Estimation of Dynamic Mixed Double Factors Model in High Dimensional Panel Data

The purpose of this article is to develop the dimension reduction techniques in panel data analysis when the number of individuals and indicators is large. We use Principal Component Analysis (PCA) method to represent large number of indicators by minority common factors in the factor models. We propose the Dynamic Mixed Double Factor Model (DMDFM for short) to re ect cross section and time series correlation with interactive factor structure. DMDFM not only reduce the dimension of indicators but also consider the time series and cross section mixed effect. Different from other models, mixed factor model have two styles of common factors. The regressors factors re flect common trend and reduce the dimension, error components factors re ect difference and weak correlation of individuals. The results of Monte Carlo simulation show that Generalized Method of Moments (GMM) estimators have good unbiasedness and consistency. Simulation also shows that the DMDFM can improve prediction power of the models effectively.Comment: 38 pages, 2 figure

Towards a Holistic Integration of Spreadsheets with Databases: A Scalable Storage Engine for Presentational Data Management

Spreadsheet software is the tool of choice for interactive ad-hoc data management, with adoption by billions of users. However, spreadsheets are not scalable, unlike database systems. On the other hand, database systems, while highly scalable, do not support interactivity as a first-class primitive. We are developing DataSpread, to holistically integrate spreadsheets as a front-end interface with databases as a back-end datastore, providing scalability to spreadsheets, and interactivity to databases, an integration we term presentational data management (PDM). In this paper, we make a first step towards this vision: developing a storage engine for PDM, studying how to flexibly represent spreadsheet data within a database and how to support and maintain access by position. We first conduct an extensive survey of spreadsheet use to motivate our functional requirements for a storage engine for PDM. We develop a natural set of mechanisms for flexibly representing spreadsheet data and demonstrate that identifying the optimal representation is NP-Hard; however, we develop an efficient approach to identify the optimal representation from an important and intuitive subclass of representations. We extend our mechanisms with positional access mechanisms that don't suffer from cascading update issues, leading to constant time access and modification performance. We evaluate these representations on a workload of typical spreadsheets and spreadsheet operations, providing up to 20% reduction in storage, and up to 50% reduction in formula evaluation time

Goods and services tax (GST) on construction capital cost and housing property price

Good and Service Tax (GST) an indirect broad-based conswnpti.on tax. Following with the implementation of GST in Malaysia on 1st April 2015, it is suspected that the construction capital cost and housing property price will increase accordingly. This study is aim to review the GST effect associated on construction capital cost and it influences towards housing developer and housing property price. Additionally, this study highlights what was the developer point of view on the GST given to them and also the housing price further proposes initiatives to the housing developers. Argument of GST effect is useful for the public administrators so that to re-consider the rate of GST and also beneficial to the construction parties to account with the GST implementation. As conclusion, this study review that GST do give an impact towards the construction capital cost, housing developer and housing property price in terms of knock-on effect

Effect of PAO-based γ-Fe2O3 and surfactant concentration on viscosity characteristic

This is a preliminary study on the viscosity characteristics of polyalphaolefin (PAO)- based γ-Fe2O3 under zero magnetic fields. By varying the concentration of magnetic nanoparticles (MNPs), PAO-based γ-Fe2O3 with different concentrations were synthesized by co-precipitation method. The effect of this factor on the viscosity characteristic of γ-Fe2O3 (< 30 nm) was investigated on the basic of a series of rheological measurement. The use of oleic acid (OA) as a coating agent and surfactant was also investigated by varying its concentration. The results show the concentration of MNPs and the amount of OA has obvious effect on viscosity characteristics of PAO-based γ-Fe2O3. In the case of comparison between the concentrations of MNPs, higher concentration of MNPs increased the viscosity of the PAO-based γ-Fe2O3 and exhibit nearly Newtonian behavior. The large amount of OA also exhibits the increment on viscosity characteristic of MNPs. The experimental data were compared with the Bingham and Casson model and the results revealed that the rheology of the polyalphaolefin (PAO)-based γ-Fe2O3 fitted the Casson model better