Search

Purpose: In this study, the relationship between female labour force participation rate and economic growth is investigated in middle-income countries. The study covers the period of 2001–2016 by employing a dynamic panel approach. Pooled Ordinary Least Square and Fixed Effects model estimations are calculated as a decision criterion to select proper GMM Method. The outcomes indicate that the proper estimation technique, which is a System-GMM model, evidences the U Feminisation Theory for the middle-income countries while controlling all other factors. Design/methodology/approach: The novelty of this study is that the research not only employs both difference and system generalised method of moments (GMM) estimators but also includes main explanatory variables such as education, fertility, and total labour force rate. The study provides an opportunity to review the U-shape nexus between the female labour force and economic growth while controlling education, fertility and total labour participation rate. Findings: The estimation implies that middle-income countries support a U-shaped relationship. The fertility rate does not impact on the female labour force, and education and total labour force level have a positive influence on women's participation in the labour market. Research limitations/implications: This study used data that include the period of 2001–2016 for middle-income countries. So, further studies can use different periods of data or different countries. Practical implications: The authors emphasise the importance of economic growth for female labour force for middle-income countries. Thus, a country intending to increase female labour force should also focus on its economic growth. As the study points out, middle-income countries staying under the minimum threshold, $4698.15 (per capita), should priorities their economic improvement policies to reach their female labour force participation goal. Those countries also should be prepared for a female labour force participation declining phase until they reach the turning point income level. Social implications: Furthermore, education is one of the critical determinants that have an impact on FLFPR. The equal opportunity for both genders to engage in education should be considered as a policy. If females do not have an equal chance to enrolment in education, it may influence the policy of increasing female labour force adversely. Fertility rate appears no more statistically significant in our study. Moreover, today, there are some countries they practise equality between genders by providing equally extended parental leave, which may be a promising policy for gender equality in the labour force and may worth a try. Originality/value: Some previous studies may suffer model mistakes due to lack of consideration the endogeneity problem and bias issue of the results as suggested by Tam (2011). Moreover, previous studies tend to choose either studying U-feminisation as excluding other variables or studying determinants of female labour force participation rate as excluding U-feminisation theory. There is not any panel data study acknowledging both concepts by using recent data to the best knowledge of the authors. Thus, the novelty of this study is that the research not only employs both difference and system generalised method of moments (GMM) estimators but also includes main explanatory variables such as education, fertility, and total labour force rate. The study provides an opportunity to review the U-shape nexus between the female labour force and economic growth while controlling education, fertility and total labour participation rate. [ABSTRACT FROM AUTHOR]

The aim of this study is to test the validity of the purchasing power parity hypothesis with the help of panel unit root tests taking into account the cross-sectional dependence as well as structural breaks for ASEAN (Indonesia, Malaysia, Thailand, Philippines, Singapore, Brunei, Vietnam, Laos, Cambodia). For this purpose, monthly data for the period 1995: 01-2017: 05 was used. According to the results of the Panel LM test which takes into account the structural breaks, it was found that the hypothesis of purchasing power parity is valid for ASEAN countries. [ABSTRACT FROM AUTHOR]

This study investigates the impact of five economic indicators -clusters, FDI, R&D, and GDP per capitaon innovation. Using a unique panel dataset obtained from eight upper/middle-income countries with similar innovation levels that are in and out of economic clusters from 2001-2014. Being in a cluster has static (countable) and dynamic (uncountable) effects. We demonstrated that from the dynamic effect variables GDP per capita, FDI, a dummy variable for being EMU member and R&D expenditure only FDI is significant. On the other hand, export numbers are correlated with innovation negatively by 1.3. The empirical support shows that the dynamic effects of clusters are not statistically significant on innovation, but static effects are. Therefore, clusters are useful for countries on trade but not innovation directly. In a nutshell, an upper middle-income country should increase trade for innovation spillover by moderation effect of being in economic unions. [ABSTRACT FROM AUTHOR]

The purpose of this study is to show the effect of monetary union on macroeconomic performance for 24 OECD countries during the period 1988-2009. According to the findings, the European Monetary Union has a positive effect on foreign trade. On the other hand, it has a negative effect. The monetary union set up without a financial union has a negative effect on macroeconomic performance by limiting the implementations of policy makers even if it has a positive contribution on trade. Thus, monetary policy implementations not supported with financial policy have a negative effect on macroeconomic performance. [ABSTRACT FROM AUTHOR]

This study proposes the time-varying nonlinear panel unit root test to investigate the convergence of ecological foot prints between the EU and candidate countries. Sixteen European countries (such as Albania, Austria, Belgium, Denmark, France, Germany, Greece, Italy, Luxembourg, Netherlands, Poland, Portugal, Romania, Spain, Sweden and Turkey) and analysis periods are selected according to data availability. This study proposes a cross-sectional Panel KSS with Fourier to test the convergence of the ecological footprints. Then, we combine this methodology with the rolling window method to take into account the time-varying stationarity of series. This study evaluated sub-components of ecological footprints separately and provided more comprehensive findings for the ecological footprint. According to empirical findings, this study proves that convergence or divergence does not show continuity over time. On the other side, this study points out the presence of divergence draws attention when considering the properties of the sub-components in general. As a result, this study shows that international policies by EU countries are generally accepted as successful to reduce ecological footprint, but these are not sufficient as expected. In this point, it is suggested to keep national policies to support international policies in the long term. [ABSTRACT FROM AUTHOR]

In all countries, the priority of policymakers is to reduce carbon emissions without reducing economic growth performance. Progress in innovation is one of the main measures that can be used to reduce carbon emissions. It is important to demonstrate the impact of innovation at the sectoral level, in terms of more realistic data on policy measures. The aim of this study is to investigate the effects of innovation on carbon emissions on a sectorial basis for fourteen countries in the G20, for the period between 1991 and 2017. The selected countries are Argentina, Brazil, Canada, France, Germany, India, Indonesia, Japan, Korea, Mexico, South Africa, Turkey, the United Kingdom, and the United States for which data is available. The results show that the Environmental Kuznets Curve (EKC) hypothesis is invalid and, in the long-term, innovations did not have a statistically significant effect on the energy sector, transport sector, and other sectors. It was also found that while an increase in innovation in the industrial sector leads to a reduction in carbon emissions, an increase in innovation in the construction sector increases carbon emissions. Therefore, it can be recommended that, in addition to national policies to reduce CO 2 emissions, specific policies should be implemented for each sector separately. • Innovation on carbon emission on a sectorial basis for 14 countries in G20 for 1971–2017. • The Environmental Kuznets Curve (EKC) hypothesis is invalid. • Long-term innovations didn't have a significant effect on the energy sector, transport sector, and other sectors. • The increase in innovation in the industrial sector leads to a reduction in carbon emissions. • Increasing innovation in the construction sector increases carbon emissions. [ABSTRACT FROM AUTHOR]

Human capital investments have a vital role in economic growth. Therefore the effects of human capital on the environment should be analyzed for sustainable economic growth. This paper contributes to the debate on the nexus between human capital and environmental degradation. Based on 21 EU countries' panel data over the period 1994–2018, this study aims to analyze the relationship between human capital and environmental pollution in different financial development levels. We employed the panel smooth transition regression model (PSTR) to assess the nexus between the variables. According to the estimation results, human capital decreases carbon emissions in the low growth regime whereas increases in the high growth regime. Besides, human capital increases carbon emissions in both low regimes of financial development and human capital, and decreases in high regimes. The analysis indicated that as human capital improves, there will be more innovation to protect the environment, and thus there is less environmental degradation. • Impacts of human capital on environment as economy grows. • 21 EU countries over the period 1994–2018. • Panel Smooth Transition Regression Model. • Human capital increases carbon emissions in both low regimes of financial development. • Human capital decreases carbon emissions in high regimes. [ABSTRACT FROM AUTHOR]