Dynamic Stochastic General Equilibrium Model Research Articles

The monetary policy of the State Bank of Vietnam, households and income distribution: the evidence from DSGE model

PurposeThis paper aims to propose a dynamic stochastic general equilibrium (DSGE) model for the State Bank of Vietnam (SBV) to assess the response from the household sector to monetary policy shocks through the consumption function. Moreover, the transmission from monetary policy to household consumption and income distribution is experimented with through the vector autoregression (VAR) model.Design/methodology/approachIn this study, the authors used the maximum likelihood estimation to estimate the DSGE and VAR models with the sample from 1996Q1 to the end of 2021Q4 (104 observations).FindingsThe DSGE model’s results show that the response of the household sector is as expected in the theory: a monetary policy shock occurs that increases the policy interest rate by 0.29%, leading to a decrease in consumer spending of about 0.041%, the shock fades after one year. Estimates from the VAR model give similar results: a monetary policy shock narrows income inequality after about 2–3 quarters and this process tends to slow down in the long run.Research limitations/implicationsBased on the research results, the authors propose policy implications for the SBV to achieve the goal of price stability, and stabilizing the macro-economic environment in Vietnam.Originality/valueThe findings of the study have theoretical contributions and empirical scientific evidence showing the effectiveness of the implementation of the SBV’s monetary policy in the context of macro-instability, namely: flexibility, caution and coordination of different measures promptly.

Estimation of industry-level basic digital capital services in China: A variable depreciation rate estimation method based on DSGE

Accurately measuring the input of digital capital is of great significance for understanding the development pattern of China's digital economy, nurturing new quality productivity, and achieving high-quality development. However, existing representative studies often assume a constant depreciation rate for capital goods, which does not align with reality. In this paper, we address this limitation by introducing dynamic stochastic general equilibrium (DSGE) model that estimates the variable depreciation rate for each capital good. By setting the depreciation rate as a function of capital maintenance expenditures and utilization rates, we provide a more realistic approach. The empirical results obtained through Monte Carlo simulation demonstrate that the trend of depreciation rates for all types of capital goods aligns with China's economic development. Additionally, we find that investment-specific technology shock plays a significant role in affecting changes in the depreciation rates of capital goods. This shock leads to an increase in capital utilization rates and a decrease in capital maintenance expenditures, resulting in higher depreciation rates. Notably, the depreciation rate of basic digital capital is more sensitive to exogenous shock compared to non-digital capital. Furthermore, the paper estimates the basic digital capital service of 19 industries in China from 1981 to 2020. The results indicate a steady increase in the services provided by basic digital capital, with particularly rapid growth observed in industries such as information transmission, software and information technology services, and the financial sector. When comparing our estimation results with those of representative literature, we find that the national-level productive capital stock and the basic digital capital services estimated using our methodology closely align with existing literature. This validation confirms the effectiveness of our methodology and the reliability of the estimated industry-level basic digital capital services.

The impact of digital inclusive financial development on local government expenditure: Evidence from China.

This paper investigates the impact of digital inclusive financial development on local government expenditure incentives at the income level. It does so by constructing a multi-level government Dynamic Stochastic General Equilibrium (DSGE) model that incorporates the financial sector. By employing empirical methods that involve uncertainty shocks and counterfactual simulations, the research yields several key findings. Firstly, the development of digital inclusive finance contributes to breaking down the urban-rural dual financial structure, thus facilitating balanced economic development within regions. Secondly, it reduces the proportion of financially excluded areas, accelerates fiscal decentralization, leading to an increase in local government fiscal revenue, and, consequently, an expansion of local fiscal expenditures. Thirdly, at a certain stage of digital inclusive finance development, it tends to crowd out residents' investment and consumption. Therefore, the decentralization of fiscal power and the expansion of local government expenditure at this stage may paradoxically inhibit regional economic growth. The study's conclusions validate the significant impact of digital inclusive finance on local government incentives at the income level.

Desirable banking competition and stability

Every financial crisis raises questions about how the banking market structure affects the real economy. Although low bank concentration may reduce markups and foster riskier behavior, concentrated banking systems appear more resilient to financial shocks. We use a nonlinear dynamic stochastic general equilibrium model with financial frictions to compare the transmissions of shocks under different competition and concentration configurations. The results reveal that oligopolistic competition amplifies the effects of the shocks relative to monopolistic competition. The transmission mechanism works through the markups, which are amplified when banking concentration is increased. The desirable banking market structure is determined according to financial stability and social welfare objectives. Moreover, we find that depending on policymakers’ preferences, a banking concentration of five to eight banks balances social welfare and bank stability objectives in the United States.

Examining business cycles and optimal monetary policy in a regional DSGE model

I construct a dynamic stochastic general equilibrium (DSGE) model consisting of geographic regions and use state level data to estimate the effects that monetary policy and financial shocks have on the four census regions of the United States. The DSGE model I use is constructed around a centralized monetary authority and financial market with regional output, labor and investment markets. I find significant heterogeneity amongst the regional structural parameters of the model, creating different business cycle dynamics for the four regions. The estimated model aligns with other economic studies that suggest that monetary shocks have a greater impact in certain geographic regions in terms of employment, inflation, wages, and consumption. Simulating the estimated model, I find that monetary policy that considers the regional variation in output and inflation can significantly lower the volatility around national output and inflation. The paper’s results suggest that regional macroeconomic conditions should be considered in monetary policy decisions.

Time-Varying Parameter Four-Equation DSGE Model

Abstract We build the time-varying parameter feature into the (Sims, E., J. C. Wu, and J. Zhang. 2023. “The Four-Equation New Keynesian Model.” The Review of Economics and Statistics 105 (4): 931–47) four-equation Dynamic Stochastic General Equilibrium (DSGE) model in this paper. We find that both parameters and impulse responses of the variables in the four-equation DSGE model exhibit significant variation over time. Allowing model parameters to vary over time also improves the model’s forecasting performance.

The NY Fed DSGE Model: A Post-COVID Assessment

We document the real-time forecasting performance for output and inflation of the New York Fed dynamic stochastic general equilibrium (DSGE) model since 2011. We find the DSGE's accuracy to be comparable to that of private forecasters before COVID but somewhat worse thereafter.

Macroeconomic impact of environmental policy uncertainty and monetary policy implications

This paper evaluates the macroeconomic implications of uncertainty arising from delays or unpredictability regarding the timing and extent of environmental policy implementation. An environmental dynamic stochastic general equilibrium (E-DSGE) model shows that increasing uncertainty about environmental policies is associated with a subsequent decline in investment, as firms prefer to postpone investment decisions. The decline in physical investment within polluting sectors subsequently induces a fall in employment, consumption and output. Using a novel climate policy uncertainty index developed by Gavriilidis (2021), alongside Google Trend data index, the paper shows that uncertainty about climate regulations has both recessionary and inflationary effects, corroborating the theoretical findings. Further analysis suggests that appropriate monetary policy tools could moderate the welfare cost arising from the environmental policy uncertainty, emphasizing the need for Central Banks to adopt a more aggressive stance in stabilizing GDP and inflation in the face of environmental policy uncertainty shocks.

Green Fiscal and Tax Policies in China: An Environmental Dynamic Stochastic General Equilibrium Approach

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.

The coevolution effect of central bank digital currency and green bonds on the net-zero economy

Directed by the net-zero emission goal, the green bond has become an essential financial tool to promote the development of the green economy. However, the greenwashing risk makes it doubtful whether the green bond can play a positive role. Therefore, this study constructs a six-sector dynamic stochastic general equilibrium (DSGE) model to analyze whether the coevolution of central bank digital currency (CBDC) and green bonds can fully play a positive role in promoting the net-zero economy. The results indicate that: (i) Increased CBDC supply has a positive effect on the economy, and also promotes green bond financing and net-zero emissions. (ii) Compared with non-interest-bearing CBDC, the coevolution of interest-bearing CBDC and green bonds is more likely to promote the net-zero economy and enhance the effectiveness of monetary policy. (iii) When the economy is overheating or in recession, the central bank can regulate green bond financing by adjusting the CBDC interest rate to promote a net-zero economy. (iv) The coevolution of interest-bearing CBDC and green bonds will achieve a higher welfare level than non-interest-bearing CBDC. This study provides guidance for the coevolution of CBDC technology innovation and green bond financial innovation.

The Block-Correlated Pseudo Marginal Sampler for State Space Models

Pseudo Marginal Metropolis-Hastings (PMMH) is a general approach to Bayesian inference when the likelihood is intractable, but can be estimated unbiasedly. Our article develops an efficient PMMH method that scales up better to higher dimensional state vectors than previous approaches. The improvement is achieved by the following innovations. First, a novel block version of PMMH that works with multiple particle filters is proposed. Second, the trimmed mean of the unbiased likelihood estimates of the multiple particle filters is used. Third, the article develops an efficient auxiliary disturbance particle filter, which is necessary when the bootstrap disturbance filter is inefficient, but the state transition density cannot be expressed in closed form. Fourth, a novel sorting algorithm, which is as effective as previous approaches but significantly faster than them, is developed to preserve the correlation between the logs of the likelihood estimates at the current and proposed parameter values. The performance of the sampler is investigated empirically by applying it to nonlinear Dynamic Stochastic General Equilibrium models with relatively high state dimensions and with intractable state transition densities and to multivariate GARCH diffusion-driven volatility in the mean models. Although we only apply the method to state space models, the approach will be useful in a wide range of applications such as large panel data models and stochastic differential equation models with mixed effects.

Dividend Taxation and Financial Business Cycles

We examine the interactions between different dividend tax systems and financial shocks in a dynamic stochastic general equilibrium (DSGE) model with an occasionally-binding investment credit limit. We show that dividend taxes largely determine the collateral value of assets, thereby occasionally distorting investment decisions and altering the propagation of financial shocks. Permanently lower dividend taxes dampen financially-driven business cycles in a state-contingent fashion. They also help explain substantial macroeconomic asymmetries following equally-sized expansionary and contractionary financial shocks.

Fiscal Policy for Inclusive Growth. A Case Study of Myanmar

Following decades of isolation under military rule, Myanmar initiated historic political reforms since 2011, but faces challenges translating liberalization into broad-based advancement. A dynamic stochastic general equilibrium modelling approach estimated on Myanmar data is used, with simulations quantifying potential growth and distributional impacts of strategic government expenditure reallocations towards infrastructure upgrading, agricultural investments, expanded social transfers and progressive tax reforms. Results indicate sustained infrastructure and rural productivity spending have high output multipliers while well-targeted transfers reduce income inequality. However, institutional absorptive capacities condition realization of social returns. Complementary governance enhancements like project oversight and competitiveness in public investment allocation prove vital. Regional peer benchmarking provides comparative lessons. Altogether, evidence-based fiscal reorientation towards addressing pressing human capital, rural-urban and firm competitiveness constraints can accelerate inclusive growth in Myanmar if pursued prudently. Sustainable expansion requires strengthening public financial management (PFM) systems and results monitoring.

The problems of macroeconomics as institutional problems: complementing the ‘what went wrong’ story with a social epistemology perspective

Abstract After the financial crisis of 2008, many economists expressed dissatisfaction with the state of macroeconomics. They criticised deficiencies in the dominant dynamic stochastic general equilibrium modelling approach and conceptions of good macroeconomic research behind that dominance. This paper argues that there is a deeper problem in macroeconomics, which remains unaddressed. I connect existing literature critical of the institutions of macroeconomics and of economics in general to the institutional preconditions of effective criticism outlined by the philosopher Helen Longino. I find that as an epistemic community, macroeconomics does not function in a way that adequately supports critical evaluation of established beliefs, norms and practices. This failure may partly explain why many views on macroeconomic modelling, the tenability of which economists questioned after the crisis, were able to persist for so long. My analysis gives additional support to several recent proposals for institutional reforms in economics.

A DSGE Model with Government-owned Banks

Abstract How relevant are government-owned banks in the economy, especially during recessions? We study the role of government-owned banks in a dynamic stochastic general equilibrium (DSGE) model with heterogeneous financial intermediaries, heterogeneous households, and minimum capital requirement constraints. We show that the capitalization of government-owned banks during recessions smooths the effects of a negative shock and helps the economy recover more quickly. However, these stabilizing effects could be partially offset by banks’ inefficiency in transforming one unit of capital into loans. Therefore, ignoring the heterogeneity between private and government-owned banks may lead to misleading assessments and conclusions regarding the effects of economic policies on the macroeconomic and banking variables. This is particularly important for evaluating the effectiveness of macroprudential policies.

Identifiability and estimation of possibly non-invertible SVARMA Models: The normalised canonical WHF parametrisation

This article focuses on the parametrisation, identifiability, and (quasi-) maximum likelihood (QML) estimation of possibly non-invertible structural vector autoregressive moving average (SVARMA) models. SVAR models are routinely adopted due to their well-known implementation strategy. However, for various economic and statistical reasons, multivariate SVARMA settings are often more suitable. These settings introduce complexity in the analysis, primarily due to the presence of the moving average (MA) polynomial. We propose a novel representation of the MA polynomial matrix using the Wiener–Hopf factorization (WHF). A significant advantage of the WHF is its ability to handle possible non-invertibility and thus models with informational asymmetry between economic agents and outside observers. Since solutions of Dynamic Stochastic General Equilibrium (DSGE) models often involve this informational asymmetry, SVARMA models in WHF parametrisation can be considered data-driven alternatives to DSGE models and used for their evaluation. Furthermore, we provide low-level conditions for the asymptotic normality of the (Q)ML estimator and analytic expressions for the score and information matrix. As application, we estimate the Blanchard and Quah model, and compare our results and implied impulse response function with the ones in the SVAR model by Blanchard and Quah and a non-invertible SVARMA model by Gouriéroux and co-authors. Importantly, we have implemented this novel method in a well-documented R-package, making it readily accessible for researchers and practitioners.

The Response of Macroeconomic Variables to Government Spending Shocks in the Sudanese Economy 1989-2019: Comparing the Structural Shocks (DSGE Approach) and Impulse Response (SVAR Model)

The importance that different (approaches and models) to modeling the macroeconomy place on theoretical coherence compared to their capacity to match the data and the quality of the econometric model description varies. Dynamic stochastic general equilibrium (DSGE) models are more theoretical, whereas vector autoregression (SVAR) models provide a better match to the data. For developed economies, there are well-established publications on measuring the response of economic indicators to government spending shocks and aggregate macroeconomic activity. In addition, such empirical studies in emerging nations are scarce. This research seeks to fill this void by utilizing the DSGE model and the SVAR approach to investigate the influence of the response of macroeconomic variables to government spending shocks in the Sudanese economy from 1989 to 2019. The findings indicate that the influence of government expenditure shocks on the Sudanese economy is inconsistent with Keynesian principles, as some selected macroeconomic indicators do not respond positively to government expenditure shocks. The non-responsiveness of the inflation rate and exchange rate to government expenditure shocks is demonstrated; this finding may indicate the monetary authority’s weakness in managing monetary variables in the Sudanese economy. In most situations, fiscal and monetary policies were in sync, and “double expansionary” and “double contractionary” policy coordination may be the proper approach; and also create tools that fit the Sudanese economy’s structure.

Modeling the impact of COVID-19 on the tourism sector in Mauritius: A dynamic stochastic general equilibrium analysis

This paper develops a Dynamic Stochastic General Equilibrium model to gauge on the detrimental effects of COVID-19 on the tourism sector and consequently on the macroeconomy of Mauritius. Findings demonstrate COVID-19-induced tourism export shock triggering subdued exports, imports, investments and tax revenues while government debt, inflation rate, transfer income experienced bullish momentum. Overall, results from the model bode well with the real macroeconomic conditions which prevailed post the pandemic. Policywise, findings advocate the development of a new sector to diversify the exporting arm of the Mauritian economy. Our model can be used not only by local authorities but also by foreign economies which exhibit similar features to those of the Mauritian economy in view of shaping out optimal policies.

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.