Forecasting Singapore economic growth with mixed-frequency data

In this paper we intend to forecast the economic growth of Singapore by employing mixed frequency data. This study is motivated by the following observations: macroeconomic variables are the important indicators of the economic performance, but they are normally available at low frequencies, e.g. quarterly for GDP and monthly for inflation. In contrast, the financial variables such as stock returns are available at high frequency, and often the asset prices are forward-looking and believed to contain useful information about future economic developments (Stock and Watson 2003). It is therefore an interesting question to raise whether or not one can use the high-frequency financial variables to better estimate and forecast the macroeconomic variables. Using mixed-frequency data in forecasting is clearly against the conventional forecasting models which generally require data with the same frequency. Time-aggregating, such as averaging, of the high frequency data is usually practiced to match the sampling rate of lower frequency data. But time-aggregation always leads to loss of individual timing information that might be important for forecasting. Hence, finding a suitable method to handle the high frequency data is a crucial task for every forecaster dealing with mixed frequency data. We employ the Mixed Data Sampling (MIDAS) regression model introduced by Ghysels, et al. (2004). MIDAS regressions are essentially tightly parameterized, highly parsimonious regressions that deal with mixed frequency data. It is designed to find a balance between retaining the individual timing information of the high frequency data and reducing the number of parameters that need to be estimated. It is believed to have better estimating and forecasting ability than many other conventional models. A number of studies adopted MIDAS models to forecast quarterly series using monthly or daily financial data, mostly from the US (Anthony 2007; Clements and Galvão 2009). Singapore is a small open economy, and vulnerable to the global economic conditions. Although its stock market is not comparable with that of the US in term of capitalization, the Singapore stock market performance is believed to be highly correlated with its real macroeconomic variable and contains important information for economic forecasting. In this paper, we forecast one-quarter-ahead Singapore GDP growth rate using Singapore stock market return sampled at various high frequencies. We investigate the forecasting performance from three models: a Mixed Data Sampling (MIDAS) regression model, a direct regression model on high frequency data and a time-averaging regression model. Our results show that MIDAS regression using high frequency stock return data produces better forecast of GDP growth rate than the other two models. Best forecasting performance is achieved using weekly stock return. The forecasting result is further improved by performing intra-period forecasting

Proactive edge caching in content-centric networks with massive dynamic content requests

Edge computing is a promising infrastructure evolution to reduce traffic loads and support low-latency communications. Furthermore, content-centric networks provide a natural solution to cache contents at edge nodes. However, it is a challenge for edge nodes to handle massive and highly dynamic content requests by users, and if without an efficient content caching strategy, the edge nodes will encounter high traffic load and latency due to increasing retrieval from content providers. This paper formulates a proactive edge caching problem to minimize the content retrieval cost at edge nodes. We exploit the inherent content caching and request aggregation mechanism in the content-centric networks to jointly minimize traffic load and content retrieval delay cost generated by the massive and dynamic content requests. We develop a Q-learning algorithm, which is an online optimal caching strategy, as it is adaptable to dynamic content popularity and content request intensity, and derive the long-term minimization of the content retrieval cost. Simulation results illustrate that the proposed algorithm can achieve a lower content retrieval cost compared with several baseline caching schemes

ENVIRONMENTAL SURROUNDINGS AND PERSONAL WELL-BEING IN URBAN CHINA

We examine the relationship between atmospheric pollution, water pollution, traffic congestion, access to parkland and personal well-being using a survey administered across six Chinese cities in 2007. In contrast to existing studies of the determinants of well-being by economists, which have typically employed single item indicators to measure well-being, we use the Personal Well-Being Index (PWI). We also employ the Job Satisfaction Survey (JSS) to measure job satisfaction, which is one of the variables for which we control when examining the relationship between environmental surroundings and personal well-being. Previous research by psychologists has shown the PWI and JSS to have good psychometric properties in western and Chinese samples. A robust finding is that in cities with higher levels of atmospheric pollution and traffic congestion, respondents report lower levels of personal well-being ceteris paribus. We find that a one standard deviation increase in suspended particles or sulphur dioxide emissions is roughly equivalent to a 12-13 percent reduction in average monthly income in the six cities. This result suggests that the personal well-being of China's urban population can be enhanced if China were to pursue a more balanced growth path which curtailed atmospheric pollution.China, Environment, Pollution, Personal Well-Being.

Existence of inverted profile in chemically responsive molecular pathways in the zebrafish liver

10.1371/journal.pone.0027819PLoS ONE611

VARIAÇÕES da Comunicadade Fitoplanctonica na Regiao Estuarina dos Rios Piraque-açu e Piraquq-mirim (aracruz-es) e Suas Relações Com Os Fatores Ambientais

RESUMO O presente trabalho foi realizado no estuário dos rios Piraquê-Açú e Piraquê-Mirim, localizado no município de Aracruz - ES (Brasil). Este estudo teve como objetivo estudar espacial e temporalmente a comunidade fitoplanctônica do estuário nos seus aspectos qualitativos e quantitativos, avaliando também a biomassa do fitoplâncton presente através da técnica do biovolume. Além disso, as variáveis abióticas (nutrientes, pH, salinidade, temperatura, transparência e oxigênio dissolvido na água) foram relacionadas com variáveis bióticas do fitoplâncton analisadas nos mesmos pontos, dispostos ao longo do estuário. Os resultados obtidos basearam-se em amostragens realizadas bimestralmente no período de agosto de 2003 a fevereiro de 2004 em quatro pontos de amostragem no estuário. As concentrações de feofitina foram superiores as concentrações de clorofila a, o que demonstrou um grau de senescência elevado da comunidade. Quanto ao aspecto qualitativo do fitoplâncton foram encontrados 156 táxons identificados à nível de espécie, gênero e variedade, sendo que a maioria destes podem ser considerados marinhos, eurialinos e planctônicos. As Classes dominantes foram Bacillariophyceae (57%), Chlorophyceae (11,5%) e Dinophyceae (8,4%). Apesar da grande riqueza de espécies que caracterizou o fitoplâncton do Rio Piraquê-Açú e Piraquê-Mirim, apenas algumas espécies foram de real importância quantitativa, dentre elas a Cyanophyceae Synechocystis aquatilis, a Chlorophyceae Chlorella minutissima e a Bacillariophyceae Melosira varians. Os maiores valores de densidade numérica total ocorreram no período chuvoso (fevereiro). Tais variações estão relacionadas ao maior aporte de material alóctone e nutrientes provenientes do escoamento superficial durante o período chuvoso. Quanto ao biovolume celular sete Classes contribuíram representativamente: Chlorophyceae, Bacillariophyceae, Cyanophyceae, Dinophyceae, Cryptophyceae, Euglenophyceae e os fitoflagelados. A maior contribuição para o biovolume total foi dada pelas Bacillariophyceae e 7 Dinophyceae. A pluviosidade foi o principal transformador externo capaz de induzir mudanças sobre o fitoplâncton. ABSTRACT This study was carried out in the estuary of the Piraquê- Açú and Piraquê-Mirim rivers, located in the municipal district of Aracruz-ES (Brazil). The aim of this study is to verify both spatial and temporal changes on phytoplanktonic community of the estuary in its qualitative and quantitative aspects, and also to evaluate the biomass through the technique of biovolume. Moreover, the obtained biotics variables were related with abiotic variables analized at the same spots along the estuary. The obtained results were based on samplings carried out bimonthly in the period of August 2003 to February 2004, emphasizing two pluviometric seasons: dry (August) and rainy (February). Pheopigments concentrations were higher than chlorophyll a concentration, showing a senescent degree of the community. The qualitative aspect of the phytoplankton community showed 156 taxons classified in species, genus and varieties, wich most of them considered as marine, eurialine and planktonic. The dominant classes were Bacillariophyceae (57%), Chlorophyceae (11,5%) and Dinophyceae (8,4%). Although, the community showed a higher diversity, just some were quantitatively significant, among them Cyanophyceae Synechocystis aquatilis, Chlorophyceae Chlorella minutissima and Bacillariophyceae Melosira varians. The highest densities of total phytoplankton occured in the rainy season. Such variations were related to a significant contribution of allochthonous nutrients and materials originated from superficial outflow during the rainy season. Regarding the biovolume, seven classes of algae showed significative contribution: Chlorophyceae, Bacillariophyceae, Cyanophyceae, Dinophyceae, Cryptophyceae, Euglenophyceae and the phytoflagellates. The most significant contribution for total biovolume was given by Bacillariophyceae and Dinophyceae. Pluviosity was the major external driving force leading to changes in phytoplankton community

Projections of air pollutant emissions and its impacts on regional air quality in China in 2020

Anthropogenic emissions of air pollutants in China influence not only local and regional environments but also the global atmospheric environment; therefore, it is important to understand how China's air pollutant emissions will change and how they will affect regional air quality in the future. Emission scenarios in 2020 were projected using forecasts of energy consumption and emission control strategies based on emissions in 2005, and on recent development plans for key industries in China. We developed four emission scenarios: REF[0] (current control legislations and implementation status), PC[0] (improvement of energy efficiencies and current environmental legislation), PC[1] (improvement of energy efficiencies and better implementation of environmental legislation), and PC[2] (improvement of energy efficiencies and strict environmental legislation). Under the REF[0] scenario, the emission of SO2, NOx, VOC and NH3 will increase by 17%, 50%, 49% and 18% in 2020, while PM10 emissions will be reduced by 10% over East China, compared to that in 2005. In PC[2], sustainable energy polices will reduce SO2, NOx and PM10 emissions by 4.1 Tg, 2.6 Tg and 1.8 Tg, respectively; better implementation of current control policies will reduce SO2, NOx and PM10 emission by 2.9 Tg, 1.8 Tg, and 1.4 Tg, respectively; strict emission standards will reduce SO2, NOx and PM10 emissions by 3.2 Tg, 3.9 Tg, and 1.7 Tg, respectively. Under the PC[2] scenario, SO2 and PM10 emissions will decrease by 18% and 38%, while NOx and VOC emissions will increase by 3% and 8%, compared to that in 2005. Future air quality in China was simulated using the Community Multi-scale Air Quality Model (CMAQ). Under RE[0] emissions, compared to 2005, the surface concentrations of SO2, NO2, hourly maximum ozone in summer, PM2.5, total sulfur and nitrogen depositions will increase by 28%, 41%, 8%, 8%, 19% and 25%, respectively, over east China. Under the PC[2] emission scenario, the surface concentrations of SO2, M2.5, total sulfur depositions will decrease by 18%, 16% and 15%, respectively, and the surface concentrations of NO2, nitrate, hourly maximum ozone in summer, total nitrogen depositions will be kept as 2005 level, over east China. The individual impacts of SO2, NOx, NH3, NMVOC and primary PM emission changes on ozone and PM.5 concentrations have been analyzed using sensitivity analysis. The results suggest that NOx emission control need to be enhanced during the summertime to obtain both ozone and PM2.5 reduction benefits. NH3 emission controls should also be considered in order to reduce both nitrate concentration and total nitrogen deposition in the future

Facile mechanochemical synthesis of non-stoichiometric silica-carbon composite for enhanced lithium storage properties

A large number of new electrode materials and novel structural designs are emerging for lithium-ion batteries, yet scalable synthesis and raw material costs still hinder the practical application of such materials. Here, we designed and fabricated a low-cost SiOx/C composite by a facile and scalable mechanofusion route with a ball-milling method. We selected aerosil and graphite precursor-needle coke, which are two widely used materials in industry, as a silicon source and carbon source, respectively. This SiOx/C composite shows a high reversible capacity (ca. 550 mAh g−1) at the 180th cycle and good rate performance. Our scalable synthesis route of electrode materials can stimulate the progress of other energy storage technologies for practical applications