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In this study, we aim to test the stochastic convergence of per capita clean energy use in 30 OECD (Organization for Economic Co-operation and Development) countries for the period of 1965–2017.

This study employed both linear and nonlinear panel unit root tests, and unlike other studies, this study allowed fractional values in addition to integer values for frequencies in the Fourier functions. Integer values of frequency indicate temporary breaks, while fractional values show permanent breaks.

The results of the linear panel unit root test indicate that clean energy use does not converge to group average for almost all OECD countries. However, the results of nonlinear panel unit root tests provide evidence that the stochastic convergence hypothesis of clean energy consumption cannot be rejected for most countries. This study does not find any evidence for stochastic convergence of clean energy use in Australia, Canada, Denmark, Ireland, Norway or Sweden. Therefore, the policies regarding clean energy are mandatory in these countries due to their effectiveness. This study also reveals that there are permanent structural breaks in the convergence process of clean energy consumption in approximately half of OECD countries.

This study considers temporary and permanent smooth structural shifts in addition to nonlinearity when testing the stationarity of clean energy consumption in a country i relative to the group average. This new method eliminates deficiencies of the previous panel data techniques. Thus, it provides more reliable results compared to existing literature.

This study aims to investigate the impact of the rise in coronavirus disease 2019 (COVID-19) cases on stock prices, exchange rates and sovereign bond yields in both Brazil and India.

The authors employ the wavelet transform coherence (WTC) and continuous wavelet transform (CWT) techniques on daily data from March 17, 2020 to May 8, 2021.

The findings show that COVID-19 has no impact on exchange rates but slightly increases sovereign bond yields from 2021 onwards. In contrast, the effect of COVID-19 on stock prices is quite high in both countries. There is a considerable consistency between COVID-19 cases and stock prices across different time–frequency dimensions. The rise in COVID-19 cases has an increasing effect on stock prices in Brazil and India, especially in the high-frequency ranges.

As far as the authors know, no prior study has simultaneously analyzed the effects of the COVID-19 pandemic on exchange rates, stock prices and sovereign bonds in Brazil and India.

This study seeks to investigate role of the coronavirus disease 2019 (COVID-19) pandemic on clean energy stocks for the United States for the period 21 January 2020–16 August 2021.

At the empirical stage, the Fourier-augmented vector autoregression approach has been used.

According to the empirical results, the response of the clean energy stocks to the feverish sentiment, lockdown stringency, oil volatility, dirty assets, and monetary policy dies out within a short period of time. In addition, the authors find that there is a unidirectional causality from the feverish sentiment index and the lockdown stringency index to the clean energy stock returns; and from the monetary policy to the clean energy stocks. At the same time, there is a bidirectional causality between the lockdown stringency index and the feverish sentiment index. The empirical findings can be helpful to both practitioners and policy-makers.

Among the COVID-19 variables used in this study is a new feverish sentiment index, which has been constructed using principal component analysis. The importance of the feverish sentiment index is that it allows us to examine the impact of the aggregate level of fear in the economy on clean energy stocks.

This study aims to test the unemployment hysteresis hypothesis for Nordic countries by considering age and gender differentials at various frequencies.

First, the authors test the linearity of the unemployment series and apply appropriate unit root tests based on the linearity test results. The authors use these tests for both original and wavelet-decomposed unemployment rates.

The authors' findings indicate that the results obtained from the original and decomposed series differ. While the authors find evidence of unemployment hysteresis in the six unemployment rates in the short run, they observe supportive results for hysteresis in the three unemployment rates in the long run.

The authors take into account different age and gender groups. Furthermore, the authors propose a testing strategy for unemployment hysteresis that considers the nonlinearity and structural breaks in unemployment rates. Finally, the authors determine whether the unemployment hysteresis is valid at various frequencies.

This study aims to investigate the effect of the tourism sector on employment in 13 Mediterranean countries. In addition, the impact of economic growth and inflation rate, which are included in the analysis as control variables, on the employment rate are investigated.

For this study, data from 1995 to 2018 and the ratio of the employed population, the number of international tourist arrivals, the annual growth rate of real gross domestic product (GDP) and the annual percentage change in the Consumer Price Index (CPI) were used. First, the authors investigated the relationship between variables using the Autoregressive Distributed Lag (ARDL) Bounds Test with Sharp and Smooth Breaks. Then, after determining the significant cointegration relationship, the long-term and short-term coefficients were also estimated.

The results show a cointegration relationship for Cyprus, Greece, Israel, Malta and Tunisia. Tourism demand has a positive effect on all these countries and economic growth positively affects the employment rate only in Greece, Israel and Tunisia. Besides, the inflation rate has a negative effect in Israel and Tunisia and a positive effect in Malta. Overall, the authors' results provide important policy suggestions, such as the training of the employees in the tourism sector should be improved to keep up with the requirements of the times.

The impact of the tourism sector on total employment varies from country to country. In particular, the employment creation policies of the sector need to be changed by taking technological changes into consideration.

Since tourism is a labor-intensive sector, tourism's impact on employment is an important research topic. However, whether this effect applies to all countries is debatable. Furthermore, the development of technology can also reduce employment in labor-intensive sectors. Therefore, this research can be regarded as important as this research addresses such a critical current issue and suggests a novel econometric method such as the ARDL Bounds Test with Sharp and Smooth Breaks.