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This paper aims to study the monetary transmission mechanism of China from January 1996 to December 2009 under endogenous structural breaks.

The study constructs a benchmark VAR model and then adds the proxy variables for four channels of monetary policy transmission as endogenous or exogenous variables in the model to study the transmission mechanism in China. Considering a number of reforms carried out in the economic and financial field in the past two decades and the possibility of structural changes in the monetary transmission mechanism, the methodology proposed by Qu and Perron is employed to allow for endogenous structural changes in the model.

By conducting a comparative analysis, conclusions can be drawn from this paper that bank lending is always the dominating channel for monetary policy to influence economy in China and the roles of the interest rate channel and the exchange rate channel have been improved in recent years. However, the role of the asset price channel in monetary policy transmission has weakened since late 2001.

This paper combines the quasi‐maximum likelihood procedure proposed by Qu and Perron in 2007 with a benchmark VAR model, thus providing a new approach to study monetary transmission mechanism and the conclusions can be more sensible.

The purpose of this paper is to provide a method for computing the spillover index first proposed by Diebold and Yilmaz (2009), with empirical application on Asian stock markets.

It is based on a VAR-structural-GARCH model.

The results clearly show that the main driver of fluctuations in Asian financial markets is the USA, with China having little connection with other markets. Further, evidence of financial contagion is found during both the 1997 Asian financial crisis and the 2008 global financial crisis.

The method has two advantages: it is both uniquely determined and dynamic.

The purpose of this paper is to examine the monetary policy transmission mechanism for the Fiji Islands using a structural vector autoregressive (SVAR) model for the period 1975 to 2005.

The SVAR model investigates how a monetary policy shock – defined as a temporary and exogenous rise in the short‐term interest rate – affects real and nominal macro variables; namely real output, prices, exchange rates, and money supply.

The results suggest that a monetary policy shock statistically significantly reduces output initially, but then output is able to recover to its pre‐shock level. A monetary policy shock generates inflationary pressure, leads to an appreciation of the Fijian currency and reduces the demand for money. The paper also analysed the impact of a nominal effective exchange rate (NEER) shock (an appreciation) on real output and found that it leads to a statistically significant negative effect on real output.

The findings of this study should be of direct relevance to the research and policy work undertaken at the Reserve Bank of Fiji.

For a small economy, such as Fiji, where monetary policy is key to sustainable macroeconomic management, this is the first paper that undertakes a dynamic analysis of monetary policy transmission. The paper uses time series data over three decades and builds a structural VAR model, rooted in theory. This paper will be of direct relevance to the Reserve Bank of Fiji. The approach and model proposed will also be useful for applied monetary policy researchers in other developing countries where inflation rate targeting is a key element of the monetary policy setting.

The purpose of this paper is to examine the effects of inflation uncertainty on real economic activity using data from four industrialised countries.

The paper uses the econometric framework developed by Elder in the context of a multivariate framework in which a structural vector autoregression (VAR) is modified to accommodate multivariate GARCH‐in‐mean (MGARCH‐M) errors. It calculates the impulse response functions for the multivariate GARCH(1,1)‐in‐mean VAR in order to see whether the specification captures the fundamental dynamics.

The results show that inflation uncertainty has differential effects on output growth across these countries.

In the context of multivariate GARCH(1,1)‐in‐mean VAR, this paper uses a non‐recursive identification scheme and separate identification for the large and small economies.

This paper aims to examine the interrelationships of monetary policy's structural shocks, the real exchange rate and stock prices.

According to quarterly data, variables such as gross domestic product, consumer price index, the real exchange rate, stock price and monetary policy indices in the structural vector autoregressions model are estimated. These variables' volatility is attributed to other variables’ structural shocks separately, and analysis of variance tables for all variables is presented.

The results show that structural shock on the exchange rate does not affect the stock price, but the monetary policy's structural shock positively impacts the real exchange rate. Moreover, the real exchange rate and monetary policy's structural shocks have a negative impact on the stock price index. However, no significant effect is found pertain to the real exchange rate structural shock, statistically.

To the best of the authors’ knowledge, the current study model is relatively novel in developing countries, and the study sought strength to develop knowledge on the subject of the study.

The study investigates the effectiveness of government policies to mitigate the impact of a pandemic. The study adopts the small open economy of Nigeria for the following reasons. First, Nigeria is the largest economy in SSA. Second, Nigeria was also significantly impacted by the COVID-19 pandemic.

The study employed the time-varying structural autoregressive (TVSVAR) model to control for the potential asymmetry in fiscal variables and to control for the shift in the structural shift, following a macroeconomic shock. As a form of robustness, the study also implements the time-varying Granger causality to formally assess the temporal instability of the variable of interest.

The results show that an oil price shock is an important source of macroeconomic instability in Nigeria. Importantly, the results indicate that the effects of fiscal policy are strongly time varying. Specifically, the results show that fiscal policy helps to stabilize the economy, (i.e. they help to reduce inflation and spur output growth) following macroeconomic shock. Further, the Granger test shows that fiscal policy helped to spur growth in Nigeria. The research and policy implications are discussed.

The study accounts for the time-varying effects of fiscal policy.

The purpose of this study is to investigate the interactive relationships between oil price shocks and the Nigeria stock market.

The paper applied the multivariate vector auto‐regression that employed the generalized impulse response function and the forecast variance decomposition error.

Empirical evidence reveals that stock market returns exhibit insignificant positive response to oil price shocks but reverts to negative effects after a period of time depending on the nature of the oil price shocks. The results are similar even with the inclusion of other variables. Also, the asymmetric effect of oil price shocks on the Nigerian stock returns indices is not supported by statistical evidences.

This is the first study to examine the dynamic linkages between stock market behaviour and oil price shocks in Nigeria.

The Russian invasion of Ukraine generated unprecedented panic in the European financial system. As expected, the European Union (EU) felt most of the negative effects of the war due to geographical proximity to Ukraine and energy dependence on Russia. This study aims to investigate the influence of Brent crude oil (BCO), Dutch Title Transfer Facility Natural Gas, and CBOE Volatility Index (VIX) on Deutscher Aktien Index (DAX), Austrian Traded Index (ATX) and Milano Indice di Borsa (FTSEMIB). The German, Austrian and Italian equity indexes were chosen due to the heavy dependence of these countries on Russian gas and oil.

The data cover the period from November 24, 2021, to June 24, 2022, including five months of the Russia–Ukraine war. To generate the intended results, vector autoregressive, structural vector autoregressive, vector error correction model, Johansen test and Granger causality test were used.

The results highlight that natural gas and the VIX carried negative effects on DAX, ATX and FTSEMIB. The BCO was expected to have influenced three selected equity indexes, while the results suggest that it was priced only in ATX.

This research provides modest evidence for the policymakers on the systemic risk that Russian gas has for the EU equity markets. From a managerial perspective, changes in oil and gas prices are a permanently integral part of portfolio risk analysis.

The main purpose of this paper is to investigate the dynamic effects of the oil price shocks on Iran’s inflation in the period 1993:2–2018:2

The main purpose of this paper is to investigate the dynamic effects of the oil price shocks on Iran’s inflation in the period 1993:2–2018:2 using the time-varying parameter vector autoregressive (TVP-VAR) model. The dynamics of the results enable us to study the amount and severity of the impact of the oil price shocks on inflation with the distinction of the sanctioned and non-sanctioned periods. The volume of oil export is used to identify the effective oil sanctions. The period is divided into sanctioned and non-sanctioned periods by Markov switching model.

The results show that the pass-through of oil price shocks into Iran’s inflation are time-varying, and there are significant differences at sanction period from other time horizons. An increase in oil price has a positive effect on inflation and its effects are stronger during the sanctions period. It is also observed that the producer price index is more sensitive to changes in the oil price than the consumer price index. The necessity of the government’s earnest efforts to improve international relations to lift the sanctions, along with diversification of exports, and making the economy of Iran independent of oil revenues is obvious.

In addition to the exogenous oil price shocks, Iran’s economy faces numerous restrictions for its oil exports due to the sanctions. The main purpose of this paper is to investigate the dynamics effects of the oil price shocks on Iran’s inflation in the period 1993:2–2018:2 using the time-varying parameter vector autoregressive (TVP-VAR) model. The dynamics of the results enable us to study the amount and severity of the impact of the oil price shocks on inflation with the distinction of the sanctioned and non-sanctioned periods. The volume of oil export is used to identify the effective oil sanctions.

The purpose of this paper is to investigate the dynamics between gross domestic product (GDP), environmental degradation and happiness, by using country-level panel-data covering 23 countries, for the period 1961-2005.

For the analysis the authors employed the vector autoregression (VAR) approach in a panel framework.

The main results show that a high level of happiness is associated with a low level of GDP on short term (one year). The joint influence of GDP and environmental degradation on happiness is not significant, while GDP and happiness are unrelated to environmental degradation.

The paper extends the literature on developed countries and offers a particular perspective on the relationship between environment degradation and happiness through a GDP growth impulse analysis.

The paper offers two main novelties: it simultaneously investigates the “well-being – environment”, and “well-being – economic dimension”, and it uses a panel-VAR approach, including the cross-country variation.