Journal of Social Economics Research

2020 ◽  
Keyword(s):  
Social Economics ◽  
Economics Research

Using GIS to Advance Social Economics Research: Geocoding, Aggregation, and Spatial Thinking

2019 ◽  
pp. 1-25 ◽  
Author(s):  
Benjamin Wilson ◽  
Neal Wilson ◽  
Sierra Martin
Keyword(s):  
Spatial Thinking ◽  
Social Economics ◽  
Economics Research

scholarly journals The social-economics research of Ivan Franko: the modern views

2016 ◽  
Vol 2016 (49) ◽  
pp. 343-367
Author(s):  
Valentyna Feshchenko ◽  
◽  
Natalija Tymochko ◽  
Keyword(s):  
Social Economics ◽  
The Social ◽  
Economics Research

A meta-analysis on the relation between fluid intelligence and reading/mathematics: Effects of tasks, age, and social economics status.

2019 ◽  
Vol 145 (2) ◽  
pp. 189-236 ◽  
Author(s):  
Peng Peng ◽  
Tengfei Wang ◽  
CuiCui Wang ◽  
Xin Lin
Keyword(s):  
Fluid Intelligence ◽  
Meta Analysis ◽  
Social Economics

Book Reviews

2004 ◽  
Vol 54 (3) ◽  
pp. 387-397
Author(s):  
Mihály Laki ◽  
Beáta Huszka
Keyword(s):  
United Nations ◽  
Development Economics ◽  
International Economics ◽  
Small And Medium Enterprises ◽  
Transitional Economies ◽  
The United Nations ◽  
Medium Enterprises ◽  
Economics Research

R. J. McIntyre and B. Dallago (eds): Small and Medium Enterprises in Transitional Economies. Palgrave Macmillan in association with the United Nations University / World Institute for Development Economics Research, 2003, 259 pp. (Reviewed by Mihály Laki); S. S. Bhalla: Imagine There's No Country. Poverty, Inequality, and Growth in the Era of Globalisation. Washington, D.C.: Institute for International Economics, 2002, 248 pp. (Reviewed by Beáta Huszka)

Data science in economics: comprehensive review of advanced machine learning and deep learning methods

2020 ◽  
Author(s):  
Saeed Nosratabadi ◽  
Amir Mosavi ◽  
Puhong Duan ◽  
Pedram Ghamisi ◽  
Ferdinand Filip ◽  
...  
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Data Science ◽  
State Of The Art ◽  
Science Methods ◽  
Learning Models ◽  
Diverse Range ◽  
Hybrid Machine ◽  
Economics Research

This paper provides a state-of-the-art investigation of advances in data science in emerging economic applications. The analysis was performed on novel data science methods in four individual classes of deep learning models, hybrid deep learning models, hybrid machine learning, and ensemble models. Application domains include a wide and diverse range of economics research from the stock market, marketing, and e-commerce to corporate banking and cryptocurrency. Prisma method, a systematic literature review methodology, was used to ensure the quality of the survey. The findings reveal that the trends follow the advancement of hybrid models, which, based on the accuracy metric, outperform other learning algorithms. It is further expected that the trends will converge toward the advancements of sophisticated hybrid deep learning models.

Broadening Black and Hispanic Participation in Basic Economics Research

2010 ◽  
Author(s):  
William A. Darity, Jr. ◽  
Gregory N. Price ◽  
Rhonda V. Sharpe
Keyword(s):  
Economics Research

The Institute of Social Economics: A Neglected Network in New York's Progressive Community

2020 ◽  
Vol 101 (2) ◽  
pp. 276-296
Author(s):  
Stephen Leccese
Keyword(s):  
Social Economics

Social Economics and the Solidarity City: Whither the Local State?

2020 ◽  
Vol 24 (3) ◽  
pp. 322-325
Author(s):  
Gordon MacLeod
Keyword(s):  
Local State ◽  
Social Economics
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