scholarly journals The Impact of the Minimum Wage on Employment: An EU Panel Data Analysis

2021 ◽  
Vol 13 (16) ◽  
pp. 9359
Author(s):  
Cristian Valeriu Paun ◽  
Radu Nechita ◽  
Alexandru Patruti ◽  
Mihai Vladimir Topan
Keyword(s):  
Panel Data ◽  
Minimum Wage ◽  
Fixed Effects ◽  
Negative Impact ◽  
Panel Data Analysis ◽  
The Elderly ◽  
Special Focus ◽  
Female Workers ◽  
Cointegration Tests ◽  
The Impact

Minimum wage laws have become one of the most debated state interventions in the economy, being considered by many specialists as a very efficient tool used to correct certain labour market failures. The aim of this paper is to explore the relationship between minimum wage and employment dynamics, with a special focus on some vulnerable categories recognized in the literature (young people, female workers, the elderly, etc.). Thus, we analysed the relation between the dynamics of minimum wages and that of employment in 22 EU countries, panel data (1999–2016). The results suggest a negative impact of the minimum wage on total employment and on sensitive categories (youth, female workers, the elderly). The long-running negative impact holds for all but one group (55–64 years). The models were tested for random and fixed effects and the results were correspondingly adjusted with country and time and random and fixed effects. Cointegration tests and the tests using lagged minimum wage also confirm a robust relationship between the dynamics of the minimum wage and that of employment over time. Our findings are consistent with many previous studies and confirm the recommendations to prudently use this public policy tool.

scholarly journals GROWTH AND OPENNESS RELATIONSHIP IN THE EU15: PANEL DATA ANALYSIS

Ekonomika ◽  
2010 ◽  
Vol 89 (2) ◽  
pp. 44-54 ◽  
Author(s):  
Erginbay Uğurlu
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Fixed Effects ◽  
Time Series Data ◽  
Negative Impact ◽  
Panel Data Analysis ◽  
Empirical Work ◽  
Series Data ◽  
The Impact ◽  
The Eu

Conventional wisdom suggests that openness of an economy promotes economic growth. There is still argument among economists concerning how a country’s macroeconomic variables and its economic growth interact in numerous econometric studies by using panel data. This paper examines the impact of openness on economic growth for the EU-15 area in 1996–2003. In our empirical work, we have used the panel data technique which is also called longitudinal data or cross-sectional time series data. Panel data is generally concerned with choosing among three alternative regressions that are named fixed effects, random effects and pooled model estimation. The variables used are growth, openness, price level, investment and government share of RGDP. We find that openness has had a weak but negative impact on economic growth in this region over this period. Also, we have found that an increase in investment and a decrease in government expenditure have supported economic growth in the EU-15 countries.

scholarly journals Determinants of Basmati Exports from Pakistan: A Panel Data Analysis

2021 ◽  
Vol 3 (1) ◽  
pp. 12-18
Author(s):  
Muhammad Munwar Hayat ◽  
Raheela Khatoon
Keyword(s):  
Panel Data ◽  
Method Of Moments ◽  
Negative Impact ◽  
Positive Impact ◽  
Panel Data Analysis ◽  
Generalized Method Of Moments ◽  
Trading Partner ◽  
Dummy Variable ◽  
Export Competitiveness ◽  
The Impact

This paper aims to estimate the impact of different factors of basmati exports from Pakistan to its trading partner. Results are obtained by using the Generalized Method of Moments (GMM) model and panel data methodology with a sample of 22 countries for the period of 2003-2019. To estimate the impact of different variables on basmati exports Generalized Method of Moments (GMM) model is used on the panel dataset. The results revealed that the inflation rate of Pakistan has a negative and significant effect on the export competitiveness of Pakistani basmati. The exchange rate of Pakistan has a positive and significant impact on the basmati export, the population of Pakistan has a negative and significant impact on basmati export. Basmati production in Pakistan also has a significant and negative impact on basmati export. The Gross Domestic Product (GDP) of Pakistan has a significant and positive impact on the basmati export while the GDP of the trading partner has a significant and negative impact on the basmati export. The dummy variable for joint border also has a positive and significant impact on basmati exports of Pakistan.

scholarly journals Tourism under the Early Phase of COVID-19 in Four APEC Economies: An Estimation with Special Focus on SARS Experiences

2020 ◽  
Vol 17 (20) ◽  
pp. 7543
Author(s):  
Bao-Linh Tran ◽  
Chi-Chung Chen ◽  
Wei-Chun Tseng ◽  
Shu-Yi Liao
Keyword(s):  
Hong Kong ◽  
New Zealand ◽  
Fixed Effects ◽  
Negative Impact ◽  
Asia Pacific ◽  
International Tourism ◽  
Special Focus ◽  
Tourism Demand ◽  
Data Set ◽  
The Impact

This study examines how experience of severe acute respiratory syndrome (SARS) influences the impact of coronavirus disease (COVID-19) on international tourism demand for four Asia-Pacific Economic Cooperation (APEC) economies, Taiwan, Hong Kong, Thailand, and New Zealand, over the 1 January–30 April 2020 period. To proceed, panel regression models are first applied with a time-lag effect to estimate the general effects of COVID-19 on daily tourist arrivals. In turn, the data set is decomposed into two nation groups and fixed effects models are employed for addressing the comparison of the pandemic-tourism relationship between economies with and without experiences of the SARS epidemic. Specifically, Taiwan and Hong Kong are grouped as economies with SARS experiences, while Thailand and New Zealand are grouped as countries without experiences of SARS. The estimation result indicates that the number of confirmed COVID-19 cases has a significant negative impact on tourism demand, in which a 1% COVID-19 case increase causes a 0.075% decline in tourist arrivals, which is a decline of approximately 110 arrivals for every additional person infected by the coronavirus. The negative impact of COVID-19 on tourist arrivals for Thailand and New Zealand is found much stronger than for Taiwan and Hong Kong. In particular, the number of tourist arrivals to Taiwan and Hong Kong decreased by 0.034% in response to a 1% increase in COVID-19 confirmed cases, while in Thailand and New Zealand, a 1% national confirmed cases increase caused a 0.103% reduction in tourism demand. Moreover, the effect of the number of domestic cases on international tourism is found lower than the effect caused by global COVID-19 mortality for the economies with SARS experiences. In contrast, tourist arrivals are majorly affected by the number of confirmed COVID-19 cases in Thailand and New Zealand. Finally, travel restriction in all cases is found to be the most influencing factor for the number of tourist arrivals. Besides contributing to the existing literature focusing on the knowledge regarding the nexus between tourism and COVID-19, the paper’s findings also highlight the importance of risk perception and the need of transmission prevention and control of the epidemic for the tourism sector.

Globalization and health: An empirical investigation

2019 ◽  
Vol 19 (3) ◽  
pp. 207-224 ◽  
Author(s):  
Vishalkumar J Jani ◽  
Nisarg A Joshi ◽  
Dhyani J Mehta
Keyword(s):  
Health Status ◽  
Panel Data ◽  
Fixed Effects ◽  
Panel Data Analysis ◽  
Health Indicators ◽  
Developed Countries ◽  
Social Dimension ◽  
Three Dimensions ◽  
Infant Mortality Rate ◽  
The Impact

This article empirically examines the impact of globalization on the health status of countries by using panel data. Unlike previous studies, it has attempted to use three different dimensions of globalization and estimate their impact on health status measured by infant mortality rate and life expectancy. It also introduces an initial level of development status as an explanatory variable and found that it has an important role. The fixed effects panel data analysis shows that globalization has a positive impact on the health indicators. Out of the three dimensions of globalization, namely, economic, social and political, the first one has the highest influence on health for the less developed countries. However, as one moves up the ladder of development, social dimension becomes more important. Moreover, the pace of improvement in health indicators is faster in developed countries, indicating a divergence between the developed and the underdeveloped world.

scholarly journals Do Female Executives Make a Difference? The Impact of Female Leadership on Gender Gaps and Firm Performance

2019 ◽  
Vol 129 (622) ◽  
pp. 2390-2423 ◽  
Author(s):  
Luca Flabbi ◽  
Mario Macis ◽  
Andrea Moro ◽  
Fabiano Schivardi
Keyword(s):  
Firm Performance ◽  
Fixed Effects ◽  
Negative Impact ◽  
Positive Impact ◽  
Female Leadership ◽  
Wage Distribution ◽  
Female Executives ◽  
Female Workers ◽  
Fixed Effects Regression ◽  
The Impact

Abstract We investigate the effects of female executives on gender-specific wage distributions and firm performance. Female leadership has a positive impact at the top of the female wage distribution and a negative impact at the bottom. The impact of female leadership on firm performance increases with the share of female workers. We account for the endogeneity induced by non-random executives’ gender by including firm fixed-effects, by generating controls from a two-way fixed-effects regression and by using instruments based on regional trends. The findings are consistent with a model of statistical discrimination in which female executives are better at interpreting signals of productivity from female workers. This suggests substantial costs of women under-representation among executives.

scholarly journals Rethinking Elective Cataract Surgery Diagnostics, Assessments, and Tools after the COVID-19 Pandemic Experience and Beyond: Insights from the EUROCOVCAT Group

Diagnostics ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 1035
Author(s):  
Daniele Tognetto ◽  
Antoine P. Brézin ◽  
Arthur B. Cummings ◽  
Boris E. Malyugin ◽  
Ozlem Evren Kemer ◽  
...  
Keyword(s):  
Cataract Surgery ◽  
Negative Impact ◽  
Waiting Times ◽  
The Elderly ◽  
Recovery Phase ◽  
Diagnostic Tools ◽  
Special Focus ◽  
Critical Issues ◽  
Precautionary Measures ◽  
The Impact

The progressive deterioration of the visual function in patients on waiting lists for cataract surgery has a negative impact on their quality of life, especially in the elderly population. Patient waiting times for cataract surgeries in many healthcare settings have increased recently due to the prolonged stop or slowdown of elective cataract surgery as a result of coronavirus disease 19 (COVID-19). The aim of this review is to highlight the impact of such a “de-prioritization” of cataract surgery and to summarize some critical issues and useful hints on how to reorganize cataract pathways, with a special focus on perioperative diagnostic tools during the recovery phase and beyond. The experiences of a group of surgeons originating from nine different countries, named the European COVID-19 Cataract Group (EUROCOVCAT), have been combined with the literature and recommendations from scientific ophthalmic societies and healthcare institutions. Key considerations for elective cataract surgery should include the reduction of the number of unnecessary visits and examinations, adoption of precautionary measures, and implementation of telemedicine instruments. New strategies should be adopted to provide an adequate level of assistance and to guarantee safety conditions. Flexibility will be the watchword and regular updates would be necessary following scientific insights and the development of the pandemic.

scholarly journals The Impact of Agricultural Technologies on Poverty and Vulnerability of Smallholders in Ethiopia: A Panel Data Analysis

2020 ◽  
Vol 147 (2) ◽  
pp. 517-544 ◽  
Author(s):  
Wubneshe Dessalegn Biru ◽  
Manfred Zeller ◽  
Tim K. Loos
Keyword(s):  
Panel Data ◽  
Unobserved Heterogeneity ◽  
Panel Data Analysis ◽  
Probit Model ◽  
Special Focus ◽  
Switching Regression ◽  
Agricultural Technologies ◽  
Adoption Decision ◽  
Vulnerable Households ◽  
The Impact

AbstractMany studies evaluating the impact of adoption on welfare focused on adoption of a single technology giving little attention on the complementarity/substitutability among agricultural technologies. Yet, smallholders commonly adopt several complementary technologies at a time and their adoption decision is best characterized by multivariate models. This paper, therefore, examines the impact of multiple complementary technologies adoption on consumption, poverty and vulnerability of smallholders in Ethiopia. The study used a balanced panel data obtained from a survey of 390 farm households collected in 2012, 2014 and 2016. A two stage multinomial endogenous switching regression model combined with the Mundlak approach and balanced panel data is employed to account for unobserved heterogeneity for the adoption decision and differences in household and farm characteristics. An ordered probit model is used to analyze the impact on poverty and vulnerability. We find that the adoption of improved technologies increases consumption expenditure significantly and the greatest impact is attained when farmers combine multiple complementary technologies. Similarly, the likelihood of households to remain poor or vulnerable decreased with the adoption of different complementary technologies. We therefore conclude that the adoption of multiple complementary technologies has substantial dynamic benefits that improve the welfare of smallholders in the study area, and given the observed low level of adoption rates, we suggest that much more intervention is warranted, with a special focus on poorer and vulnerable households, to ensure smallholders get support to improve their input use.

scholarly journals Determinants of Income Inequality in EU Candidate Countries: A Panel Analysis

2019 ◽  
Vol 57 (4) ◽  
pp. 397-413
Author(s):  
Vesna Bucevska
Keyword(s):  
Income Inequality ◽  
Fixed Effects ◽  
Negative Impact ◽  
Panel Data Analysis ◽  
Potential Candidate ◽  
Eu Candidate Countries ◽  
Main Determinants ◽  
The Government ◽  
The Impact ◽  
The Eu

AbstractDespite increasing income per capita, the EU candidate and potential candidate countries remain confronted with high levels of income inequality. The purpose of our paper is to identify the main determinants of income inequality among the EU candidate countries. In addition to macroeconomic factors, we also analyze the impact of demographic variables to provide more reliable estimates. Using panel data analysis with fixed effects in the period 2005-2017 for three EU candidate countries (North Macedonia, Serbia and Turkey) we find that the unemployment rate, the level of economic development and the investment rate are the main determinants whose increase leads to a bigger income differentiation in the analyzed countries. The government indebtedness has also a statistically significant, but a negative impact on income inequality. The other two macroeconomic variables in the model – the terms of trade and inflation are statistically insignificant. Among the demographic factors, population growth and education significantly affect income inequality among the EU candidate countries. The obtained results suggest that a sustainable economic growth combined with active measures in the labor market and the improvement of education level of the population could lead to more equal income distribution.

scholarly journals The Outbreak of COVID-19 and Stock Market Responses: An Event Study and Panel Data Analysis for G-20 Countries

2020 ◽  
pp. 097215092095727
Author(s):  
Bhanwar Singh ◽  
Rosy Dhall ◽  
Sahil Narang ◽  
Savita Rawat
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Event Study ◽  
Stock Markets ◽  
Stock Price ◽  
Negative Impact ◽  
Panel Data Analysis ◽  
Abnormal Returns ◽  
Developed Countries ◽  
The Impact

This study examines the impact of the COVID-19 outbreak on the stock markets of G-20 countries. We use an event study methodology to measure abnormal returns (ARs) and panel data regression to explain the causes of ARs. Our sample consists of indices in G-20 countries. The observed window comprises 58 days post the COVID-19 outbreak news release in the international media, and the estimation window consists of 150 days before the event date. We find statistically significant negative ARs in the four sub-event windows during the 58 days. Negative ARs are significant for developing as well as developed countries. The findings of this study reveal that cumulative average abnormal return (CAAR) from day 0 to day 43, ranging from –0.70 per cent to –42.69 per cent, is a consequence of increased panic in the stock markets resulting from an increased number of COVID-19 positive cases in the G-20 countries. From day 43 to day 57, CAAR ranging from –42.69 per cent to –29.77 per cent indicates the recovery of stock markets after a major stock price correction due to COVID-19. Additionally, the results of panel data analysis confirm the recovery of stock markets from the negative impact of COVID-19.

scholarly journals The Consequences of Corruption on Economic Growth in Mediterranean Countries: Evidence from Panel Data Analysis

2018 ◽  
Author(s):  
Hicham Boussalham
Keyword(s):  
Economic Growth ◽  
Fixed Effects ◽  
Negative Impact ◽  
Panel Data Analysis ◽  
Suitable Model ◽  
Fixed Effects Model ◽  
Mediterranean Countries ◽  
Individual Effects ◽  
The Individual ◽  
The Impact

This study attempts to assess the impact of corruption on economic growth in the Mediterranean countries, during the period from 1998 to 2007. Econometric analysis using panel regression has been adopted to test this effect. Individual effects models such as random effects model and fixed effects model were applied to the study sample of 160 observations, and to choose the suitable model, we implemented several tests. For our analysis, we used a basic model that includes the dependent variable GDP per capita as a factor of economic growth and the corruption perception index as the independent variable concerned. Then we completed the model with several standardized macroeconomic control variables mentioned above and applied the individual effects models. The outcomes illustrate that corruption has a negative impact on the selected Mediterranean countries’ economic growth.

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