Search Results (64)

This paper constructs and estimates a novel two-sector Dynamic Stochastic General Equilibrium (DSGE) model to analyze the macroeconomics of Kazakhstan’s dual-energy structure, where a large fossil fuel sector coexists with an emerging renewable segment. The model’s key innovation is its integration of an endogenous, depletable oil stock and a dual-inflation Taylor-type rule, which together capture the specific transmission channels between hydrocarbon dependence and green investment. By differentiating between oil-driven and core inflation, the framework quantifies how oil price volatility transmits monetary conditions to the renewable sector. Bayesian estimation, using sectoral data from national accounts, reveals a pronounced asymmetry: oil stock/discovery dynamics and oil revenue fluctuations dominate macroeconomic volatility, while the renewable sector exhibits stable output but remains vulnerable to oil-driven monetary tightening transmitted mainly through indirect channels. The results indicate that Kazakhstan’s ongoing energy transition offers a stabilizing diversification benefit in principle but remains structurally constrained by macroeconomic dynamics and fiscal patterns anchored to hydrocarbon conditions. These findings provide a quantitative basis for designing transition policies that mitigate cross-sector spillovers and support effective diversification in resource-dependent economies. Full article

CBAM is reshaping the external conditions under which open economies pursue decarbonization, raising new questions about how domestic carbon pricing can remain effective while supporting sustainability. We develop an environmental DSGE model for a small open economy with a cleaner green sector and an emissions-intensive brown sector, an endogenous green innovation margin, and a banking sector that prices sector-specific transition risk through credit spreads. Carbon pricing affects the economy through relative prices and resource reallocation, while CBAM acts as an export-revenue wedge that weakens cash flows in exposed activities and tightens financing conditions. In the baseline, a coordinated increase in the domestic effective carbon price cuts emissions quickly and shifts investment toward the green sector, with aggregate activity recovering as reallocation proceeds. Under CBAM, the near-term contraction is deeper, and the spread spikes more, but endogenous green innovation and a policy mix that combines targeted green credit support with macroprudential measures deliver a smoother adjustment and the largest welfare gains. The results suggest that coherent policy packages linking carbon pricing, innovation support, and financial stability are central to managing the transition in an open economy. Full article

This paper investigates how external shocks propagate through fiscal transmission mechanisms in a commodity-dependent economy within a dynamic macroeconomic framework. The study contributes to the literature on macroeconomic fluctuations by examining the interaction between external revenue volatility, fiscal behavior, and institutional features in shaping short-run dynamics and medium-term outcomes. A Dynamic Stochastic General Equilibrium (DSGE) model is developed and calibrated to the Ecuadorian economy. The framework explicitly incorporates procyclical fiscal behavior, public capital accumulation, and endogenous spending efficiency, allowing for a structural analysis of fiscal transmission channels under external and productivity shocks. Counterfactual simulations are employed to assess the role of fiscal policy design and institutional constraints. The results show that while productivity shocks remain a key driver of output fluctuations, external revenue shocks significantly influence macroeconomic volatility through fiscal channels. Procyclical fiscal responses amplify fluctuations by reducing public investment and spending efficiency, slowing public capital accumulation and prolonging output contractions. Alternative fiscal configurations mitigate short-run volatility, although their effectiveness depends critically on institutional features governing spending efficiency. Overall, the analysis highlights that macroeconomic dynamics in resource-dependent economies are shaped not only by external shocks, but also by the interaction between fiscal policy design and institutional capacity. Integrating these elements into DSGE models provides a more comprehensive understanding of fiscal transmission mechanisms and macroeconomic volatility. Full article

Rising residential land prices push up housing prices and worsen credit misallocation. These patterns emerge amid cyclical real estate fluctuations and heavy land-based public finance. Such pressures undermine macroeconomic stability and sustainable land-use. The land price circuit breaker is widely applied with a price cap and state dependence, yet its trigger mechanism and interaction with inflation targeting remain underexplored. This study addresses three core questions. First, how does the circuit breaker’s discrete trigger and rule-switching logic differ from traditional static price ceilings? Second, can the mechanism, via the collateral channel, restrain excessive land price hikes, improve credit allocation, and, thereby, stabilize land price dynamics and long-run macroeconomic performance? Third, how does the circuit breaker interact with inflation targeting, and through which endogenous channels does a strict target dampen housing prices and raise activation probability? This study develops a multi-sector DSGE model with an embedded land price circuit breaker. The price cap is modeled as an occasionally binding constraint. A dynamic price band and trigger indicator capture the policy’s switch between slack and binding states. The framework incorporates interactions among local governments, the central bank, developers, and households. It also links firms and the secondary housing market. Under different inflation-targeting rules, this study uses impulse responses, an event study, and welfare analysis to assess trigger conditions and macroeconomic effects. The findings are threefold. First, a strict inflation target increases the probability of a circuit breaker being triggered. It channels housing-demand shocks toward land prices and creates a “nominal anchor–relative price constraint” linkage. Second, once activated, the circuit breaker narrows the gap between land price and house-price growth. It weakens the procyclicality of collateral values. It also restrains credit expansion by impatient households. These effects redirect credit toward firms, improve corporate financing, reduce the decline in investment, and accelerate output recovery. Third, the circuit breaker limits new land supply and shifts demand toward the secondary housing market. This generates a supply-side effect that releases existing stock and stabilizes prices, thereby weakening the amplification mechanism of housing cycles. This study identifies the endogenous trigger logic and cross-market transmission of the land price circuit breaker under a strict inflation target. It shows that the mechanism is not merely a price-management tool in the land market but a systemic policy variable that links the real estate, finance, and fiscal sectors. By dampening real estate procyclicality, improving credit allocation, and stabilizing macroeconomic fluctuations, the mechanism offers new insights for sustainable land-use policy and macroeconomic stabilization. Full article

This paper proposes a novel framework that integrates Deep Learning Neural Networks into the Stochastic Parameterized Expectations Algorithm (DLNN-PEA) to solve nonlinear rational expectations models. This method enhances traditional PEA-based solvers by employing a deep neural expectations operator that captures complex nonlinearities and asymmetries. The DLNN-PEA is implemented in Matlab R2024b. It combines deep learning approximation with the standard expectation-iteration structure of the PEA, replacing the conventional shallow ANN-based operator with a deeper architecture that improves both accuracy and stability. The methodology is applied to the stochastic Neoclassical Growth Model, where the DLNN-PEA is trained to approximate conditional expectations and decision rules under uncertainty. The results show rapid convergence, reduced boundary-related issues, and stable performance even in high-volatility environments. Compared with ANN-PEA, deep architectures exhibit greater robustness and adaptability, making them suitable for economic models characterized by stronger nonlinearities and richer state dynamics. Beyond the benchmark model, the proposed framework is well-suited for medium-scale DSGE models, nonlinear monetary policy environments, and macro-financial simulations involving high-dimensional state spaces. These features make DLNN-PEA a practical tool for applied macroeconomic analysis and model-based policy evaluation. Full article

Shimer documents that the search-and-matching model driven by productivity shocks explains only a small share of the observed volatility of unemployment and vacancies, which is known as the Shimer puzzle. We revisit this evidence by replacing the representative firm’s optimization with a deep reinforcement learning (DRL) agent that learns its vacancy-posting policy through interaction in a Diamond–Mortensen–Pissarides (DMP) model. Comparing the learning economy with a conventional log-linearized DSGE solution under the same parameters, we find that while both frameworks preserve a downward-sloping Beveridge curve, learning-based economy produces much higher volatility in key labor market variables and returns to a steady state more slowly after shocks. These results point to bounded rationality and endogenous learning as mechanisms for labor market fluctuations and suggest that reinforcement learning can serve as a useful complement to standard macroeconomic analysis. Full article

The growing importance of local governments, alongside the swift development of their bond markets, provides a novel framework for examining the coordination of monetary and local government fiscal policies in China. This investigation contributes a new viewpoint on local fiscal sustainability by emphasizing the role of policy coordination. Empirical evidence derived from regression models and proxy structural vector autoregression (Proxy SVAR) analyses conducted in this study substantiates the presence of coordination between monetary and local government fiscal policies in China; nevertheless, such coordination may pose risks to long-term local fiscal sustainability. Drawing on empirical data, this study utilizes a dynamic stochastic general equilibrium (DSGE) model that integrates key features characteristic of the Chinese economy to investigate the coordination of monetary and local government fiscal policies, as well as the effects of this coordination on local fiscal sustainability. The results derived from the baseline model indicate that although monetary and local fiscal policies in China are coordinated, such coordination facilitates the accumulation of local government debt, which ultimately compromises long-term local fiscal sustainability. Furthermore, the baseline model is extended and examined through multiple analytical approaches. When local government competition is introduced, monetary policy and local government fiscal policy become disconnected, which undermines local fiscal sustainability. Conversely, when local government cooperation is introduced, monetary policy and local government fiscal policy become more coordinated, which in turn improves local fiscal sustainability. Moreover, a higher steady-state debt level among local governments promotes greater coordination between monetary and fiscal policies, resulting in stronger fiscal sustainability. However, the imposition of debt constraints on local governments diminishes this coordination and adversely affects local fiscal sustainability. Additionally, in the absence of local financial friction, monetary and local fiscal policies exhibit increased coordination; however, this may potentially undermine long-term local fiscal sustainability. It is therefore imperative for the central government of China to prioritize the harmonization of monetary and local fiscal policies and to consider their implications for local fiscal sustainability, while simultaneously encouraging intergovernmental cooperation and the establishment of an integrated large-scale market. Full article

This paper highlights the importance of accounting for both the maturity structure of government debt and the composition of fiscal instruments when studying the macroeconomic effects of fiscal policy. Using a dynamic stochastic general equilibrium (DSGE) model featuring a debt maturity structure and six exogenous fiscal shocks spanning both the expenditure and revenue sides, we show that long-maturity debt systematically weakens the expansionary effects of fiscal policy under dovish monetary policy, particularly in response to increases in government purchases, government investment, and capital income tax cuts, where long-term financing leads to the significant crowding-out of private activity. In contrast, short-term debt financing yields output multipliers that often exceed unity. The maturity structure also alters the relative efficacy of fiscal instruments: while labor income tax cuts produce the largest multipliers under short-term debt, government purchases become more potent under long-term debt financing. We also show that the stark difference between short- and long-term debt becomes muted under a hawkish monetary regime. Our results have important policy implications, suggesting that the maturity composition of public debt should be carefully considered in the design of fiscal policy, particularly in high-debt economies. Full article

This paper extends the micro-founded DSGE open economy model by incorporating unionized labor markets. Unlike the standard framework with atomistic unions, large labor unions consider broader economic conditions and internalize the impact of their wage settlements on the aggregate economy. By emphasizing the interplay between internal and external sources of economic distortions and monetary policy regimes, we demonstrate that the economy’s openness, the degree of wage-setting centralization, and different monetary policy regimes influence unions’ wage-setting behavior and macroeconomic outcomes. The analysis identifies three key effects—the monetary policy effect, the intertemporal substitution effect, and the open economy effect—that large unions internalize when adjusting their wage demands in response to policy actions and external conditions. This novel wage-based mechanism alters the New Keynesian Phillips curve, with implications for the conduct of monetary policy, particularly in shaping the economy’s response to shocks and equilibrium determinacy. The real effects of monetary policy shocks under different policy settings depend on large unions’ internalization effect. In a unionized labor market, the impact of monetary shocks on the real economy is amplified compared to the standard case with atomistic unions. Additionally, interactions among large unions, openness, and monetary policy regimes affect determinacy properties of equilibrium (i.e., uniqueness of the solution path) under various forms and timing of monetary policy rules. This paper offers new insights into how union coordination interacts with monetary policy regimes and trade openness to shape macroeconomic stability (uniqueness of rational expectations equilibrium) and the dynamic response of the economy to shocks. These findings enhance our understanding of monetary policy design in economies with strong large labor institutions and external trade exposure—an area that remains underexplored in the existing DSGE literature. Full article

This article examines the theoretical foundations of economic forecasting based on DSGE models. DSGE models are the main direction of contemporary macroeconomics theory—the inclusion of the stochastic processes and expectations of economic agents in the analysis of economic processes made them one of the best economic forecasting tools. The methodological basis of this paper is two approaches of economic forecasting theory: technical analysis and fundamental analysis. In this article, we have performed the calibration of the DSGE model with investment adjustment costs for the Latvian economy and compared these results with the statistical data filtered with the SSA method. Key results have shown the ability of both approaches to capture the dynamics of the main Latvian macroeconomic indicators. Full article

In this study, we aimed to assess the effectiveness of monetary policy in influencing housing prices in Morocco. Bayesian estimation over the period 2007Q2–2017Q2 of a dynamic stochastic general equilibrium model allowed us to reveal a significant impact of the increase in policy interest rates on the prices of residential goods. Indeed, the implementation of a restrictive monetary policy in Morocco will drive the prices of this type of asset downward. Despite this empirical finding, the historical decomposition of shocks impacting the inflation of residential property prices shows that interest rates explain only a small portion of the variations in housing prices in this country. Our results also indicate that an increase in the share of borrowers extends the time required for economic and financial variables to return to their equilibrium state. This is a sign of the potential dangers of fueling housing bubbles through credit booms. Full article

This paper contributes to the literature by demonstrating that behavioral macroeconomic models better explain macroeconomic volatility in emerging economies compared to traditional rational expectations frameworks. We explore behavioral macroeconomics as a foundation for sustainable economic policies by comparing New Keynesian models under rational expectations and behavioral heuristics across multiple economies. The model parameters are estimated using the Generalized Method of Moments (GMM) for rational expectations and the Simulated Method of Moments (SMM) for the behavioral framework, evaluating their ability to replicate empirical second moments of output, inflation, and interest rates. The GMM, suited for linear models, provides analytical solutions, ensuring computational efficiency, while the SMM, designed for non-linear models, enables greater flexibility by generating simulated data and departing from restrictive DSGE assumptions. Our findings reveal that the behavioral model—incorporating heterogeneity, heuristic switching, and bounded rationality—better captures the persistent and volatile macroeconomic conditions observed in Central and Eastern European (CEE) economies. In contrast, rational expectations models perform better in advanced economies, where agents rely more on forward-looking information. These results emphasize the need to integrate behavioral features into macroeconomic modeling to enhance empirical accuracy and inform sustainable monetary policy tailored to diverse economic environments. Full article

This paper investigates how different parametrisations of the monetary policy reaction function and different mechanisms of expectation formation shape the macroeconomic outcomes in the estimated Smets–Wouters type of DSGE model. The initial macroeconomic conditions of the simulations correspond to the high inflation environment of early 2022. The simulation results show that, under the hybrid expectations, the terminal monetary policy rate is significantly higher than under the rational expectations for all Taylor rule parametrisations. Under hybrid expectations, the inflation rate is much more persistent than under the rational expectations; three years is not enough to reach the inflation target of two percent, even for the quite hawkish calibration of the Taylor rule. In the modelled economy, relatively fast inflation stabilisation for the hawkish Taylor rule has its own price in form of the cumulative output loss when compared with the dovish Taylor rule. Simulations are also performed for the case where the central bank misspecifies the expectation formation mechanism in the DSGE model and follows an interest rate path implied by a false model. The results show that the hawkish reaction is preferable for both correctly and incorrectly specified models. Full article

This study investigates the dual dynamics of investment shocks and policy responses in stabilizing South Korea’s macroeconomy during the COVID-19 pandemic, utilizing a Bayesian DSGE framework. The model integrates sophisticated mathematical components, including stochastic differential equations, Bayesian inference, and impulse response functions, to analyze the transmission mechanisms of investment shocks and the relative efficacy of fiscal and monetary interventions. The estimation is conducted through Markov Chain Monte Carlo simulations. Using data from the first quarter of 2020 to the first quarter of 2023, the analysis quantifies the pandemic-induced shocks’ impact on critical macroeconomic indicators, including enterprise output, household consumption, employment, and investment. The findings reveal that heightened investment costs significantly constrained economic performance, with fiscal measures, such as increased government spending and targeted stimulus packages, demonstrating superior stabilization effects compared to monetary interventions. These results emphasize the importance of well-coordinated policy responses in mitigating economic disruptions and enhancing resilience during crises. This study not only provides novel insights into the mathematical modeling of economic stabilization strategies but also offers actionable recommendations for policymakers navigating pandemic-induced challenges. Full article

This study investigates the integration of non-economic policies into the framework for assessing macroeconomic coherence as applied by the Chinese government, with a particular focus on green policies. We examine the impact of non-economic factors on social disagreement and investor disagreement (expectations), and how these influences interact with macroeconomic regulation, employing both empirical evidence and dynamic stochastic general equilibrium (DSGE) theoretical models. In the basic analysis section, we merge statistical data on social divergence with policy implementation, utilizing multiple regression and deep neural network models. Our findings provide direct evidence that non-economic policies significantly regulate social sentiment. Additionally, theoretical analyses using contagion models, grounded in real textual data on social and investor divergence, demonstrate that expectations of social sentiment can ultimately affect economic variables. In the extended analysis, we enhance the classic DSGE model to delineate the pathways through which non-economic policies impact the macroeconomy. Drawing from our analyses, we propose specific optimization measures for non-economic policies. The results indicate that targeted policy optimization can effectively manage social disagreement, thereby shaping expectations and harmonizing non-economic with economic policy initiatives. This alignment enhances the coherence of macroeconomic policy interventions. The innovative contribution of this study lies in its provision of both theoretical and empirical evidence supporting the formulation of non-economic policies for the first time, alongside specific recommendations for improving the consistency of macroeconomic policies. Full article