Spatial spillover effects and risk contagion around G20 stock markets based on volatility network

Employing the spatial econometric model as well as the complex network theory, this study investigates the spatial spillovers of volatility among G20 stock markets and explores the influential factors of financial risk. To achieve this objective, we use GARCH-BEKK model to construct the volatility network of G20 stock markets, and calculate the Bonacich centrality to capture the most active and influential nodes. Finally, we innovatively use the volatility network matrix as spatial weight matrix and establish spatial Durbin model to measure the direct and spatial spillover effects. We highlight several key observations: there are significant spatial spillover effects in global stock markets; volatility spillover network exists aggregation effects, hierarchical structure and dynamic evolution features; the risk contagion capability of traditional financial power countries falls, while that of “financial small countries” rises; stock market volatility, government debt and inflation are positively correlated with systemic risk, while current account and macroeconomic performance are negatively correlated; the indirect spillover effects of all explanatory variables on systemic risk are greater than the direct spillover effects.     

The effect of corruption on environmental performance: Does spatial dependence play a role?

Different from previous studies that mainly focused on conventional estimation techniques, this paper explores the role of spatial dependence in the effect of corruption on environmental performance by using a spatial panel data model. Our results show that the direct effects, indirect effects and total effects of corruption on environmental performance are negative and highly significant, implying that corruption is detrimental to environmental performance. More importantly, we find that there is a significant spatial spillover effect between corruption and environmental performance, namely being surrounded by highly corrupt countries has a negative impact on the local country’s environmental performance. Our results also suggest that a larger population density will worsen the environment, while urbanization has a significant positive impact. These results provide some important implications for policymakers seeking to improve their environmental performance.     

Economic policy uncertainty,oil price volatility and stock market returns: Evidence from a nonlinear model

This paper investigates the nonlinear relationship between economic policy uncertainty, oil price volatility and stock market returns for 25 countries by applying the panel smooth transition regression model. We find that oil price volatility has a negative effect on stock returns, and this effect increases with economic policy uncertainty. Furthermore, there is pronounced heterogeneity in responses. First, oil-exporting countries whose economies depend more on oil prices respond more strongly to oil price volatility than oil-importing countries. Second, stock returns of developing countries are more susceptible to oil price volatility than that of developed countries. Third, crisis plays a crucial role in the relation between oil price volatility and stock returns.     

Spatial Growth Regressions: Model Specification,Estimation and Interpretation

Abstract

We attempt to clarify a number of points regarding use of spatial regression models for regional growth analysis. We show that as in the case of non-spatial growth regressions, the effect of initial regional income levels wears off over time. Unlike the non-spatial case, long-run regional income levels depend on: own region as well as neighbouring region characteristics, the spatial connectivity structure of the regions, and the strength of spatial dependence. Given this, the search for regional characteristics that exert important influences on income levels or growth rates should take place using spatial econometric methods that account for spatial dependence as well as own and neighbouring region characteristics, the type of spatial regression model specification, and weight matrix. The framework adopted here illustrates a unified approach for dealing with these issues.     

Do constraints created by economic growth targets benefit sustainable development? Evidence from China

An economic growth target is a declaration by policy authorities of commitment to that target and the corresponding allocation of resources. The constraints created by economic growth target are an important economic management method in China, which has helped China's economy to achieve remarkable achievements. However, it has also brought about serious environmental problems, threatening China's sustainable development. Using the data about economic growth targets in the work reports of 30 Chinese provincial governments from 2006 to 2017, this paper constructs several spatial measurement methods, such as the spatial Durbin model, to examine the constraints created by economic growth target's impacts on air pollution. The main conclusions are as follows. First, a significant “U-shaped” relationship exists between the constraints created by economic growth targets and air pollution. Second, the spatial Durbin model analysis revealed that PM_2.5 across China's provinces display significant positive spatial spillover effects and spatial agglomeration characteristics. Third, the direct, indirect, and total effects of constraints created by economic growth targets on air pollution are all statistically significant and depict a “U shape.” Finally, the constraints created by economic growth targets have an apparent threshold effect on air pollution, and the inhibiting effects increase with human capital and industrial restructuring. However, with the increase in foreign direct investments, constraints created by economic growth targets may increase air pollution. The conclusions of this paper are of great significance for improving the management of local government economic growth targets and sustainable development.     

Time-varying asymmetric volatility spillover between global markets and China’s A,B and H-shares using EGARCH and DCC-EGARCH models

This paper investigates the volatility spillover and dynamic conditional correlation between three types of China’s shares including A, B and H-shares with 12 major emerging and developed markets from 2002 to 2017 using EGARCH and multivariate DCC-EGARCH models. Both models found that Chinese equities are more related with their neighbouring countries such as Singapore, Japan, Australia and ASEAN-5 than with US, Germany and UK. The EGARCH model, with an auxiliary term added to capture the volatility spillover, found no volatility spillover between A-share markets and other advanced and emerging markets during the GFC and extended-crisis periods while this behaviour is not observed for B-share and H-share markets. However, the multivariate DCC model found strong evidence of contagion effect in both return correlations and volatility spillover for all China’s markets. In addition, both models found increased regional and global integration in A-share and B-share markets but not the H-share market. Finally, the results from both models provide clear evidence of distinct behaviours associated with return and volatility spillover in these three share types, suggesting foreign investors should consider the heterogeneity in volatility spillover and return correlations of these Chinese share types when forming investment strategies.     

The effects of corruption on growth performance of the mena countries

This article aims at testing the effects of institutional characteristics on growth in countries of the Middle East and North Africa (MENA) region. For this purpose we consider conditional convergence in terms of initial conditions, macroeconomic performance, trade openness, government size, natural resource abundance and institutional and political structures for a sample of 90 countries over the period 1960–2000. We use regional indicators and MENA-specific variables in order to test for the effects of each variable on the growth performance of the MENA economies. We highlight the direct and indirect impacts of both corruption and bureaucratic quality on the MENA growth compared to the other regions of the world.     

均衡性转移支付、税制结构与共同富裕

新发展阶段，要加快实现共同富裕，就需要重视均衡性转移支付和税制结构的调节作用。基于极值熵值法测度的共同富裕综合指数构建面板Tobit模型、空间滞后模型和门槛模型，从均衡性转移支付和税制结构的不同视角，探究上述因素对共同富裕的多重影响，结果发现：从基准回归和空间滞后模型看，共同富裕存在显著的空间溢出效应，均衡性转移支付对共同富裕的直接和空间促进效应尚未体现，以直接税和间接税为主体的税制结构的直接和空间效应显著为正，且均衡性转移支付能够调节税制结构的直接和空间溢出效应。进一步分析发现，均衡性转移支付与共同富裕之间存在由“门槛效应”引起的非线性关系，合理的均衡性转移支付显著促进共同富裕，且随着均衡性转移支付的提升，其促进效应不断减弱。动态空间滞后模型显示，共同富裕滞后一期的直接和空间溢出效应均显著为正。以上研究结论对中国政府优化财税体制、推进共同富裕具有重要启示。     

A discrete-time model for daily S & P500 returns and realized variations: Jumps and leverage effects

We develop an empirically highly accurate discrete-time daily stochastic volatility model that explicitly distinguishes between the jump and continuous-time components of price movements using nonparametric realized variation and Bipower variation measures constructed from high-frequency intraday data. The model setup allows us to directly assess the structural inter-dependencies among the shocks to returns and the two different volatility components. The model estimates suggest that the leverage effect, or asymmetry between returns and volatility, works primarily through the continuous volatility component. The excellent fit of the model makes it an ideal candidate for an easy-to-implement auxiliary model in the context of indirect estimation of empirically more realistic continuous-time jump diffusion and Lévy-driven stochastic volatility models, effectively incorporating the interdaily dependencies inherent in the high-frequency intraday data.     

Incorporating Transportation Network Structure in Spatial Econometric Models of Commodity Flows

Abstract

We use a spatial econometric extension of the traditional regression-based gravity model to model commodity flows, focusing on a formal methodology for incorporating information regarding the highway network into the spatial connectivity structure of the spatial autoregressive econometric model. We show that our simple approach to incorporating this information in the model produces improved model fit and higher likelihood function values. Empirical estimates of the relative importance of the different types of origin–destination connectivity between regions indicates that the strongest spatial autoregressive effects arise when both origin and destination regions have neighbouring regions located on the highway network.     

Oil price shocks and economic growth: The volatility link

This paper shows that oil shocks impact economic growth primarily through the conditional variance of growth. Our comparison of models focuses on density forecasts. Over a range of dynamic models, oil shock measures and data, we find a robust link between oil shocks and the volatility of economic growth. We then develop a new measure of oil shocks and show that it is superior to existing measures; it indicates that the conditional variance of growth increases in response to an indicator of the local maximum oil price exceedance. The empirical results uncover a large pronounced asymmetric response of the growth volatility to oil price changes. The uncertainty about future growth is considerably lower than with a benchmark AR(1) model when no oil shocks are present.     

Factor pricing of cryptocurrencies

In this paper, we study the cryptocurrency pricing factors. We review the literatures which state that the cryptocurrency market is weakly efficient. We use the Fama–MacBeth method to investigate the pricing factors. The classical equity-based risk factors including size, momentum, and value to growth from the Fama–French three factor model are studied. We use crypto-unique coin-to-token as a proxy for value-to-growth. For volatility risk factor category, we investigate realized volatility, skewness and jump. We also investigate liquidity factors including bid–ask, volume growth and Roll’s measure. The macro factors are found not to be an explanatory factor. The attention factor works sometimes. The factor model constructed by the significant factors explain most of the excess return of cryptocurrencies.     

Some empirical evidence on the real effects of nominal volatility

It has been argued that volatility in nominal macroeconomic aggregates has had a negative effect on real output, in particular that such volatility contributed to slow output growth in the early 1980s. This paper reexamines the effects of volatility in nominal macroeconomic aggregates in the context of a modern simultaneous equation framework where the volatility of, nominal macroeconomic variables is modeled as the conditional variance of two variables of interest: the federal funds rate and inflation. The empirical framework is the recently developed multivariate GARCH-in-mean vector autoregressive model. We confirm evidence that inflation volatility and tight monetary policy have directly affected output growth, but find that volatility in the federal funds rate has not.     

Search Engine Optimization: What Drives Organic Traffic to Retail Sites?

The lion's share of retail traffic through search engines originates from organic (natural) rather than sponsored (paid) links. We use a dataset constructed from over 12,000 search terms and 2 million users to identify drivers of the organic clicks that the top 759 retailers received from search engines in August 2012. Our results are potentially important for search engine optimization (SEO). We find that a retailer's investments in factors such as the quality and brand awareness of its site increases organic clicks through both a direct and an indirect effect. The direct effect stems purely from consumer behavior: The higher the quality of an online retailer, the greater the number of consumers who click its link rather than a competitor in the list of organic results. The indirect effect stems from our finding that search engines tend to place higher quality sites in better positions, which results in additional clicks because consumers tend to click links in more favorable positions. We also find that consumers who are older, wealthier, conduct searches from work, use fewer words, or include a brand name product in their search are more likely to click a retailer's organic link following a product search. Finally, the quality of a retailer's site appears to be especially important in attracting organic traffic from individuals with higher incomes. The beneficial direct and indirect effects of an online retailer's brand equity on organic clicks, coupled with the spillover effects on traffic through other online and traditional channels, leads us to conclude that investments in the quality and brand awareness of a site should be included as part of an SEO strategy.     

Openness and inflation volatility: Panel data evidence

Trade openness can affect inflation volatility via the incentives faced by policy-makers or the structure of production and consumption, but the sign of this effect, as predicted from economic theory, is ambiguous. This paper provides evidence for a negative effect of openness on inflation volatility using a dynamic panel model that controls for the endogeneity of openness and the effects of both average inflation and the exchange rate regime. Our results offer one explanation for the recent decline in inflation volatility observed in many countries. The relationship is shown to be strongest amongst developing and emerging market economies, and we argue that the mechanisms linking openness and inflation volatility are likely to be strongest amongst this group of countries.     

Poverty volatility and poverty in developing countries

This article examines the effect of poverty volatility on poverty in developing countries. Poverty volatility refers to the amplitude of the change in poverty rates over a given period of time. Variations in poverty rates can potentially arise from countries' vulnerability to a variety of shocks that induce greater macroeconomic volatility, including economic growth volatility. The empirical analysis shows that poverty volatility consistently induces a rise in poverty rates, and this positive poverty effect of poverty volatility increases as the degree of poverty volatility rises. Policies that help reduce poverty volatility (including by dampening economic growth volatility) would contribute to poverty reduction.     

Do Neighbours Influence Value‐Added‐Tax Introduction? A Spatial Duration Analysis

The spatial survival models typically impose frailties, which characterize unobserved heterogeneity, to be spatially correlated. However, the spatial effect may not only exist in the unobserved errors, but it can also be present in the baseline hazards and the dependent variables. A new spatial survival model with these three possible spatial correlation structures is explored and used to investigate the implementation of value‐added tax (VAT) in 99 countries over the period 1970–2009. Estimation is performed by a Bayesian approach through the Markov chain Monte Carlo method. The estimation results suggest the presence of a significant spatial correlation among the VAT introductions of neighbouring countries.     

Impact of Islamic banking development and major macroeconomic variables on economic growth for Islamic countries: Evidence from panel smooth transition models

This study examines the nonlinear relationship between Islamic banking development, major macroeconomic variables and economic growth in Islamic countries. Using the panel smooth transition model, the results show a positive nonlinear relationship between Islamic banking development and economic growth. Moreover, the relationship between the macroeconomic variables and economic growth is asymmetric and regime-dependent. Further, by using the dynamic panel quantile model, we show that for many cases the Islamic banking variables lead economic growth across the quantiles. More specifically, foreign direct investment, oil production and inflation have a positive impact on economic growth during the normal financial development state, while government consumption, one-lag economic growth, terms of trade and financial development have a negative impact on economic growth for this state. The human capital index, education and the rule of law have an insignificant impact, regardless of the prevailing regime. The results for the separated oil-importing and oil-exporting economies are generally consistent with the combined sample regarding the Islamic banking development variables. As for the macro variables, they have a positive and significant (insignificant) effect on EG for the oil-importing (oil-exporting) economies for almost all models.     

Housing investment: What makes it so volatile? Theory and evidence from OECD countries

This paper explains how mortgage market liberalization can introduce greater volatility in the housing market, which is a stylized fact documented from OECD countries, with a DSGE model where households face a credit constraint and housing is used as collateral. The housing collateral constraint creates a link between the housing market and borrowing capacity, a link that amplifies the response of housing demand to technology shocks and strengthens in economies with more liberalized mortgage markets.     

The effect of banking market structure on the volatility of growth of manufacturing sectors in developing countries

I explore the effect of banking concentration and banking competition on the volatility of the growth of value added of manufacturing sectors in the developing countries. In this paper, I bring together two strands of literature, one that discusses the effect of financial intermediation on volatility of growth and another one that discusses the effect of banking concentration and competition on credit access. Following the industrial organization literature, I look at the effect of banking competition and banking concentration on the volatility of manufacturing sectors separately. I find that banking concentration has a dampening effect on the volatility of growth of the industries. On the other hand, I find that as banking competition increases, the volatility of the growth of industries increases, also.