Equilibrium Model Research Articles

Fiscal policy in the face of the health crisis: A simulation using a hybrid DSGE‐SIR model

AbstractThis study employs a dynamic stochastic general equilibrium (DSGE) model, integrated with a Susceptible‐Infected‐Recovered (SIR) epidemiological framework, to assess the macroeconomic impacts of fiscal policy during the COVID‐19 pandemic in Morocco. Calibrated with Moroccan COVID‐19 data, the model links epidemiological dynamics to macroeconomic variables, offering a detailed analysis of fiscal interventions. The primary objective is to evaluate the effectiveness of various fiscal measures, including government spending shocks, consumption tax cuts, and labor tax reductions, in stimulating economic activity and supporting households and businesses impacted by the pandemic. The results indicate that government spending shocks significantly stimulated economic activity and employment, but also led to increased public debt and inflationary pressures, thereby illustrating the inherent trade‐offs. Consumption tax cuts, intended to boost demand, had mixed effects on inflation; while prices for some goods declined, higher demand caused price increases in others. Labor tax reductions, aimed at enhancing employment, generated varied effects on labor supply and contributed to rising public debt due to lower tax revenues. The study underscores the necessity of balanced fiscal strategies to achieve both immediate economic recovery and long‐term fiscal sustainability, highlighting the critical role of well‐calibrated fiscal policies in mitigating the economic consequences of pandemics.

Transmission of flood damage to the real economy and financial intermediation: Simulation analysis using a DSGE model

We assess physical risk associated with floods in Japan, using a dynamic stochastic general equilibrium (DSGE) model. We construct a model that incorporates transmission mechanism of floods and estimate the model using the data of flood-induced damage to capital stock and public infrastructure collected by the government in the last 40 years. The result of the analysis is threefold. First, a flood that reduces the private capital stock by about 0.1% as a direct effect causes GDP to fall by about 0.1% in the first period, with a gradual recovery to pre-flood level. Second, floods dampen GDP through multiple channels. From the supply side, a decline in capital stock inputs and total factor productivity (TFP) reduce GDP. From the demand side, the balance sheets of firms and financial intermediaries are impaired, resulting in disruptions to financial intermediation and depressing GDP. Based on our estimates, all these channels are quantitatively comparable in magnitude. Third, the quantitative impacts of flood shocks on GDP up to now have been minor compared to the standard structural shocks that are considered important in existing macroeconomic studies. However, according to the estimates that use the relationship between the key variables in our model together with climate change scenarios published by the Network for Greening the Financial System (NGFS), the impacts of these shocks could become somewhat larger in the future.

Economic effects of shocks in the coal industry: An analysis based on DSGE model

This paper examines the impact of the coal sector on the economy from the perspective of industry shocks. Existing research primarily focuses on the relationship between coal consumption and the economy. An 8-sector dynamic stochastic general equilibrium (DSGE) model is constructed, based on China's input-output tables from 2005 to 2020, to depict the economic effects of coal sector shocks. The research findings are: (1) The DSGE model reveals a close connection between the coal industry and the macroeconomy. (2) The coal sector shocks have the largest impact on the electricity sector. (3) Coal sector shocks primarily affect the macroeconomy through non-energy manufacturing sectors. (4) As the economic development level increases, the influence of coal sector shocks on the macroeconomy gradually diminishes. The econometric analysis indicates that the role of coal is no longer significant in the high stage of economic development. The results of the panel quantile regression model also show the same result. Based on these conclusions, this paper suggests that as China gradually enters a new stage of development, it can gradually reduce coal consumption.

Combination of two-fluid model and delayed equilibrium model for the critical flow in a slit

Accurately predicting the mass flux, pressure profile, and velocity profile of the critical flow in a slit is essential for analyzing the breaking process of the liquid phase and calculating the aerosol source term for leak-before-break (LBB) monitoring and Loss of Coolant Accident (LOCA) risk analysis. A new critical flow model combining Two-fluid Model (TFM) and Delayed Equilibrium Model (DEM) is built to get accurate profiles while avoiding the same phase velocity in DEM and the arbitrary critical flow criterion in TFM. The new model is verified using past experiments of the critical flow in a slit. It proves to be accurate in mass flux but not in critical pressure, with maximum relative errors of around 25% in mass flux and around 80% in critical pressure. The new model is optimized for higher accuracy in critical pressure. The empirical equation of saturated phase mass flow rate fraction gradient is optimized by conducting approximate pressure profile calculation and regression analysis. The maximum relative error decreases little while the ratio of critical pressure relative errors lying in the range of ±40% increases after optimization. In contrast, the difference in the average abstract relative error of pressure between original TFM-DEM and DEM is much larger, for the maximum relative error of mass flux and critical pressure are around 25% and 110%. The comparison between the original and optimized TFM-DEM proves that the new critical flow model is accurate in mass flux and can be optimized to raise pressure calculation accuracy. The comparison between the original TFM-DEM and DEM proves that the phase velocity difference is the major source of accuracy improvement in the pressure profile.

Transition finance facilitates lower-cost achievement of climate targets: A case study of China

Low-carbon transition in carbon-intensive industries is crucial for achieving climate targets. However, it's challenging for enterprises and projects in these industries to access the necessary funding for their transition within the existing financial system. In this context, transition finance supports the low-carbon transition of carbon-intensive industries, injecting momentum into achieving carbon neutrality goals. However, the precise impact of transition finance on the macroeconomy remains uncertain, and the effective strategies for its implementation to effectively advance national climate objectives are still unclear. This study integrates the stock-flow consistent method into a computable general equilibrium model to evaluate the macroeconomic impact of transition finance supporting China's climate goals. Results indicate that promoting investment in energy systems capital within carbon-intensive industries through transition finance can reduce the economic cost of achieving carbon reduction targets in China, with a reduction ranging from 0.02 % to 0.26 %. Additionally, transition finance optimizes the energy structure in the short term, mitigates the exit of high-carbon industries, and lessens the impact of climate targets on these enterprises. However, implementing transitional financing requires enhanced information disclosure and strict regulation of fund flows to mitigate potential credit risks. The research findings provide valuable insights into China's transition finance policy formulation and serve as a reference for other regions seeking financial support to achieve climate targets.

Toward integrated dam assessment: evaluating multi-dimensional impacts of the Grand Ethiopian Renaissance Dam on Sudan

Abstract The Grand Ethiopian Renaissance Dam (GERD) on the Nile is expected to influence many ecosystem services, such as flood regulation, hydro-electricity production, food supply, and habitat provision, among others. Understanding these impacts (positive and negative) requires a comprehensive evaluation framework. This study develops and applies an integrated simulation framework for assessing the impacts of the GERD on Sudan, focusing on the simultaneous economywide effects of riverine flood hazards, irrigation water supply, hydropower generation, and floodplain-dependent industries, namely traditional fired clay brick production. The simulation framework incorporates three models: a river infrastructure system model, a flood model, and a Computable General Equilibrium Model. Results indicate positive impacts for hydropower generation and flood control, marginal benefits for water supply to existing irrigation, and negative consequences for brick production and the construction sector. Assuming that the GERD starts its long-term operation in 2025, we find an overall positive economic impact on Sudan’s Gross Domestic Product in 2025, with an increase of up to just over 0.1%, subject to river flow conditions. Recognizing the differences in impacts across sectors and income groups, the study emphasizes the need for interventions that ameliorate negative effects. While the study captures several impacts, other effects on the environment, recession agriculture, and soil fertility require further investigation. Still, our findings underscore the importance of adopting an integrated simulation approach to dam evaluation, acknowledging the interconnected nature of water and related sectors in national economies.

Urban system equilibrium model in an asymmetric polycentric city and the influence of rail transit investment

Taking bus and subway into account, an asymmetric polycentric urban system equilibrium model is constructed to explore the impacts of rail transit on the distribution of residents and labor force in a linear polycentric urban system. By comparing the urban system equilibria before and after the introduction of rail transit, the influence of rail transit on urban performance is analyzed. The results show that the introduction of rail transit makes the advantaged center more attractive for the labor force, and further widens the economic level gap between the two business centers. Specifically, larger distance between the two commercial centers and the higher subway travel cost would strengthen the polarization effect caused by rail transit investment. Since the improvement of transportation makes it easier for residents to accept long-distance commuting and they are more willing to choose the jobs in the advanced center.

Non-equilibrium thermal models of lithium batteries

Temperature fluctuations impact battery performance, safety, and health. Industry-standard cell-level models of these phenomena ignore thermal gradients within the electrodes’ active material, i.e., assume the latter to be in “thermal equilibrium”. We present a “non-equilibrium” thermal model that explicitly accounts for spatial variability of temperature with the active material (and the carbon-binder domain). We investigate the conditions, expressed in terms of the heat-generation rate and the thermal properties of a cell’s liquid (electrolyte) and solid (active material and CBD) phases, under which the thermal equilibrium assumption breaks down and our model should be used instead. The differences between these two thermal models are investigated further by coupling them with an industry-standard electrochemical model. The resulting thermal–electrochemical model demonstrates the importance of thermal gradients within the active material at high C-rates (discharge current densities) and for large grain sizes. Under these conditions, the equilibrium assumption underestimates internal temperature by as much as 50%. These two thermal models are then applied to a commercial NMC battery with multiple units. Our non-equilibrium model predicts the battery surface temperature that is in good agreement with measurements, while the equilibrium model underestimates the observed temperature.

The Real Equilibrium Exchange Rate of the Czech Koruna – the BEER Approach

The aim of this paper is to develop a model of the real equilibrium CZK/EUR exchange rate with all relevant explanatory variables. Emphasis will be placed on examining the longest possible time horizon, with a period of real convergence, but also economic stagnation. The model is based on the theoretical BEER approach using a cointegration or error correction model that distinguishes between short-term and long-term relationships. The results show that the Czech koruna strengthens when the productivity differential, terms of trade differential or gross fixed capital formation increase, while the koruna weakens when the VIX index representing global risk aversion increases. For the real interest rate differential, the hypothesis that the koruna strengthens in the short run during the improvement but weakens in the long run probably due to the country's risk premium, was confirmed. Moreover, it turned out that the start of the European Central Bank's quantitative easing led to strengthening of the Czech koruna, while the start of the CNB's foreign exchange interventions in 2013 led to weakening of the Czech koruna.

Unconventional Monetary Policy Response to Covid-19 and Its Impact on Inflation in Morocco

This study explores the impact of unconventional monetary policy on Morocco’s economy during the Covid-19 pandemic. We used a hybrid model combining a financial dynamic stochastic general equilibrium (DSGE) model with a standard epidemiology model, enabling us to consider both economic and epidemiological factors. Our results indicate that unconventional monetary policy cannot fully mitigate the adverse effects of a pandemic, except for an exogenous increase in Central Bank claims. We also found that Morocco’s high inflation is partly due to Bank Al-Maghrib’s unconventional monetary measures in response to the pandemic. Our research underscores the importance of monetary authorities balancing the benefits and risks of unconventional monetary policy. While it can stimulate the economy during crises, it should be used judiciously to avoid long-term negative effects. Incorporating epidemiological factors into macroeconomic models is crucial for understanding the intricate interplay between the economy and public health crises.

Effectiveness of a PCM-based heat sink with partially filled metal foam for thermal management of electronics

Electronics often experience overheating, which occurs when insufficient or improper cooling causes temperatures to rise quickly, potentially leading to component failure. Recently, a passive technique utilizing phase change material (PCM)-based heat sinks is suitable for modern electronic cooling. However, due to its low thermal conductivity, Aluminum (Al) foam as a thermal conductivity enhancer (TCE) is used. In this study, a partial filling approach is employed, involving a heat sink designed to cool a protruding electronic component (EC) attached to a metal fin. The enthalpy-porosity method and the thermal equilibrium model are applied. Results show that the efficiency of the heat sink is improved by increasing the filling ratio of the Al foam, thereby reducing the EC temperature by 15.85 °C, shortness the melting time by more than 1000 s, and the overall effective conductivity enhanced by 25 times compared to the case without Al foam. In addition, the optimal partial filling ratio is determined to be 2/3, due to the considerable savings of 33.33 % in material cost and overall heat sink weight. The findings suggest that partial filling is a strategy that can be employed to achieve a more comprehensive performance in thermal management using PCM-based heat sinks.

McFine: python-based Monte-Carlo multi-component hyperfine structure fitting

Abstract Modelling complex line emission in the interstellar medium (ISM) is a degenerate, high-dimensional problem. Here, we present McFine, a tool for automated multi-component fitting of emission lines with complex hyperfine structure, in a fully automated way. We use Markov chain Monte Carlo (MCMC) to efficiently explore the complex parameter space, allowing for characterising model denegeracies. This tool allows for both local thermodynamic equilibrium (LTE) and radiative-transfer (RT) models. McFine can fit individual spectra and data cubes, and for cubes encourage spatial coherence between neighbouring pixels. It is also built to fit the minimum number of distinct components, to avoid overfitting. We have carried out tests on synthetic spectra, where in around 90 per cent of cases it fits the correct number of components, otherwise slightly fewer components. Typically, Tex is overestimated and τ underestimated, but accurate within the estimated uncertainties. The velocity and line widths are recovered with extremely high accuracy, however. We verify McFine by applying to a large Atacama Large Millimeter/submillimeter Array (ALMA) N2H+ mosaic of an high-mass star forming region, G316.75-00.00. We find a similar quality of fit to our synthetic tests, aside from in the active regions forming O-stars, where the assumptions of Gaussian line profiles or LTE may break down. To show the general applicability of this code, we fit CO(J = 2-1) observations of NGC 3627, a nearby star-forming galaxy, again obtaining excellent fit quality. McFine provides a fully automated way to analyse rich datasets from interferometric observations, is open source, and pip-installable.

CBDC and banking stability: Modeling cascading effects on reserves, lending, and liquidity

This research uses a dynamic modelling approach to design and simulate an equilibrium model of the interaction between CBDC issuance, deposits and bank reserves. With many central banks announcing their intention to issue central bank digital currencies (CBDCs), it has become imperative to rigorously analyse the potential impact of these issues on the banking system. This study aims to examine the implications of the introduction of CBDCs within a robust analytical framework, in order to inform policymakers and financial sector players about the possible consequences of this major monetary innovation. The study results show that overconfidence of economic agents towards CBDCs can drastically reduce bank reserves, thereby limiting the lending capacity of banks and creating liquidity problems. Similarly, increasing reserve requirements in fiat currency for each unit of CBDC issued can constrain bank reserves and restrict loans and deposits. Additionally, a rise in interest rates on CBDC-related loans can discourage borrowers, thereby reducing loan demand and affecting banking activity. An increase in interest rates leads to a decrease in the quantity of CBDC in circulation, an increase in bank reserves and deposits in CBDC, and a decrease in bank loans. Monitoring the level of confidence of economic agents towards CBDCs is crucial to avoid excessive speculation.

Climate Change's Effect on Household Food Security in Sub-Saharan Africa and Optimal Monetary Policy

The resurgence of food insecurity in Sub-Saharan Africa during the past decade highlights the need to comprehend the phenomenon within a framework that includes all economic agents in these times of intensification of climate change. Thus, this paper, using a Dynamic Stochastic General Equilibrium (DSGE) model, analyzes the effects of climate shocks occurring in agricultural and non-agricultural sectors on household food security in Sub-Saharan Africa, while determining optimal monetary policy responses to mitigate these adverse effects. Findings highlight that climate shocks affecting the non-agricultural sector are more detrimental to long-term household food security than those affecting the agricultural sector, particularly for urban households. To mitigate these effects, flexible policies targeting food price inflation and headline inflation seem appropriate for rural and urban households, respectively. Nevertheless, in the absence of political and social pressure, flexible headline inflation targeting is optimal for mitigating climate shocks effects on Sub-Saharan Africa's food security.

The nexus between local government debt risk, real estate sector, and financial stability

Rising local government debt and downturn in the real estate sector pose significant challenges to China’s economic growth and financial stability. To analyze these challenges, this paper develops a dynamic stochastic general equilibrium (DSGE) model to study the nexus between government debt risk, real estate sector, and financial stability. The findings suggest that an increase in debt risk initiated by a housing demand shock could have a persistent and magnified effect on the financial sector and the macroeconomy. The amplification mechanism originates from risk spillover and debt crowding-out effect, which trigger the negative feedback between the debt and financial risk. Longer debt maturity and the implementation of credit policy could effectively moderate the contractionary effects of this risk interaction on the economy.

Regional aggregation bias in the global computable general equilibrium model: Issues in assessing the economic impact of climate change and trade liberalization

This study examined the bias introduced by regional aggregation (RA) when assessing the effect of climate change and trade liberalization through computational experiments. The analysis used global computable general equilibrium models with different pre-aggregation levels, based on the GTAP10 database. The bias was quantified by comparing the effects between large-scale and aggregated models. The results revealed that RA bias comprised over 35% of estimated effects related to climate change and global trade liberalization; it reversed the change direction in the simulation and deviated changes beyond the variation range observed in the sensitivity analysis; and it increased in developing countries where the proportions of imports were high. Much RA bias is artificially created by aggregating countries with different initial shocks, which then spreads to other countries through a pseudo-trade structure. Therefore, adopting a disaggregated global model is crucial to improve the accuracy of climate change assessments with diverse shocks worldwide.

Which decarbonization policy mixes are better for China's power sector? A simulation balancing aggregate abatement effects and economic impacts

The decarbonization policies are currently being planned or implemented worldwide, particularly for emerging economies such as China. When the government designs a preferred decarbonization policy mix, both environmental and economic impacts should be considered. This paper focuses on decarbonization policy mixes in China's power sector, including renewable electricity subsidies (ES), tradable green certificates (TGC), and two carbon pricing instruments. An integrated model combining a partial equilibrium model and an input-output framework was constructed to investigate their abatement effects and economic impacts. The results show that the combination of multiple decarbonization policies can achieve greater emission reduction or lower economic losses compared to implementing them separately. The mix of carbon pricing and TGC shows the least economic losses; the mix of carbon pricing, ES, and TGC achieves maximum abatement effect. A narrow focus on carbon emission reduction would hinder the economic development. The combination of multiple decarbonization policies can trigger more substantial variations in the supply chain of the power sector than their individual implementation. Those policy mixes including carbon tax may achieve lower carbon emissions and economic losses compared to those including a carbon emissions trading market. Therefore, policymakers should conduct a comprehensive simulation of the multiple impacts of policy mixes before implementing them, encompassing both direct impacts on the power sector and indirect impacts on its upstream sectors.

Modeling the Tourism Market Behavior Based on Discrete Equilibrium Models “Supply – Price – Demand”

Abstract The work is devoted to the modeling of the behavior of the tourism market in the conditions of a supply random lag, distributed according to normal and uniform distribution laws. The behavior of dependences on the tourist market of supply and demand on the price is considered. The modeling of the behavior of the tourism market was carried out using a market dynamic model in the plane of variables “supply – price – demand” taking into account the interests of different groups of consumers, primarily from the point of view of pricing. The delay between changes in supply and demand volumes is taken into account using a Cobweb model. To test this method, information was collected on family expenses when traveling abroad (outbound tourism, tourist vacations lasting 7-15 days) by surveying the employees of 38 travel organizations as of 2021. Three segments of the tourism market are identified: low ($2000 − 4000), medium ($4000 − 12000), and VIP-segment ($12,000 − 20,000). The analysis of the modeling results showed that the behavior of tourists of different segments can significantly influence the market dynamics. The use of a Cobweb model allowed for determining the level of stability of tourist behavior and assessing the possibility of consumer migration from one segment to another. Sensitivity to price changes and response to new offers from different segments can be different, which is important for determining pricing strategies, marketing, and the development of new tourism products.

Market Regulation, Cycles, and Growth Dynamics in a Monetary Union

AbstractWe build a two‐country currency union dynamic stochastic general equilibrium (DSGE) model with endogenous growth to assess the role of product market regulation (PMR) and labor market regulation (LMR) for growth and the adjustment to shocks. We show that with endogenous growth, there is no reason to expect real income convergence. Large shocks can lead to permanent changes of output and real exchange rates. Differences are exacerbated by different PMR and LMR. Less regulated economies have higher trend growth and recover faster from negative shocks. Results are consistent with higher inflation, lower employment, and disappointing total factor productivity (TFP) growth rates experienced in more regulated euro area members.

The Technical Default Spread

Abstract We study the quantitative impact of lender control rights on corporate investment, asset prices, and the aggregate economy. We build a general equilibrium model in which the breaching of a loan covenant (technical default) entails a switch in investment control rights from borrowers to lenders. Lenders optimally choose low-risk projects, thus mitigating borrowers’ risk-taking incentives and lowering the cost of equity. This mechanism generates strong macroeconomic effects and mitigates the financial accelerator. Consistent with our model, proximity to technical default in the data is associated with 4.12% lower returns and lower exposure to systematic risk.