scholarly journals Internet usage and the shadow economy: Evidence from panel data

2013 ◽  
Vol 37 (1) ◽  
pp. 111-121 ◽  
Author(s):  
Ceyhun Elgin
Keyword(s):  
Panel Data ◽  
Shadow Economy ◽  
Internet Usage

scholarly journals Which Types of Education are Important for Economic Growth?

2019 ◽  
Vol 11 (4) ◽  
pp. 1
Author(s):  
Yutaka Kurihara
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Positive Impact ◽  
Internet Usage ◽  
Quality Education ◽  
The Other ◽  
Educational Systems ◽  
High Quality ◽  
High Quality Education ◽  
The Relationship

The relationship between education and economic growth has been discussed on numerous occasions, and there is a consensus that education plays an important role toward economic growth. This paper empirically examines 55 countries’ panel data to determine which types of education are playing important roles for achieving economic growth. The results showed that the improvement of educational systems, finance skill, Internet usage, and English proficiency has a positive impact on economic growth. On the other hand, educational systems and Internet usage also shrink inequality in the economy. High quality education for students is important for attaining economic growth, and it would confer student’s chances and opportunities and promote sound economic growth.

scholarly journals Country innovative development: impact of the shadow economy

2020 ◽  
pp. 41-49
Author(s):  
Alina Vysochyna ◽  
Olena Kryklii ◽  
Mariia Minchenko ◽  
Aygun Akbar Aliyeva ◽  
Kateryna Demchuk
Keyword(s):  
Regression Analysis ◽  
Panel Data ◽  
Fixed Effects ◽  
Shadow Economy ◽  
Slovak Republic ◽  
Panel Data Analysis ◽  
Innovative Development ◽  
State Management ◽  
Panel Data Regression ◽  
Data Regression

This article generalizes arguments and counterarguments within the scientific discussion regarding the determination of the influence of illegal economic activity and expansion of the shadow economy on innovative country development. The systematization of the scientific works on the above problems proves that there is no one no complexity and unity in the above-mentioned scientific findings, which, in turn, demonstrates the necessity of further theoretical and empirical search in this sphere. Thus, it was developed a scientific hypothesis about the negative influence of the shadow economy on innovative country development. In order to test this hypothesis it was developed a scientific and methodological approach that consists of several stages: 1) correlation analysis in order to eliminate multicollinearity problem between control variables; 2) analysis of dataset descriptive statistics; 3) running Hausman test in order to clarify specification of the regression model (fixed or random effects model); 4) realization of the panel data regression analysis for the whole country sample and separately for Ukraine, characteristics of its results. Technically all stages of the research are realized with the help of Stata 12/S.E. software. The country sample consists of 9 countries (Azerbaijan, Estonia, Hungary, Latvia, Lithuania, Poland, Slovak Republic, Slovenia, and Ukraine). Time horizon – 2008-2018. Running of the panel data regression analysis (model specification – with fixed effects) allow confirming research hypothesis for the whole country sample (an increase of shadow economy negatively affected innovative country development: an increase of shadow economy to GDP ratio in 1 % leads to the decrease of the Global Innovation Index in 0.5 points). However, it was not proved for Ukraine separately. It leads to the conclusion that innovative development in Ukraine does not highly dependent on the shadow economy scale because of more significant obstacles on the way to innovation adoption (institutional inefficiency, regulatory drawbacks, etc.). Keywords: innovative economic growth, innovative state management, panel data analysis, shadow economy.

scholarly journals Internet Usage and Household Investment on Risky Financial Assets

2020 ◽  
Vol 3 (4) ◽  
Author(s):  
Rundong Guo
Keyword(s):  
Panel Data ◽  
Financial Markets ◽  
Logit Model ◽  
Fixed Effects ◽  
Internet Usage ◽  
Financial Assets ◽  
Fixed Effects Model ◽  
Risky Assets ◽  
The Impact ◽  
Part Model

Using panel data from the China Family Panel Studies for 2010, 2014 and 2016, this paper uses a two-part model, with the first part using a fixed-effects panel logit model and the second part using a linear logit fixed-effects model to study the impact of Internet usage on Chinese households' participation in risky financial markets and the intensity of investment in risky assets after participation. The results find that Internet usage can promote household participation in the risky finance market and increase household investment in risky assets. Therefore, accelerating Internet usage can promote Chinese households' participation in the risk finance market.

FAKTOR - FAKTOR YANG MENENTUKAN BESARAN SHADOW ECONOMY PADA BRICS COUNTRIES DAN INDONESIA

INFO ARTHA ◽  
2017 ◽  
Vol 1 ◽  
pp. 29-38
Author(s):  
Acwin Hendra Saputra ◽  
Rahadi Nugroho
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Significant Influence ◽  
Shadow Economy ◽  
Panel Data Analysis ◽  
Accurate Information ◽  
Tax Burden ◽  
Brics Countries ◽  
Economic Framework ◽  
The World

Shadow economy is a fact faced by all countries in the world. Despite the existence of the shadow economy which can not be disputed, the accurate information regarding the existence of shadow economy is very difficult to be obtained because all parties involved in it do not want to be identified (hidden nature). The aims of this study is to analyze the determinants that have significant influence on the shadow economy for BRICS Countries and Indonesia. Using panel data for 6 countries we find that the performance of government, intensity of regulatory on economic framework, tax burden significantly affect shadow economy. EGLS panel data analysis results reveal the key determinants of shadow economy estimates. Then, those determinants are used to compare the shadow economy among examined countries to obtain estimates of each country's performance. In this research, Indonesia has relatively good performance compared with BRICS Countries regarding shadow economy determinants. 

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