International Economic Review最新文献

This study provides new mechanisms for identifying and estimating explosive bubbles in mixed-root panel autoregressions with a latent group structure. A postclustering approach is employed that combines k-means clustering with right-tailed panel-data testing. Uniform consistency of the k-means algorithm is established. Pivotal null limit distributions of the tests are introduced. A new method is proposed to consistently estimate the number of groups. Monte Carlo simulations show that the proposed methods perform well in finite samples; and empirical applications of the proposed methods identify bubbles in the U.S. and Chinese housing markets and the U.S. stock market.

We provide a quantitative analysis of the distributional effects of the 2018 increase in tariffs by the United States and its major trading partners. We build a trade model with incomplete asset markets and households that are heterogeneous in their age, income, wealth, and labor skill. When tariff revenues are used to reduce distortionary taxes on consumption, labor, and capital income, the average welfare loss from the trade war is equivalent to a permanent 0.1% reduction in consumption. Much larger welfare losses are concentrated among retirees and low-wealth households, whereas only wealthy households experience a welfare gain.

This article quantifies the value of U.S. highways. We develop a multisector general equilibrium model with many locations in the United States (i.e., counties) and many countries. In the model, producers choose shipping routes subject to domestic and international trade costs, endogenous congestion, and port efficiency at international transshipment points. Applying the model, we find that removing the Interstate Highway System reduces real GDP by $421–$578 billion. The results highlight the gains from intersectoral and international trade as well as the role of domestic transportation infrastructure in shaping regional comparative advantage.

School Choice provides students with the opportunity to attend better schools than those in their neighborhood. This is crucial for students from disadvantaged areas where schools may be of lower quality. Our theoretical model and numerical simulations show that the widely used Deferred Acceptance (DA) algorithm has limitations in providing access to better schools (ABS). When schools have varying levels of quality and when there are priorities linked to neighborhood schools, the DA algorithm experiences significant limitations in providing ABS. Top Trading Cycles, when compared to DA, offers greater ABS, particularly for disadvantaged students.

Two types of interventions are commonly implemented in networks: characteristics interventions, which influence individuals' intrinsic incentives, and structural interventions, which target the social links among individuals. In this article, we provide a general framework to evaluate the distinct equilibrium effects of both types of interventions. We show that any structural intervention is outcome-equivalent to an endogenously determined characteristics intervention. We present a wide range of applications of our theory, including evaluating a potential new link in a community, identifying the most wanted criminal(s) in delinquent networks, and determining whether a structural intervention improves certain welfare measures.

We show that in Italy the legalization of divorce unleashed the forces of secularization, making educated persons more likely to contract a civil instead of a religious marriage. This process, ignited by institutional change, is also shaped by culture: higher social capital or weaker family ties make the choice of civil marriage more responsive to education. These results emerge from both aggregate and individual data, and can be rationalized through a model of religiosity, education and marriage choices. In this framework, the option to divorce increases the relative returns to human capital - thereby increasing the prevalence of civil marriage.

In buyer–seller relationships, offering trade credit to buyers fosters long-term collaboration but seller provision varies systematically as relationships evolve. We study the optimal provision dynamics of trade credit when the seller's information about the buyer is incomplete. We show how the interaction of self-enforcing relational contracts and formal contracts determines optimal payment contract choice. We find that payment contracts can be interpreted as screening technologies and imply distinct learning opportunities about the buyer's type. In line with empirical evidence, the model predicts that all transitions between payment terms lead to seller trade credit provision in the long run.

This article identifies shocks to the Federal Reserve's inflation target as vector autoregression innovations that make the largest contribution to future movements in long-horizon inflation expectations. The effectiveness of this scheme is documented via Monte-Carlo experiments. The estimated impulse responses indicate that a positive shock to the target is associated with a large increase in inflation and long-term interest rates in the United States. Target shocks are estimated to be a vital factor behind the increase in inflation during the pre-1980 period and are an important driver of the decline in long-term interest rates over the last two decades.

This article provides theory and evidence on the spatial determinants of regional patient flows. We develop a theoretical model that explains a patient's choice to consult a general practitioner by a measure of spatial accessibility. We empirically test this gravity-type model using regional patient flows and detailed data on the spatial distribution of residents and physicians in Austria. Our measure of spatial accessibility is a crucial determinant of patient flows that substantially increases the explanatory power of regular gravity models. Counterfactual simulations show heterogeneous effects of exiting physicians on health-care accessibility and patient mobility.