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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 environmental deterioration has become one of the most economically consequential and charged topics. Numerous scholars have examined the driving factors failing to consider the structural breaks. This study aims to explore sustainability using the per capita ecological footprints (EF) as an indicator of environmental adversities and controlling the resources rent [(natural resources (NR)], labor capital (LC), urbanization (UR) and per capita economic growth [gross domestic product (GDP)] of China.

Through the analysis of the long- and short-run effects with an autoregressive distributed lag model (ARDL), structural break based on BP test and Granger causality test based on vector error correction model (VECM), empirical evidence is provided for the policies formulation of sustainable development.

The long-run equilibrium between the EF and GDP, NR, UR and LC is proved. In the long run, an environmental Kuznets curve (EKC) relationship existed, but China is still in the rising stage of the curve; there is a positive relationship between the EF and NR, indicating a resource curse; the UR is also unsustainable. The LC is the most favorable factor for sustainable development. In the short term, only the lagged GDP has an inhibitory effect on the EF. Besides, all explanatory variables are Granger causes of the EF.

A novel attempt is made to examine the long-term equilibrium and short-term dynamics under the prerequisites that the structural break points with its time and frequencies were examined by BP test and ARDL and VECM framework and the validity of the EKC hypothesis is tested.

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.

The study aims to determine the long and short-term causal relationships between the variables associated with the adjustment of monetary policy and the stock market in India in the presence of structural breaks.

The study employed the autoregressive distributed lag (ARDL) bounds test and the Error Correction Model to assess long- and short-term causal relationships. The study also used non-frequentist Bayesian inferences for the validity of estimation robustness. The Bai–Perron test is used to identify breakpoint dates for the Indian stock market index, and the Granger Causality test is employed to ascertain the direction of causality.

The F-bounds test reveals cointegration among the variables throughout the examined period. Specifically, the weighted average call money rate (WACR), inflation (WPI), currency exchange rate (EXE), and broad money supply (M3) exhibit statistical significance with precise signs. Furthermore, the study identifies the negative impact of the COVID-19 outbreak in March 2020 on the Indian stock market.

Although the study provides significant insights, it is not exempt from constraints. A significant limitation is selecting a relatively limited time period, specifically from April 2008 to September 2023. The limited time frame of this study may restrict the applicability of the results to more comprehensive economic settings, as dynamics between the monetary policy and the stock market can be influenced by multiple factors over varying time periods. Furthermore, the utilisation of the Weighted Average Call Money Rate (WACR) rather than policy rates such as the Repo rate presents an additional constraint as it may not comprehensively account for the impacts of particular policy initiatives, thereby disregarding essential complexities in the connection between monetary policy variables and financial markets.

The findings of the study suggest that investors and portfolio managers should consider economic issues while developing long-term investing plans. Reserve Bank of India should exercise prudence to prevent any discretionary measures that may lead to a rise in interest rates since this adversely affects the stock market. To mitigate risk, investors should closely monitor the adjustment of monetary policy variables.

The study has important social implications, especially regarding the lower levels of financial literacy among investors in India. Considering the complex nature of the study’s emphasis on monetary policy adjustments and their impact on the stock market. Investors face the risk of significant losses due to unexpected adjustments in monetary policy. Many individuals may need help understanding how policy changes impact their investments. Therefore, RBI must consider both price and financial stability when formulating monetary policies. Furthermore, market participants should consider the potential impact of fluctuating monetary policy variables when devising their long-term investment strategies. Given that adjustments in interest rates can markedly affect stock market dynamics, investors must carefully assess the implications of monetary policy decisions on their portfolios.

The study uses dummy variables in the ARDL model to represent structural breaks that emerged from the COVID-19 pandemic (as determined by the Bai–Perron multiple breakpoint test). The study also used the Perron unit root test to find out the stationary of the series in the presence of structural breaks. Additionally, the study also employed Bayesian inferences to affirm the robustness of the estimates.

The purpose of this paper is to examine the impact of structural breaks on the conditional variance of carbon emission allowance prices.

The authors employ the symmetric GARCH model, and two asymmetric models, namely the exponential GARCH and the threshold GARCH.

The authors show that the forecast performance of GARCH models improves after accounting for potential structural changes. Importantly, we observe a significant drop in the volatility persistence of emission prices. In addition, the effects of positive and negative shocks on carbon market volatility increase when breaks are taken into account. Overall, the findings reveal that when structural breaks are ignored in the emission price risk, the volatility persistence is overestimated and the news impact is underestimated.

The authors are the first to examine how the conditional variance of carbon emission allowance prices reacts to structural breaks.

The purpose of this paper is to examine the pricing efficiency of the Malaysian crude palm oil (CPO) market before and after the structural break. This study uses the daily closing price of CPO and CPO futures (CPO-F) for the period ranging from June 2009 to August 2016 while taking structural breaks into account.

In this study, symmetric and asymmetric long-run relationship model are employed, such as the Johansen cointegration, VECM, TAR and M-TAR models, to examine the impact of structural breaks on the pricing efficiency of the Malaysian CPO market.

This finding establish that Malaysian CPO price is efficient before and after the structural break. The consistent efficiency of the Malaysian CPO market supports the trading of the CPO-F in Globex and the use of Malaysian CPO pricing as the reference price. This study establishes that a structural break in the Malaysian CPO price series does not affect the pricing efficiency of the market.

This study shows that using Malaysian CPO price as a reference price is sustainable even in the event of a structural break. Therefore, market participants in the Malaysian CPO market have less to worry about the CPO price as it supports the weak form of efficiency. Price deviation in the short run may not lead to arbitrage profit as transaction cost may not be covered.

This study implies that if there is distortion in the price due to shocks, both manufacturers and producers need to hedge their positions in the futures market (subject to their positions in the underlying market). By entering into the futures market, pricing is locked in advance; hence, price risk is eliminated. Such a distortion could also affect the efficiency of the CPO price, therefore this study also addresses the issue of efficiency of the local CPO market.

Previous studies on Malaysian CPO pricing efficiency did not take the effect of structural break into consideration, making it difficult for these studies to show consistency in the efficiency of the Malaysian CPO market.

This paper investigates the relationship between domestic gold prices and inflation in Vietnam based on the monthly series of the gold price index and consumer price index over the period of December 2001–July 2020.

The co-integration between the domestic gold price and inflation is examined within the autoregressive distributed lag-error correction (ARDL bounds testing) framework. This paper also applies the vector error correction model (VECM) and impulse response function analysis to explore the causal relationship between these two variables. Moreover, since both gold and inflation series are likely to have structural changes over time, a unit root test controlling for significant breaks is employed in this paper.

Findings from the ARDL bounds testing model suggest the presence of a co-integration between the underlying variables. The VECM indicates that shocks in inflation lead to a negative response to gold prices in the long run. In the short term, only fluctuations in gold prices impact inflation, and this causality is unidirectional.

Gold is regarded as a critical financial asset to preserve wealth from inflation pressure in the case of Vietnam. These findings propose implications for both investors and policymakers.

Empirical results suggest that inflation has a long-term impact on gold prices in the Vietnamese market. In the existence of a permanent inflationary shock, domestic prices of gold respond negatively to this shock; hence, gold can act as a good hedge against inflation in Vietnam.

The purpose of this study is to explore the role of gold as a hedge against inflation in the case of the United Arab Emirates.

The study utilizes monthly data on the local sharia-compliant spot gold contract traded on the Dubai Gold and Commodity Exchange (DGCX) and the corresponding consumer price index series over the period December 2015 to January 2021. The econometric approach employed by the study involves a unit root testing procedure that allows the timing of significant breaks to be estimated. A cointegration analysis is then conducted using a nonlinear autoregressive distributed lag (NARDL) model, taking into consideration the presence of structural breaks in addition to short- and long-run asymmetries.

The results reveal that consumer and gold prices are cointegrated, which implies that investing in gold can hedge against inflation in the long run. No sufficient evidence, nonetheless, is found in support of the ability of gold to serve as a hedge against inflation in the short run.

The findings have several important policy implications for policymakers and investors that are further discussed in the study.

This paper aims to investigate the influence of air and rail transportation on pollution in Turkey from 1970 to 2020.

Fourier Autoregressive Distributive Lags (ADL) and Fourier Fractional ADL cointegration tests (Banerjee et al., 2017; Ilkay et al., 2021) are employed to analyze the relationship be-tween the variables. Cointegration tests that take into account soft transitions under structural changes are implemented. Structural change issues are crucial for this topic since the changes in countries’ environmental policies and transportation habits are shaped by the decisions taken in relation to environmental regulations. Finally, for robustness purposes, we tested the estimated equation with a completely different methodology. Thus, a Machine Learning (ML) analysis is conducted, through a Ridge Regression (RR).

The findings obtained by applying Fourier Autoregressive Distributive Lags (FADL) and Fourier Fractional ADL cointegration tests, which can control for structural changes, reveal the existence of a long-term relationship between the variables. In addition, FMOLS estimates emphasize that economic growth and air transport can lead to increased pollution in the long run, while rail transport reduces it. Moreover, the statistically significant trigonometric terms indicate the existence of a smooth structural change among the variables. Robustness checks are performed through a Machine Learning (ML) analysis, which roughly confirms the previous results.

To our knowledge, existing research in Turkey focuses mainly on road transport, while the impact of rail and air transport on pollution has not yet been investigated. As such, this study will be a significant addition to the academic literature.

Within a multivariate framework, this study examines the asymmetric and threshold impact of external debt on economic growth in Egypt during the period 1980–2019.

The paper uses a nonlinear autoregressive distributed lag (NARDL) bounds testing approach to cointegration and a vector error-correction model to estimate the short- and long-run parameters of equilibrium dynamics. A multiple structural breaks model is estimated to test nonlinearity in the relationship between external debt and economic growth.

Results of the NARDL model show a robust statistically significant negative long-run impact on economic growth stemming from both positive and negative external-debt-induced shocks. In terms of magnitude, on the one hand, the impact of external-debt-induced negative shocks exceeds that of the positive. In the short and long run, on the other hand, the growth impact of external debt in Egypt is symmetric. There is also support for the nonlinearity hypothesis in which a negative impact on growth of external debt obtains once the threshold level of external debt-to-GDP ratio equals or exceeds 96.7%.

Identifying the threshold level after which external debt becomes harmful to economic growth would help inform policymakers in Egypt about maximum external debt levels that can be sustained without impairing economic growth.

The current study makes a substantial contribution to the extant literature on the debt-growth tradeoffs. It breaks ground by being the first tract that examines, using a NARDL model, asymmetry and nonlinearity of debt-growth tradeoffs in Egypt.