Co-movement in Stock Prices in Emerging Economies: The Case of the Caricom Region

The Grand Anse Declaration of 1989 recognised the need for financial integration within the emerging economies that comprise the CARICOM region, as a way of furthering the wider process of economic integration and, indeed, economic development in that region. Using co-movement as a measure of financial integration, this paper investigates the co-movement in stock prices among the Barbados, the Jamaica and the Trinidad and Tobago Stock Exchanges, the three major exchanges within the CARICOM region. It also examines how integrated these exchanges are with the New York Stock Exchange. The GARCH-Copula methodology and, to a lesser extent, estimated correlation coefficients, are used to attain this objective. There appears to be co-movement in stock prices and returns within the CARICOM stock markets and significant dependence structures between the returns of the three CARICOM stock markets. However, there is considerably less evidence of integration between the CARICOM markets and the New York Stock Exchange.     

Capital market integration in ASEAN: A non-stationary panel data analysis

Motivated by the establishment of ASEAN Economic Community (AEC) at the end of 2015, we examine saving-investment relationship in various subgroups of ASEAN to assess their capital market integration. The results from second generation panel unit-root and cointegration tests that account for cross-sectional dependence as well as estimates of long-run saving-retention rate provide some evidence of market integration in ASEAN. The analysis of short-run dynamics suggests that capital mobility in ASEAN during 1980–2014 appears similar to that in OECD countries during 1970–1999. More importantly, across different panel estimators and subgroups of membership, there is considerable heterogeneity among the member countries. The saving-investment association is very weak, thereby implying very high capital mobility, in more developed members such as Singapore, Malaysia, and Brunei; the association is very strong, implying very low capital mobility, for much less developed members such as Laos, Myanmar, and Cambodia. The results call for renewed effort to develop capital markets in less developed nations and integrate them with the rest of the membership in ASEAN. In this paper, we also address several major shortcomings of the original Feldstein-Horioka framework.     

A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.     

Environmental taxes with heterogeneous consumers: an application to energy consumption in France

This paper constructs a model with four groups of households who have preferences over labor supply, consumption of polluting (energy related) and non-polluting (non-energy) goods, and emissions. It quantifies the model for the French economy and computes its optimal tax equilibria under nine second-best tax regimes. We find that the redistributive role of environmental taxes requires the polluting goods to be taxed at a rate much below their marginal social damage. These goods may even require an outright subsidy if the society values equality ‘a lot’. Secondly, if environmental taxes that have an exclusively externality-correcting role, they benefit all types—although the gains are rather modest. The gains and losses become more substantial when environmental taxes have a redistributive role as well. Third, setting the environmental tax at its Pigouvian level, rather than its optimal externality-correcting-cum-redistributive level, benefits the high-income group at the expense of the low-income groups. Fourth, nonlinear taxation of polluting goods, and nonlinear commodity taxation in general, is a powerful redistributive mechanism. Fifth, introducing environmental taxes in the current French tax system, with its suboptimal income taxes, results in substantial welfare gains for the highest income group and a sizable loss for the least well-off persons.     

A Bayesian analysis of a variance decomposition for stock returns

We apply Bayesian methods to study a common vector autoregression (VAR)-based approach for decomposing the variance of excess stock returns into components reflecting news about future excess stock returns, future real interest rates, and future dividends. We develop a new prior elicitation strategy, which involves expressing beliefs about the components of the variance decomposition. Previous Bayesian work elicited priors from the difficult-to-interpret parameters of the VAR. With a commonly used data set, we find that the posterior standard deviations for the variance decomposition based on these previously used priors, including “non-informative” limiting cases, are much larger than classical standard errors based on asymptotic approximations. Therefore, the non-informative researcher remains relatively uninformed about the variance decomposition after observing the data. We show the large posterior standard deviations arise because the “non-informative” prior is implicitly very informative in a highly undesirable way. However, reasonably informative priors using our elicitation method allow for much more precise inference about components of the variance decomposition.     

The saving–investment correlation puzzle is still a puzzle

A number of simulation studies claim to have solved the Feldstein–Horioka puzzle by demonstrating that a high time-series correlation between saving and investment naturally arises from business cycle shocks. This paper uses panel data of saving and investment controlled for business cycle shocks to empirically test the significance of cyclical shocks — productivity, fiscal and the terms of trade shocks — in explaining a high saving–investment correlation. The estimation results reveal that conventional aggregate shocks only partially explain the high saving–investment correlation. Moreover, country differences in the size of the GNP and the non-traded sector do not significantly affect the saving–investment correlation. The saving–investment correlation puzzle remains a puzzle after all.     

蜜月游市场特征的相关与回归分析——针对北京常住居民蜜月游市场

在我国,蜜月游市场发展迅猛,潜力巨大,收益率颇高.特别值得注意的是,我们调研发现:高收入者与非高收入者共享蜜月游这一高端旅游产品.为此我们进行了相关的定量分析,以进一步研究其发展脉络,揭示其变动趋势,为政府主管部门及相关旅游企业提供决策依据.     

A dynamic approach to the analysis of strategic alliances

The increasing trend in strategic alliance formation between major firms around the world, has prompted researchers from various disciplines to look at this phenomenon in great detail. In this paper, we review alternate approaches in the literature in this area. We then propose a non-linear dynamic approach to study the formation of competitive strategic alliances and contrast it with the traditional game-theoretic approach. The pros and cons of these two approaches are discussed with reference to a competitive alliance scenario. Dynamic models have significant managerial implications as they enable us to investigate ‘if-then’ type scenarios and project the impact of different strategies.     

非线性时序模型LM检验的两类临界值检验统计功效比较

本文基于模拟方法比较了不同非线性时序模型的LM检验的功效和规模，同时也考虑一般化线性检验BDS检验参与比较，目的在于探讨蒙特一卡洛渐近法检验与自举法（bootstrap）检验的两类临界值的统计功效何者更为有效。通过实证与对比分析，结果表明，当样本小于200或自回归系数接近单位根，或者线性性检验是ARCHT或BDS时，就可以考虑应用自举法临界值而非渐近临界值。而且还发现，BDS检验仅在一般性上优于LM检验。     

货币政策和银行风险承担：一种非线性关系

宽松的货币政策会通过估值、收入和现金流机制,追逐收益机制以及中央银行沟通和反应机制等渠道增加银行风险承担,通过风险转移机制降低银行风险承担,从而导致货币政策与银行风险承担之间可能存在复杂的非线性关系。本文使用面板阈值模型,基于我国银行业数据研究了货币政策对银行风险承担的影响,发现我国货币政策对银行风险承担的影响存在门限效应,即货币政策对银行风险承担的影响取决于货币政策基准利率偏离泰勒规则利率的程度。当这种偏离小于门限值时,宽松货币政策会增加银行风险承担;当这种偏离大于门限值时,宽松货币政策会降低银行风险承担。本文研究对更好地理解我国货币政策对银行风险承担及金融稳定的影响有一定参考意义。