Presence Of Structural Breaks Research Articles

Geo-political risks, uncertainty, financial development, renewable energy, and carbon intensity: Empirical evidence from countries at high geo-political risks

Geopolitical risks and uncertainty negatively affect the economy and environmental quality. High geopolitical risks and high uncertainty increase carbon emission intensity by increasing dependence on fossil fuels. However, research in this area is still in its infancy and more empirical evidence is needed to justify the causal link. This research examines the causal mechanism linking geopolitical risk, uncertainty, financial development, renewable energy, and carbon intensity in a sample of eighteen countries with high geopolitical risk between 1985 and 2021. The selected countries have a high intensity of geopolitical risks due to internal and external conflicts that have worsened in recent years. We employ cointegration techniques from Hatemi-J [1] and Maki [2] in the presence of structural breaks, fully modified ordinary least squares (FMOLS), canonical cointegration regression (CCR) models, and static time-variant Granger causality (1969) test. We find robust empirical evidence that geopolitical risk, financial development, renewable energy, uncertainty, and carbon intensity have a cointegrating relationship in the presence of structural breaks. Results from FMOLS and CCR models indicate that carbon intensity responds differently to changes in geopolitical risk, renewable energy, uncertainty, and financial development. Environmental and energy policymakers should mitigate carbon intensity through long-run rather than short-run mechanisms to achieve SDG12 and SDG13.

Modelling Mixed-Frequency Time Series with Structural Change

AbstractPredictive ability of time series models is easily compromised in the presence of structural breaks, common among financial and economic variables amidst market shocks and policy regime shifts. We address this problem by estimating a semiparametric mixed-frequency model, that incorporate high frequency data either in the conditional mean or the conditional variance equation. The inclusion of high frequency data through non-parametric smoothing functions complements the low frequency data to capture possible non-linear relationships triggered by the structural change. Simulation studies indicate that in the presence of structural change, the varying frequency in the mean model provides improved in-sample fit and superior out-of-sample predictive ability relative to low frequency time series models. These hold across a broad range of simulation settings, such as varying time series lengths, nature of structural break points, and temporal dependencies. We illustrate the relative advantage of the method in predicting stock returns and foreign exchange rates in the case of the Philippines.

Dynamic linkages between the monetary policy variables and stock market in the presence of structural breaks: evidence from India

PurposeThe 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.Design/methodology/approachThe 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.FindingsThe 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.Research limitations/implicationsAlthough 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.Practical implicationsThe 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.Social implicationsThe 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.Originality/valueThe 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.

Impact of oil price, economic globalization, and inflation on economic output: Evidence from Latin American oil-producing countries using the quantile-on-quantile approach

This research examines the impact of oil prices, economic globalization, and inflation on the economic output in oil-producing countries in Latin America. We employ advanced time series techniques to achieve precision in findings and reliability of policy inferences. We use cointegration techniques with and without structural breaks because oil prices are highly volatile, and the economies analyzed are unstable in the face of political and social changes. Additionally, we performed a sensitivity analysis using standard quantile and the newly developed quantile-on-quantile regressions to measure the impacts of the covariates on real per capita output. Finally, we use causality Fourier techniques to identify the direction of causal relationships between the series. We found that the oil price, economic globalization, inflation, and output have a long-term equilibrium relationship in the presence of structural breaks. Likewise, quantile models show that the impacts of inflation, economic globalization, and oil prices on economic output are extensively non-linear across the quantile distribution. We found a negative connection between inflation and economic output in the surveyed territories. We propose that those responsible for energy policy in the countries studied should rethink crude oil policies to maximize the benefits of oil exploitation under stagnant globalization and growing inflation.

Remittances and economic growth: Evidence from South Africa using ARDL in the presence of structural breaks

The aim of this study is to investigate the relationship between remittances and economic growth in South Africa, using data running from 1970 to 2019. We utilize the ARDL bounds testing approach to explore the relationship between remittances and economic growth, incorporating control variables and addressing structural breaks. Our findings suggest that the structural change in economic growth occurred in 2008 during the global financial crisis, while the break point for remittances emerged in 1997. After taking into consideration the presence of structural breaks, our study found the estimated coefficient for remittances to be statistically significant at the 1% level of significance. The coefficient is negative, indicating that remittances have a negative impact on economic growth. This result is robust to alternative estimators, including the fully modified least squares technique and the impulse response function. Despite employing different estimation methods, the consistent finding of a negative relationship between remittance inflows and economic growth underscores the reliability of our conclusion. Being a recipient of remittances, it is appropriate for a study of this nature to guide policy makers in formulating appropriate policies to benefit from the full impact of remittances, diversify the economy, and reduce reliance on remittance inflows.

Is Tourism-Led-Growth Hypothesis Valid in the Presence of Structural Breaks?

This study revisited the tourism-led growth hypothesis (TLGH) in the presence of structural breaks using the structural break technique of Ditzen et al. (2021). To estimate the impact of tourism on economic growth along the identified structural breaks, we employed Fixed Effects and Feasible Generalised Least Squares methods. Findings showed four structural break dates (1999, 2004, 2009 and 2014), two of which coincided with the Global Financial Crisis (2008-2009) and the Ebola outbreak (2014). Despite the presence of structural breaks, the TLGH remains valid.

Testing the Balanced Growth Hypothesis in the Presence of Structural Breaks: Evidence from Developed and Developing Countries

Testing the Balanced Growth Hypothesis in the Presence of Structural Breaks: Evidence from Developed and Developing Countries

Yield rate in the Warsaw office market and its determinants. Further studies

This article is a continuation and extension of a previous study which, to the best of the author’s knowledge, was the first scientific attempt to identify determinants of the yield rate in the Warsaw office market. The paper is based on the Gordon growth model. In this approach, the yield rate of buildings offering office space to let is a function of the risk-free interest rate, the risk premium and a constant rate of growth of generated cash flows. In the article, five different elements of the risk premium were identified (term structure, alternative investments’, market (country) specific, monetary and local office market capacity risk premium). The Error Correction Model was formulated based on quarterly time series data from 2007Q1 to 2021Q2. Most investors in the office market in Poland are financial institutions representing foreign capital. Therefore, the innovation of the paper and its main goal was to define which factors play key roles in determining yield rates in the Warsaw office space market – national or regional/international. However, the selected group of Polish determinants were indicated as having prevailing an impact on the yield rate in the Warsaw office market than the corresponding determinants from the European Monetary Union and the USA. Based on the model, the lead-lag, as well as asymmetric relations, were depicted. Moreover, the use of dummy variables checks, the Chow test and the Markov switching model indicated the presence of structural breaks and the existence of the two regimes in the model.

Towards smart sustainable cities: Does technological innovation mitigate G7 CO2 emissions? Fresh evidence from CS-ARDL

Sustainable cities are considered paradigmatic to achieve COP27 targets, but scant literature has analyzed the association with CO2 emission (CE) mitigation policies, especially for the G7 economies. This study traces the impacts of urbanization, innovation, income, and energy consumption on CE for the G7 countries from 1995 to 2019. The time period is important due to the rapid increase in urbanization, globalization, and, at the same time, technology diffusion. The study is focused on novel and relevant panel data econometric methods that tackle cross-section dependence, non-normality of data, and heterogeneity in slope coefficients. The empirical outcome first confirms the long-run cointegrating relationship among the variables in the presence of structural breaks by employing the advanced panel cointegration test. Technologies related to environmental management and energy consumption are positively linked with CE. However, the role of income per capita is found to be inverse with CE. In contrast, the effect of urbanization in different models is mixed for CE. Innovation and its interaction with urbanization are crucial for limiting CE and promoting sustainable cities in G7 economies. This indicates that urbanization with environment-friendly innovation can help G7 countries foster sustainable cities and achieve COP27 targets in general, specifically the Sustainable Development Goal of sustainable cities. The results were tested for the multiplicative effect of different variables with urbanization and innovation. Regarding policy insights, the study recommends focusing on smart and sustainable cities with environment-related innovations and transitioning towards cleaner energy from conventional energy consumption.

Key Macroeconomic Variables under Exchange Rate Volatility: Time-Varying Causality in the Presence of Structural Breaks and Nonlinearity

Key Macroeconomic Variables under Exchange Rate Volatility: Time-Varying Causality in the Presence of Structural Breaks and Nonlinearity

Evaluating the Symmetrical and Asymmetrical Linkage Between Gold Price and Indian Stock Market in the Presence of Structural Change

This article investigates the symmetrical and asymmetrical linkage between gold prices and the Indian stock market in the presence of structural breaks. The study covers a time frame from April 1993 to December 2019. The study employs both linear autoregressive distributed lag (ARDL) and non-linear ARDL (NLARDL) models. The major findings of the study are as follows: first, both the ARDL and NLARDL models indicate the co-movement of gold prices and the Indian stock market. Second, based on the long-run parameters of both the models, the long-run relationship between the variables could not be established. Third, short-run parameters show that positive shocks in gold prices depress the Indian stock market; however, negative shocks in gold prices have a positive but insignificant relationship with the Indian stock market. The asymmetric reaction of the Indian stock market will yield new insights for investors, fund managers, and policymakers.

Dynamic effects of energy consumption, economic growth, international trade and urbanization on environmental degradation in Nigeria

MotivationA crucial but difficult goal for governments and policymakers in Nigeria in recent years has been the sustainability of economic growth. This goal must be accomplished by regulating or lowering greenhouse gas emissions, which calls for switching to a low- or zero-carbon production system. The lack of in-depth empirical studies on the environmental impact of socioeconomic variables on Nigeria and a number of unresolved issues from earlier research are what led to the current study. ObjectiveThis study fills an important empirical gap by investigating the existence of an Environmental Kuznets Curve hypothesis and the long and short-run dynamic impact of socioeconomic variables on ecological sustainability in Nigeria. Data and methodAnnual time series data covering the period 1980 to 2020 and the Autoregressive Distributed Lag technique in the presence of structural breaks were adopted for this study. ResultsThe empirical findings support the existence of environmental Kuznets curve hypothesis for Nigeria in the long and short run. Energy consumption and total import exacerbates environmental deterioration in the long and short run, whereas total export improves environmental quality in the long and short run. Financial development, which contributed to a conspicuous decrease in the level of environmental destruction in the long run, escalated it in the short run. In contrast, urbanization caused a significant increase in environmental damage in the long run but motivated a decrease in biodiversity loss in the short run. ImplicationsThe government, policymakers, and all energy stakeholders should take additional measures to ensure the implementation and diversification of energy sources to accommodate more renewable energy sources that emit less carbon in order to promote efficiency in Nigeria's production processes and lower carbon emissions. In order to promote the production and trade of environmentally friendly goods, they should also revise and strengthen environmental policies. With affordable, dependable, and sustainable energy use for higher productivity and inclusive growth, Nigeria will be able to achieve its long-term development goals of good health and wellbeing.

Aggregate demand uncertainty outbreaks and employment hysteresis in G7 countries

The slow recovery following the recent financial crisis in many developed countries, and the predictable long lasting economic effects of the Covid-19 pandemic have raised a new interest on the topic of employment hysteresis. In the presence of hysteresis there is no predetermined long-run equilibrium level of aggregate employment. As the economic system is not self-adjusting toward a unique equilibrium, timely, and sustained expansionary macroeconomic policies should be applied to mitigate the impact of negative shocks. The purpose of this paper is to uncover hysteresis effects in the macrodynamics of employment along with variations in its intensity that may result from outbreaks in aggregate demand uncertainty. We estimate a switching employment equation based on the play model of hysteresis, which describes a dynamic process whereby non-convex adjustment costs and uncertainty create intervals of weak reaction of employment to small changes in forcing variables, but spurts in the reaction to large demand shocks. As a novel feature, the estimation allows the presence of structural breaks in the value of the switching parameter of the employment equation due to aggregate demand uncertainty outbreaks. We have concluded that hysteresis effects increased in general in crisis periods associated to outbreaks of uncertainty in aggregate demand.

Portfolio diversification possibilities of cryptocurrency: global evidence

ABSTRACT This article explores the cointegration, co-movement, and causality relationships amongst the equity, debt, and cryptocurrency markets to determine the risk diversification possibilities of an investment portfolio. We employ daily data extracted from the Bloomberg data terminal from 2 August 2017 to 2 June 2022 to investigate the short- and long-run relationships between these markets. Indices from the U.S.A., Europe, China, Australia, and Japan are selected as the proxies for the analysis. The autoregressive distributed lag (ARDL) model, followed by unit root testing in the presence of structural breaks, indicates no long-run relationship among six financial variables and the cryptocurrency market. Although the Toda Yamamoto causality test does reveal unidirectional causality running from European and Chinese markets to the cryptocurrency market, we find no evidence to prove the existence of any bidirectional causality between markets. Furthermore, we use the R-squared metrics to analyse the market behaviour and co-movement between the cryptocurrency market and other financial markets. The test findings exhibit a lower level of co-movement behaviour. Our overall results suggest potential portfolio diversification possibilities between cryptocurrency and financial markets based on Modern Portfolio Theory (MPT).

THE INFLUENCE OF SHORT-TERM AND LONG-TERM FACTORS ON THE DEVELOPMENT OF KEY SECTORS OF THE SOCIO-ECONOMIC SPHERE OF THE ALTAI KRAI

A prerequisite for the stable progressive development of the economy at any level is the predictability of the behavior of its elements. In modern conditions, the economy of the region can be affected by both external factors and internal changes.
 The purpose of the study is to identify short-term and long-term factors affecting the development of key indicators of socio-economic development for the region. The article presents the results of modeling the influence of these factors on the indicators of the main economic sectors of the region and the social sphere.
 The obtained results are provided by the application of econometric methodology. In particular, the methods of checking for a unit root are used, taking into account possible nonlinearity, seasonality and the presence of structural breaks, Granger causality, nonlinear cointegration relationship.
 Thus, the hypothesis of a nonlinear long-term relationship between nominal accrued wages and the consumer price index has been confirmed, a long-term relationship between the coefficients of natural and migration growth, a causal relationship between the development of the main sectors of the economy of the region with the external price environment has been revealed.
 Further steps are proposed to develop the results obtained, in particular, in the development, modification and control of the implementation of strategic planning documents of the region.

Unveiling the influence of COVID-19 on the online retail market: A comprehensive exploration

The global economy has experienced significant disruptions due to the COVID-19 pandemic, profoundly impacting production and consumption patterns. This paper examines the effect of the pandemic on consumer goods prices, focusing on a sample of hand sanitizers, soap, disinfectants, and baking yeasts. The selection of these products was motivated by multiple and comprehensive criteria, where we considered various factors such as changes in consumption patterns during the pandemic, the relevance of these products in household consumption, consumer behavior, availability of historical price data, their significance in daily domestic life, and their utility in the prevention of the disease. Employing a time-series analysis, the study investigates the relationship between product prices and the S&P 500 index, as well as the presence of structural breaks in the time series. The results reveal a significant correlation between all prices in the sample and the S&P 500 index, indicating the index's efficacy as an indicator of the overall economic state. Moreover, the study identifies a single structural break in each price time series, coinciding with the onset of the COVID-19 pandemic. Notably, hand sanitizers, soap, and disinfectants exhibit particularly substantial price jumps near the time of the break. These findings offer crucial insights into the impact of the COVID-19 pandemic on consumer prices, which can guide policy decisions aimed at mitigating the pandemic's economic consequences.

Do petrol prices rise faster than they fall? Evidence from the UK retail and wholesale petrol sectors

This study investigates the presence of price asymmetries in the UK retail and wholesale petrol sectors over the period of January 2020–July 2022. The scope of this research is to explore whether petrol prices rise faster than they fall according to changes in input costs, namely fuel and international crude oil prices for the retail and wholesale sector respectively. As the time sample considers the shocks of covid-19 restrictions and rising inflation, the presence of structural breaks is assumed which may contribute to asymmetric behaviour. The Autoregressive Distributive Lag (ARDL) approach is implemented in the pricing equation of the model by formulating four versions for each sector, according to the presence of asymmetries and price-cost margins. The results provide significant evidence of price asymmetries in the retail petrol sector; however, such asymmetries are less pronounced over high margin periods. The wholesale sector is found to be more flexible to changes in crude oil prices as asymmetries are less persistent throughout the sample. Therefore, consumers face rigid petrol prices because of retail firms’ decisions, which should be the focus of policy makers.

Testing for integrated electricity series – A formalized synthesis of known problems

This paper reviews and discusses methodological choices and statistical inferences relevant to the literature that has worked at identifying long-memory behaviours within the stochastic features of electricity series (consumption and prices). We argue that persisting divergences reported in this literature can be linked to the (non)-treatment of key identification challenges in time-series econometrics. We synthetized those problems in a formalized fashion focusing on the followings: presence of structural breaks in the series (i); inferences affecting panel data structure such as cross-sectional dependence among the series, heterogeneous slope coefficients as well as the problem of missing observations (ii); the issue of integrated time-series observed with noise and some implications for cointegrated relations (iii).

Vulnerability of Food Security in the Presence of Deteriorating Exchange Rate Regime in Pakistan

This study aims to investigate the relationship between Food Security and Exchange Rate in Pakistan. The Augmented Dicky Fuller and Zivot Andrew tests of stationarity and the ARDL approach to cointegration have been used. The Gregory Hansen test of cointegration is applied to confirm the ARDL Bounds Test outcomes in the presence of Structural Breaks in the series. In Pakistan, the Exchange Rate has a significant deleterious influence on Food Security in the long run. For GDP growth, Arable Land and Agriculture Value Added, there is a significant positive long run association with Food Security. But, only Arable Land has a short run significant positive impact on food security in Pakistan. Therefore, amassed Arable Land is worthy for improving the food security situation both in the short and long runs. The flagging exchange rate in Pakistan is not advantageous for food security, as the country is a net importer.

Spillover Effects in the Presence of Structural Breaks, Persistence and Conditioned Heteroscedasticity

The intention of this article is to develop an instrument to overcome the limitations caused by traditional analyses and present a combined STR — Smooth Transition Regression model (EGARCH, STRIGARCH, and STR-FIEGARCH) to analyze the contagion effects of the 2008 financial crisis. The proposed instrument will aid the analysis of contagion and the impact of changes in long-term interest rates on the returns of international stock indices and forecasting, with special emphasis on the effects caused by structural breaks, persistence, and conditioned heteroscedasticity. The methodology begins with unit root tests with one and two structural breaks. In the second step, the asymmetry will be analyzed considering the STR models, which will determine the asymmetry relationship between interest rates and the long term, so that in a later step, these asymmetries will be used in the composition of a volatility estimation model, being based on the ARCH models: (i) EGARCH and (ii) FIEGARCH. This study provides a useful instrument based on modeling techniques to make the decision-making process more efficient and objective, providing a choice of instruments that assess the effect of changes in interest rates on stock market indices when influenced by falls, with structural data and better forecasting performance. The results show that the developed mixture models obtained better performance in predicting the effect or impact of changes in interest rates on stock market indices when influenced by structural breaks. STR and the ARCH family are useful instruments that make the decision-making process clearer and more objective when choosing instruments that assess the spillover effect of long-term interest rates on the profitability of international financial indices.