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The purpose of this paper is to investigate the potential link between remittances and economic volatility in small island developing states.

The paper estimates a panel data model using a database containing 20 small island developing states (SIDS) observed over annual intervals between 1986 and 2005.

The results suggest that, in general, remittance flows have a stabilising influence on output and investment volatility. However, given the importance of these flows to SIDS, the volatility of remittances also has a significant and positive impact on both investment and consumption volatility.

The policy implications of the study's findings is that SIDS (similar to how oil‐producing nations take oil price fluctuations into account when considering policy changes) may have to monitor and forecast future remittance flows and take these projections into account when making changes to either their monetary or fiscal policy stance.

Workers' remittances have grown dramatically worldwide, particularly in SIDS, where they constitute one of the main sources of foreign exchange. Given the importance of these flows to economic growth and development in these countries, this study examines the potential link between remittances and economic volatility.

The purpose of this paper is twofold, first, to develop an effective tool to assess the performance of the overall economy by creating an assessment ratio that reflects the two top priorities of monetary policy, promoting economic growth and maintaining price stability, and second, to use the annual assessment ratios to build two subsamples, outperformance (better than the historical average) and underperformance, to examine and compare the changes in impacts of monetary and fiscal policy tools on important economic variables in different economic conditions, instead of different time periods.

The assessment ratio is defined as the gross domestic product (GDP) gap/standard deviation of inflation. Essentially, this Growth/Volatility ratio quantifies the price volatility-adjusted long-term output growth, that is, the long-term output growth given 1 per cent of the standard deviation of inflation. The growth has a positive impact on the ratio, while the effect of price volatility is negative. The ratio reflects not only the Fed’s dual goal but also the fundamental economic conditions. A higher value of the ratio indicates that the economy can better handle inflation risk in driving the long-term output growth. As the inflation level is adjusted in the numerator (GDP gap), not the denominator, no matter the Fed is engaging in the fight against inflation, or for reflation (promoting inflation) to prevent deflation and pursue price stability (Bernanke, 2002), the ratio remains consistent with the Fed’s dual goal and prefers a higher value.

Results of this study suggest that impacts of monetary and fiscal policy tools on key economic variables may be cyclic as the economic condition changes. The policy tools can significantly affect inflation volatility and the price volatility-adjusted long-term real output growth in the subpar economic conditions identified with lower assessment ratios. The effects become insignificant when the general economic performance exceeds the historical average. More importantly, results of this study indicate that the funds rate can effectively lower the price volatility, while the fiscal tools can promote long-term real output growth in the subpar economic conditions. Therefore, when inflation volatility spikes and the real output growth slows, the decisive and timely monetary and fiscal policy decisions become necessary to enhance policy effectiveness.

The assessments of effectiveness of monetary policy in the literature are based on some or all of four descriptive statistics: inflation, inflation volatility, output growth, and growth volatility. Each of them measures only one aspect of an economic phenomenon and cannot reflect the well-known conflicting relationship between maintaining price stability and promoting economic growth. For instance, from the policy perspective, a higher price volatility combined with a higher GDP growth rate for one period may or may not outperform another period with lower price volatility and growth rate. However, the assessment ratio created in this study considers both price volatility and economic growth simultaneously and can, therefore, be used as an effective measure of the overall economic performance.

This study investigates the impact of US dollar volatility and oil rents on the performance of small and medium-sized enterprises (SMEs) in the Gulf Cooperation Council (GCC) region, with an emphasis on understanding how these factors influence SME financing constraints in economies with fixed currency regimes.

Employing a random effects panel regression analysis, this research considers US dollar volatility and oil rents as independent variables, with SME performance, measured through the financing gap, as the dependent variable. Controls such as trade balance, inflation deltas and gross domestic product (GDP) growth are included to isolate their effects on SME financing constraints.

The study reveals a significant positive relationship between dollar volatility and the financing gap, suggesting that increased volatility can exacerbate SME financing constraints. Conversely, oil rents did not show a significant direct influence on SME performance. The trade balance and inflation deltas were found to have significant effects, highlighting the multifaceted nature of economic variables affecting SMEs.

The study acknowledges potential biases due to omitted variables and the limitations inherent in the use of secondary data.

Findings offer pertinent guidance for SMEs and policymakers in the GCC region seeking to develop strategies that mitigate the impact of currency volatility and support SME financing.

The research provides new insights into the dynamics of SME performance within fixed currency regimes, which significantly contributes to the limited literature in this area. The paper further underscores the complex connections between global economic factors and SME financial health.

The stock market has shown fluctuating degrees of volatility because of the recent COVID-19 pandemic in India. The present research aims to investigate the effect of the COVID-19 on the stock market volatility, and whether the economic package can control the market volatility or not, measured by a set of certain sector-level economic features and factors such as resilience variables.

We examine the correlation matrix, basic volatility model and robustness tests to determine the sector-level economic features and macroeconomic factors helpful in diminishing the volatility rising because of the COVID-19.

The outcomes of this study are significant as policymakers and financial analysts can apply these economic factors to set policy replies to handle the unexpected fluctuation in the stock market in sequence to circumvent any thinkable future financial crisis.

The originality of the paper is to measure the variables affecting the stock market volatility due to COVID-19, and understand the impact of capital market macroeconomic variables and dummy variables to theoretically explain the COVID-19 impact on stock market volatility.

Remittances are the fastest growing source of foreign exchange earnings for developing countries. The purpose of this paper is to assess the impact of remittances on economic volatility of the receiving country.

A panel of 95 countries over the period 1970‐2005 is employed in the analysis. To assess the impact of remittances on volatility a multivariate model is estimated using a panel fixed effects approach with cross‐section weights.

The study reports that remittances can play a key role in mitigating the effect of adverse output shocks but exert no significant influence on consumption and investment volatility. Moreover, important differential impacts exist across the various country groupings.

Countries that are dependent on remittances may have to monitor and forecast future remittance flows and take these projections into account when making changes to either their monetary or fiscal policy stance.

The findings provided in this paper should be of use to policymakers in developing countries.

We aim to clarify the effect of economic uncertainty on Chinese stock market fluctuations. We extend the understanding of the asymmetric connectedness between economic uncertainty and stock market risk and provide different characteristics of spillovers from economic uncertainty to both upside and downside risk. Furthermore, we aim to provide the different impact patterns of stock market volatility following several exogenous shocks.

We construct a Chinese economic uncertainty index using a Factor-Augmented Variable Auto-Regressive Stochastic Volatility (FAVAR-SV) model for high-dimensional data. We then examine the asymmetric impact of realized volatility and economic uncertainty on the long-term volatility components of the stock market through the asymmetric Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling (GARCH-MIDAS) model.

Negative news, including negative return-related volatility and higher economic uncertainty, has a greater impact on the long-term volatility components than positive news. During the financial crisis of 2008, economic uncertainty and realized volatility had a significant impact on long-term volatility components but did not constitute long-term volatility components during the 2015 A-share stock market crash and the 2020 COVID-19 pandemic. The two-factor asymmetric GARCH-MIDAS model outperformed the other two models in terms of explanatory power, fitting ability and out-of-sample forecasting ability for the long-term volatility component.

Many GARCH series models can also combine the GARCH series model with the MIDAS method, including but not limited to Exponential GARCH (EGARCH) and Threshold GARCH (TGARCH). These diverse models may exhibit distinct reactions to economic uncertainty. Consequently, further research should be undertaken to juxtapose alternative models for assessing the stock market response.

Our conclusions have important implications for stakeholders, including policymakers, market regulators and investors, to promote market stability. Understanding the asymmetric shock arising from economic uncertainty on volatility enables market participants to assess the potential repercussions of negative news, engage in timely and effective volatility prediction, implement risk management strategies and offer a reference for financial regulators to preemptively address and mitigate systemic financial risks.

First, in the face of domestic and international uncertainties and challenges, policymakers must increase communication with the market and improve policy transparency to effectively guide market expectations. Second, stock market authorities should improve the basic regulatory system of the capital market and optimize investor structure. Third, investors should gradually shift to long-term value investment concepts and jointly promote market stability.

This study offers a novel perspective on incorporating a Chinese economic uncertainty index constructed by a high-dimensional FAVAR-SV model into the asymmetric GARCH-MIDAS model.

Consumption volatility is a key source of economic growth volatility; thus, it is an important factor in designing macroeconomic policy. The purpose of this paper is to investigate the factors that determine household consumption volatility, using urban household survey (UHS) data over the period 2002–2009 in 18 provinces in China.

Both a traditional variance decomposition method and an advanced variance decomposition method are used.

The traditional variance decomposition method suggests that heterogeneity of consumption goods is the key to analyze consumption volatility in China. Consumption of transportation makes the highest aggregate contribution and per-unit volatility in consumption volatility, whereas consumption of food makes the second highest aggregate contribution and the lowest per-unit volatility. Further investigation with the advanced variance decomposition method, which allows the authors to capture intertemporal dynamics and cross-household differences simultaneously, finds that the main factor determining the consumption volatility in China is intertemporal dynamics, rather than cross-household differences.

Future research could fruitfully explore four issues. First, consumption upgrading has increased the volatility of China’s household consumption. How much will this affect economic growth in China under its “new normal” conditions, and how should the Chinese government respond? Second, differences between UHS data and aggregate data in the calculations of consumption risk sharing need to be investigated. Third, it is important to investigate the channels through which the Chinese government can enhance its ability to spread consumption risks and thus reduce consumer consumption volatility. Finally, further study could extend the current 18 provinces to a nation-wide sample and update the data beyond 2009 to estimate the impact of the global financial crisis.

The results suggest that when policy makers design macroeconomic policies to smooth consumption volatility, they should consider heterogeneity in household consumption goods, regional disparity and intertemporal dynamics simultaneously. Well-managed volatility of Chinese household consumption can contribute to a stable economic growth in China and the world.

Well-managed volatility of Chinese household consumption can contribute to a stable economic growth in China and the world.

This paper fills this gap by using China’s UHS data to assess consumption volatility from the perspectives of heterogeneity in household consumption goods, cross-household differences and intertemporal dynamics. We make three contributions to the literature. The first contribution of this paper consists of demonstrating the contributions of heterogeneity in household consumption goods to consumption volatility. The second contribution consists of using the advanced variance decomposition method proposed by Crucini and Telmer (2012). This decomposition methodology allows the authors to examine whether household consumption volatility is due to cross-household differences or intertemporal dynamics. The third contribution is that this paper takes Chinese residents’ consumption fluctuations as the starting point to analyze the impact of consumption fluctuations on the future trend of China’s economy.

The purpose of this paper is to construct a frequency-domain framework to study the asymmetric spillover effects of international economic policy uncertainty on China’s stock market industry indexes.

This paper follows the time domain spillover model, asymmetric spillover model and frequency domain spillover model, which not only studies the degree of spillover in time domain but also studies the persistence of spillover effect in frequency domain.

It is found that China’s economic policy uncertainty plays a dominant role in the spillover effect on the stock market, while the global and US economic policy uncertainty is relatively weak. By decomposing realized volatility into quantified asymmetric risks of “good” volatility and “bad” volatility, it is concluded that economic policy uncertainty has a greater impact on stock downside risk than upside risk. For different time periods, the sensitivity of long-term and short-term spillover economic policy impact is different. Among them, asymmetric high-frequency spillover in the stock market is more easily observed, which provides certain reference significance for the stability of the financial market.

The originality aims at extending the traditional research paradigm of “time domain” to the research perspective of “frequency domain.” This study uses the more advanced models to analyze various factors from the static and dynamic levels, with a view to obtain reliable and robust research conclusions.

The purpose of this paper is to reveal the economic impact of policy reversals related to market liberalization reforms in China.

To perform the analysis, the authors hand-collect 59 financial market liberalization policy reversals from 1999 to 2017. These reversals are related to the liberalization of the stock market, bond market, derivatives market, forex market, lending market, and real estate market etc. The authors employ a stylized equilibrium interest rate model from Li et al. (2013) to deduce the impact of policy reversals on economic growth and the associated volatility after the announcement of each policy reversal.

First, the authors discover that about half of reversals are related to some tradeoff between the economic growth and the volatility associated with growth. Second, the authors also find that about a quarter of the reversals are detrimental to both the growth and the stability. These reversals, if known to policymakers, should be entirely avoided or corrected. Third, using a simple diagnostic test, the authors can identify detrimental reversals at the intra-day frequency by computing the change of the term spread and the volatility before and after the reversals.

The findings are useful for identifying effective policymaking in developing countries where mature democratic and rigorous policymaking processes are often lacking and formulating economic policies is challenging. The findings suggest that policy reversals serve China well by improving the quality of the policy made without posing destructive consequences to the existing economic infrastructure. This empirical evidence is important for a better understanding of the benefits of policy reversals on economic growth.

The empirical procedure provides a timely and objective evaluation of policy shifts, allowing for the general public to discern the rationale behind the policy decisions. Consequently, stakeholders’ trust and confidence in policymakers is enhanced so that the probability of the successful implementation of structural reforms may increase in these developing countries.

First, the results reveal some successful examples of Chinese policymaking in the path of liberalizing financial market. The authors find that the Chinese liberalization policy flip-flops have resulted in a more balanced growth on some occasions with reduced growth rate and volatility. Second, the proposed methodology provides an objective evaluation of policy shifts, allowing for the public to infer the general direction of the impact generated by policy shifts. Subsequently, stakeholders’ trust and confidence in policymakers can be enhanced and/or restored if the process of finding a successful path of structural reforms is unambiguous. Finally, the interest rate model also provides a timely method to evaluate the impact of policy shifts at an intra-day frequency, whereas most macroeconomic indicators are available at longer frequencies such as monthly or quarterly. The timeliness in understanding the economic consequences of policy reversals can be critical to prevent the destructive consequences of bad ones.