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This study aims to investigate, for the first time in the literature, the stochastic properties of the US aggregate health-care price inflation rate series, using the data on health-care inflation rates for a panel of 17 major US urban areas for the period 1966-2006.

This goal is undertaken by applying the first- and second-generation panel unit root tests and the panel stationary test developed recently by Carrion-i-Silvestre et al. (2005) that allows for endogenously determined multiple structural breaks and is flexible enough to control for the presence of cross-sectional dependence.

The empirical findings indicate that after controlling for the presence of cross-sectional dependence, finite sample bias, and asymptotic normality, the US aggregate health-care price inflation rate series can be characterized as a non-stationary process and not as a regime-wise stationary innovation process.

The research findings apply to understanding of health-care sector price escalation in US urban areas. These findings have timely implications for the understanding of the data structure and, therefore, constructs of economic models of urban health-care price inflation rates. The results confirming the presence of a unit root indicating a high degree of inflationary persistence in the health sector suggests need for further studies on health-care inflation rate persistence using the alternative measures of persistence. This study’s conclusions do not apply to non-urban areas.

The mean and variance of US urban health-care inflation rate are not constant. Therefore, insurers and policy rate setters need good understanding of the interplay of the various factors driving the explosive health-care insurance rates over the large US metropolitan landscape. The study findings have implications for health-care insurance premium rate setting, health-care inflation econometric modeling and forecasting.

Payers (private and public employers) of health-care insurance rates in US urban areas should evaluate the value of benefits received in relation to the skyrocketing rise of health-care insurance premiums.

This is the first empirical research focusing on the shape of urban health-care inflation rates in the USA.

This study aims to examine the stationarity characteristics of per capita GDP of 17 Asian countries and subpanels for South Asia, East Asia, and high income Asian countries in nonlinear framework.

The authors employed a recently developed nonlinear panel unit root test suggested by Ucar and Omaga in PESTAR framework for full panel and the subpanels.

The results indicate that per capita GDP for the full panel of Asian countries and panel of South Asian countries are linear nonstationary, whereas for the panel of East Asia and high income developed countries have a nonlinear data generating process and are stationary.

The use of newly developed nonlinear panel unit root test for Asian countries is the main contribution of the study. In that aspect, this is the first study to employ such a test in this area.

This paper provides a selective survey of the panel macroeconometric techniques that focus on controlling the impact of “unobserved heterogeneity” across individuals and over time to obtain valid inference for “structures” that are common across individuals and over time. We consider issues of (i) estimating vector autoregressive models; (ii) testing of unit root or cointegration; (iii) statistical inference for dynamic simultaneous equations models; (iv) policy evaluation; and (v) aggregation and prediction.

The purpose of this paper is to examine the presence of unit roots in the stock prices of 16 OECD countries.

Heterogeneous panel unit root tests developed by Im et al. (1997/2003) and Pesaran (2007).

Under the assumption of cross-sectional independence across the panel, the authors find no evidence of unit roots, thus failing to reject mean reversion in the stock prices for all the countries in the sample. However, under the assumption of cross-sectional dependence, an assumption borne out by the diagnostic test results, the authors find support for the presence of unit roots in the stock prices.

Thus, the use of more robust panel unit root tests seems to raise questions about the long-run predictability of the stock market, at least in the context of the OECD countries.

Thus, it seems that in the long run, an investment policy of buy and hold has still much to offer.

The paper aims to re‐examine the stationarity properties of unemployment rates in 12 European Union (EU) countries over the period 1988: I‐1999: IV.

This paper applies a battery of second‐generation panel unit root tests that allow for cross‐sectional correlation.

The study shows that, contrary to previous empirical literature, hysteresis does not characterise EU unemployment.

This paper uses recent advances in the econometrics of panel unit root tests. The new tests have more power than the traditional ones in detecting the null hypothesis of a unit root.

There are several studies that investigate evidence for mean reversion in stock prices. However, there is no consensus as to whether stock prices are mean reverting or random walk (unit root) processes. The goal of this paper is to re‐examine mean reversion in stock prices.

The authors use five different panel unit root tests, namely the Im, Pesaran and Shin t‐bar test statistic, the Levin and Lin test, the Im, Lee, and Tieslau Lagrangian multiplier test statistic, the seemingly unrelated regression test, and the multivariate augmented Dickey Fuller test advocated by Taylor and Sarno.

The main finding is that there is no mean reversion of stock prices, consistent with the efficient market hypothesis.

One issue not considered by this study is the role of structural breaks. It may be the case that the efficient market hypothesis is contingent on structural breaks in stock prices. Future studies should model structural breaks.

The findings have implications for econometric modelling, in particular forecasting.

This paper adds to the scarce literature on the mean reverting property of stock prices based on panel data; thus, it should be useful for researchers.

For the past decades, issues concerning the impact of economic integration on financial integration, especially exchange rate integration, has been criticized among several regions such as ASEAN. This chapter intends to: (i) test for the exchange rate integration among the ASEAN-5, including Indonesia, Philippines, Malaysia, Singapore, and Thailand, using panel data techniques; and (ii) determine the impact of economic integration on the level of exchange rate integration among the ASEAN-5 countries. The purchasing power parity (PPP) is tested using panel unit root tests on monthly data. The results confirm the PPP among the ASEAN-5 countries due to lower transaction costs from ASEAN agreements. The chapter applies Multivariate GARCH (M-GARCH) models using daily data to determine the level of exchange rate integration among the ASEAN-3, including Malaysia, Singapore, and Thailand. The results of panel cointegration tests using quarterly data of economic integration and exchange rate integration confirm the impact of international trade openness on exchange rate integration. With free trade agreements leading to lower trade barriers, lower transaction costs, and low transportation costs, the economic integration among ASEAN countries practically leads to a higher degree of exchange rate integration. The findings imply that trade liberalization has the strongest effect on the real exchange rate. As such, regulators of ASEAN countries should pay more attention to the exchange rate policies of each other because of the interdependence of their exchange rates.

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.

This article explores the size‐growth relationship for a panel of large US credit unions, using the panel unit root tests of Im et al. (2003) and Maddala and Wu (1999). The reference point is Gibrat’s Law, or the Law of Proportionate Effect, according to which firm growth rates are independent of firm sizes. The panel unit root tests are applied to the log as sets and log membership series of a sample of 997 surviving credit unions which reported data over the period 1993 to 2002. In each case the panel unit root tests fail to reject the null hypothesis of non‐stationarity in the logarithmic size series for all credit unions. The implication is that credit union sizes follow random walks, producing a tendency for industry concentration to increase in the long term. With many of the largest institutions currently offering portfolios of products and services similar to those of commercial banks and other financial institutions, these implications of the panel unit root test results appear consistent with observed patterns within the sector in recent years.

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.