Search Results (62)

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

We investigate the performance of estimators of the generalized empirical likelihood and minimum contrast families in the estimation of dynamic stochastic general equilibrium models, with particular attention to the robustness properties under misspecification. From a Monte Carlo experiment, we found that (i) the empirical likelihood estimator—as well as its version with smoothed moment conditions—and Bayesian inference obtained, in that order, the best performances, including misspecification cases; (ii) continuous updating empirical likelihood, minimum Hellinger distance, exponential tilting estimators, and their smoothed versions exhibit intermediate comparative performance; (iii) the performance of exponentially tilted empirical likelihood, exponential tilting Hellinger distance, and their smoothed versions was seriously compromised by atypical estimates; (iv) smoothed and non-smoothed estimators exhibit very similar performances; and (v) the generalized method of moments, especially in the over-identified case, and maximum likelihood estimators performed worse than their competitors. 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

This paper examines the relationship between a technology shock and employment, considering price, wage rigidities, and heterogeneous agents. To explore this relationship, we utilized a Dynamic Stochastic General Equilibrium (DSGE) model, incorporating households with varying savings rates. For empirical validation, we conducted a Structural Vector Autoregression (SVAR) analysis using data from two economies with distinct savings patterns—the United States and China. This approach allowed us to assess the impact of technology shocks on employment dynamics across different savings environments. Under these conditions, we observe that the effect of technology on aggregate employment is initially positive. Still, it gradually decreases in the mid-term, eventually switching to a negative impact before slowly recovering to equilibrium. The reason for this phenomenon depends on (i) the magnitude of fluctuations in price and wage, precisely, which variable’s fluctuations have a greater magnitude, and (ii) which effect, between income effect and substitute effect, is preferred by restricted and unrestricted households. Due to (i), real wages change, and because of (ii), households make different labor supply decisions, leading to fluctuations in employment in response to technology shocks. Full article

We develop a dynamic, stochastic general equilibrium (DSGE) model for the euro area that accounts for climate change-related risk considerations. The model features polluting (“brown”) firms and non-polluting (“green”) firms and a climate module with endogenous emissions modeled as a byproduct externality. In the model, exogenous shocks propagate throughout the economy and affect macroeconomic variables through the impact of interest rate spreads. We assess the business cycle and policy implications of transition risk stemming from changes in the carbon tax, and the implications of the micro- and macroprudential tools that account for climate considerations. Our results suggest that a higher carbon tax on brown firms dampens economic activity and volatility, shifting lending from the brown to the green sector and reducing emissions. However, it entails welfare costs. From a policy-making perspective, we find that when the financial regulator integrates climate objectives into its policy toolkit, it can minimize the trade-off between macroeconomic volatility and welfare by fully coordinating its micro- and macroprudential policy tools. Full article

Along with the new stage of prevention and control of the COVID-19 pandemic and the vision and goals of combatting climate change, the challenges of the transition to a green economy have become more severe. The need for green recovery of the economy, stability and security of energy production and consumption, and the coordination of low-carbon transformation and socio-economic development has become increasingly urgent. This paper proposes a new theoretical framework to study the effect of carbon emission reduction on the mutual application of the carbon market, fiscal policy and monetary policy under the non-homothetic preference of energy product consumption. By constructing an environmental dynamic stochastic general equilibrium (E-DSGE) model with residents’ non-homothetic preferences, this paper finds that coordinating the carbon market and macroeconomic policies can achieve economic and environmental goals. However, the transmission paths for each are different. The carbon market influences producers’ abatement efforts and costs through carbon prices. Monetary policy controls carbon emissions by adjusting interest rates, while fiscal policy controls carbon emissions by adjusting total social demand. Improving non-homothetic preferences will amplify business cycle fluctuations caused by exogenous shocks, thus assuming the role of a “financial accelerator”. Further research shows that non-homothetic preferences influence the heterogeneity of different policy mixes. Finally, this paper discovers that the welfare effects, the relative size and difference of long-term and short-term effects resulting from the different policy mixes, also depend on the level of non-homothetic preferences. The intertemporal substitution mechanism due to the improvement of non-homothetic preferences endows low-carbon production with “option” characteristics. Our study reveals the role of non-homothetic preferences on the effectiveness of policy implementation. It highlights the importance of matching monetary and fiscal policies with the carbon market based on the consumption and production side. It provides ideas for policy practice to achieve the goal of “dual carbon” and promoting coordinated socio-economic development. Full article

This research aims to explore the fiscal and public finance viability on climate physical risk externalities cost for building social-economic-environmental sustainability. It analyzes climate physical risk impact on the real business cycle to change the macroeconomic output functions, its regressive cyclic impact alters tax revenue income and public expenditure function; This research also analyzes that the climate physical risk escalates social-economic inequality and change fiscal-financial policy functions, illustrates how the climate damage cost and adaptation cost distorts fiscal-finance cyclical and structural equilibrium function. This research uses binary and multinomial logistic regression analysis, dynamic stochastic general equilibrium method (DSGE) and Bayesian estimation model. Based on the climate disaster compensation scenarios, damage cost and adaptation cost, analyzing the increased public expenditure and reduced revenue income, demonstrates how climate physical risk externalities generate binary regression to financial fiscal equilibrium, trigger structural and cyclical public budgetary deficit and fiscal cliff. This research explores counterfactual balancing measures to compensate the fiscal deficit from climate physical risk: effectively allocating resources and conducting the financial fiscal intervention, building greening fiscal financial system for creating climate fiscal space. Full article

Implementing green fiscal and tax policies for reducing emissions and pollution without negatively impacting economic growth remains a challenge. We aimed to determine whether environmental protection and economic growth can both be attained under a green fiscal and tax policy. Specifically, we created a dynamic stochastic general equilibrium (DSGE) model to explore the environmental, economic, and welfare impacts of green fiscal and tax policies. Additionally, a welfare analysis based on an environmental DSGE (E-DSGE) model was performed. We found that (1) raising the environmental or energy tax rate was beneficial for reducing emissions and environmental pollution. However, this approach inhibited economic growth, an outcome not conducive to improving welfare. (2) Increasing the subsidy rate for emission reduction not only incentivized businesses to reduce emissions but also improved economic growth and welfare. (3) The emission reduction mechanisms of environmental tax policies, energy tax policies, and subsidy policies are different. Among them, the environmental tax policy and the energy tax policy both reduce pollution by forcing businesses to increase their emission reduction efforts, but the former is a tax on pollution emissions, while the latter is a tax on energy consumption. However, emission reduction subsidy policies incentivize companies to increase their emission reduction efforts and reduce pollution emissions by alleviating their financial burden. (4) Increasing government spending on environmental remediation could promote economic growth. However, considering that this does not motivate companies to reduce emissions, increasing their share will lead to a reduction in emission reduction subsidies, ultimately negatively impacting social welfare. (5) An environmental tax would cause greater losses in welfare than an energy tax. These findings will enable policymakers to optimize expenditures and tax systems. Full article

In this study, we explored the impact of bank leverage and financial frictions on the transmission of real and financial shocks. Two new Keynesian dynamic stochastic general equilibrium (DSGE) models, with and without financial frictions, were employed in the context of the Tunisian economy. In the analysis, we considered three types of shocks—productivity, monetary, and adverse bank capital shocks. The findings reveal that, in the model with financial frictions, the response of macroeconomic and financial variables to demand and supply shocks was more pronounced than in the baseline model, where frictions primarily exist at the borrower level. In this study, we underscored the significance of financial shocks, particularly negative bank capital shocks, in triggering substantial macroeconomic and financial fluctuations, especially when banks operate with higher leverage ratios. Additionally, the inclusion of financial frictions in the DSGE model enhanced its ability to capture the empirical features of real and financial shocks, providing valuable insights for effective monetary policymaking. The results provide foundational insights for Tunisian policymakers to assess the impact of financial frictions in the context of the Tunisian economy. This is significant for the Central Bank of Tunisia, which has not yet adopted a specific DSGE model. Therefore, through our analysis, we determined the amplificatory role of financial frictions in the dynamics of macroeconomic and financial variables in Tunisia and examined the main transmission channels of shock propagation. Full article