DSGE Research Articles

Effect of Financial Frictions on Monetary Policy Conduct: A Comparative Analysis of DSGE Models with and without Financial Frictions

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.

Inefficient shocks and optimal monetary policy

Real disturbances that lead to trade-offs between inflation and output gap stabilization have not been studied much in the context of monetary policy settings in emerging markets and developing economies (EMDEs). We identify market price support present in the agriculture sectors of the EMDEs as inefficient shocks that lead to such trade-offs. Using a three-sector new Keynesian dynamic stochastic general equilibrium model, we show trade-offs between core-inflation and output gap stabilization under discretionary and commitment policies. This result departs from the popular viewpoint, stating that the strict core-inflation targeting is an optimal monetary policy for EMDEs susceptible to relative price changes.

Currency Flowback and Opening Up Bond Markets

The internationalization of the Renminbi (RMB) has become a practical reality in global financial markets and economic dynamics. Understanding the mechanism of currency flowback, the movement of the RMB back to China’s domestic financial system after being utilized abroad, is crucial in comprehending the evolving landscape of global finance and China’s position within it. This article investigates the relationship between currency flowback and RMB internationalization through theoretical frameworks, empirical evidence, and model simulations. The opening of bond markets plays a pivotal role in facilitating currency flowback and promoting RMB internationalization by attracting foreign investors and increasing the liquidity of domestic bond markets. A Dynamic Stochastic General Equilibrium (DSGE) model incorporating bond market opening-up illustrates the potential for improved financial stability and economic resilience. However, the conclusions drawn from simulations are contingent on maintaining a moderate foreign holding ratio of domestic bonds to mitigate risks associated with excessive foreign ownership.

A General and Efficient Method for Solving Regime-Switching DSGE Models

A General and Efficient Method for Solving Regime-Switching DSGE Models

Impact of fiscal policies on the labor market with search friction: An estimated DSGE model for Japan

This study investigates the effects of heterogenous fiscal policies on Japan's labor market amidst increasing national debt and economic downturns. We develop a Dynamic Stochastic General Equilibrium model incorporating labor market search friction, staggered wage negotiation, price stickiness and productive government employment. This model is used to compare the impacts of multiple fiscal policies—including government employment spendings, direct government expenditures, and tax cuts—on employment. The model, estimated with macroeconomic data of Japan spanning 1985 to 2019, offers a detailed look at how fiscal policies influence employment dynamics.Our analysis shows that increasing employment within the government sector significantly lowers unemployment rates, with a long-term unemployment reduction effect (multiplier) of −0.4. Collectively, all fiscal policies contribute to 23.96 % of the employment rate fluctuations, with government employment policies playing a dominant role, accounting for 8.55 % of these variations. This underscores the significant stabilizing effect of government employment policies in the labor market and their capacity to boost private sector employment through enhanced household income and increased private sector productivity. This research not only sheds light on the critical role of public sector interventions during economic downturns but also enhances our understanding of the effectiveness of Japan's fiscal policies.

Green transition and financial stability: The role of green monetary and macroprudential policies and vouchers

This paper analyzes a mix of alternative policies in supporting the green transition and the phase-out of fossil fuels, without compromising financial stability. An environmental dynamic stochastic general equilibrium (E-DSGE) model with two sectors (green and brown) and endogenous default is developed to assess potential climate-induced financial stability threats that can be mainly generated through physical and transition risks mechanism. Those risks are evaluated through a compound capital depreciation shock and a carbon tax shock. The paper offers several findings. First of all, a too stringent carbon tax would increase the medium-term default rate in both sectors, harming financial stability due to potentially detrimental effects on banks’ balance sheet. Second, there exists a trade-off in implementing green monetary or macroprudential policies: if a policy can encourage the green transition, financial stability is compromised due to a rise in default rates. In contrast, if a policy aims to reduce vulnerabilities and financial stability risks, then the phase-out of the polluting sector to foster the green sector would be hard to achieve. The model finds that under certain physical and transition risks, a dual interest rate policy, coupled with a fiscal policy in which carbon tax revenues are redistributed to households as vouchers to encourage the consumption of green goods, is able to support the green transition and safeguard financial stability. Therefore, top-down and bottom-up approaches are the keys for sustainability in the whole economy and financial system.

Real-time forecast of DSGE models with time-varying volatility in GARCH form

Recent research shows that time-varying volatility plays a crucial role in non-linear modeling. Contributing to this literature, we suggest an approach that allows for straightforward computation of DSGE models with time-varying volatility, where the volatility component is formulated as a GARCH process. As an application of our approach, we examine the forecasting performance of this DSGE-GARCH model using euro area real-time data. Our findings suggest that the DSGE-GARCH approach is superior in out-of-sample forecasting performance in comparison to various other benchmarks for the forecast of inflation rates, output growth and interest rates, especially in the short term. Comparing our approach to the widely used stochastic volatility specification using in-sample forecasts, we also show that the DSGE-GARCH is superior in in-sample forecast quality and computational efficiency. In addition to these results, our approach reveals interesting properties and dynamics of time-varying correlations (conditional correlations).

A DSGE model approach to examining the impact of the Russian–Ukrainian War and oil shocks on the Moroccan economy

AbstractThis study explores the impact of oil shocks on the Moroccan economy using a dynamic stochastic general equilibrium (DSGE) model. The DSGE simulations reveal that these shocks, exacerbated by the war in Ukraine, led to a contraction in the output gap, consumption, investment, and savings, as well as increased inflation. These results highlight the vulnerability of the Moroccan economy to external shocks, particularly those linked to energy prices. They underline the need for Morocco to diversify its energy sources and reduce its dependence on oil imports. Furthermore, our results suggest that economic policies should focus on mitigating the effects of these shocks. Future research could seek to refine this model by incorporating other factors likely to influence the Moroccan economy, such as changes in global demand or specific government policies.

Macroprudential policies and Brexit: A welfare analysis

AbstractBrexit will have implications on financial stability and the implementation of macroprudential policies. The United Kingdom (UK) will no longer be subject to the jurisdiction of the European Systemic Risk Board. This paper studies the welfare implications of this change of regime. By means of a dynamic stochastic general equilibrium model, I compare the pre‐Brexit scenario with the new one, in which the UK sets macroprudential policy independently. I find that, after Brexit, the UK is better off by setting its own macroprudential policy without taking into account Europe's welfare as a whole.

Analysis of economic and mathematical models of monetary stimulation for the development of smart industry

Abstract The article considers economic and mathematical models in the context of monetary stimulation of financial and economic development of the smart industry. The article analyses AD-AS, DSGE, VAR, CAPM, RBC, Phillips Curve and Cobb-Douglas models. The advantages and disadvantages of the models in the context of monetary stimulation of smart industry development are identified. The analysis has revealed that all the considered models have certain disadvantages, such as complexity of use and lack of clarity in interpreting the results, as well as limited consideration of factors that are important in monetary stimulation of the smart industry. The reviewed VAR model is limited in taking into account all factors affecting economic variables and is sensitive to specification, which leads to significant changes in the final results depending on the included variables and their specification. The CAPM model is based on assumptions about market efficiency that do not always correspond to reality, while the RBC model is characterised by the absence of instability and unrealistic assumptions about market behaviour. The Phillips Curve model shows instability when inflation and unemployment respond to economic shocks in different ways, which is unacceptable in the context of monetary stimulation for the development of the smart industry. The analysis identified the advantages and disadvantages of all models, which allowed us to objectively assess the actual conditions of the models. The analysis has shown that, given the above shortcomings and the specifics of the current economic environment, the Cobb-Douglas model is the most effective for analysing and forecasting the development of the smart industry in Ukraine. The other models considered may also be useful for stimulating the development of the smart industry, but they do not provide the same flexibility and ease of use as the Cobb-Douglas model. Thus, given the specifics of monetary policy, the Cobb-Douglas model seems to be the most appropriate tool for analysing and forecasting monetary stimulus for the development of the smart industry in Ukraine. It allows for a wide range of production factors and is simple to analyse and interpret the final results, making it the most suitable for addressing complex issues of monetary stimulation in the context of smart industry development. Keywords monetary stimulation, smart industry, development, modeling

The impact of COVID‐19 pandemic on the Thai economy and the effectiveness of monetary policy: A Bayesian DSGE model approach

AbstractThis study estimates a medium‐scale dynamic stochastic general equilibrium model for the Thai economy to evaluate the impact of the COVID‐19 pandemic containment policy on key macroeconomic aggregates. The shock to labor supply is considered as the main transmission channel. The paper discussed the role of monetary policy in regard to economic recovery and also identified the dominant shocks driving the business cycle. Thai quarterly series from 2011Q1 to 2021Q2 is used for the Bayesian estimation of the model. Though the pandemic shock caused a sharp decline in output, consumption and investment, the results suggest a fast recovery in the growth rates of the variables in about 2.5 years. At the same time, the dominant shocks that account for output variation in the medium to long term are investment, labor supply and productivity shocks. Monetary policy is effective in shortening the recovery due to its impact on private investment. The key drivers of Thai household consumption in the long run are investment, labor supply and productivity shocks. On average, the investment shock appears to be the key driver of the business cycle at all horizons.

Analysis of The Impact of The Country's Tax Policies During The Outbreak of The Covid-19 On The Country's Employment Level: A Dynamic Stochastic General Equilibrium Approach

Analysis of The Impact of The Country's Tax Policies During The Outbreak of The Covid-19 On The Country's Employment Level: A Dynamic Stochastic General Equilibrium Approach

Empirical evidence on the Euler equation for investment in the US

SummaryIs the typical specification of the Euler equation for investment employed in dynamic stochastic general equilibrium (DSGE) models consistent with aggregate macro data? The answer is yes using state‐of‐the‐art econometric methods that are robust to weak instruments and exploit information in possible structural changes. Unfortunately, however, there is very little information about the values of the parameters in aggregate data because investment is unresponsive to changes in capital utilization and the real interest rate. Bayesian estimation using fully specified DSGE models is more accurate due to both informative priors and cross‐equation restrictions.

Would the Euro Area Benefit from Greater Labor Mobility?

We assess how within euro area labor mobility impacts economic dynamics in response to shocks. In the analysis we use an estimated two-region monetary union dynamic stochastic general equilibrium model that allows for a varying degree of labor mobility across regions. We find that, in contrast with traditional optimal currency area predictions, enhanced labor mobility can either mitigate or exacerbate the extent to which the two regions respond differently to shocks. The effects depend crucially on the nature of shocks and variable of interest. In some circumstances, even when it contributes to aligning the responses of the two regions, labor mobility may complicate monetary policy tradeoffs. Moreover, the presence and strength of financial frictions have important implications for the effects of labor mobility. If the periphery’s risk premium is more responsive to its indebtedness than our estimates, there are various shocks for which labor mobility may help stabilize the economy. Finally, the euro area’s economic performance following the Global Financial Crisis would not have been necessarily smoother with enhanced labor mobility.

Inter-industry trade and business cycle dynamics

Abstract Motivated by the increased importance of trade between industrialized and less-developed countries, we build a two-sector dynamic stochastic general equilibrium model featuring inter-industry trade as well as intra-industry trade to analyze the business cycle dynamics of industrialized countries. We find that import-competing sectors are more sensitive to domestic productivity shocks than exporting sectors, due to their stronger reliance on domestic demand. This generates pressure to adjust relative prices and to reallocate factors of production. It also propagates the international spillover effects of productivity shocks leading to stronger business cycle comovement across countries, relative to a traditional business cycle model that does not feature inter-industry trade.

Merging Structural and Reduced-Form Models for Forecasting

Abstract Recent economic crises have posed important challenges for forecasting. Models estimated pre-crisis may perform badly when normal economic relationships have been disrupted. Meanwhile, forecasting, especially in central banks, is increasingly based on a suite of models, following two main approaches: structural (DSGE) and reduced form. The challenge remains to identify which model – or combination of models – is likely to make better forecasts in a changing environment. We explore this issue by assessing the forecasting performance of combinations of a medium-scale DSGE model with standard reduced-form methods applied to the Spanish economy and a reference period that includes both the great recession and the sovereign debt crisis. Our findings suggest that: (i) the mean reverting properties of the DSGE model cause it to underestimate the growth of real variables following the inclusion of crisis episodes in the estimation period; (ii) despite this, reduced-form VARs benefit from the imposition of an economic prior from the structural model; but (iii) pooling information in the form of variables extracted from the structural model with (B)VAR methods does not improve forecast accuracy. By analysing the quantiles of the predictive distributions, we also provide evidence that merging models can help improve the forecast in a context including crisis episodes.

The financialization of local government debt in China and its risk transmission to commercial banks

China's local government debt has risen sharply due to fiscal stimulus and decentralized financing. This debt expansion increases systemic risk as default risk is transmitted to banks, the primary holders of local debt. Using a Dynamic Stochastic General Equilibrium model incorporating local governments and banks, we show that local debt expansion increases banks' nonperforming loans and crowds out private credit, increasing bank risk-taking. We empirically examine 2010–2019 data on 350 Chinese banks and find that the level of local debt positively impacts bank risk-taking, especially low-capital, nonstate, and unlisted banks. The mechanisms operate through an increase in nonperforming loans due to default risk and a reduced regional repayment capacity due to crowded-out private credit. Our study reveals the impact of local debt on bank risk and financial stability in China. Policy implications include strengthening bank regulation and pursuing diversified government financing.

From parameters to policies: sensitivity analysis and fiscal and monetary reactions

PurposeThis paper seeks to explore the sensitivity of these parameters and their impact on fiscal policy outcomes. We use the existing literature to establish possible ranges for each parameter, and we examine how changes within these ranges can alter the outcomes of fiscal policy. In this way, we aim to highlight the importance of these parameters in the formulation and evaluation of fiscal policy.Design/methodology/approachThe role of fiscal policy, its effects and multipliers continues to be a subject of intense debate in macroeconomics. Despite adopting a New Keynesian approach within a macroeconomic model, the reactions of macroeconomic variables to fiscal shocks can vary across different contexts and theoretical frameworks. This paper aims to investigate these diverse reactions by conducting a sensitivity analysis of parameters. Specifically, the study examines how key variables respond to fiscal shocks under different parameter settings. By analyzing the behavioral dynamics of these variables, this research contributes to the ongoing discussion on fiscal policy. The findings offer valuable insights to enrich the understanding of the complex relationship between fiscal shocks and macroeconomic outcomes, thus facilitating informed policy debates.FindingsThis paper aims to investigate key elements of New Keynesian Dynamic Stochastic General Equilibrium (DSGE) models. The focus is on the calibration of parameters and their impact on macroeconomic variables, such as output and inflation. The study also examines how different parameter settings affect the response of monetary policy to fiscal measures. In conclusion, this study has relied on theoretical exploration and a comprehensive review of existing literature. The parameters and their relationships have been analyzed within a robust theoretical framework, offering valuable insights for further research on how these factors influence model forecasts and inform policy recommendations derived from New Keynesian DSGE models. Moving forward, it is recommended that future work includes empirical analyses to test the reliability and effectiveness of parameter calibrations in real-world conditions. This will contribute to enhancing the accuracy and relevance of DSGE models for economic policy decision-making.Originality/valueThis study is motivated by the aim to provide a deeper understanding of the roles macroeconomic model parameters play concerning responses to expansionary fiscal policies and the subsequent reactions of monetary authorities. Comprehensive reviews that encompass this breadth of relationships within a single text are rare in the literature, making this work a valuable contribution to stimulating discussions on macroeconomic policies.

A DSGE model of energy efficiency with vintage capital in Chinese industry

As the conventional method for estimating the impact of energy prices on energy consumption, the reduced form approach creates a “black box” interpretation of the energy price-intensity relationship without identifying the channels, or their magnitudes, through which prices matter. This shortcoming is particularly serious for China that has multiple ownership types operating under different government policy regimes. To remedy this shortcoming, this paper formulates a dynamic stochastic general equilibrium (DSGE) model that incorporates a range of technology avenues – both embodied and disembodied – for achieving energy-savings in response to rising energy prices. Employing Chinese firm-level data, the paper recovers key parameters in the DSGE model by indirect inference; so the model can replicate the stylized facts based on the firm-level data. A key finding is that embodied putty-clay investment is a critical channel for achieving energy efficiency, on which SOEs most depend, non-state-owned enterprises depend less, and foreign-funded enterprises least depend.

Solving linear DSGE models with Newton methods

This paper presents and compares Newton-based methods from the applied mathematics literature for solving the matrix quadratic that underlies the recursive solution of linear DSGE models. The methods are compared using nearly 100 different models from the Macroeconomic Model Data Base (MMB) and different parameterizations of the monetary policy rule in the medium-scale New Keynesian model of Smets and Wouters (2007) iteratively. We find that Newton-based methods compare favorably in solving DSGE models, providing higher accuracy as measured by the forward error of the solution at a comparable computation burden. The methods, however, suffer from their inability to guarantee convergence to a particular, e.g. unique stable, solution, but their iterative procedures lend themselves to refining solutions either from different methods or parameterizations.