliability of meta-analyses in the presence of spurious precision.

Firms, workers, and consumers in developing countries are increasingly connected to each other and to the rest of the world through the internet. Can this connectivity transform poor economies, as technology optimists hope, or are there more deeply rooted barriers to economic development? Research on the topic is growing rapidly. In this article we provide an overview of existing evidence from 153 studies on the extent to which, and how, internet connectivity affects economic development. Not surprisingly, estimates vary widely with the context, particular outcome, and form of internet studied. Overall, the literature points toward sizable economic impacts in many—though not all—settings.

The anticipation of Ukraine's postwar reconstruction has led to an avalanche of academic and policy analyses on how to rebuild the country. To help the profession navigate this rapidly expanding literature, this article provides a synthesis and critical overview of the proposals. After describing the historical context, damages inflicted by Russian aggression, and funds required for Ukraine's recovery, we summarize principles, phases, and policies needed to deeply modernize the country. The reconstruction of Ukraine should provide a template for other recovery programs.

There is a rapidly advancing literature on the macroeconomics of climate change. This review focuses on developments in the construction and solution of structural integrated assessment models (IAMs), highlighting the marriage of state-of-the-art natural science with general equilibrium theory. We discuss challenges in solving dynamic stochastic IAMs with sharp nonlinearities, multiple regions, and multiple sources of risk. Key innovations in deep learning and other machine learning approaches overcome many computational challenges and enhance the accuracy and relevance of policy findings. We conclude with an overview of recent applications of IAMs and key policy insights.