Culture, Economic Preference and Economic Development with Python: Evidence from Two New Datasets

Linwei Ma

2022

Abstract

With the development of society, economy and technology, an increasing number of scholars are attaching more value to the power of culture. Consequently, this paper uses Python, a computer programming language, as a research tool for data analysis and examines the relationship between culture and economic outcomes using two new datasets of cultural features and economic preferences across countries, and based on two indicators of economic outcomes, income per worker and total factor productivity. In the course of the study, our independent variable data cultural economic preferences are derived from Geert Hofstede’s Six-dimensional Cultural Index and Global Preferences Survey. In addition, our dependent variables income per worker and total factor productivity are obtained from the Penn World Table. With a known strong positive relationship between the cultural preference for individualism and economic outcomes, we initially screen out the preferences for a positive relationship with individualism by drawing a heat map model using Python. Then, we verify the conjecture that there is a positive correlation between cultural economic preferences and economic outcomes by producing scatter plots with the dependent variable added. The final regression model is made to determine the extent to which the independent and dependent variables are correlated by the magnitude of the correlation coefficient. Through our research, we find that culture has a significant impact on economic performance.

Paper Citation

in Harvard Style

Ma L. (2022). Culture, Economic Preference and Economic Development with Python: Evidence from Two New Datasets. In Proceedings of the International Conference on Big Data Economy and Digital Management - Volume 1: BDEDM, ISBN 978-989-758-593-7, pages 854-863. DOI: 10.5220/0011355500003440

in Bibtex Style

@conference{bdedm22,
author={Linwei Ma},
title={Culture, Economic Preference and Economic Development with Python: Evidence from Two New Datasets},
booktitle={Proceedings of the International Conference on Big Data Economy and Digital Management - Volume 1: BDEDM,},
year={2022},
pages={854-863},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011355500003440},
isbn={978-989-758-593-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Big Data Economy and Digital Management - Volume 1: BDEDM,
TI - Culture, Economic Preference and Economic Development with Python: Evidence from Two New Datasets
SN - 978-989-758-593-7
AU - Ma L.
PY - 2022
SP - 854
EP - 863
DO - 10.5220/0011355500003440