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The specific objective of the study is to investigate the presence of natural rate of crime rates in selected emerging economies by using panel unit roots. The majority of the literature examines the issue using conventional unit root tests in a country-specific context. Meanwhile, there is no panel unit root investigation has been undertaken considering both cross-sectional dependence (CD) and structural changes.

As a result, this study is to fill the aforementioned gap and validate the natural rate of crime rates for 10 countries by using a Fourier panel unit root test. The advantage of the test is that structural shifts are modelled as gradual or smooth changes with a Fourier approximation, and it also accounts cross-sectional dependency. Thus, the Fourier panel unit root test may have better performance in capturing potential changes in the nature of data.

The result of the conventional unit roots test shows evidence of the hysteresis effect in crime, as it stands does not adequately account for smooth transitions or breaks. On contrary, the Fourier panel unit root test confirms the natural rate hypothesis in crime rates. The present results highlight the detrimental effects of crime cannot be abated by short-run deterrence policies.

Contrary to previous studies, the theoretical implications of the study imply that the empirical models consider the dynamic nature of crime rates should account for natural rate properties instead of the hysteresis assumption.

This paper aims to examine the stochastic convergence of the per capita CO₂ emissions among the top four crude oil exporter countries, namely, Canada, Iraq, Russia and Saudi Arabia, from 1960 to 2017. Assessing the stationarity and unit root properties of the environmental series in these countries is important as their large fossil fuel resources increases the potential for rising CO₂ emissions compared to other countries.

In addition to implementing the conventional unit root tests, the authors also benefit from the application of three nonlinear unit root tests, namely, wavelet unit root test, nonlinear unit root test of Güriş (2019) and the Fourier quantile unit root test. These methods are robust to the presence of possible structural breaks and other forms of nonlinearities, while the wavelet unit root test enables us to examine the stochastic behavior of the variables in both time and frequency domains. Hence, they all provide more reliable inferences on the convergences of the CO₂ emissions compared to their standard competitors.

The standard unit root test results show strong evidence in favor of non-stationarity in all countries. This conclusion supports the results of the other nonlinear unit root tests and the overall findings of the Fourier quantile unit root test. The wavelet unit root test provides a controversial finding. However, due to its limitations, its findings must be interpreted with caution. The details of the Fourier quantile unit root test indicate that per capita CO₂ emissions follow mean-reverting properties in middle quantile ranges for Canada, Russia and Iraq. This validates the asymmetric behaviors of per capita CO₂ emissions in these countries.

The novelty of the work can be stated in two ways. First, among the available studies, this is the first paper to emphasize the importance of examining the convergence of per capita CO₂ emissions among the top four oil exporters. Second, to the best of the knowledge, no study has yet been undertaken in which all these methods have been simultaneously applied. Sustainable environmental policies depend heavily on the CO₂ series’ properties. Thus, the findings can provide significant environmental and economic implications for policymakers to construct feasible and optimal policies in climate change mitigation.

This study aims to examine the hysteresis hypothesis in unemployment using monthly data from 13 countries in transition.

Stationarity in the unemployment rate of selected transition economies was analyzed using four different group unit root tests, namely, linear, structural breaks, non-linear and structural breaks and non-linear.

The empirical results show that the unemployment hysteresis hypothesis is valid for the majority of transition economies, including Bulgaria, Croatia, the Czech Republic, Estonia, Hungary, the Kyrgyz Republic, Latvia, Lithuania, Poland, Romania and Slovenia. However, the results strongly reject the null hypothesis of unemployment hysteresis for the Kazakhstan and the Slovak Republics.

This study revealed that, for countries in transition, advanced unit root tests exhibit greater validity when compared to standard tests

This paper aims to test purchasing power parity (PPP) hypothesis for Greece, Italy, Ireland, Portugal and Spain, which are known as the GIIPS countries.

The authors conduct a comprehensive analysis by using unit root approaches without and with structural breaks and non-linearity.

The PPP is valid for the GIIPS countries. Considering structural breaks in non-linear framework plays a crucial role.

There is no empirical study testing PPP hypothesis by focusing on the GIIPS countries. This study further takes into account for structural breaks and non-linearity in the real exchange rates of these countries.

The purpose of this paper is to re-examine the weak form efficiency of five African stock markets (South Africa, Nigeria, Egypt, Ghana and Mauritius) using various tests to assess the impact of non-linearity effect and thin trading which are prevalent in African markets on market efficiency.

The weekly returns of S&P/IFC return indices for five African countries over the period 2000-2013 were obtained from DataStream and analyzed. The study adopted the newly developed Non-Linear Fourier unit root test advanced by Enders and Lee (2004, 2009) which allows for an unknown number of structural breaks with unknown functional forms and non-linearity in data generating process of stock prices series to test the Random Walk Hypothesis (RWH) for the five markets, and an augment regression model.

In light of the empirical evidence the author(s) using Non-linear Fourier Unit Root Test only fail to reject the RWH for South Africa, Nigeria and Egypt leading to the conclusion that these markets follow the RWH and weak-form efficient whilst Ghana and Mauritius are weak-form inefficient. Besides, evaluating non-linear models without adjusting for thin trading effect shows that, South Africa and Ghana markets are weak-form efficient while Nigeria, Egypt and Mauritius are not. However, after accounting for thin trading effect, the author(s) find that South Africa and Egypt markets follow the RWH. The findings imply that market efficiency results depend on the methodology used.

This paper provides further evidence on stock market efficiency in emerging markets. The finding suggests that thin trading and non-linearity effect influences markets efficiency tests in African stock markets. Thus, recent structural adjustment and liberalization policies have not enhanced stock market operations in Africa. This paper therefore has implications for policy makers and international investors.

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.

The purpose of this study aims to analyze the dynamic behavior of the relationship between atmospheric carbon emissions and the Organisation for Economic Co-operation and Development (OECD) industrial production index (IPI) in the short and long term by applying multifractal techniques.

Multifractal de-trended cross-correlation technique is used for this analysis based on the relevant literature. In addition, it is the most widely used approach to estimate multifractality because it generates robust empirical results against non-stationarities in the time series.

It is revealed that industrial production causes long and short term environmental costs. The OECD IPI and atmospheric carbon emissions were found to have a strong correlation between the time domain. However, this relationship does not mostly take into account the frequency-based correlations with the tail effects caused by shocks that are effective on the economy. In this study, the long-term dependence of the relationship between the OECD IPI and atmospheric carbon emissions differs from the correlation obtained by linear methods, as the analysis is based on the frequency. The major finding is that the Hurst coefficient is in the range 0.40-0.75 indicating.

In this study, the local singular behavior of the time-series is analyzed to test for the multifractality characteristics of the series. In this context, the scaling exponents and the singularity spectrum are obtained to determine the origins of this multifractality. The multifractal time series are defined as the set of points with a given singularity exponent a where this exponent a is illustrated as a fractal with fractal dimension f(α). Therefore, the multifractality term indicates the existence of fluctuations, which are non-uniform and more importantly, their relative frequencies are also scale-dependent.

The results provide information based on the fluctuation in IPI, which determines the main conjuncture of the economy. An optimal strategy for shaping the consequences of climate change resulting from industrial production activities will not only need to be quite comprehensive and global in scale but also policies will need to be applicable to the national and local conditions of the given nation and adaptable to the needs of the country.

The results provide information for the analysis of the environmental cost of climate change depending on the magnitude of the impact on the total supply. In addition to environmental problems, climate change leads to economic problems, and hence, policy instruments are introduced to fight against the adverse effects of it.

This study may be of practical and technical importance in regional climate change forecasting, extreme carbon emission regulations and industrial production resource management in the world economy. Hence, the major contribution of this study is to introduce an approach to sustainability for the analysis of the environmental cost of growth in the supply side economy.

The purpose of this paper is to empirically test the economic convergence that operate between five selected Asian countries (namely Thailand, Singapore, Malaysia, the Philippines and Indonesia). In particular, it seeks to investigate how increased economic integration has impacted the inter-country income levels among the five founding members of ASEAN.

A new Machine Learning (ML) approach is applied along with a panel data analysis (GMM), and the application of KOF Globalization Index.

The Generalized Method of Moments (GMM) results highlight that the endogenous growth theory seems to be supported for the selected Asian countries, indicating evidence of diverging forces resulting from unequal growth and polarization dynamics. Overcoming the technical issues raised by the econometric approach, the new ML algorithm brings contrasted but interesting results. Using the KOF Globalization Index, the authors confirm how the last phase of globalization set the conditions for an economic convergence among sample members.

Using the KOF Globalization Index, the authors confirm how the last phase of globalization set the conditions for an economic convergence among sample members. As a matter of fact, the new LSTM algorithm has provided consistent evidence supporting the existence of converging forces. In fact, the results highlighted the effectiveness of the experiments and the algorithm we chose. The high predictability of the authors’ model and the absence of self-alignment in the values showed a convergence be-tween the economies.

In the Iranian economy, investing in the housing market has been very important and beneficial for investors and households, because of inflationary environment, low real interest rates, underdeveloped financial and tax systems and economic sanctions. Hence, prediction of house prices is the main concern of housing market agents in the economy. The purpose of this paper is to test the stationary properties of Iran's provinces to improve the prediction of future housing prices.

In this paper, the authors have tested the stationary properties of 20 Iran’s province centers over the period from 1993 to 2017 using a novel Fourier quantile unit root test and conventional ordinary/generalized least squares (O/GLS) linear unit root/stationary tests.

According to conventional O/GLS linear unit root/stationary tests, most of the house prices series exhibit random walk behavior, whereas by applying the Fourier quantile unit root test, the null hypothesis of unit root is rejected for 15 out of 20 series. Other results indicated that house prices of cities responded differently to positive and negative shocks.

Previous studies only addressed conventional OLS or GLS linear unit root or stationary tests, but novel Fourier quantile unit root test was not used. New results were obtained based on this unit root test, that, as a priori knowledge, will help benefiting from the positive effects, or avoiding being victimized by the negative effects.

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.