scholarly journals The Effects of Health Sector Fiscal Decentralisation on Availability, Accessibility, and Utilisation of Healthcare Services: A Panel Data Analysis

2021 ◽  
Author(s):  
Arianna Rotulo ◽  
Christina Paraskevopoulou ◽  
Elias Kondilis
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Fixed Effects ◽  
Central Government ◽  
Panel Data Analysis ◽  
Health Sector ◽  
National Health System ◽  
Healthcare Services ◽  
Italian Regions ◽  
Fiscal Decentralisation

Background: Fiscal Decentralisation (FD) is a widely implemented decentralisation policy consisting of the allocation of pooling and spending responsibilities from the central government to lower levels of governance within a country. In 2001, The Italian National Health System (SSN) has introduced a strong element of FD, making regions responsible for their own pooling of resources and for their budgets. Despite the relevance, only few studies exist on health sector-FD in Italy, mostly looking at the effects of FD on infant mortality. Methods: This study performs a fixed-effects panel data analysis of Italian Regions and Autonomous provinces between the years 2001 and 2017, to investigate the effects of health sector-FD on availability, accessibility, and utilisation of healthcare services in Italy. Results: FD decreases availability of staff and hospital beds, decreases utilisation of care, measured by hospitalisation rates, and increases interregional patients' mobility for healthcare purposes, a finding suggesting increased disparities in access to healthcare. These effects seem to be stronger for public – rather than private – services, and are more prominent in poorer areas. Conclusion: This evidence suggest that FD has created a fragmented and unequal healthcare system, in which levels of availability, utilisation of, and accessibility to resources – as well as the extent of public sector’s retrenchment – coincide with the wealth of the area.

scholarly journals Capital Investments and Manufacturing Firms’ Performance: Panel-Data Analysis

2020 ◽  
Vol 12 (4) ◽  
pp. 1689 ◽  
Author(s):  
Vanja Grozdić ◽  
Branislav Marić ◽  
Mladen Radišić ◽  
Jarmila Šebestová ◽  
Marcin Lis
Keyword(s):  
Data Analysis ◽  
Firm Performance ◽  
Panel Data ◽  
Fixed Effects ◽  
Panel Data Analysis ◽  
Manufacturing Firms ◽  
Capital Investments ◽  
Short Term ◽  
Term Performance

The main goal of this study was to examine the effects of capital investments on firm performance, using panel-data analysis. For this purpose, financial data were gathered for 60 manufacturing firms based in Serbia, in the period from 2004 to 2016. The main research hypotheses were developed in accordance with the definition, nature, and time aspect of capital investments. Therefore, empirical expectation of this study was that the relationship between capital investments and firm performance should be positive—they probably bring losses to the firm in the short term, but they should increase firm performance in the long term. Finally, the results have indeed shown that capital investments have statistically significant negative effect on the short-term performance, but positive effect on the long-term performance of the analyzed firms, while controlling for time-fixed effects and certain internal factors.

Data hiding the truth for the last few years: a panel data analysis of crimes against women

2019 ◽  
Vol 5 (2) ◽  
pp. 132-143
Author(s):  
Aarthee Ragunathan ◽  
Ezhilmaran Devarasan
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Violence Against Women ◽  
Fixed Effects ◽  
Panel Data Analysis ◽  
Ordinary Least Squares ◽  
Content Type ◽  
Thomson Reuters ◽  
Crime Types ◽  
Crimes Against Women

PurposeThe offence against femininity has not only destroyed India’s development but also its future. When it comes down to the most important factor like sex, the social evils like “sati” and “dowry” that had been plaguing our country have been banned in India. India is the most dangerous nation in regard to sexual violence against women, according to the summary of the Thomson Reuters Foundation, 2018. The purpose of this paper is to determine the relationship between the total populations of women with other different types of women crime in all states in India.Design/methodology/approachThis paper will review existing panel data analysis literature and apply this knowledge in finding the highly occurred women crimes in India. Using R software the following models are analysed: pooled ordinary least squares, fixed effects models and random effects models for analysing the women crimes in India.FindingsIn this paper, the authors identify that the fixed effects model is more appropriate for the analysis of women crimes in India.Practical implicationsViolence against women is a social, economic, developmental, legal, educational, human rights and health issue. This paper can be used to find the importance of women crime types. Moreover, the police or legal department can take actions according to the crime types.Originality/valueThere is a lack of literature considering the crimes against women. This will help the society to understand women crime types because the only type of violence that has received much attention by the media is rape. But, through our panel data analysis, we conclude that kidnapping, abduction and dowry death are the most occurred crimes against women in India.

scholarly journals Econometric analysis of the effects of equity capitalization strategies on Brazilian companies performance

2010 ◽  
Vol 8 (1) ◽  
pp. 583-589
Author(s):  
Otavio Prospero Sanchez ◽  
Elmo Tambosi Filho ◽  
Luis Carlos Domingos
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Fixed Effects ◽  
Panel Data Analysis ◽  
Superior Performance ◽  
Local Market ◽  
Firm Financing ◽  
Negative Effect ◽  
International Investors ◽  
Financing Strategy

This article explores the effect in performance of two types of firm financing strategies in Brazilian market, IPO and debentures. We use a fixed effects panel data analysis of 264 firms during the period from 2002 to 2008 to analyze how firms that performed IPO and issued debentures differentiate from others, in terms of Tobin Q. We found that firm that performed IPO have shown a negative effect on Tobin Q while firms that performed debentures, a popular financing strategy in Brazil, showed superior performance. These findings, while consistent with previous literature, make important contributions to the understanding of local market conditions given that Brazilian IPO have being very attention grabbing for international investors.

scholarly journals Firm Performance and Market Behavior during First Wave of COVID-19 in Egypt: Panel Data Analysis

2021 ◽  
Vol 13 (2) ◽  
pp. 1
Author(s):  
May Elewa
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Stock Price ◽  
Fixed Effects ◽  
Business Processes ◽  
Panel Data Analysis ◽  
Trade Volume ◽  
Fixed Effects Model ◽  
Net Profit ◽  
The Impact

The purpose of this paper is to identify the impact of market capital MC and net profit NP on stock price SP and trade volume (TV) in the developing Egyptian business context. This study collects data from 29 non-financial organizations registered on the EGX 30 during the 6 month, 1/1/2020 to 30/6/2020, lockdown in Egypt due to the first wave of COVID-19. Data for the monthly confirmed cases and death cases of COVID-19 are collected for the 6 months of the study and compared to the monthly records of closing prices and trade volume in Egyptian poundsEGP. The study population represents 174 firm year observations. The firms studied operate in cash, have annual financial reports during the period 1/1 to 31/12, obtain complete financial data, and have not been eliminated all throughout the study. In this work the pooled model, the fixed effects model, and the random effects model are used.SPSSis applied to achieve the required statistical analysis. The study is a panel data analysis. Outcomes demonstrate existing substantial effects between market capital MC and stock price SP during the first wave of COVID-19. However, no significant effect is evident of the market capital MC and net profit NP with the trade volume TV during the first wave of this pandemic. This literature is advantageous for external and internal stakeholders and regulatory bodies. The study is a modest contribution that may help boost the business processes to reach better financial performance in times of unexpected catastrophes.

scholarly journals Climate change and food security in EAC region: a panel data analysis

2019 ◽  
Vol 4 (4) ◽  
pp. 270-284
Author(s):  
Walaa Mahrous
Keyword(s):  
Climate Change ◽  
Food Security ◽  
Data Analysis ◽  
Panel Data ◽  
Fixed Effects ◽  
Global Climate ◽  
Panel Data Analysis ◽  
Content Type ◽  
East African Community ◽  
The Impact

Purpose This study aims to analyze the impact of global climate change on food security in the East African Community (EAC) region, using panel data analysis for five countries, over 2000-2014. Design/methodology/approach The determinants of food security are expressed as a function of rainfall, temperature, land area under cereal production, and population size. The paper used pooled fixed effects to estimate the relationship among these variables. Findings Findings show that food security in EAC is adversely affected by temperature. However, precipitation and increasing areas cultivated with cereal crops will be beneficial to ensure everyone's food security. Originality/value Actions for mitigating global warming are important for EAC to consolidate the region’s economic, political and social development/stability.

scholarly journals Economic growth and height of youth: a panel data analysis on 27 provinces in China, 1985–2014

2019 ◽  
Author(s):  
Ke Hong YU ◽  
Xiao Mei Gan ◽  
Xu WEN
Keyword(s):  
Economic Growth ◽  
Data Analysis ◽  
Panel Data ◽  
Fixed Effects ◽  
Panel Data Analysis ◽  
Practical Significance ◽  
Average Height ◽  
Longitudinal Surveys ◽  
Chinese Youth ◽  
The Impact

Abstract Background: This study aimed to empirically examine the influence of China’s macroeconomic development on the height of Chinese youth in the past 30 years, using provincial panel data collected from more than one million children. Methods: Panel data from seven longitudinal surveys (1985, 1991, 1995, 2000, 2005, 2010, and 2014) of the Chinese National Surveys on Students’ Constitution and Health, including students aged 7–22 years from 27 provinces, were utilized for data analysis. Fixed-effects models were used to estimate the association between economic growth and height. Results: For every 1% increase in per capita disposable income (PCDI), the average height of students significantly increased by approximately 0.009%. Stated another way, this implies that a doubling of income is associated with 0.9% increase in height, which is significant for height. The coefficient of PCDI in the last decade is higher than that of in the early two decades. The average height of boys was approximately 3.9% higher than that of girls. The average height difference between high and low ages in the sample was 1.9%. The impact of policies on students' height was extremely small and may have little practical significance. Conclusion: China’s economic growth has a significant positive effect on the height of urban Chinese students without stagnation.

Panel Data

2021 ◽  
pp. 637-657
Author(s):  
Vera Costa ◽  
Rui Portocarrero Sarmento
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Spatial Data ◽  
Fixed Effects ◽  
Panel Data Analysis ◽  
Time Data ◽  
Theoretical Concepts ◽  
R Language ◽  
Over Time

Panel data is a regression analysis type that uses time data and spatial data. Thus, the behavior of groups, for example, enterprises or communities, is analyzed through a time scale. Panel data allows exploring variables that cannot be observed or measured or variables that evolve over time but not across groups or communities. In this chapter, two different techniques used in panel data analysis is explored: fixed effects (FE) and random effects (RE). First, theoretical concepts of panel data are presented. Additionally, a case study example of the use of this type of regression is provided. Panel data analysis is performed with R language, and a step-by-step approach is presented.

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