scholarly journals Investigating if the Financial Markets Performance Affects the Shadow Economy: Additional Evidence From EU Countries

2021 ◽  
Vol 12 (5) ◽  
pp. 130
Author(s):  
Pyrros Papadimitriou ◽  
Thomas Poufinas ◽  
George Galanos ◽  
Charalampos Agiropoulos
Keyword(s):  
Financial Markets ◽  
Shadow Economy ◽  
Underground Economy ◽  
Legal Aspects ◽  
Extensive Literature ◽  
Policy Makers ◽  
Panel Data Regression ◽  
Inflation Rates ◽  
Advanced Economies ◽  
Data Regression

The shadow economy also known as the informal or unobserved or underground economy, is a phenomenon that affects not only emerging markets and developing countries but also advanced economies. In general, this undeclared economic activity is hard to measure given its hidden nature in addition to its relation with unlawful activities. Nevertheless, apart from the legal aspects that may appear, shadow economy has negative implications in terms of tax revenue and social security contributions for the nations. To this end, an extensive literature has explored the measurement issues as well as the root causes of this phenomenon proving that the underground economy constitutes a significant portion of the overall economy in a number of countries. This paper tries to investigate the relationship between the shadow economy and the financial markets. This paper employs a number of panel data regression models to detect the association between the financial market metrics and the shadow economy (as a% of GDP). The outcome of this paper is that it finds evidence that increased market capitalization, GDP per capita and FDI as well as low unemployment and inflation rates contribute to low levels of shadow economy. This can be of value to policy makers and the competent authorities of the countries that wish to find means to contain their shadow economy.

scholarly journals Grey power and the Economy: Aging and Inflation Across Advanced Economies

2017 ◽  
Vol 51 (4) ◽  
pp. 514-552 ◽  
Author(s):  
Tim Vlandas
Keyword(s):  
Regression Analysis ◽  
Older People ◽  
Panel Data Regression ◽  
Inflation Rates ◽  
Advanced Economies ◽  
Data Regression ◽  
Democratic Parties ◽  
Social Democratic Parties ◽  
Larger Sample

What explains the cross-national variation in inflation rates across countries? In contrast to most literature, which emphasizes the role of ideas and institutions, this article focuses on electoral politics and argues that aging leads to lower inflation rates. Countries with a larger share of elderly exhibit lower inflation because older people are both more inflation averse and politically powerful, forcing parties seeking their votes to pursue lower inflation. Logistic regression analysis of survey data confirms that older people are more inflation averse and more likely to punish incumbents at the ballot box for inflation. Panel data regression analysis shows that social democratic parties have more economically orthodox manifestos in European countries with more elderly people, and that the share of elderly is negatively correlated with inflation in both a sample of 21 advanced economies and a larger sample of 175 countries. Aging therefore pushes governments to pursue lower inflation.

scholarly journals Fredrich Schneider and Dominik H. Enste. The Shadow Economy—An International Survey. New Delhi / Thousand Oaks / London: Sage Publications. 2006. Paperback. Indian Rs 550.00.

2007 ◽  
Vol 46 (1) ◽  
pp. 99-101
Author(s):  
Sophia Ahmad
Keyword(s):  
Economic Policy ◽  
Social Security ◽  
Money Laundering ◽  
Shadow Economy ◽  
Underground Economy ◽  
Economic Crime ◽  
New Delhi ◽  
International Survey ◽  
Policy Makers

Social security fraud, economic crime, prostitution, money laundering, smuggling, and other illegal actions have one thing in common—they are all considered to be “shadow economy” activities. Such activities are increasing and require immediate attention from social and economic policy-makers and law-regulating authorities. Fredrich Schneider and Dominik H. Enste have made a commendable effort to highlight the causes, effects, and size of the underground economy in their new book.

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 The Effect of Financial Deepening on Economic Growth, Inequality, and Poverty: Evidence from 73 Countries

2020 ◽  
Vol 15 (2) ◽  
pp. 15-27
Author(s):  
Catur Sugiyanto ◽  
Zefania Yolanda
Keyword(s):  
Economic Growth ◽  
Income Inequality ◽  
Developing Economies ◽  
Financial Deepening ◽  
Negative Effects ◽  
Positive Effects ◽  
Panel Data Regression ◽  
Advanced Economies ◽  
Data Regression ◽  
Negative Effect

AbstractThis study aims to analyze the effect of financial deepening on economic growth, income inequality, and poverty rates in 73 countries during the period 1991–2015. Panel data regression and the interaction of dummy variables are used to measure the effect. The results indicate that financial deepening has positive effects on economic growth, but negative effects on income inequality and poverty rates; has significant effect on economic growth in advanced economies (AEs) and significant effect on income equality and poverty rates in emerging markets and developing economies (EMDEs). These findings show that countries have to be selective in developing their financial sectors as it either can have positive or negative effect.

scholarly journals Working capital level influence on SME profitability

2016 ◽  
Vol 23 (1) ◽  
pp. 44-63 ◽  
Author(s):  
Godfred Adjapong Afrifa ◽  
Kesseven Padachi
Keyword(s):  
Small And Medium Enterprises ◽  
Working Capital ◽  
Policy Makers ◽  
Content Type ◽  
Cash Conversion Cycle ◽  
Panel Data Regression ◽  
Data Regression ◽  
Firm Profitability ◽  
Medium Enterprises ◽  
The Relationship

Purpose – The purpose of this paper is to report the results of an investigation of the relationship between working capital level, measured by the cash conversion cycle (CCC) and profitability of small and medium enterprises (SMEs). Design/methodology/approach – The paper employs panel data regression analysis on a sample of 160 Alternative Investment Market (AIM)-listed SMEs for the period from 2005 to 2010. Findings – The empirical results show that there is a concave relationship between working capital level and firm profitability and that there is an optimal working capital level at which firms’ profitability is maximised. Furthermore, an examination as to whether or not deviations from the optimal working capital level reduce firm profitability indicate that deviations above or below the optimum decrease profitability. Research limitations/implications – The sample is limited to AIM-listed SMEs, and therefore the findings cannot be generalised to all firms. Practical implications – Overall, the evidence suggests that firms should strive and attain the optimal working capital level in order to maximise their profitability. Originality/value – The results are of importance to both SMEs and policy makers providing insight into the nature of CCC and its relationship to SMEs profitability.

scholarly journals Reciprocity Between Productivity and Credit Growth in Vietnam’s Co-operatives Credit Institutions

2020 ◽  
Vol 11 (1) ◽  
pp. 93
Author(s):  
Van Duong Ha
Keyword(s):  
Research Data ◽  
Regression Method ◽  
Credit Growth ◽  
Policy Makers ◽  
Factors Affecting ◽  
Panel Data Regression ◽  
Data Regression ◽  
Optimal Policies ◽  
Bidirectional Interactions ◽  
Credit Institutions

Co-operative credit institutions (CCIs) play an important role for achieving the national mission of financial inclusion. Therefore, we should be taking a wider view of productivity and credit and assessing productivity and credit growth. These are factors affecting the CCIs' operations and goals. This study used the panel data regression method with research data from thirty-two selected CCIs in Vietnam from 2013 to 2018. This study’s purpose to discover the reciprocity relationship productivity and credit growth in Vietnam's CCIs. By assessing the factors affecting the productivity and credit growth, the research results have determined the bidirectional interactions and causal relationships between productivity and credit growth. Based on the findings the study offers policy implication and new insights for developing a more sustainable CCIs and further emphasizes optimal policies to CCIs management that helps the policy-makers, CCIs managers and executives in improving the overall productivity, and the credit growth of CCIs going forward.

MIXING WASHINGTON CONSENSUS WITH BEIJING CONSENSUS AND CORRUPTION IN AFRICA

2016 ◽  
Vol 61 (02) ◽  
pp. 1640029
Author(s):  
OMER GOKCEKUS ◽  
YUI SUZUKI
Keyword(s):  
African Country ◽  
Domestic Institutions ◽  
Regression Analyses ◽  
African Countries ◽  
Economic Openness ◽  
Panel Data Regression ◽  
Beijing Consensus ◽  
Advanced Economies ◽  
Data Regression

In theory, trade intensity should positively affect the quality of domestic institutions and governance; the higher the economic openness, the lower the corruption. In practice, however, the growth of economic openness has not been accompanied by the expected improvements in corruption for 34 African countries between 1990 and 2009. This paper presents a plausible explanation for this conundrum. Results from panel data regression analyses indicate that a switch from trading with the Advanced Economies to trading with China increases the perceived corruption level. For instance, in a “representative” African country, a 10% point substitution from trading with the Advanced Economies to trading with China makes its ICRG corruption score decline—indicating increased corruption—by 29%.

A mechanism to improve the allocation of public investment funds

2020 ◽  
Vol 26 (7) ◽  
pp. 1522-1533
Author(s):  
A.V. Larionov
Keyword(s):  
Panel Data ◽  
Random Effects ◽  
Public Investment ◽  
Allocative Efficiency ◽  
Investment Funds ◽  
The Public ◽  
Panel Data Regression ◽  
Data Regression ◽  
Efficiency And Effectiveness ◽  
Effective System

Subject. This article deals with the issue of improving the public investment allocative efficiency. Objectives. The article aims to develop an approach to improve the efficiency and effectiveness of public investment in the economy. Methods. The study is based on a panel data regression with random effects. Conclusions and Relevance. All sectors of the economy have different demand for investment resources attracted, determined by operational and technological aspects. The results of the study can be used to develop an effective system of public investment.

Determinants Of Capital Structure For Multinational And Domestic Companies In India: Panel Data Regression Model

2019 ◽  
Vol 118 (7) ◽  
pp. 147-154
Author(s):  
K. Maheswari ◽  
Dr. J. Gayathri ◽  
Dr. M. Babu ◽  
Dr.G. Indhumathi
Keyword(s):  
Panel Data ◽  
Capital Structure ◽  
Regression Model ◽  
Business Risk ◽  
Return On Assets ◽  
Panel Data Regression ◽  
Data Regression ◽  
Return On Capital ◽  
Domestic Companies ◽  
The Capital Structure

The capital structure refers to the components of capital needed to establish and expand its business activities. The study was made with an objective to examine the determinants of capital structure of multinational and domestic companies listed in S&P BSE automobile sector. The study concluded that there is significant impact on capital structure determinants such as size, business risk, non debt shield tax, return on assets, tangibility, profit, return on capital employed and liquidity on the capital structure of multinational and domestic companies of Indian Automobile Sector.  

FAKTOR DETERMINAN PEMBENTUK STRUKTUR MODAL PADA PERUSAHAAN SEKTOR FARMASI PERIODE 2012 - 2016

2017 ◽  
Vol 2 ◽  
pp. 241-250
Author(s):  
Neng Ria Kanita ◽  
Hendryadi Hendryadi
Keyword(s):  
Panel Data ◽  
Capital Structure ◽  
Firm Size ◽  
Stock Exchange ◽  
Pharmaceutical Manufacturing ◽  
Manufacturing Companies ◽  
Purposive Sampling ◽  
Panel Data Regression ◽  
Data Regression ◽  
Partial Effects

This study aims to examine the simultaneous and partial effects of profitability, liquidity, and firm size on capital structure. The sample is 10 pharmaceutical manufacturing companies listed in Indonesia Stock Exchange period 2012-2016, using purposive sampling. The technique of analysis used is panel data regression (pooled regression). The results showed that the selected model is the fixed effect. Simultaneously NPM, CR, and Firm Size have a significant effect on capital structure. Partially NPM has a negative and significant effect on capital structure. CR partially have a negative and not significant effect on capital structure. Partially Firm Size have a positive and significant effect on capital structure. Variables that have a significant effect on capital structure are NPM and Firm Size. While CR does not significantly affect the capital structure. Keywords: Capital Structure, Profitability, Liquidity, Firm Size

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