Study on the Regional Economic Data Analysis and Mining Platform Base on OLAM

2010 ◽  
Author(s):  
Ying Cai ◽  
Jiangping Chen ◽  
Xiaoqing Fan ◽  
Zhenguo Yu
Keyword(s):  
Data Analysis ◽  
Economic Data ◽  
Regional Economic

Measurement Error in U.S. Regional Economic Data

2021 ◽  
Author(s):  
Craig Wesley Carpenter ◽  
Anders Van Sandt ◽  
Scott Loveridge
Keyword(s):  
Measurement Error ◽  
Economic Data ◽  
Regional Economic

scholarly journals A Framework for Spatiotemporal Analysis of Regional Economic Agglomeration Patterns

2018 ◽  
Vol 10 (8) ◽  
pp. 2800 ◽  
Author(s):  
Rui Jin ◽  
Jianya Gong ◽  
Min Deng ◽  
Yiliang Wan ◽  
Xuexi Yang
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Panel Data Analysis ◽  
Interaction Model ◽  
Spillover Effects ◽  
Spatiotemporal Pattern ◽  
Regional Economic ◽  
Spatial Panel ◽  
Economic Agglomeration ◽  
Spatial Panel Data

Understanding regional economic agglomeration patterns is critical for sustainable economic development, urban planning and proper utilization of regional resources. Taking Guangdong Province of China as the study area, this paper introduces a comprehensive research framework for analyzing regional economic agglomeration patterns and understanding their spatiotemporal characteristics. First, convergence and autocorrelation methods are applied to understand the economic spatial patterns. Then, the intercity spatial interaction model (ISIM) is proposed to measure the strength of interplay among cities, and social network analysis (SNA) based on the ISIM is utilized, which is designed to reveal the network characteristics of economic agglomerations. Finally, we perform a spatial panel data analysis to comprehensively interpret the influences of regional economic agglomerations. The results indicate that from 2001 to 2016, the economy in Guangdong showed a double-core/peripheral pattern of convergence, with strengthened intercity interactions. The strength and external spillover effects of Guangzhou and Shenzhen enhanced, while Foshan and Dongguan had relatively strong absorptive abilities. Moreover, expanding regional communication and cooperation is key to enhancing vigorous economic agglomerations and regional network ties in Guangdong by spatial panel data analysis. Our results show that this is a suitable method of reflecting regional economic agglomeration process and its spatiotemporal pattern.

Computers and the Gender Wage Differential

2008 ◽  
pp. 93
Author(s):  
Linda Yuet-Yee Wong
Keyword(s):  
Data Analysis ◽  
Exploratory Data Analysis ◽  
Wage Differential ◽  
White Collar ◽  
Economic Data ◽  
Computer Skill ◽  
Labor Quality ◽  
Exploratory Data ◽  
And Gender ◽  
College Educated

In this article, I report results of an exploratory data analysis that challenge the conventional wisdom on the relation between computer use and gender wage. Using the micro-economic data of 1984, 1993, and 2001, I find 1) the wage premium for females using computers at work is about 19-26 per cent higher than males within the high bluecollar sector, and 2) college-educated females who use computers at work earn a substantially higher wage than college-educated males. These results indicate that computers have re-structured work by deemphasizing physical skill that benefits women, and that college- educated women in the white-collar sector have unobserved female labor quality that could positively correlate with computer skill.

Societal impact of university innovation

2018 ◽  
Vol 41 (11) ◽  
pp. 1309-1335 ◽  
Author(s):  
Benjamin Yeo
Keyword(s):  
Economic Performance ◽  
Significant Proportion ◽  
Economic Data ◽  
Regional Economic ◽  
Content Type ◽  
Economic Productivity ◽  
Multiple Variables ◽  
Regional Economic Performance ◽  
The Impact ◽  
University Patent

PurposeThis study aims to use university patent and regional economic data to investigate the current and future impact of university innovation, measured using multiple variables, on real economic productivity.Design/methodology/approachUsing university patent and regional economic data, regression models are built to determine the impact of university innovation on current and future regional economic performance.FindingsThe findings demonstrate that university innovation generates sustained impact on economic performance, but by itself, is insufficient in driving economic performance; and different measures of university innovation have different degrees of impact. University innovation makes up a small, albeit significant, proportion of the drivers of economic performance.Research limitations/implicationsThere are four implications. First, developing countries can leverage university–industry collaborations for economic growth. Second, innovation management must encourage continuous university innovation for sustainable economic productivity. Third, Science, Technology, Engineering and Mathematics (STEM) and non-STEM innovation warrant attention. Fourth, successful innovation policies should be tailored to their unique societal contexts.Originality/valueAlthough innovation is a driver of economic performance, there is a lack of studies that focus specifically on universities, operationalize performance using gross domestic product measures and take into account impact lags by exploring universities’ current and future impacts.

scholarly journals An Approach for Reconstruction of Realistic Economic Data Based on Frequency Characteristics between IMFs

2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Hao Du ◽  
Hao Gong ◽  
Suyue Han ◽  
Peng Zheng ◽  
Bin Liu ◽  
...  
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Time Series Data ◽  
Low Frequency ◽  
Test Method ◽  
Series Data ◽  
Permutation Entropy ◽  
Intrinsic Mode Functions ◽  
Economic Data ◽  
Index Method

Reconstruction of realistic economic data often causes social economists to analyze the underlying driving factors in time-series data or to study volatility. The intrinsic complexity of time-series data interests and attracts social economists. This paper proposes the bilateral permutation entropy (BPE) index method to solve the problem based on partly ensemble empirical mode decomposition (PEEMD), which was proposed as a novel data analysis method for nonlinear and nonstationary time series compared with the T-test method. First, PEEMD is extended to the case of gold price analysis in this paper for decomposition into several independent intrinsic mode functions (IMFs), from high to low frequency. Second, IMFs comprise three parts, including a high-frequency part, low-frequency part, and the whole trend based on a fine-to-coarse reconstruction by the BPE index method and the T-test method. Then, this paper conducts a correlation analysis on the basis of the reconstructed data and the related affected macroeconomic factors, including global gold production, world crude oil prices, and world inflation. Finally, the BPE index method is evidently a vitally significant technique for time-series data analysis in terms of reconstructed IMFs to obtain realistic data.

TRENDS IN THE DEVELOPMENT OF MODERN DATA ANALYSIS SYSTEMS IN THE ECONOMY

2020 ◽  
pp. 79-84
Author(s):  
A.N. Borodulin ◽  
Keyword(s):  
Data Analysis ◽  
Economic Crisis ◽  
Support System ◽  
Software Tools ◽  
Information Support ◽  
Economic Data ◽  
Business Analysis ◽  
Global Economic Crisis ◽  
Analytical Processing ◽  
Information Support System

The article discusses the main trends in the development of software in the field of business analysis. Promising directions of using software tools for analytical processing of economic data in recent years are identified. The authors also substantiate ways to solve problems in the information support system for companies activities caused by the pandemic and the global economic crisis.

Further report on the sociolinguistic survey of multilingual communities: survey of Cayo District, British Honduras

1974 ◽  
Vol 3 (1) ◽  
pp. 1-32 ◽  
Author(s):  
R. B. Le Page ◽  
Pauline Christie ◽  
Baudouin Jurdant ◽  
A. J. Weekes ◽  
Andrée Tabouret-Keller
Keyword(s):  
Cluster Analysis ◽  
Data Analysis ◽  
Social Role ◽  
Methodological Approach ◽  
Economic Data ◽  
Linguistic Features ◽  
Social Situations ◽  
British Honduras ◽  
Creole Languages ◽  
Cayo District

ABSTRACTThe sociolinguistic survey of Cayo District, British Honduras is here further reported upon (cf. LinS i. 155–72 (1972)). We are concerned with acquisition of language habits in a situation in which the child' verbal behaviour reflects its search for identity and social role. For 280 children, the incidence of five linguistic features in from three to five sections of an interview has been calculated. The linguistic profiles of the children were examined by a computer-programmed cluster analysis. In addition, each child' family and each child were interviewed at home, providing socio-economic data. Analysis is incomplete but does suggest an analogue to the child' acts of identity. The paper illustrates a methodological approach that may be useful in other social situations. (Sociolinguistic identity, multilingualism, creole languages, sociolinguistic survey, cluster analysis, British Honduras.)

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