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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 purpose of this paper is to examine the time series properties of 26 macroeconomic variables in Papua New Guinea (PNG) over the period 1970‐2006.

Both unit root and stationarity tests without a structural break and the Lagrange Multiplier (LM) unit root test with one and two structural breaks developed by Lee and Strazicich are applied to each of the 26 macroeconomic variables in PNG. Compared to popular ADF‐type endogenous unit root tests such as those proposed by Zivot and Andrews and Lumsdaine and Papell, the LM unit root test with one and two structural breaks has the advantage that it is unaffected by breaks under the null.

The unit root and stationarity tests without structural breaks find at best mixed evidence of mean reversion and/or trend reversion for most variables. This result is likely to reflect the failure of these tests to allow for structural breaks, given the power to find stationarity declines if the data contain a structural break that is ignored. When the LM unit root test with one and two structural breaks is applied, it is found that at least 23 of the 26 macroeconomic variables are trend stationary.

The time series properties of macroeconomic variables have important implications for several macroeconomic theories. There are, however, few studies of the time series properties of macroeconomic variables in developing countries and no comprehensive studies for any of the Pacific Island countries. This paper begins to fill this gap as the first to provide a systematic examination of the time series properties of macroeconomic variables in Paua New Guinea.

This paper aims to examine the relationship between Indian rupee-US dollar exchange rate and the macroeconomic fundamentals for the post-economic reform period.

The authors have used an empirical model which includes a range of important macroeconomic variables based on the basic monetary theories of exchange rate determination. At the first stage of the analysis, they have tested structural break in the data. Subsequently, they have employed the fully modified ordinary least square, Wald’s coefficient restriction and impulse response functions (IRF) to estimate the monetary model in the long- and short-run horizons.

Results of analyses indicate that the macroeconomic fundamentals determine exchange rate in a significant way, but their effect varies sizably across the periods. The IRF illustrate the importance of interest rate in controlling exchange rate volatility.

The analysis of the behavior of inter-relationship among macroeconomic variables will help policymakers in a deep-rooted understanding of this complex and time-varying relationship.

Most of the existing studies have tested the impact of a single or a few macroeconomic fundamentals on exchange rate. But in the present study, we have tested the impact of a range of important variables, i.e. money supply, real income or output, price level and trade balance. Further, considering the importance of structural breaks in data, they authors have employed standard tests of structural break and incorporated the issue in the cointegration analysis.

This paper aims to model the relationship between oil price and stock returns for selected sectors in Nigeria using monthly data from January 2007 to December 2016.

The authors use both the linear (symmetric) autoregressive distributed lag (ARDL) by Pesaran et al. (2001) and non-linear (asymmetric) ARDL by Shin et al. (2014), and they also account for structural breaks using the Bai and Perron (2003) test that allows for multiple structural changes in regression models.

The results indicate that the strength of this relationship varies across sectors, albeit asymmetric and breaks. The authors identify two structural breaks that occur in 2008 and 2010/2011, which coincidentally correspond to the global financial crisis and the Arab spring (Libyan shutdowns), respectively. Moreover, the authors observe strong support for asymmetry and structural breaks for some sectors in the reaction of sector returns to movement in oil prices. These findings are robust and insensitive when considering different oil proxies. While further extensions can be pursued, the consideration of asymmetric effects as well as structural breaks should not be jettisoned when modelling this nexus.

This study is one of the very few studies that have investigated the sectoral behaviour of stocks to oil price shocks, particularly in Nigeria. This paper contributes to the oil stock literature using the recent technique of asymmetry and also considering the role structural breaks play in the relationship between oil price and stock returns.

The purpose of this paper is to report on a sequential three-stage analysis of inflation persistence using monthly data from 11 inflation targeting (IT) countries and, for comparison, the USA, a non-IT country with a history of credible monetary policy.

First, the authors estimate inflation persistence in a rolling-window fractional-integration setting using the semiparametric estimator suggested by Phillips (2007). Second, the authors use tests for unknown structural breaks as a means to identify effects of the regime switch and the global financial crisis on inflation persistence. The authors use the sequences of estimated persistence measures from the first stage as dependent variables in the Bai and Perron (2003) structural break tests. Finally, the authors reapply the Phillips (2007) estimator to the subsamples defined by the breaks.

Four countries (Canada, Iceland, Mexico, and South Korea) experience a structural break in inflation persistence that coincide with the implementation of the IT regime, and three IT countries (Sweden, Switzerland, and the UK), as well as the USA experience a structural break in inflation persistence that coincides with the global financial crisis.

The authors find that in most cases the estimates of inflation persistence switch from mean-reversion nonstationarity to mean-reversion stationarity.

Monetary policy implications differ between pre- and post-global financial crisis.

Global financial crisis affected the persistence of inflation rates.

First paper to consider the effect of the global financial crisis on inflation persistence.

This study reexamines the sustainability of fiscal policy in Sweden.

To test the sustainability of fiscal policy, two approaches are used; the methodology of Kejriwal and Perron (2010), testing for multiple structural changes in a cointegrated regression model and time-varying cointegration test of Bierens and Martins (2010), and Martins (2015).

Using the first approach of testing for multiple structural changes in a cointegrated regression model, the results indicate that government spending and revenue are cointegrated with two breaks. An estimation of a two-break long-run model shows that the slope coefficient increases from 0.678 to 0.892 from the first to the second regime, implying that fiscal deficits were weakly sustainable in the first two regimes, from 1800 to 1943, and from 1944 to 1974. Further, results from time-varying cointegration test indicate that cointegration between spending and revenue in Sweden is time-varying. Fiscal deficits were found to be unsustainable for the periods 1801–1811, 1831–1838, 1853–1860 , 1872–1882, 1897–1902, 1929–1940 and 1976–1982 and weakly sustainable over the rest of the study period.

A number of implications arise from this study: (1) Accounting for breaks in cointegration analysis and in the estimation of the level relationship between spending and revenue is very important because ignoring breaks may lead to an overestimated slope coefficient and hence a bias on the magnitude of fiscal deficit sustainability. (2) In testing for cointegration between spending and revenue, assuming a constant cointegrating slope when it is actually time-varying can also be misleading because deficits can be sustainable for a period of time and unsustainable over another period.

The contribution of this study is three-fold; first, the study uses a long series of annual data spanning over a period of two centuries, from 1800 to 2011. Second, because of the importance of structural change in economics, to examine the existence of a level relationship between spending and revenue, the study uses the methodology of Kejriwal and Perron (2010) to test for multiple structural changes in a cointegrated regression model, as well as time-varying cointegration of Bierens and Martins (2010) and Martins (2015).

The purpose of this paper is to explore whether stock index volatility series exhibit real long memory.

The authors employ sequential procedure to test structural break in volatility series, and use DFA and 2ELW to estimate long memory parameter for the whole samples and subsamples, and further apply adaptive FIGARCH (AFIGARCH) to describe long memory and structural break.

The empirical results show that stock index volatility series are characterized by long memory and structural break, and therefore it is appropriate to use AFIGARCH to model stock index volatility process.

This study empirically investigates the properties of long memory and structural break in stock index volatility series. The conclusion has a certain reference value for understanding the properties of long memory and structural break in volatility series for academic researchers, market participants and policy makers, and for modeling and forecasting future volatility, testing market efficiency, pricing financial assets, constructing quantitative investment strategy and measuring market risk.

The purpose of this paper is to investigate the linkages between Indian stock markets with other Asian stock markets namely, Hong Kong, Indonesia, Japan, South Korea, Malaysia, Taiwan and China. Such a study is particularly important because if the level of integration among the markets is high, then investing in different markets will not generate long term gains from portfolio diversification or reduction in risk.

The paper applies unit root test in the presence of endogenous structural breaks that uses a Lagrange Multiplier (LM) test statistics and the Gregory and Hansen cointegration technique that allows for endogenous determined structural break in the relationship have been applied.

The results suggest that the Indian stock markets are not integrated with any of the Asian markets either individually or collectively, and conclude that Indian markets are not sensitive to the dynamics in these markets in the long run.

Since the level of integration has been studied keeping in mind the different economical phases like recession and boom, the study has incorporated the possibility of existence of structural breaks in the individual stock return series as well as in their relationship. The lack of evidence on interlinkage of Indian stock markets with other Asian markets suggests that the trend of Indian markets is not in sync with other markets, possibly due to difference in macroeconomic structure. Since the level of integration has been studied keeping in mind the different economical phases like recession and boom, the study has incorporated the possibility of existence of structural breaks in the individual stock return series as well as in their relationship. The lack of evidence on interlinkage of Indian stock markets with other Asian markets suggest that the trend of Indian markets is not in sync with other markets, possibly due to difference in macroeconomic structure.

This paper aims to model the relationship between oil price and six major agricultural commodity prices using monthly data from January 1997 to December 2016.

The authors use both the linear autoregressive distributed lag by Pesaran et al. (2001) and the nonlinear autoregressive distributed lag by Shin et al. (2014), and they also account for structural breaks using the Bai and Perron (2003) test that allows for multiple structural changes in regression models.

These findings are discernible from the authors’ analyses. First, the linear analysis indicates a significant positive effect of oil prices on the agricultural commodity prices, which supports evidence on the non-neutrality hypothesis. Second, oil price asymmetries seem to matter more when dealing with agricultural commodity prices, except for groundnut. Third, it may be necessary to pre-test for structural breaks when modelling the relationship between oil price and agricultural prices regardless of the commodity being analysed. Fourth, the asymmetric effect for the agricultural commodity prices is non-neutral to oil prices, except for rice in the case of structural breaks.

This paper contributes to the on-going debate on the oil–agricultural commodity nexus using the recent technique of asymmetry and also considering the role structural breaks play in the relationship between oil price and agricultural commodity prices.

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.