Journal of Economic Dynamics & Control最新文献

英文中文

Leaning against persistent financial cycles with occasional crises 倾向于持续的金融周期和偶尔的危机

IF 2.3 3区经济学 Q2 ECONOMICS

Journal of Economic Dynamics & Control

Pub Date : 2026-02-01 Epub Date: 2025-12-22 DOI: 10.1016/j.jedc.2025.105245

Thore Kockerols , Erling Motzfeldt Kravik , Yasin Mimir

We investigate the conditions under which a leaning against the wind (LAW)-type monetary policy is advisable to address risks to financial stability stemming from housing credit imbalances. We do so within an endogenous regime-switching dynamic stochastic general equilibrium (DSGE) model with occasional crises, effective lower bound (ELB) on interest rates, and intrinsically persistent financial cycles driven by partly backward-looking house price expectations. Under empirically plausible financial cycles, LAW amplifies the transmission of supply shocks to inflation by strengthening the countercyclical response of collateral values and domestic demand. This results in heightened inflation volatility and a lower average inflation rate, thereby increasing the frequency of ELB episodes. In our baseline estimated model, we find that these costs far outweigh the benefits of a less likely and less severe crisis. However, we also show that LAW may become advisable, depending on specific conditions, including (i) if the central bank focuses less on near-term output stabilization but more on medium-term growth stability by counteracting financial imbalances, or (ii) if the expectations-driven financial cycles are intrinsically less persistent or more policy-responsive than currently observed. Higher long-run capital regulation is better suited to addressing risks to financial stability as it significantly reduces the fluctuations in inflation and output by reducing both the frequency of ELB and the severity of crises.

我们研究了在哪些条件下，逆风（LAW）型货币政策是可取的，以解决住房信贷失衡引发的金融稳定风险。我们在一个内源性制度转换动态随机一般均衡（DSGE）模型中进行研究，该模型具有偶发危机、利率的有效下限（ELB）以及由部分向后看的房价预期驱动的内在持续的金融周期。在经验上合理的金融周期中，LAW通过加强抵押品价值和国内需求的反周期反应，放大了供给冲击对通胀的传导。这导致通货膨胀波动加剧，平均通货膨胀率降低，从而增加了ELB发作的频率。在我们的基线估计模型中，我们发现这些成本远远超过了不太可能和不那么严重的危机所带来的好处。然而，我们也表明，LAW可能会变得可取，这取决于具体情况，包括(i)如果央行通过抵消金融失衡而不太关注近期产出稳定，而是更关注中期增长稳定，或者（ii）如果预期驱动的金融周期本质上比目前观察到的更不持久或更具政策响应性。加强长期资本监管更适合于应对金融稳定风险，因为它通过降低低负债的频率和危机的严重程度，大大减少了通货膨胀和产出的波动。

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引用次数: 0

Tradeoffs for the poor, divine coincidence for the rich 穷人得失，富人得失

IF 2.3 3区经济学 Q2 ECONOMICS

Journal of Economic Dynamics & Control

Pub Date : 2026-01-01 Epub Date: 2025-12-01 DOI: 10.1016/j.jedc.2025.105221

Marco Del Negro , Ibrahima Diagne , Keshav Dogra , Pranay Gundam , Donggyu Lee , Brian Pacula

We use an estimated medium-scale HANK model to investigate how the tradeoff between stabilizing inflation and consumption volatility varies for households with different levels of wealth. Consumption for the rich is mostly affected by demand shocks via their exposure to highly procyclical profits—for them, stabilizing consumption and inflation coincide. The poor are more vulnerable to supply shocks, hence aggressively stabilizing inflation is costly in terms of their consumption volatility. While they dislike inflation because it erodes real wages, they are hurt even more by an aggressive monetary policy response to inflation, which reduces real wages further while increasing unemployment.

我们使用估计的中等规模HANK模型来研究不同财富水平的家庭在稳定通胀和消费波动之间的权衡是如何变化的。富人的消费主要受到需求冲击的影响，因为他们面临着高度顺周期的利润——对他们来说，稳定的消费和通货膨胀是一致的。穷人更容易受到供应冲击的影响，因此，就他们的消费波动而言，积极稳定通胀是代价高昂的。虽然他们不喜欢通胀，因为它侵蚀了实际工资，但对通胀采取激进的货币政策对他们的伤害更大，因为这进一步降低了实际工资，同时增加了失业率。

引用次数: 0

Back in time. fast. Accelerated time iterations 回到过去。快。加速时间迭代

IF 2.3 3区经济学 Q2 ECONOMICS

Journal of Economic Dynamics & Control

Pub Date : 2026-01-01 Epub Date: 2025-12-03 DOI: 10.1016/j.jedc.2025.105226

Pablo Winant

We present two complementary algorithms to solve nonlinear rational expectations models characterized by first order conditions: an accelerated time-iteration method and a Newton–Krylov solver. Both approaches exploit an explicit construction of the derivative operator (and the model Jacobian) and achieve quadratic convergence near the solution, yielding large computational gains over standard time iteration. We show how to apply these linear operators without forming dense matrices and invert the resulting systems efficiently using truncated Neumann series or GMRES. On three benchmark models (consumption–savings, RBC, and a two-country model), the two methods produce the same solution with substantially reduced runtimes.

我们提出了两种互补的算法来求解一阶条件下的非线性理性期望模型：一种加速时间迭代法和一种Newton-Krylov求解法。这两种方法都利用了导数算子（和模型雅可比矩阵）的显式构造，并在解附近实现了二次收敛，在标准时间迭代中产生了大量的计算增益。我们展示了如何在不形成密集矩阵的情况下应用这些线性算子，并使用截断的诺伊曼级数或GMRES有效地反演得到的系统。在三个基准模型（消耗-节约、RBC和一个两国模型）上，这两种方法产生了相同的解决方案，并且大大缩短了运行时间。

引用次数: 0

Unemployment risk, liquidity traps, and monetary policy 失业风险、流动性陷阱和货币政策

IF 2.3 3区经济学 Q2 ECONOMICS

Journal of Economic Dynamics & Control

Pub Date : 2026-01-01 Epub Date: 2025-12-05 DOI: 10.1016/j.jedc.2025.105238

Dario Bonciani , Joonseok Oh

We study optimal monetary policy in a model with incomplete markets, in the form of uninsurable unemployment risk, and an occasionally binding zero lower bound (ZLB) constraint. The optimal policy consists of keeping the nominal rate at zero longer than implied by current macroeconomic conditions. Such policy improves expected labour market conditions, substantially mitigating the rise in unemployment risk and precautionary savings. As a result, we find that market incompleteness does not significantly amplify contractions in output and inflation at the ZLB. However, when the central bank follows more realistic policy rules instead of the optimal policy, incomplete markets exacerbate the fall in demand, emphasising the importance of unemployment insurance for output stabilisation.

本文研究了不完全市场模型下的最优货币政策，该模型具有不可保险的失业风险和偶尔约束的零下限约束。最优政策是将名义利率维持在零的时间比当前宏观经济状况所暗示的更长。这种政策改善了预期的劳动力市场状况，大大减轻了失业风险的上升和预防性储蓄。因此，我们发现市场不完全性并没有显著放大ZLB的产出收缩和通货膨胀。然而，当央行遵循更现实的政策规则，而不是最优政策时，不完整的市场加剧了需求的下降，突显了失业保险对稳定产出的重要性。

引用次数: 0

Uncertainty shocks in an intangible economy 无形经济中的不确定性冲击

IF 2.3 3区经济学 Q2 ECONOMICS

Journal of Economic Dynamics & Control

Pub Date : 2026-01-01 Epub Date: 2025-11-28 DOI: 10.1016/j.jedc.2025.105230

Shuonan Zhang

This paper studies uncertainty shocks in the context of an intangible economy. I build a two-sector dynamic stochastic general equilibrium (DSGE) model to understand a shift in investment composition and its implications for the transmission of uncertainty shocks. The model is motivated by the role of intangible capital as a cushion, mitigating the adverse effects of uncertainty on investment, as suggested by firm-level data. The quantitative analysis shows that heightened uncertainty directs resources toward the intangible sector, making the economy more intangible-intensive. The rising importance of intangibles diminishes aggregate volatility in the uncertainty-driven business cycle.

本文研究了无形经济背景下的不确定性冲击。我建立了一个两部门动态随机一般均衡（DSGE）模型来理解投资构成的转变及其对不确定性冲击传导的影响。正如公司层面的数据所表明的那样，该模型的动机是无形资本作为缓冲的作用，减轻了不确定性对投资的不利影响。定量分析表明，不确定性的增加将资源引向无形部门，使经济更加无形密集。在不确定性驱动的商业周期中，无形资产重要性的上升降低了总波动性。

引用次数: 0

Optimal credit market policy 最优信贷市场政策

IF 2.3 3区经济学 Q2 ECONOMICS

Journal of Economic Dynamics & Control

Pub Date : 2026-01-01 Epub Date: 2025-11-26 DOI: 10.1016/j.jedc.2025.105223

Matteo Iacoviello , Ricardo Nunes , Andrea Prestipino

We study optimal credit market policy in a stochastic, quantitative, general equilibrium, infinite-horizon economy with collateral constraints tied to housing prices. Collateral constraints imply that the competitive equilibrium is Pareto inefficient. Taxing housing or borrowing in good states and subsidizing it in recessions leads to a Pareto-improving allocation for borrowers and savers. Quantitatively, the welfare gains afforded by the optimal tax are significant. The optimal tax reduces the covariance of house prices with consumption, and, by doing so, it increases house prices on average and delivers welfare gains both in steady state and around it. We also show that the welfare gains stem from mopping up after the crash rather than the ex-ante macroprudential aspect, aligning with prior research that emphasizes the importance of ex-post measures compared to preventive policies alone.

我们研究了一个随机、定量、一般均衡、无限视界经济中抵押约束与房价挂钩的最优信贷市场政策。附带约束意味着竞争均衡是帕累托无效率的。在经济状况良好的州对住房或借贷征税，并在经济衰退时对其进行补贴，会导致借款人和储蓄者的帕累托分配得到改善。从数量上讲，最优税收所带来的福利收益是显著的。最优税收减少了房价与消费的协方差，这样做，它提高了房价的平均水平，并在稳定状态和稳定状态附近提供了福利收益。我们还表明，福利收益源于崩溃后的清理，而不是事前的宏观审慎方面，与先前的研究一致，强调事后措施与单独的预防性政策相比的重要性。

引用次数: 0

Scalable global solution techniques for high-dimensional models in Dynare Dynare中高维模型的可伸缩全局解决方案技术

IF 2.3 3区经济学 Q2 ECONOMICS

Journal of Economic Dynamics & Control

Pub Date : 2026-01-01 Epub Date: 2025-11-26 DOI: 10.1016/j.jedc.2025.105225

Aryan Eftekhari , Michel Juillard , Normann Rion , Simon Scheidegger

For over three decades, Dynare has been a cornerstone of dynamic stochastic modeling in economics, relying primarily on perturbation-based local solution methods. However, these techniques often falter in high-dimensional, non-linear models that demand more comprehensive approaches. This paper demonstrates that global solutions of economic models with substantial heterogeneity and frictions can be computed accurately and swiftly by augmenting Dynare with adaptive sparse grids (SGs) and high-dimensional model representation (HDMR). SGs mitigate the curse of dimensionality, as the number of grid points grows significantly slower than in traditional tensor-product Cartesian grids. Additionally, adaptivity focuses grid refinement on regions with steep gradients or non-differentiabilities, enhancing computational efficiency. Complementing SGs, HDMR tackles large state spaces by approximating policy functions with a hierarchical expansion of low-dimensional terms. Using a time iteration algorithm, we benchmark our approach on an international real business cycle model. Our results show that both SGs and HDMR alleviate the curse of dimensionality, enabling accurate solutions for at least 100-dimensional models on standard hardware in relatively short times. This advancement extends Dynare’s capabilities beyond perturbation approaches, establishing a versatile platform for sophisticated non-linear models and paving the way for integrating the most recent global solution methods, such as those from machine learning.

三十多年来，Dynare一直是经济学中动态随机建模的基石，主要依靠基于摄动的局部解方法。然而，这些技术在需要更全面的方法的高维非线性模型中经常出现问题。本文证明了通过自适应稀疏网格（SGs）和高维模型表示（HDMR）增强动态模型，可以准确、快速地计算具有大量异质性和摩擦的经济模型的全局解。SGs减轻了维度的诅咒，因为网格点的数量增长明显慢于传统的张量积笛卡尔网格。此外，自适应将网格细化重点放在陡峭梯度或不可微区域，提高了计算效率。作为一种补充，HDMR通过使用低维项的分层扩展来近似策略函数来处理大型状态空间。我们使用时间迭代算法，将我们的方法作为国际真实商业周期模型的基准。我们的研究结果表明，SGs和HDMR都缓解了维度的诅咒，在相对较短的时间内为标准硬件上的至少100维模型提供了准确的解决方案。这一进步将Dynare的功能扩展到摄动方法之外，为复杂的非线性模型建立了一个通用平台，并为集成最新的全局解决方案方法（如机器学习方法）铺平了道路。

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引用次数: 0

Estimation of nonlinear DSGE models through Laplace based solutions 基于拉普拉斯解的非线性DSGE模型估计

IF 2.3 3区经济学 Q2 ECONOMICS

Journal of Economic Dynamics & Control

Pub Date : 2026-01-01 Epub Date: 2025-11-29 DOI: 10.1016/j.jedc.2025.105220

Elnura Baiaman kyzy , Roberto Leon-Gonzalez

This paper proposes a novel Laplace-based solution to non-linear DSGE models that has a closed-form likelihood. We implicitly use a non-linear approximation to the policy function that is invertible with respect to the shocks, implying that in the approximation the shocks can be recovered uniquely from some of the control variables. Using perturbation methods and a Lagrange inversion formula, we are able to calculate the derivatives of the likelihood and construct the Laplace based solution. In contrast with previous likelihood-based approaches, the method used here requires neither the introduction of linear shocks nor simulation to evaluate the likelihood. Using US data, we estimate linear and nonlinear variants of a well-known neoclassical growth model with and without time-varying variances. We find that a nonlinear heteroscedastic model has a much better empirical performance. Furthermore, our models allow us to ascertain that the monetary policy shock causes most of the time changes in economic uncertainty.

本文提出了一种新颖的基于拉普拉斯的具有闭似然的非线性DSGE模型求解方法。我们隐式地使用对冲击可逆的策略函数的非线性近似，这意味着在近似中，冲击可以从一些控制变量中唯一地恢复。利用摄动方法和拉格朗日反演公式，我们能够计算出似然的导数，并构造出基于拉普拉斯的解。与以前基于似然的方法相比，这里使用的方法既不需要引入线性冲击，也不需要模拟来评估似然。利用美国的数据，我们估计了一个著名的新古典增长模型的线性和非线性变量，有时变方差和没有时变方差。我们发现非线性异方差模型具有更好的经验性能。此外，我们的模型使我们能够确定货币政策冲击在大多数情况下导致经济不确定性的变化。

引用次数: 0

Drivers of firm-level tail dependence: A machine learning approach 企业层面尾部依赖的驱动因素：一种机器学习方法

IF 2.3 3区经济学 Q2 ECONOMICS

Journal of Economic Dynamics & Control

Pub Date : 2026-01-01 Epub Date: 2025-11-15 DOI: 10.1016/j.jedc.2025.105207

Thomas Conlon , John Cotter , Ioannis Ropotos

The paper studies the determinants of firm-level tail dependence of companies with respect to foreign markets using machine learning. We measure dependence for a comprehensive international set of firms using copulas and we find that left tail dependence is consistently stronger than right tail dependence with their gap widening in recessionary periods. We then apply random forest regressions to identify and characterize the factors that account for the total panel variation of tail risk. The World Uncertainty Index, the R2 integration measure and coskewness with respect to foreign markets are the most important determinants. For US firms individual ownership variables such as the number of total or foreign investors dominate the remaining firm-level characteristics in explaining tail dependence. Our results contribute to the understanding of crash risk in the modern global financial landscape with implications for asset managers.

本文利用机器学习研究了企业对国外市场的尾部依赖的决定因素。我们使用copulas来衡量一组综合的国际企业的依赖，我们发现在经济衰退时期，随着它们的差距扩大，左尾依赖始终强于右尾依赖。然后，我们应用随机森林回归来识别和表征导致尾部风险总面板变化的因素。世界不确定性指数、R2整合测度和对国外市场的余偏性是最重要的决定因素。对于美国公司来说，个人所有权变量，如总投资者或外国投资者的数量，在解释尾部依赖时主导了公司层面的剩余特征。我们的研究结果有助于理解现代全球金融格局中的崩溃风险，并对资产管理公司产生影响。

引用次数: 0

Stochastic extended path 随机扩展路径

IF 2.3 3区经济学 Q2 ECONOMICS

Journal of Economic Dynamics & Control

Pub Date : 2026-01-01 Epub Date: 2025-12-02 DOI: 10.1016/j.jedc.2025.105227

Stéphane Adjemian , Michel Juillard

The Extended Path (EP) method solves DSGE models under certainty equivalence, capturing nonlinearities and occasionally binding constraints but ignoring the role of uncertainty. We propose the Stochastic Extended Path (SEP), which restores this channel by computing conditional expectations with quadrature and unscented transforms. To avoid the exponential explosion of a full tree of future shocks, we introduce a sparse tree representation that scales linearly with the horizon. We further develop a hybrid SEP, combining SEP with perturbation corrections to capture long-run effects of volatility at low cost. Accuracy is benchmarked in an asset pricing model with a closed-form solution, where hybrid SEP outperforms perturbation methods. We then illustrate the approach in an RBC model with a lower bound on investment.

扩展路径（EP）方法在确定性等价条件下求解DSGE模型，捕获非线性和偶尔约束，但忽略了不确定性的作用。我们提出了随机扩展路径（SEP），它通过计算条件期望与正交和无气味变换来恢复该通道。为了避免未来冲击的完整树的指数爆炸，我们引入了一个稀疏树表示，它与地平线线性缩放。我们进一步开发了一种混合SEP，将SEP与扰动校正相结合，以低成本捕获波动性的长期影响。准确度在资产定价模型中以封闭形式的解决方案为基准，其中混合SEP优于扰动方法。然后，我们在具有投资下界的RBC模型中说明了该方法。

引用次数: 0

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Journal of Economic Dynamics & Control

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