Equity market and money supply spillovers and economic growth in BRICS economies: A global vector autoregressive approach

Previous studies report that private credit as a proxy of financial development contributes to economic growth in BRICS economies. This paper employs three additional measures of financial development, namely equity market, money supply and market capitalization, and further investigates cross-country evidence on the impact of equity market and money supply spillovers on economic growth in BRICS economies. Utilizing a Global Vector Autoregressive (GVAR) framework and quarterly data from 1989Q1 and to 2012Q4 from BRICS economies, we find that equity market and money supply variables do not predict the contributions of financial development in each BRICS member in boosting economic growth in the other member countries. However, market capitalization significantly influences economic growth. These results suggest that, besides private credit, market capitalization is another key channel of promoting growth in individual economies and the region. Policy implications of the findings are discussed.     

Time-frequency effect of crude oil and exchange rates on stock markets in BRICS countries: Evidence from wavelet quantile regression analysis

This study examines the effects of oil prices and exchange rates on stock market returns in BRICS countries (Brazil, Russia, China, India and South Africa) from a time–frequency perspective over the period 2009–2020. We use wavelet decomposition series to develop a threshold rolling window quantile regression to detect time–frequency effects at various scales. The empirical results are as follows. First, our findings confirm that the effects of both crude oil prices and exchange rates on BRICS stock returns are asymmetric. Positive shocks of crude oil have a greater impact on a bull market, whereas negative shocks have a greater impact on a bear market. Second, there is a short-term enhancement effect of crude oil and exchange rate on BRICS stock markets. In addition, volatility in the macro financial environment also exacerbates the impacts of oil prices and exchange rates on the stock market, and these fluctuations are heterogeneous. Overall, these findings provide useful insights for international investors and policy makers.     

Dependence structures between Chinese stock markets and the international financial market: Evidence from a wavelet-based quantile regression approach

In this study, we investigate the dependence structures between six Chinese stock markets and the international financial market including possible safe haven assets and global economic factors under different market conditions and investment horizons. The research is conducted by combining a quantile regression approach with a wavelet decomposition analysis. Although we find little or insignificant dependence under short investment horizons, we detect the strong asymmetric dependence of oil prices and the US dollar index on the six Chinese stock markets in the medium and long terms. Moreover, not only is crude oil not a safe haven, it may damage Chinese stock markets as it increases over the long term, even in bull markets. Meanwhile, appreciation of the US dollar (depreciation of RMB) damages (boosts) Chinese stock markets during bull (bear) market conditions under long investment horizons. Moreover, we find that VIX (volatility index)-related derivatives may serve as good risk management tools under any market condition, while gold is a safe haven asset only during crisis periods.     

The impact of COVID-19 on the G7 stock markets: A time-frequency analysis

We examine the co-movement of the G7 stock returns with the numbers of confirmed COVID-19 cases and causalities based on daily data from December 31, 2019 to November 13, 2020. We employ the wavelet coherence approach to measure the impact of the numbers of confirmed cases and deaths on the G7 stock markets. Our findings reveal that both the number of confirmed COVID-19 cases and the number of deaths exhibit strong coherence with the G7 equity markets, although we find heterogeneous results for the Canadian and Japanese equity markets, in which the numbers of COVID-19 cases and the deaths exhibit only a weak relationship. This evidence is more pronounced in the long-term horizon rather than the short-term horizon. Moreover, the lead-lag relationship entails a mix of lead-lag relations across different countries. We present the implications of these findings for both policymakers and the international investment community.     

Value at risk and return in Chinese and the US stock markets: Double long memory and fractional cointegration

Given that the United States is an engine of global stock market while China is the largest emerging market with a cornucopia of anomalies in particular, it is vital to investigate the risk-return relationship in the two markets. This paper brings new insights not only into risk-return tradeoff, but also to the leverage effect, with the application of the fractionally co-integrated vector auto-regression (FCVAR) model capturing the fractional cointegrated relationship and long memory property. Results show that China stock markets own the property of double long memory but the US markets don’t. Most of all, in the US market, a positive risk-return tradeoff exists for the whole sample while after the crisis, even we find the negative relation, it’s not a volatility feedback effect but low risk and high returns. However, there is only a volatility feedback effect in China stock markets. Besides, there is a leverage effect in the US market, while Chinese market exhibits a reverse one, another anomaly, indicating significant difference in the two markets again.     

Risk spillover analysis across worldwide ESG stock markets: New evidence from the frequency-domain

With the increasing global awareness of green environmental protection, the international environmental, social, and governance (ESG) stock markets are developing rapidly together with rising risk linkages across worldwide markets. Therefore, this study explores the risk spillover characteristics of international ESG stock markets in the time and frequency domains and constructs a risk linkage network to further explore the risk contagion mechanism. The results show that in most cases, the developed North American market is the core of outward risk spillover in international ESG stock markets. The entire system presents a small-world structure, and the internal regions display different risk spillover characteristics. Moreover, international ESG markets generally have strong time–frequency spillover and medium-frequency (a month to a year) spillover. In contrast, the high- (a day to a month) and low-frequency (more than one year) spillovers are located at relatively low levels, but they will rise significantly under sudden financial events. The empirical results expand the ESG stock market's theoretical framework and provide a reference for investors and market regulators to reduce the investment risk of ESG.     

The heterogeneous impact of taxation on economic development: New insights from a panel cointegration approach

In this paper, we study the role of taxation on long-run income performance. In the theoretical part of the study, we develop a stylized model based on Barro (1990), in which income taxation has two contradictory roles in the standard Solow (1956) setup: on the one hand, taxation appropriates resources that would otherwise be used for physical capital accumulation, and on the other, it is the source of government spending, which is used to support private production. In the empirical part of the study, the impact of consumption tax, personal income tax, corporate profit tax and property tax on income is estimated using the common correlated effects (CCE) panel cointegration approach, which allows for cross-sectional dependencies and provides both panel- and country-specific results. The panel findings for 30 OECD countries for the period of 1995–2016 indicate that only consumption tax has a statistically significant negative effect on long-run income. However, because the type and sign of the tax coefficients are heterogeneous for the country-specific results, we conclude that taxation has heterogeneous effects on income.     

Risk spillover between the US and the remaining G7 stock markets using time-varying copulas with Markov switching: Evidence from over a century of data

This paper analyses the risk spillover effect between the US stock market and the remaining G7 stock markets by measuring the conditional Value-at-Risk (CoVaR) using time-varying copula models with Markov switching and data that covers more than 100 years. The main results suggest that the dependence structure varies with time and has distinct high and low dependence regimes. Our findings verify the existence of risk spillover between the US stock market and the remaining G7 stock markets. Furthermore, the results imply the following: 1) abnormal spikes of dynamic CoVaR were induced by well-known historical economic shocks; 2) The value of upside risk spillover is significantly larger than the downside risk spillover and 3) The magnitudes of risk spillover from the remaining G7 countries to the US are significantly larger than that from the US to these countries.     

Forecasting the Chinese stock market volatility with international market volatilities: The role of regime switching

The purpose of this paper is to investigate the role of regime switching in the prediction of the Chinese stock market volatility with international market volatilities. Our work is based on the heterogeneous autoregressive (HAR) model and we further extend this simple benchmark model by incorporating an individual volatility measure from 27 international stock markets. The in-sample estimation results show that the transition probabilities are significant and the high volatility regime exhibits substantially higher volatility level than the low volatility regime. The out-of-sample forecasting results based on the Diebold-Mariano (DM) test suggest that the regime switching models consistently outperform their original counterparts with respect to not only the HAR and its extended models but also the five used combination approaches. In addition to point accuracy, the regime switching models also exhibit substantially higher directional accuracy. Furthermore, compared to time-varying parameter, Markov regime switching is found to be a more efficient way to process the volatility information in the changing world. Our results are also robust to alternative evaluation methods, various loss functions, alternative volatility estimators, various sample periods, and various settings of Markov regime switching. Finally, we provide an extension of forecasting aggregate market volatility on monthly frequency and observe mixed results.     

Predictability of bull and bear markets: A new look at forecasting stock market regimes (and returns) in the US

The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines dimensionality reduction, regime-switching models, and forecast combination to predict excess returns on the S&P 500. First, we aggregate the weekly information of 146 popular macroeconomic and financial variables using different principal component analysis techniques. Second, we estimate Markov-switching models with time-varying transition probabilities using the principal components as predictors. Third, we pool the models in forecast clusters to hedge against model risk and to evaluate the usefulness of different specifications. Our weekly forecasts respond to regime changes in a timely manner to participate in recoveries or to prevent losses. This is also reflected in an improvement of risk-adjusted performance measures as compared to several benchmarks. However, when considering stock market returns, our forecasts do not outperform common benchmarks. Nevertheless, they do add statistical and, in particular, economic value during recessions or in declining markets.     

The performance of the global bottom-up approach in the M5 accuracy competition: A robustness check

The M5 accuracy competition has presented a large-scale hierarchical forecasting problem in a realistic grocery retail setting in order to evaluate an extended range of forecasting methods, particularly those adopting machine learning. The top ranking solutions adopted a global bottom-up approach, by which is meant using global forecasting methods to generate bottom level forecasts in the hierarchy and then using a bottom-up strategy to obtain coherent forecasts for aggregate levels. However, whether the observed superior performance of the global bottom-up approach is robust over various test periods or only an accidental result, is an important question for retail forecasting researchers and practitioners. We conduct experiments to explore the robustness of the global bottom-up approach, and make comments on the efforts made by the top-ranking teams to improve the core approach. We find that the top-ranking global bottom-up approaches lack robustness across time periods in the M5 data. This inconsistent performance makes the M5 final rankings somewhat of a lottery. In future forecasting competitions, we suggest the use of multiple rolling test sets to evaluate the forecasting performance in order to reward robustly performing forecasting methods, a much needed characteristic in any application.     

Statistics of extreme events in risk management: The impact of the subprime and global financial crisis on the German stock market

Given the growing need for managing financial risk and the recent global crisis, risk prediction is a crucial issue in banking and finance. In this paper, we show how recent advances in the statistical analysis of extreme events can provide solid methodological fundamentals for modeling extreme events. Our approach uses self-exciting marked point processes for estimating the tail of loss distributions. The main result is that the time between extreme events plays an important role in the statistical analysis of these events and could therefore be useful to forecast the size and intensity of future extreme events in financial markets. We illustrate this point by measuring the impact of the subprime and global financial crisis on the German stock market in extenso, and briefly as a benchmark in the US stock market. With the help of our fitted models, we backtest the Value at Risk at various quantiles to assess the likeliness of different extreme movements on the DAX, S&P 500 and Nasdaq stock market indices during the crisis. The results show that the proposed models provide accurate risk measures according to the Basel Committee and make better use of the available information.     

A model of vertical integration and investment in generation capacity in electricity markets: The case of the bidding game

The aim of this work is to assess the impact of (partial) vertical integration between generators and retailers on generation capacity choice and its subsequent welfare consequences. We present a framework in which final demand is perfectly inelastic and stochastic. Nevertheless, wholesale demand is elastic because of the existence of outside opportunities (mainly international transmission capacity). The model is a three-stage game. Neither transmission nor retail costs are taken into account.

In the first stage of the game, generators choose capacity only knowing distribution of demand and thus maximizing their expected profit. The second stage of the game represents the competition for market share between retailers in a market where consumers have switching costs. The former face unknown demand and maximize their utility based on two factors: the expected profit and a risk element. Finally, generators submit bid functions to the system operator given known demand and maximizing their profit during the last stage of the game. Retailers and generators interact in the wholesale market, which is cleared by the system operator whose function is to match supply (represented by the bids of the generators) and demand through a system of single price auctions. The wholesale market is the only means to buy and sell energy; there are no bilateral contracts between firms, except if they are vertically integrated.

We compare fully disintegrated and partially vertically integrated structures using a comparative statics approach. In this paper, the analysis will focus on the last stage of the game: the bidding game. We find that partial vertical integration between generators and retailers tends to lower wholesale prices but not unambiguously. Depending on which firm (vertically integrated or disintegrated generator) has installed the higher capacity and depending on level of demand, prices can stay unchanged or even rise.     

The intermediating role of the Chinese renminbi in Asian currency markets: Evidence from partial wavelet coherence

This study presents an innovative perspective on the dynamic interdependence of Asian currency markets, focusing particularly on the intermediating role of the Chinese renminbi (CNY) in introducing the co-movement between non-major Asian currencies. In this regard, the multivariate factor stochastic volatility (SV) model is estimated and continuous wavelet analysis is applied. The novelty of this study is that it employs wavelet coherence analysis to identify the localized time-varying co-movement of Asian currencies and their lead–lag relations specific to a particular scale and thus investment horizon. Furthermore, the CNY’s intermediating role in inducing co-movement between Asian currencies is examined by applying dynamic partial correlation analysis based on the multivariate factor SV model and partial wavelet coherence analysis, which evaluate the degree of the co-movement between Asian currencies after controlling for the common influence of the CNY. The results clearly indicate the prominent role of the CNY in facilitating region-wide connectedness of Asian currency markets.     

The role of credit supply shocks in pacific alliance countries: A TVP-VAR-SV approach

This paper analyzes the effect of loan supply shocks on the real economic activity of Pacific Alliance countries using a Time-Varying Parameter VAR with Stochastic Volatility (TVP-VAR-SV) model which is identified by sign restrictions. Two main results arise from the analysis. First, loan supply shocks have an important impact on real economic activity in all Pacific Alliance countries: about 1% in Colombia, Mexico, and Peru, and about 0.5% in Chile. Thus, its contribution to business cycle fluctuations is similar to that of aggregate supply shocks and aggregate demand shocks in both stability and slowdown periods. Second, the power of loan supply shocks to affect economic activity do not remain constant over the time and its evolution across periods is heterogeneous among all Pacific Alliance countries. The sensitivity analysis indicates that the results of the model are robust to different priors specifications and to multiple sets of sign restrictions.     

A purposeful approach for implementing preventive measures among European teaching professionals: bullying,deteriorated organizational factors and the mediating role of job dissatisfaction in poor health perception

Abstract

This research aims at examining how workplace bullying, a collection of predominant organizational factors and job dissatisfaction may both directly and indirectly influence the emergence of negative health perception among teaching professionals in occupational settings. The method utilized for testing the research hypotheses is based on Partial Least Squares Structural Equation Modeling (PLS-SEM), which enables the simultaneous assessment of construct measurement and the estimation of hypothesized relationships. A sample population of 2328 European educators has been employed to reach research objectives. Results suggest that negative health perception escalates when there is a direct conditioned correlation between this factor and either bullying or certain working conditions, while indirect effects are unveiled when dissatisfaction is added to the research framework as mediating construct. From a theoretical perspective, this work contributes to human resource management research on the subject of detection and prevention of those underlying organizational constituents that might potentially undermine occupational health. From a utilitarian perspective, the findings of this research encapsulate promising implications not only for teaching professionals but also for educational institutions that pursue the continual improvement of health and performance in their educators through human resource management.     

Estimating the effects of democratization in African countries: A simultaneous equations approach

This paper analyzes impacts of democratization in Africa, including effects of improved, property rights on economic growth and of greater political participation on civil violence. Democracy is endogenous to economic growth and other outcomes, which hampers most, empirical analysis. This paper uses a minimum distance simultaneous equations estimation to, account for all endogenous variables while including time and country fixed effects. The method yields a test of fit of the model, which is strong. Results indicate a positive significant effect of property rights institutions on economic growth in the presence of time and country fixed effects. Estimates also show a negative significant effect of political participation on civil violence and, strong effects of aid per capita on both economic growth and civil violence.     

Research on the time-varying effects among green finance markets in China: A fresh evidence from multi-frequency scale perspective

Green finance is an essential instrument for achieving sustainable development. Objectively addressing correlations among different green finance markets is conducive to the risk management of investors and regulators. This paper presents evidence on the time-varying correlation effects and causality among the green bond market, green stock market, carbon market, and clean energy market in China at multi-frequency scales by combining the methods of Ensemble Empirical Mode Decomposition Method (EEMD), Dynamic Conditional Correlation (DCC) GARCH model, Time-Varying Parameter Vector Autoregression with Stochastic Volatility Model (TVP-VAR-SV), and Time-varying Causality Test. In general, the significant negative time-varying correlations among most green finance markets indicate a prominent benefit of risk hedging and portfolio diversification among green financial assets. In specific, for different time points and lag periods, the green finance market shock has obvious time-varying, positive and negative alternating effects in the short-term scales, while its time delay and persistence are more pronounced in the medium-term and long-term scales. Interestingly, a positive event shock will generate positive connectivity among most green finance markets, whereas a negative event including the China/U.S. trade friction and the COVID-19 pandemic may exacerbate the reverse linkage among green finance markets. Furthermore, the unidirectional causality of “green bond market - carbon market - green stock and clean energy markets” was established during 2018–2019.     

A look into the factor model black box: Publication lags and the role of hard and soft data in forecasting GDP

We derive forecast weights and uncertainty measures for assessing the roles of individual series in a dynamic factor model (DFM) for forecasting the euro area GDP from monthly indicators. The use of the Kalman smoother allows us to deal with publication lags when calculating the above measures. We find that surveys and financial data contain important information for the GDP forecasts beyond the monthly real activity measures. However, this is discovered only if their more timely publication is taken into account properly. Differences in publication lags play a very important role and should be considered in forecast evaluation.     

探讨餐饮业跨国巨头进入我国二线城市的机遇与挑战——基于星巴克公司的个案研究

在全球金融危机蔓延的当下,以星巴克为代表的餐饮业跨国巨头纷纷选择转战二线城市。我国二线城市潜在的强大购买力是吸引外商的最重要的砝码,但是高速的近乎疯狂的扩张以及二线城市本身固有的中国式的特点,都给跨国公司的成功经营带来了巨大的挑战和威胁。笔者将以星巴克扩张为例,由浅入深,循序渐进,进行扩张过程中的利弊得失分析,并提出行之有效的可行性建设意见。