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The purpose of this paper is to consider whether or not the introduction of inflation targeting (IT) impacts on the mean-reversion properties of inflation and output growth.

Focusing on eight Asian countries of which four are inflation-targeters, the authors employ a two-state Markov-switching model which characterizes the behavior of inflation and output growth as regime-dependent based on periods of stationarity or non-stationarity.

In contrast to a literature that offers mixed findings, the authors find the presence of stationary inflation and output growth in one regime for all IT countries, except for South Korea which is characterized by stationary output growth in both regimes. In the cases of South Korea and Thailand, IT reduces the probability of inflation remaining in a non-stationary regime. IT increases the probability of South Korea remaining in a regime of low persistence output growth. While IT is important in understanding behavior, so are other considerations such as exchange rate volatility, as well as the Asian and global financial crises.

In contrast to other unit root tests of inflation and output growth, a novelty of the approach is that the authors obtain new insights in terms of two concepts of stationarity that allow for inflation and output growth to switch between stationary and non-stationary regimes (partial stationarity), or between stationary regimes of differing degrees of persistence (varied stationarity).

This paper investigates whether mean reversion holds for a panel of 16 OECD stock price indices for the period 1970 to 2011.

We employ seemingly unrelated regression (SUR)-based linear and non-linear unit root tests which are not only able to exploit the power of panel data analysis but also account for cross sectional dependencies as well as identify which panel members are stationary.

In contrast to a literature that offers mixed findings on stationarity, it was found that most of our sample is characterized as mean- or trend-reverting with approximated half-lives in the region of three to five years.

In contrast to other panel unit root tests of stock prices, the authors identify which individual panel members are stationary and non-stationary using a SURADF test. A further novelty of our approach is that we also develop a SUR-based panel KSS test that allows us to explore the possibility that stock prices exhibit non-linear stationarity.

The electronic nose is an array of chemical or gas sensors and associated with a pattern-recognition framework competent in identifying and classifying odorant or non-odorant and simple or complex gases. Despite more than 30 years of research, the robust e-nose device is still limited. Most of the challenges towards reliable e-nose devices are associated with the non-stationary environment and non-stationary sensor behaviour. Data distribution of sensor array response evolves with time, referred to as non-stationarity. The purpose of this paper is to provide a comprehensive introduction to challenges related to non-stationarity in e-nose design and to review the existing literature from an application, system and algorithm perspective to provide an integrated and practical view.

The authors discuss the non-stationary data in general and the challenges related to the non-stationarity environment in e-nose design or non-stationary sensor behaviour. The challenges are categorised and discussed with the perspective of learning with data obtained from the sensor systems. Later, the e-nose technology is reviewed with the system, application and algorithmic point of view to discuss the current status.

The discussed challenges in e-nose design will be beneficial for researchers, as well as practitioners as it presents a comprehensive view on multiple aspects of non-stationary learning, system, algorithms and applications for e-nose. The paper presents a review of the pattern-recognition techniques, public data sets that are commonly referred to as olfactory research. Generic techniques for learning in the non-stationary environment are also presented. The authors discuss the future direction of research and major open problems related to handling non-stationarity in e-nose design.

The authors first time review the existing literature related to learning with e-nose in a non-stationary environment and existing generic pattern-recognition algorithms for learning in the non-stationary environment to bridge the gap between these two. The authors also present details of publicly available sensor array data sets, which will benefit the upcoming researchers in this field. The authors further emphasise several open problems and future directions, which should be considered to provide efficient solutions that can handle non-stationarity to make e-nose the next everyday device.

This study aims to investigate the stationarity and convergence of CO₂ emissions series in MENA countries. The stationarity and unit root properties of per capita carbon dioxide (CO₂) emissions series are explored by an increasing amount of studies, which use different methodologies. Examining the time series properties of energy and environmental series is crucial for both researchers and the policymakers, given the close link between energy, environment and the real economy. In fact, if energy exhibits the presence of a unit root, this suggests that this series does not revert to its equilibrium level after being hit by a shock.

The contribution of this work is twofold. First, to the author’s knowledge, a very little attention has been paid to the topics of stationarity and convergence of CO₂ emissions in the case of Middle East and North Africa (MENA) member states, especially in a panel context. Convergence analyses of CO₂ emissions for MENA countries can improve the knowledge of energy and environmental scenario of the area, giving some ideas for appropriate future policies. Second, this is the first study that jointly analyzed time series and panel data properties of emissions series for these countries.

The author finds that relative per capita CO₂ emissions in the 19 MENA countries are a mixture of I(0) and I(1) processes and there is a weak evidence to support the stationarity of CO₂ emissions. After having verified the presence of cross-sectional dependence in the series, the panel unit root tests in presence of cross-section dependence show strong evidence in favor of non-stationarity. In addition, after performing tests for ß-convergence, it is also found that per capita CO₂ emissions are converging on average in 11 out of 19 sample’s countries, while s-convergence analysis reveals that the variance of per capita CO₂ emissions decreased over time, which is an indication of convergence.

Important policy implications emerge from the empirical results. Sustainable environmental and energy policies rely heavily on the CO₂ series’ properties. In this regard, determining whether shocks to CO₂ emissions are permanent or transitory is important for setting feasible goals for sustainable environmental policies. Given that per capita CO₂ emissions are essentially associated with a quality of life, the issues of their reduction have been the leading agenda in energy and environmental management over the past two decades.

This paper aims to investigate, with the view to determine the effectiveness of blueprints that are designed to boost hydroelectricity use, the unit root properties of hydroelectricity consumption in 50 countries for the period from 1965 to 2012.

A newly proposed non-linear unit root test is used for the purpose of estimations.

The results show that 26 countries (which are mostly developing countries) or 52 per cent of the total sample have unit roots in their hydroelectricity consumption series.

The policy implication of these results is that policies associated with the enhancement of hydroelectric power use are likely to be effective in several cases, especially in the developing countries.

The main contribution of this paper is that we estimate the non-stationarity of hydroelectricity series within a non-linearity framework. Failure to use a non-linearity method in the presence of non-linear data-generation processes will create biased inferences and wrong policy implications.

In the last few decades, there has been growing interest in forecasting with computer intelligence, and both fuzzy time series (FTS) and artificial neural networks (ANNs) have gained particular popularity, among others. Rather than the conventional methods (e.g., econometrics), FTS and ANN are usually thought to be immune to fundamental concepts such as stationarity, theoretical causality, post-sample control, among others. On the other hand, a number of studies significantly indicated that these fundamental controls are required in terms of the theory of forecasting, and even application of such essential procedures substantially improves the forecasting accuracy. The aim of this paper is to fill the existing gap on modeling and forecasting in the FTS and ANN methods and figure out the fundamental concepts in a comprehensive work through merits and common failures in the literature. In addition to these merits, this paper may also be a guideline for eliminating unethical empirical settings in the forecasting studies.

The purpose of this paper is to revisit the evidence for purchasing power parity (PPP) using long, low‐frequency data (over 100 years) for 23 organization for economic co‐operation and development (OECD) countries against each of four different base currencies – the Deutsch mark, the Japanese yen, the British pound, and the US dollar.

The paper uses standard unit root tests and level and trend stationarity tests, and also investigates the robustness of the results to alternative testing methodologies from statistical physics, such as Lo's modified rescaled range statistic and the Hurst exponent.

The results indicate that the theory of PPP does not hold.

Motivated by the mixed results from previous research on the validity of the theory of PPP, the robustness of standard unit root and stationarity tests to alternative testing methodologies are investigated. In particular, the paper uses two tests from statistical physics – Lo's modified R/S statistic and the Hurst exponent.

This paper aims to examine two hypotheses that have not been well investigated in the existing literature. One hypothesis is that the real interest rates of industrial countries tend to be mean‐reverting during the current floating exchange rate period. Another hypothesis is that the real interest rates of the countries involved in forming the Euro area are more likely to behave as nonlinear stationary series than those of other industrial countries.

The study applies the conventional linear unit root tests and recently developed nonlinear unit root tests, as well as the tests of specifying nonlinearity in time series, to the short‐term real interest rates of 16 industrial countries.

The results of the study provide support for both hypotheses.

The results imply that, having adopted target‐zone type stabilization policies for years, the central banks of European Monetary Union (EMU) countries were likely to have exercised monetary policies in a nonlinear way, especially in the process of meeting the requirements of joining EMU.

The study provides stronger evidence than previous studies for the theory that real interest rates of industrial countries tend to have mean‐reverting behavior. The study suggests that more active monetary policies for inflation control in the floating exchange rate period may have enhanced mean reversion in real interest rates.

This paper aims to investigate the integrational properties of real GDP for 125 countries.

The paper applies the Kwiatkowski et al. univariate test and a KPSS‐type univariate test that accounts for multiple structural breaks – a test procedure proposed by Carrion‐i‐Silvestre et al. The panel versions of the KPSS‐type test, proposed by Carrion‐i‐Silvestre et al. with and without structural breaks, are also applied.

The paper finds that, while univariate tests with and without structural breaks provide mixed results on persistence, the panel test suggests that shocks to national output are persistent.

This is a multi‐country study that focuses on both developed and developing countries and uses more recent data to provide new and comparable evidence on the persistence of output.

The monetary approach to long run exchange rate determination is reexamined for the Canadian — US dollar exchange rate. We first test for non‐stationarity, and then conduct a multivariate cointegration analysis to examine the validity of the monetary model in determination of exchange rates over the long run. Our results uphold the validity of the monetary approach.