Structural Breaks Research Articles

The Impact of the Tourism Industry on Economic Growth in Afghanistan (2008 – 2020)

This study aims to explore the relationship between Afghanistan’s tourism industry and its economic growth. We utilized the ARDL model with structural breaks and time series data spanning from 2008 to 2020, the result reveals that both tourism expenditure and revenue significantly affect Afghanistan’s economic growth, in both long and short periods. Particularly, a unit rise in international tourism expenditure leads to a 0.692 unit increase in economic growth, meanwhile, a unit rise in global tourism revenue leads to a 0.125 unit increase in economic growth. These findings provide valuable insights for policymakers to enhance tourism development and allocate resources effectively. It also encourages domestic and foreign investment by showcasing tourism's economic potential. Additionally, local communities, particularly in areas like Bamyan and the Wakhan Corridor, can leverage opportunities in hospitality, handicrafts, and cultural tourism.

Stochastic convergence behaviour in carbon dioxide emissions: Fourier panel unit root approach

ABSTRACT This study examines the convergence of per capita carbon dioxide emissions using two Fourier-based panel unit root tests allowing for smooth transitions. Additional panel unit root tests without structural breaks and with sharp shifts were conducted for comparison. The analysis spans 68 countries from 1965 to 2019. Results reveal non-stationarity in emissions for low- and middle-income countries, while emissions in high-income countries were stationary under constant and trend components. Evidence indicates limited convergence, with constrained forms observed only in high-income nations. These findings align partially with the Environmental Kuznets Curve hypothesis. This study offers nuanced insights into global carbon dioxide emission dynamics and enriches the empirical discourse on environmental sustainability.

A dataset of structural breaks in greenhouse gas emissions for climate policy evaluation

The quantitative assessment of policies aimed at climate change mitigation requires rigorously identifying abnormal changes in greenhouse gas emissions. We present a new dataset of robust level changes in greenhouse gas emissions that cannot be explained by aggregate socioeconomic fluctuations. Modern methods of structural break identification based on two-way fixed effects models are employed to estimate the size of significant level changes in emissions. The resulting dataset spans information for all major greenhouse gases in OECD countries across 37 IPCC sectors, from 1995 to 2022. The data unveils large differences in abnormal changes in emissions across gases, countries and sectors, as well as over time. Our resulting data can be applied to a broad range of research questions, including the analysis of the comparative efficacy of policy instruments to mitigate climate change.

Examining the Contribution of Trade to GDP: A Case Study of Pakistan

International trade contributes a significant role in economic development of a country. A country that performs well in international trade signifies economic stability. Pakistan has maintained International economic relationships with other countries over the years. This study examined the association of Gross domestic product (GDP) with exports, imports and trade openness in the perspective of Pakistani economy from 1985 to 2023 by using Ordinary Least Square (OLS) method. Descriptive statistics, unit root test and correlogram of Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) were determined. The data has been evaluated using EViews software. The outcomes of the research revealed that all series Exports, Imports and Trade Openness have significant impact on GDP. Moreover, Imports and exports have positive effect on GDP while trade Openness has negative impact on GDP. All the series were stationary at first difference I(1) whereas Residuals were stationary at level I(0). Through which it was concluded that Cointegration exist. Overall OLS model was best fit. But CUSUM square showed that model was not stable and have some structure breaks. It is recommended that researchers should extend this study and remove structure breaks by using state space models, Markov Regime switching and threshold models.

Forecasting realized betas using predictors indicating structural breaks and asymmetric risk effects

Forecasting realized betas using predictors indicating structural breaks and asymmetric risk effects

Enhanced Structural Break Detection in Functional Means

Enhanced Structural Break Detection in Functional Means

Extreme-value Test for Structural Breaks in Spatial Trends

Extreme-value Test for Structural Breaks in Spatial Trends

Assessing digital financial inclusion and financial crises: The role of financial development in shielding against shocks.

Digital financial inclusion (DFI) has been proven to be a central factor in driving economic development and reducing inequality in countries. However, its impact on financial crises (FC) has yet to be clearly examined, particularly in the context of current Financial Development (FD). Therefore, this study examines the influence of DFI on FC across 52 countries from 2004 to 2020, focusing on how this impact varies with the level of FD. Using a combination of Threshold Regression (PTR) and Bayesian regression methods, the research first identifies structural breaks in the DFI-FC relationship, with FD as the threshold variable. Bayesian regression is then employed to address challenges such as small sample sizes, endogeneity, and autocorrelation, while assessing DFI's differential impact across countries with varying FD levels. The PTR analysis reveals a threshold value of 0.6036, indicating a non-linear DFI-FC relationship depending on FD levels. In low FD countries, DFI reduces the risk of FC, whereas in high FD countries, uncontrolled DFI increases it. Based on the results, we suggest that financial institutions should strengthen efforts to promote investment in digital technology by implementing digital skills training programs, providing capital to businesses and individuals, and facilitating support from financial institutions in countries with low FD. Meanwhile, for countries with high FD, regulatory authorities should establish stricter regulations and supervision mechanisms for digital financial activities to mitigate the risks of FC.

The Asymmetric Relationship Between Oil Price Fluctuation on Exchange Rate Variation: Empirical Evidence from Malaysia and Thailand

The purpose of this study is to investigate the effects of oil price fluctuations on exchange rate variations, particularly for Malaysia and Thailand. The study utilizes monthly observation data from 1994 to 2021 and uses structural breaks, cointegration relationships, and Nonlinear Autoregressive Distributed Lag (NARDL) estimates. Both countries had distinct long- and short-term relationships, but there was also an asymmetric relationship between oil prices and multilateral exchange rates revealed by the study. The asymmetric and non-asymmetric causality relationship for both countries indicate a unidirectional non-asymmetric causality between the oil price and the exchange rate variation. The empirical findings will be of great assistance to policymakers in evaluating global oil price fluctuations as a crucial indicator for monitoring and stabilizing currencies as a long-term monetary policy strategy.

Sovereign Bond Holdings under Bank Competition in Vietnam

This article investigates the impact of bank competition on the holdings of sovereign bonds. Using bank-level data from Vietnam for 2007–2021, we design various proxies to indicate bank competition and apply the system generalized method of moments (GMM) to conduct main regressions. We find that banks are more likely to hold domestic treasury securities in response to greater market competition. We add strength to our analysis by conducting subsample checks to allow for potential structural breaks due to the financial and COVID-19 pandemic crises. In addition, we find that sovereign debt holdings are less prominent when banks are more inclined to search for higher income during periods of intense competition. Meanwhile, the risk profile of the financial institution does not modify the potency of the market competition-bond holding association. These results suggest that banks would retain more sovereign debt under competitive pressure for strategic rather than precautionary motives.

Retraction notice: Exploring the influencing factors of environmental deterioration: evidence from China employing ARDL–VECM method with structural breaks

Retraction notice: Exploring the influencing factors of environmental deterioration: evidence from China employing ARDL–VECM method with structural breaks

Economic Determinants of E-Commerce: A Frequency-Domain Causality Analysis of CPI and Personal Loans in Türkiye

This study explores the relationship between e-commerce volume, the Consumer Price Index (CPI), and personal loan rates in Turkey, focusing on the period from 2015 to 2024. By employing time series analysis and frequency-domain causality tests, the research aims to identify the factors influencing the growth of e-commerce in Turkey, particularly in response to economic fluctuations. Traditional unit root tests, including the Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests, were used alongside the Zivot-Andrews test to account for structural breaks in the data. The findings suggest a significant positive impact of personal loans on e-commerce volume, while CPI fluctuations show a nuanced effect, with short-term inflation dampening consumer activity and long-term inflation promoting price-sensitive shopping behaviors. Frequency-domain tests further reveal that personal loans have a stronger long-term causal impact on e-commerce than CPI. These results underline the crucial role of digital finance mechanisms and consumer credit in supporting the expansion of Turkey’s digital economy. The study contributes to the literature by highlighting the interplay between economic indicators and e-commerce dynamics in emerging markets.

Mortality evolution in Italy: the end of regional convergence?

Abstract Between 1992 and 2007, the Italian healthcare system underwent a profound and complex transformation. This reform rekindled interest in the study of health and mortality inequalities in Italy, and fears were expressed that the new system could trigger a rise in health disparities across regions. We contribute to the debate examining the evolution of life expectancy across Italian regions from 1974 to 2019, focusing on regional convergence. Applying sigma- and beta-convergence analysis in a novel way, we detect structural breaks—marked trend variations—occurring shortly after the most significant policy reforms of the national health system, with stronger discontinuities among males. While not establishing any direct causal link, our findings suggest that the legislative changes of the period, focused on decentralizing responsibilities and management, may have halted the pre-existing trend towards homogenization and possibly opened up a new phase of re-emerging regional survival disparities.

Reconsidering the pollution haven hypothesis: an investigation of international trade, foreign direct investment, and carbon emission nexus in Nigeria

ABSTRACT The interconnectedness among communities globally has heightened environmental concerns because of associated cross-border transactions. As such, we reconsider the impact of international trade (TR) and FDI on CO2 in Nigeria to test the PHH between 1981 and 2020 using the ARDL approach. The study utilises the Lee-Strazicich (L-S) unit root test for a structural break and the Toda-Yamamoto Granger causality test. FDI causes CO2, whereas TR and CO2 influence each other. The ARDL estimates show that TR and FDI reduce CO2 in the short run but positively affect long-run CO2, supporting the long-run PHH. Government regulation positively impacts short-run CO2 while slowing CO2 discharge in the long run. The moderation effect shows that FDI*RQ increases CO2 in the short run and declines pollution in the long run. TR*RQ interaction reduces CO2 in both periods. The study concludes on green technology transfer and improvement in environmental regulations for sustainability drive.

Temporal networks with node-specific memory: Unbiased inference of transition probabilities, relaxation times, and structural breaks

One of the main challenges in the study of time-varying networks is the interplay of memory effects with structural heterogeneity. In particular, different nodes and dyads can have very different statistical properties in terms of both link formation and link persistence, leading to a superposition of typical timescales, suboptimal parametrizations, and substantial estimation biases. Here we develop an unbiased maximum-entropy framework to study empirical network trajectories by controlling for the observed structural heterogeneity and local link persistence simultaneously. An exact mapping to a heterogeneous version of the one-dimensional Ising model leads to an analytic solution that rigorously disentangles the hidden variables that jointly determine both static and temporal properties. Additionally, model selection via likelihood maximization identifies the most parsimonious structural level (either global, node specific, or dyadic) accounting for memory effects. As we illustrate on real-world social networks, this method enables an improved estimation of dyadic transition probabilities, relaxation times, and structural breaks between dynamical regimes. In the resulting picture, the graph follows a generalized configuration model with given degrees and given time-persisting degrees, undergoing transitions between empirically identifiable stationary regimes. Published by the American Physical Society 2024

On the Detection of Structural Breaks: The Case of the Covid Shock

ABSTRACTBoth the Federal Reserve (Fed) and the European Central Bank (ECB) have been criticized for not having perceived that the outbreak of Covid at the beginning of 2020 would lead to a structural change in inflation in the early 2020s. Both central banks viewed the initial inflation surge in 2021 as temporary and delayed monetary tightening until 2022. We argue that the existing literature on structural breaks could not have been useful to policymakers because it identifies the breaks in an arbitrary way. The tests used to identify breaks do not incorporate prior knowledge that a break may have occurred so that the tests have very little power to detect a break that occurs at the end of the sample. We show that, in the event of a major shock, such as Covid, using knowledge that a break may have occurred and testing for a break in a recursive way as new data become available could have alerted policymakers to the break in inflation. We conduct Monte Carlo simulations suggesting that our method would have identified that a break had occurred in inflation by the end of 2020, well before policymakers had perceived the break.

Does less finance harm economic growth as well? A nonlinear smooth transition model (STAR) perspective

ABSTRACT Our study provides an in-depth examination of the relationship between financial development and economic growth in Morocco, revealing key threshold effects through a nonlinear smooth transition model (STAR). Analysis of Moroccan banking and stock market development indexes reveals that the stock market was significantly impacted by the 2008 global financial crisis, showing a decline, while the banking system continued an upward trajectory. STAR model estimation further underscores a nonlinear relationship, marked by three structural breaks over the 1987–2020 period. The novelty of this paper stems in the fact that it is the first in the literature to test the hypothesis ‘Does less finance harm economic growth as well?’ instead of the famous debate triggered by the 2008 global financial crisis ‘Does too much finance harm economic growth?’ Which led us to identify the threshold below which the Moroccan financial sector harms economic growth and which corresponds to 0.32 on the scale of our index.

Impact of Fossil Fuel, Renewable Energy, and Public-Private Partnership Investments on Sustainable Growth and Carbon Emissions in Pakistan

This paper examines the longer-term and causal impact of public-private partnership (PPP) investment in energy and technological innovation on consumption-based carbon emissions in Pakistan during the period from 1990 to 2023. This analysis includes important covariates, such as international trade (exports and imports), economic growth (GDP), and renewable energy consumption, to explore the factors influencing Pakistan's carbon emissions. The theoretical lens for the study is based on the Environmental Kuznets Curve (EKC) theory, which posits that economic growth can initially lead to rising carbon emissions, but stronger long-term technological development and a transition towards renewable energy would turn the tide against environmental degradation. Moreover, Transition Theory emphasizes the importance of PPPs and technological innovation in transitioning Pakistan's energy system from fossil fuels to sustainable energy solutions. By employing advanced estimation techniques, including the Maki cointegration test (1996) that accounts for multiple structural breaks, the research shows that the variables in question are bound in a long-run equilibrium relationship. An export and consumption of renewable energy indicate significantly reduced consumption-based carbon emissions, while more imports, GDP, and (PPP) investment in non- renewable energy positively relates to increased emissions according to results for 182 countries. Overall, the study presents solid empirical proof that trade, technological changes, and a move toward renewable energy can help lower carbon emissions in Pakistan. The authors further recommend the establishment of policies to promote renewable energy investments via PPPs, foster technological progress in low-carbon technologies, implement carbon pricing instruments, such as taxes on energy-intensive goods, and harmonize trade policies to promote low-carbon exports"

Evaluating the Impact of Oil Market Shocks on Sovereign Credit Default Swaps in Major Oil-Exporting Economies

This study analyzes the impact of oil market fluctuations on Sovereign Credit Default Swaps (SCDS) in three key oil-exporting economies: Saudi Arabia, Russia, and the United Arab Emirates (UAE). The study investigates how various oil shocks, namely demand, supply, and market risk, affect sovereign credit risk and how these effects are transmitted within and across these economies. Time-domain and frequency-domain analyses were used to categorize oil market shocks and structural break analysis was incorporated to account for significant global events. The findings indicate that Saudi Arabia is a primary source of credit risk volatility, influencing Russia and the UAE, with the latter being significantly affected as a net recipient of such risks. Structural breaks, such as those associated with the COVID-19 pandemic, introduce shifts in impact patterns. This study underscores the significant role of demand shocks in shaping sovereign credit risk across the countries examined. These insights are essential for policymakers, investors, and financial analysts focused on sovereign credit risk management in oil-exporting economies, highlighting the importance of considering structural changes in economic conditions.

Stochastic and club convergence analysis of environmental tax revenues across EU countries.

The European Union (EU) has taken several initiatives over the past two decades to harmonize environmental taxation policies across member countries. The directive on energy taxation (Directive 2003/96/EC) provides the framework for the taxation of energy products within the EU. These harmonization efforts are part of a broader strategy to ensure environmental sustainability and combat climate change. This paper examines whether these efforts have had any impact on the convergence of environmental taxation across EU countries during the period 1995-2021. This paper uses a new panel unit root test that accounts for cross-correlations and structural breaks within the panel since regulations on taxation increase the possibility that EU countries may have commonalities on these issues. The club convergence test is also used to test for the existence of multiple equilibria within groups of countries. The results of the traditional convergence test show that environmental tax revenues are converging across EU countries. Furthermore, the results of the stochastic convergence test indicate that there is a convergence of relative environmental tax revenues. As for the break dates, the results from the tax revenue series show that the first and second break are concentrated in the periods 2002-2007 and 2012-2017, respectively. Finally, the results of the club convergence test reject the full panel convergence and reveal the existence of different convergence clubs. The empirical results of this paper have some implications for environmental taxation in the EU.