International Economic Review最新文献

We present a tractable model that accommodates asset-market sentiment in a standard Dynamic Stochastic General Equilibrium (DSGE) setting, allowing us to quantitatively evaluate sentiment-driven macroeconomic fluctuations. In our model, changes in households' perceived uncertainty about housing prices lead to self-fulfilling fluctuations in housing prices, which then impact investment and output through entrepreneurs' collateral constraints. Household sentiment shocks hence are transmitted and propagated to the macroeconomy, generating boom–bust cycles. Uncertainty, housing prices, and the real economy are linked. Quantitatively, the sentiment shock in the form of risk–panic is a crucial driver of business cycle fluctuations despite the presence of various competing shocks.

Are corporate earnings (CE) announcements important for economic activity? We address this question using a novel identification method that combines the valuable information from CE announcements with the heteroscedasticity of shocks experienced on these particular days. Our results demonstrate that CE announcements have a significant impact on the macroeconomy, exhibiting dynamics similar to traditional financial disruptions. We establish that CE announcements' shocks can be classified as financial shocks, highlighting their critical role in the financial system.

We study the currency risk premium and the forward premium bias in a two-country New Keynesian model with production, no physical capital, and recursive utility. Monetary policy follows an interest rate feedback rule and exogenous total factor productivity (TFP) growth follows a long-run risk process with stochastic volatility, which we estimate from data. With cross-country heterogeneity in TFP and monetary policy, reasonable currency risk premia emerge under complete and incomplete markets but the forward premium bias is trivial. We diagnose the challenge faced by this fairly standard production model to explain the forward premium bias.

Structural models of traffic congestion, such as the bottleneck model, are used to answer important, policy-relevant questions. However, existing models typically assume that no travelers are inframarginal regarding when to travel; that is, given equilibrium travel times, no travelers strictly prefer their ex ante departure time to all others. In this article, I address this shortcoming by incorporating inframarginal travelers into these models. This change significantly improves these models' ability to fit the data and changes policy prescriptions. In the case of congestion pricing, it typically changes the optimal toll by at least 25% and significantly worsens the distributional impacts.

This article develops a job-search model with unobserved worker heterogeneity and learning about worker types from unemployment duration. The model features negative duration dependence that stems from unobserved heterogeneity, skill depreciation, and statistical discrimination. We estimate job-finding rates implied by our model using microlevel data from the Current Population Survey. We find that removing interview costs counterfactually, thereby eliminating statistical discrimination, substantially increases the job-finding rates of the long-term unemployed. The performance of low-skill workers at the interview stage with discriminating firms plays a key role in explaining our counterfactual result.

We examine source dependence in the setting of effort provision. Our first experiment elicits preference over uncertain piece rate schemes to perform a real-effort task. Our second experiment elicits effort after receiving an uncertain gift. We vary the probability of winning and the familiarity of natural sources of uncertainty. We show that subjects are averse to unfamiliar sources for moderate or high probability, but less so for low probability. Moreover, effort exhibits more insensitivity to the probability under the unfamiliar source compared with the familiar source. Our findings support the validity and generalizability of source dependence in applied settings.

With climate change increasing the frequency and intensity of natural disasters, what should central banks do in response to these catastrophic events? Looking at IMF reports for 34 disaster-years, which occurred in 16 disaster-prone countries from 1999 to 2017, reveals lack of any systematic approach adopted by monetary authorities in response to climate shocks. Using a small-open-economy New-Keynesian model with disaster shocks, we show that consistent with textbook theory, inflation targeting remains the welfare-optimal regime. Therefore, the best strategy for monetary authorities is to resist the impulse of accommodating in response to catastrophic natural disasters, and focus on price stability.

This article documents the role of inflows (new listings) and outflows (sales) in explaining the volatility and comovement of housing-market variables. An “ins versus outs” decomposition shows that both flows are quantitatively important for housing-market volatility. The correlations between sales, prices, new listings, and time-to-sell are stable over time, whereas the signs of their correlations with houses for sale are found to be time-varying. A calibrated search-and-matching model with endogenous inflows and outflows and shocks to housing demand matches many of the stable correlations and predicts that the correlations with houses for sale depend on the source and persistence of shocks.

Asset pricing and climate policy are analyzed in a global economy where consumption goods are produced by both a green and a carbon-intensive sector. Given that the economy is initially heavily dependent on carbon-intensive capital, the desire to diversify assets complements the attempt to mitigate economic damages from climate change. In the longer run, however, a trade-off between diversification and climate action emerges. We derive the optimal carbon price and the equilibrium risk-free rate, and risk premia. Climate disasters significantly decrease the risk-free rate but increase risk premia on financial assets, especially if no climate policy is implemented.

We use China's growth experience as a laboratory to study how reductions in administrative and regulatory entry barriers contribute to growth. We develop a model of endogenous productivity and market structure with heterogeneous firms and frictional entry and calibrate it to Chinese manufacturing firms. We show that the reduction of entry barriers brings about 1.05 percentage points of productivity growth over the 1990–2004 period, accounting for 18.3% of the productivity growth in the 2004–7 period. A decomposition exercise shows that entry mainly affects growth through promoting a more competitive market structure, which more than offsets the negative Schumpeterian effect.