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This study examines whether OECD countries have converged over time in terms of export diversification. Focusing on the period 1995–2023, the study employs a new Fourier function-enhanced panel unit root test that takes into account gradual changes instead of sudden breaks. The findings show that more than half of OECD countries have not converged in terms of export diversification. Export diversification plays an important role in achieving economic growth and development as well as long-term sustainability goals. In this context, the study provides critical data for policymakers in support of sustainable development goals. The results point to the need to reassess the economic and environmental impacts of export diversification policies in OECD countries.

Our study investigates the relationship between technology innovation and human development in technologically advanced countries using data from quarterly observations from the last decade of the twentieth century to the first two decades of the twenty-first century. This objective of this study is to implement Quantile-on-Quantile regression (QQ) technique that as formulated by Sim and Zhou (J Bank Finance 55:1–8, 2015) and the renowned Granger-causality in quantiles as proposed by Troster (Econom Rev 37(8):850–866, 2018) examine the basic relationship between the given quantiles of technology innovation and their effects on the quantiles of human development. Therefore, the outcomes of this study explain the overall interdependence of technology innovation and affect the overall human development index. It is enumerated that the empirical results indicate that a significant positive relationship exists between technology innovation and human development in all selected technologically advanced countries, predominantly in both low and high tails. Moreover, the outcomes of Granger causality quantiles indicate a bi-directional fundamental relationship between these two variables in the dataset of all countries. The outcomes of the observations are extended to the recent findings on these two variables’ nexus and imply a differential impact on the technologically advanced countries. This causality guides us to offer some specific policy recommendations to each group of countries.

This study examines the stationarity properties of fossil fuel energy consumption in BRICS countries - Brazil, Russia, India, China, and South Africa - utilizing panel stationarity tests alongside the Zivot-Andrews unit root test. Conducted with annual data spanning from 1995 to 2023, the analysis first assesses cross-sectional dependence and investigates the interdependencies of energy consumption shocks across the nations. Following this, second-generation unit root tests are implemented based on the initial findings. The panel unit test results indicate that while oil and coal consumption exhibit stationary characteristics, natural gas consumption does not. Further country-specific analyses reveal the presence of structural breaks in fossil fuel consumption patterns. The findings suggest that the dynamics of energy consumption in BRICS countries are significantly influenced by economic transformations and policy shifts. This study highlights the necessity of accounting for structural breaks when assessing long-term trends in energy consumption and offers crucial insights for policymakers tasked with formulating sustainable energy policies.

As the third-largest SO2 emitter in the world, China is facing mounting domestic and external pressure to tackle the increasingly serious SO2 pollution. Figuring out the convergence and persistence of sulfur dioxide (SO2) emissions matters much for environmental policymakers in China. This study mainly utilizes the Fourier quantile unit root test to survey the convergence of the SO2 emissions per capita in 74 cities of China during the period of December 2014 to June 2019, by conducting five traditional unit root tests and a quantile root unit test as a comparative analysis. The empirical results indicate that the SO2 emissions per capita in 72 out of 74 cities in China are convergent in the sample period. The results also suggest that the unit root behavior of the SO2 emissions per capita in these cities is asymmetrically persistent at different quantiles. For the cities with the convergent SO2 emissions, the government should consider the asymmetric mean-reverting pattern of SO2 emissions when implementing environmental protection policies at different stages. For Hefei and Nanjing, the local governments need to enact stricter environmental protection policies to control the emission of sulfur dioxide.

In the aftermath of the COVID-19 pandemic crisis, government debt has surged to unprecedented levels in most countries, including those of North Africa. In this study, we investigate the issue of public debt sustainability in four North African countries (Algeria, Libya, Morocco, and Tunisia). The Generalized Supremum Augmented Dickey–Fuller (GSADF) results show that Algeria, Libya, Morocco, and Tunisia have experienced periods of explosive public debt during the studied period. The identified episodes of explosive debt behavior can be seen as periods of unsustainable fiscal policy. Moreover, the Quantile Auto-Regressive (QAR) unit root results point to strong debt sustainability at the lower quantiles for the selected countries, while at the middle and upper quantiles, public debt exhibits an unsustainable dynamic. This finding, therefore, points to weak sustainability of debt and fiscal policies in Algeria, Morocco, Libya, and Tunisia. This paper provides further evidence that fiscal policies have become more unsustainable than sustainable in recent years in these countries. Consequently, fiscal policymakers in MENA countries should not overlook the unsustainability of public debt and its various effects when developing any strategy aimed at stimulating the economy through ever larger debt levels.

This article develops a novel test for a unit root in general transitional autoregressive models, which is based on the infimum of t-ratios for the coefficient of a parametrized transition function. Our test allows for very flexible specifications of the transition function and short-run dynamics and is significantly more powerful than all the other existing tests. Moreover, we develop a large sample theory general enough to deal with randomly drifting parameter spaces, which is essential to properly test for a unit root against stationary transitional models. An empirical application of our test to the exchange rate data is also provided.

This paper examines the time-series properties of house price to earnings ratio (HPER) in the UK using aggregate and regional data. Specifically, we utilise a series of unit root tests to examine the null hypothesis of nonstationary HPERs. These include linear tests as well as a nonlinear test and also a test which accounts for abrupt structural change. The results are against the notion of stationary HPERs. This implies that house prices may permanently diverge from earnings.

The asymptotic validity of tests is usually established by making appropriate primitive assumptions, which imply the weak convergence of a specific function of the data, and an appeal to the continuous mapping theorem. This paper, instead, takes the weak convergence of some function of the data to a limiting random element as the starting point and studies efficiency in the class of tests that remain asymptotically valid for all models that induce the same weak limit. It is found that efficient tests in this class are simply given by efficient tests in the limiting problem— that is, with the limiting random element assumed observed—evaluated at sample analogues. Efficient tests in the limiting problem are usually straightforward to derive, even in nonstandard testing problems. What is more, their evaluation at sample analogues typically yields tests that coincide with suitably robustified versions of optimal tests in canonical parametric versions of the model. This paper thus establishes an alternative and broader sense of asymptotic efficiency for many previously derived tests in econometrics, such as tests for unit roots, parameter stability tests, and tests about regression coefficients under weak instruments.

Price theory suggests that commodity prices should be stationary series. Yet, tests for unit roots rather frequently imply that these prices are not stationary. This seeming inconsistency is investigated by applying alternative specifications of unit root tests to prices of corn, soybeans, barrows and gilts, and milk. The preponderance of evidence suggests that nominal prices do not have unit roots, but the results are sensitive to the specification of the test equation. Accounting for a structural change that shifts the mean appears to be an important issue in unit root tests.