科技服务业产出测算：指标确立、数据收集与未来预测

科技服务业产出测算是对科技服务业产出数据的统计与分析，加强科技服务业产出数据的规范统计和应用分析可为我国政府调整产业政策提供重要数据支撑。以科技服务业产出测算为研究对象，结合学者观点、国家标准及各级政府相关产业政策，提出将分支产业作为初始指标的横向统计思路，构建科技服务业产出测算指标体系。在数据收集方面，强调要做好“收”与“填”两个基本工作；在指标确立和数据收集基础上，进一步提出未来预测的两种方法，以此作为科技服务业产出数据预测的初步探索；提出应从统一数据统计标准、完善数据调查与公开制度、加强数据资源开发3个方面建立健全我国科技服务业产出数据测量与管理体制机制。     

Macroeconomic consequences of state fragility in sub‐Saharan Africa

Are poor macroeconomic outcomes primarily the result of economic policies, or of deeper underlying state fragility problems in sub‐Saharan Africa? We attempt to answer this question by using carefully specified dynamic panel regression techniques to show how state fragility conditions help to explain the differences in the macroeconomic performance of sub‐Saharan African economies, and to identify the most plausible mechanisms of transmission. We find that countries with greater fragility suffer higher macroeconomic volatility and crisis; they also experience weaker growth. When we disaggregate state fragility into its various components, we find that it is the security and social components that have the strongest causal impact on macroeconomic outcomes, while the political component is, at best, weak. Therefore, we conclude that it is state fragility conditions, and not necessarily macroeconomic policies, that are of first‐order importance in explaining the differences in macroeconomic performance for African countries. The knock‐on effects are mostly mediated through the fiscal channel, the aid channel, and the finance channel. Accordingly, we recommend that interventions in fragile states should best focus on exploiting the potential for using fiscal policy, aid, and finance as instruments to improve macroeconomic outcomes in sub‐Saharan Africa.     

Leverage effect on stochastic volatility for option pricing in Hong Kong: A simulation and empirical study

This paper explores the importance of incorporating the financial leverage effect in the stochastic volatility models when pricing options. For the illustrative purpose, we first conduct the simulation experiment by using the Markov Chain Monte Carlo (MCMC) sampling method. We then make an empirical analysis by applying the volatility models to the real return data of the Hang Seng index during the period from January 1, 2013 to December 31, 2017. Our results highlight the accuracy of the stochastic volatility models with leverage in option pricing when leverage is high. In addition, the leverage effect becomes more significant as the maturity of options increases. Moreover, leverage affects the pricing of in-the-money options more than that of at-the-money and out-of-money options. Our study is therefore useful for both asset pricing and portfolio investment in the Hong Kong market where volatility is an inherent nature of the economy.     

Volatility forecasting: long memory,regime switching and heteroscedasticity

In this article, we account for the first time for long memory, regime switching and the conditional time-varying volatility of volatility (heteroscedasticity) to model and forecast market volatility using the heterogeneous autoregressive model of realized volatility (HAR-RV) and its extensions. We present several interesting and notable findings. First, existing models exhibit significant nonlinearity and clustering, which provide empirical evidence on the benefit of introducing regime switching and heteroscedasticity. Second, out-of-sample results indicate that combining regime switching and heteroscedasticity can substantially improve predictive power from a statistical viewpoint. More specifically, our proposed models generally exhibit higher forecasting accuracy. Third, these results are widely consistent across a variety of robustness tests such as different forecasting windows, forecasting models, realized measures, and stock markets. Consequently, this study sheds new light on forecasting future volatility.     

Stock market volatility forecasting: Do we need high-frequency data?

The general consensus in the volatility forecasting literature is that high-frequency volatility models outperform low-frequency volatility models. However, such a conclusion is reached when low-frequency volatility models are estimated from daily returns. Instead, we study this question considering daily, low-frequency volatility estimators based on open, high, low, and close daily prices. Our data sample consists of 18 stock market indices. We find that high-frequency volatility models tend to outperform low-frequency volatility models only for short-term forecasts. As the forecast horizon increases (up to one month), the difference in forecast accuracy becomes statistically indistinguishable for most market indices. To evaluate the practical implications of our results, we study a simple asset allocation problem. The results reveal that asset allocation based on high-frequency volatility model forecasts does not outperform asset allocation based on low-frequency volatility model forecasts.     

Time Inhomogeneous Multiple Volatility Modeling

Price variations at speculative markets exhibit positive autocorrelationand cross correlation. Due to large parameter spaces necessaryfor joint modeling of variances and covariances, multivariateparametric volatility models become easily intractable in practice.We propose an adaptive procedure that identifies periods ofsecond-order homogeneity for each moment in time. To overcomethe high dimensionality of the problem we transform the multivariateseries into a set of univariate processes. We discuss thoroughlythe implementation of the adaptive technique. Theoretical andMonte Carlo results are given. We provide two applications ofthe new method. For a bivariate exchange rate series we comparethe multivariate GARCH approach with our method and find thelatter to be more in line with the underlying assumption ofindependently distributed innovations. Analyzing a 23-dimensionalvector of asset returns we underscore the case for adaptivemodeling in high-dimensional systems.     

Simulating the Evolution of the Implied Distribution

Motivated by the implied stochastic volatility literature (Britten–Jones and Neuberger, forthcoming; Derman and Kani, 1997; Ledoit and Santa–Clara, 1998) this paper proposes a new and general method for constructing smile–consistent stochastic volatility models. The method is developed by recognising that option pricing and hedging can be accomplished via the simulation of the implied risk neutral distribution. We devise an algorithm for the simulation of the implied distribution, when the first two moments change over time. The algorithm can be implemented easily, and it is based on an economic interpretation of the concept of mixture of distributions. It can also be generalised to cases where more complicated forms for the mixture are assumed.     

The anticipated and concurring effects of the EMU: exchange rate volatility, institutions and growth

Reduced exchange rate volatility and higher and less heterogeneous quality of institutional rules and macroeconomic policies are two of the main (anticipated and concurring) effects expected from a currency union.In this paper, we measure the magnitude of these two effects for the Eurozone countries looking at real effective exchange rates (REER) and at different indicators of quality of institutional rules and macroeconomic policies (QIRMP). We find that the first effect is much stronger than the second when we compare relative changes for Eurozone countries and the rest of the world in the relevant period.We further evaluate the impact of both effects on economic growth on a larger sample of countries. Our findings show that both have significant impact on levels (more robust) and on rates of growth (weaker) of per capita GDP.     

Effectiveness and Effects of China’s Capital Controls

I. IntroductionNations at every stage of development and in every region of the world are more closelylinked through trade in goods and services, through flows of funds and investments ineach others’ economies than ever before. But in sharp contrast to more and more nationsloosening restrictions on international trade, controls over capital flows are still substantialnearly everywhere except in the most developed economies. This is certainly the case inChina, where restrictions on movements …     

循环经济的投入产出分析

本文运用投入产出理论对循环经济进行了量化分析，首先，在模型中将循环经济部门从生产部门和消除污染部门中分离开来，在投入不变的条件下，运用循环经济下的各种经济指标来研究新的投入产出关系。其次，通过比较研究的方法，来分析循环经济对整个国民经济的影响程度及对其效果进行评价。最后本文还探讨了在不引入循环生产部门的情况时循环经济的投入产出关系。