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This study examines the importance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand. To this end, the authors construct a small open economy New Keynesian dynamic stochastic general equilibrium (DSGE) model. The model encompasses several essential characteristics, including incomplete financial markets, incomplete exchange rate pass-through, deviations from the law of one price and a banking sector. The authors consider generalized Taylor rules, in which policymakers adjust policy rates in response to output, inflation, credit growth and exchange rate fluctuations. The marginal likelihoods are then employed to investigate whether the central bank responds to fluctuations in the exchange rate and credit growth.

This study constructs a small open economy DSGE model and then estimates the model using Bayesian methods.

The authors demonstrate that the monetary authority does target exchange rates, whereas there is no evidence in favor of incorporating credit growth into the policy rules. These findings survive various robustness checks. Furthermore, the authors demonstrate that domestic shocks contribute significantly to domestic business cycles. Although the terms of trade shock plays a minor role in business cycles, it explains the most significant proportion of exchange rate fluctuations, followed by the country risk premium shock.

This study is the first attempt at exploring the relevance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand.

Several studies have examined the impact of market fundamentals on house prices. However, the effect of economic sectors on housing prices is limited despite the existence of two-speed economies in some countries, such as South Africa. Therefore, this study aims to examine the impact of mining activities on house prices. This intends to understand the direction of house price spreads and their duration so policymakers can provide remediation to the housing market disturbance swiftly.

This study investigated the effect of mining activities on house prices in South Africa, using quarterly data from 2000Q1 to 2019Q1 and deploying an auto-regressive distributed lag model.

In the short run, we found that changes in mining activities, as measured by the contribution of this sector to gross domestic product, impact the housing price of mining towns directly after the first quarter and after the second quarter in the non-mining cities. Second, we found that inflationary pressure is instantaneous and impacts house prices in mining towns only in the short run but not in the long run, while increasing housing supply will help cushion house prices in both submarkets. This study extended the analysis by examining a possible spillover in house prices between mining and non-mining towns. This study found evidence of spillover in housing prices from mining towns to non-mining towns without any reciprocity. In the long run, a mortgage lending rate and housing supply are significant, while all the explanatory variables in the non-mining towns are insignificant.

These results reveal that enhanced mining activities will increase housing prices in mining towns after the first quarter, which is expected to spill over to non-mining towns in the next quarter. These findings will inform housing policymakers about stabilising the housing market in mining and non-mining towns. To the best of the authors’ knowledge, this study is the first to measure the contribution of mining to house price spillover.

This 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.

The 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.

This 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.

This 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.

This study examines the differences in the economic stimulus effects, transmission mechanisms, and output multipliers of government consumption, government traditional investment, and government science and technology investment.

This study constructs and estimates a New Keynesian model of endogenous technological progress embedded in the research and development (R&D) and technology transfer sectors. Using Chinese macroeconomic time series data from 1996 to 2019, this study calibrates and estimates the model and analyzes the impulse response function and a counterfactual simulation of expenditure structure adjustment.

The results show that compared with the traditional dynamic stochastic general equilibrium (DSGE) model, the endogenous process of technological progress amplifies the impact of government consumption shock and traditional government investment shock on the macroeconomy, leading to greater economic cycle fluctuations. As government investment in science and technology has positive external spillover effects on firm R&D activities and the application of innovation achievements, it can promote more sustainable economic growth than government consumption and traditional investment in the long run.

This study constructs an extended New Keynesian model with different types of government spending, which includes endogenous technological progress within the R&D and technology transfer sectors, thereby linking fiscal policy, business cycle fluctuations and long-term economic growth. This model can study the macroeconomic impact of fiscal expenditure structure adjustment when fiscal expansion is limited. In the Bayesian estimation of model parameters, this study not only uses macroeconomic variables but also adds a sequence of private R&D investment.

Public debt forecasts represent a key policy issue. Many methodologies have been employed to predict debt sustainability, including dynamic stochastic general equilibrium models, the stock flow consistent method, the structural vector autoregressive model and, more recently, the neuro-fuzzy method. Despite their widespread application in the empirical literature, all of these approaches exhibit shortcomings that limit their utility. The present research adopts a different approach to public debt forecasts, that is, the random forest, an ensemble of machine learning.

Using quarterly observations over the period 2000–2021, the present research tests the reliability of the random forest technique for forecasting the Italian public debt.

The results show the large predictive power of this method to forecast debt-to-GDP fluctuations, with no need to model the underlying structure of the economy.

Compared to other methodologies, the random forest method has a predictive capacity that is granted by the algorithm itself. The use of repeated learning, training and validation stages provides well-defined parameters that are not conditional to strong theoretical restrictions This allows to overcome the shortcomings arising from the traditional techniques which are generally adopted in the empirical literature to forecast public debt.

As a by-product of the production process, emissions can follow output fluctuations. Hence, disregarding the relationship between economic fluctuations and emissions could result in undesirable environmental outcomes. This study aims to investigate the environmental and economic effects of abatement subsidies on overall emissions during business cycles in Australia.

A real business cycle (RBC) model is devised and parameterised in this paper. RBC models have been recently introduced to environmental policy analysis, and this study contributes to the literature by investigating the effects of a potential subsidy policy in an RBC framework. The model is also calibrated and provides solutions for the Australian economy.

The authors find that under a steady-state situation, supporting abatement can result in reducing emissions by 6.45% while it imposes welfare costs to the economy (by 0.61%). Simulation results show that an optimal abatement policy should be pro-cyclical, with the abatement subsidy increasing during expansions and decreasing during recessions. As well, in a subsidy policy setting, emissions would react pro-cyclically, i.e. emissions increase (decrease) when the gross domestic product increases (decreases). The abatement reaction by firms, however, is different, because when a positive productivity shock occurs, firms reduce abatement and allocate resources to production. Nonetheless, as time passes, the increased subsidy provides a strong enough incentive to allocate resources to abatement and, subsequently, abatement increases.

This paper investigates how an emission reduction subsidy should be adapted to macroeconomic fluctuations so that it can limit variations in emissions.

This paper analyzes real and welfare effects of a permanent change in inflation rate, focusing on macroprudential policy’ role and its interaction with monetary policy.

While investigating disinflation costs, the authors simulate a medium-scale dynamic general equilibrium model with borrowing constraints, credit frictions and macroprudential authority.

Providing discussions on different policy scenarios in a context where still it is expected high inflation, there are three key contributions. First, when macroprudential authority actively operates to improve financial stability, losses caused by disinflation are limited. Second, a Taylor rule directly responding to financial variables might entail a trade-off between price and financial stability objectives, by increasing disinflation costs. Third, disinflation is welfare improving for savers, while costly for borrowers and banks. Indeed, while savers benefit from policies reducing price stickiness distortion, borrowers are worried about credit frictions, coming from collateral constraint.

The paper suggests threefold policy implications: the macroprudential authority should actively intervene during a disinflation process to minimize costs and financial instability deriving from it; policymakers should implement a disinflationary policy stabilizing also output; the central bank and the macroprudential regulator should pursue financial and price stability goals, separately.

This paper is the first attempt to study effects of a permanent inflation target reduction in focusing on the macroprudential policy’ role.

The author augments an otherwise standard business cycle model with a richer government sector and adds money-in-utility (MIU) considerations to study economic fluctuations.

More specifically, real money balances enter in a non-separable way with consumption and leisure. This specification is then calibrated to Bulgarian data after the introduction of the currency board (1999–2020) gives a role to money in accentuating economic fluctuations.

This novel mechanism allows the framework to reproduce – better than the real business cycle (RBC) model – the observed variability and correlations among model variables, and those characterizing the labor market in particular. In addition, money is non-neutral and affects aggregate economic activity.

This is the first micro-founded monetary-DSGE (dynamic stochastic general equilibrium) model on Bulgaria trying to explain the role of money for economic fluctuations.

The degree of development and the way to identify a fiscal shock matter in evaluating the effects of the fiscal policy. This paper contributes to the debate on the effects of a fiscal expansion on private consumption and the real effective exchange rate.

This paper uses a sign-restriction method to identify a fiscal shock in the panel structural VAR analysis in the context of both developed and developing countries.

The authors’ find that (1) private consumption increases in response to a positive government spending shock in both groups, yet such consumption effect is greater in developing than industrial countries; (2) the response of real effective exchange rate to the government spending shock varies across groups: it depreciates in developed countries and appreciates in developing countries; (3) trade balance improves in both groups.

This study sheds light on the differential effects of fiscal shock on consumption and real exchange rate in both developed and developing economies.

Monetary policy has major impacts on macroeconomic indicators of the country. Accordingly, uncertainty regarding monetary policy shifts can cause challenges and risks for businesses, financial markets and investors. Thus, the purpose of this study is to investigate how real estate market volatility responds to monetary policy uncertainty.

The GARCH-MIDAS model is applied in this study to investigate the nexus between monetary policy uncertainty and real estate market volatility. This model was fundamentally instituted to accommodate low-frequency variables.

The results of this study reveal that increased monetary policy uncertainty highly affects the volatility in real estate market during the peak period of COVID-19 as compared to full sample period and COVID-19 recovery period; hence, a significant decline is evident in real estate market volatility during crisis.

This study is particularly focused on peak and recovery period of COVID-19 considering the geographical region of Greece, Japan and the USA. This study provides a complete perspective on the nexus between monetary policy uncertainty and real estate markets volatility in three distinct economic views.