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Purpose: The relationship between public expenditure and revenue that determines the budget balance in the explanation of budget deficits is very important. This study aimed to examine the association between public spending and income in Turkey. Methodology: This article applies the continuous wavelet transform method (CWT) to study the relationship between government revenues and expenditures in Turkey. The study, which covers the period 2006-2020, consists of monthly data. The following four CWT tools were used in the analysis: Wavelet Power Spectrum, Cross Wavelet Power, Wavelet Coherence, and Phase Difference. Results: The results of the study, controlling taxes rather than expenditures, play a key role in reducing fiscal deficits in Turkey in the short term. It is revealed that the dynamics of the budget balance in the medium term can be explained by the spend-tax hypothesis and that the tax burden can be alleviated by spending cuts. In the long term, results were obtained that support the spend-tax hypothesis. Conclusion: The paper reveals that taxes play an important role in controlling budget deficits in the short run. It turns out that the dynamics of the budget balance can be explained in the medium term by expenditure cuts and then the tax burden can be alleviated. In the long run, implementing fiscal policies based on public spending rather than taxation will be more effective against budget deficits.

It is essential for sustainable economic development to comprehend how environmental factors impact public health. This study analyses this relationship in the context of Pakistan using long‐term data. This study aims to determine how environmental factors influence health production function in Pakistan to enlighten policy decisions that can improve human life and advance the cause of sustainable development. We hypothesize, based on prior research, that urbanization and rainfall will increase life expectancy in Pakistan, while deforestation, temperature, and CO2 emissions will decrease it. To verify our theory, we use the autoregressive distributed lag (ARDL) method to calculate the long‐run association between the variables, as well as the Zivot–Andrews and Lee–Strazicich unit root tests to identify structural breaks. Utilizing the bound and Gregory–Hansen co‐integration tests, co‐integration is confirmed. According to ARDL estimates, there are statistically significant correlations between factors that affect Pakistan's life expectancy, such as deforestation, temperature, and CO2 emissions, as well as rainfall and urbanization. The findings of this study underscore the importance of addressing environmental degradation and deforestation in Pakistan. For enhancing human life and achieving sustainable development objectives in the nation, it is essential to modernize forest laws and regulations and adopt eco‐friendly technologies. [ABSTRACT FROM AUTHOR]

Purpose: The relationship between public expenditure and revenue that determines the budget balance in the explanation of budget deficits is very important. This study aimed to examine the association between public spending and income in Turkey. Methodology: This article applies the continuous wavelet transform method (CWT) to study the relationship between government revenues and expenditures in Turkey. The study, which covers the period 2006-2020, consists of monthly data. The following four CWT tools were used in the analysis: Wavelet Power Spectrum, Cross Wavelet Power, Wavelet Coherence, and Phase Difference. Results: The results of the study, controlling taxes rather than expenditures, play a key role in reducing fiscal deficits in Turkey in the short term. It is revealed that the dynamics of the budget balance in the medium term can be explained by the spend-tax hypothesis and that the tax burden can be alleviated by spending cuts. In the long term, results were obtained that support the spend-tax hypothesis. Conclusion: The paper reveals that taxes play an important role in controlling budget deficits in the short run. It turns out that the dynamics of the budget balance can be explained in the medium term by expenditure cuts and then the tax burden can be alleviated. In the long run, implementing fiscal policies based on public spending rather than taxation will be more effective against budget deficits. [ABSTRACT FROM AUTHOR]

Amid China's dynamic economic backdrop, Economic Policy Uncertainty (EPU) and stock market indices hold pivotal roles, this research delves into EPU and its connection with the stock price index (SPI). By uncovering patterns linking these variables, the study aims to provide a nuanced understanding of their relationship. We employ wavelet coherence analysis and a phase difference approach to investigate EPU impact on China's SPI from 2010 to 2020. Through this lens, the interactions between these economic variables are illuminated. Using wavelet coherence analysis, the temporal dynamics of EPU and SPI are explored. The phase difference approach further highlights the temporal alignment of fluctuations, capturing the intricate relationship. The analysis reveals compelling findings. A robust correlation between EPU and the SPI emerges, particularly at low frequencies, underscoring a substantive connection. The phase difference analysis indicates a positive influence of EPU on stock prices, highlighting its impact on SPI. Besides, implications imply EPU shapes stock market behavior, moving beyond mere correlation. A causal link is established, emphasizing EPU's proactive role in influencing stock prices. Bidirectional causation underscores the interdependence of EPU and stock price movements. This research enhances understanding of EPU's effects on stock prices in China. Finally, this study provides important implications for investors, policymakers, and businesses, guiding strategic decisions amid a dynamic economic landscape. [ABSTRACT FROM AUTHOR]

This paper aims to revisit the interdependency between business conditions, climate policy change, and the environmental pollution of the USA. Interestingly, our paper represents a completion to the existing literature on three levels at least. First, we propose to analyze this issue during normal periods and periods of turmoil, particularly the COVID-19 outbreak. To do so, contrary to previous studies that used economic growth, we employ the ADS index as a real-time business conditions measurement. Second, we employ a frequency approach, based on the continuous wavelet transform, allowing us to understand the nature of the relationship. Understanding whether the relationship holds in the short- or long-term is useful for policymakers in monitoring public policies to achieve CO2 emission reduction as well as to investors interested in high value-added projects. Our analysis shows that, during the last two decades, the relationship between business conditions as well as climate uncertainty index and CO2 emissions is observed during the long- and short-term, and driven through economic conditions. However, during the crisis periods, the effect is detected across various scales and the relationship is bi-directional. Our results have several practical implications for the US policymakers to consider when setting policies for fighting pollution emissions and environmental protection. [ABSTRACT FROM AUTHOR]

The gravest challenge for economic sustainability is the undetermined growth in the financial and economic risks of the nation, which need to be overcome with adequate measures without compromising economic growth. The uncertainty of economic factors produces fluctuations in the financial sector and makes them more vulnerable. However, the existing literature has not significantly focused on the economic and financial risk challenge for sustainable economic growth. Therefore, to fill the gap, an in-depth study is imperative to explore the association between these risks. To do so, this study incorporates both economic and financial risk to determine how risks are interconnected across time (frequency) and how they are linked by utilizing quarterly data from 1984-Q1 to 2020-Q4 and by applying both the “wavelet power spectrum (WPS)” and “wavelet coherence (WTC)” approaches, to examine the time-frequency dependency of each variable on the other. The findings of WTC revealed that the economic and financial risks have a positive dependency on each other in India at high, medium, and low frequencies. Likewise, the wavelet power spectrum outcomes reflect the high economic and financial risks vulnerability during 1991, 1992, and 1996. In addition, for the robustness check, the study employed both the “quantile regression (QR)” and “quantile-on-quantile regression (QQR)”. Both the QQR and QR endorsed the positive association between FR and ER. Hence, our paper is the first research of its kind for the Indian economy, and it extends to the existing literature by examining the link between the two most significant indicators in terms of both time and frequency dependency. The findings in our paper offer excellent perspectives for investors and policymakers to assess prospects for investment and policy changes if necessary.

Various empirical studies have examined the nexus between financial markets, but this study focused on the comovement among prominent markets. Our study examines the interrelationship among main financial markets, i.e., stock, oil, and commodity during the recent pandemic. The interconnections among the selected markets are investigated using a battery of wavelet coherence tools and the Granger causality test. From the wavelet coherence analysis, our findings indicate strong co-movements among the VIX, oil volatility, and commodity prices during pandemic and localized in all scales and over the sample period. The dependency strength among the considered economies is noted to increase in pandemic, which implies increased short- and long-term benefits for the investors. Moreover, Our result exhibits a feedback causality between OVIX and crude oil, VIX and S&P 500, and gasoline and VIX. Interestingly, a unidirectional causality exists between VIX and crude oil, S&P 500 and crude oil, Brent and crude oil, gasoline, crude oil, and VIX and OVIX. We advocate that the findings will be helpful for portfolio managers, investors, and officials around the world. [ABSTRACT FROM AUTHOR]

The Iraqi economy is a rentier economy; it depends heavily on crude oil revenues to finance the federal general budget. Hence, when any volatility in crude oil prices occurs, it will directly affect public revenues, so the fiscal policy goes to exceptional resources to finance the budget, including the internal public debt. Based on the pertinent conversations, this paper aims to study the impact of volatility oil prices on internal public debt by applying (ICSS) and the wavelet approach on the monthly dataset covering the period between 2004 and 2021. we found many breakpoints in the time series; it was the same as an increase in the proportion of the internal public debt and debt returns and debt growth rate at a significant level of 5%. And then, we found that the positive impact between the volatility oil prices on internal public debt variables is identified by considerable alterations throughout time during the sample period. Therefore, the most important requirements for economic stability are to diversify the sources of public revenue and reduce dependence on crude oil as a major resource for the public budget to avoid any shocks in global oil prices. [ABSTRACT FROM AUTHOR]

This study examines the relationship between stock returns and inflation in the United States from 1800 to 2017 using wavelet techniques, complemented with linear and nonlinear causality approaches. Wavelet analysis shows evidence of weak co‐movement between stock returns (real and nominal) and inflation in the short run and strong co‐movement between them in the long run. A movement towards the long run increases the strength of co‐movement between the two variables. Analysis based on annual data and time domain indicates unidirectional causality running from nominal stock returns to inflation using both linear and nonlinear causality tests. However, causality between real stock returns and inflation vary depending on the tests employed. Time‐scaled analysis shows that irrespective of the causality tests, a feedback relationship exists between stock returns (nominal and real) and inflation at the intermediate and long time scales. Results based on monthly data for time domain show bidirectional causality between stock returns (nominal and real) and inflation using both linear and nonlinear causality tests. Analysis by frequency bands reveals that, irrespective of the causality tests, stock returns (both nominal and real) have no link with inflation in the short to medium term. Some important policy implications are derived from the foregoing findings. [ABSTRACT FROM AUTHOR]

The transmission line is an integral part of the electrical power system; however, a fault has a negative impact on the system, like blackout, power loss, financial losses, and socio-economic impact. This fault occurs due to ageing conductors, lightning stroke, switching surge and human interference. We reviewed the protection scheme implemented in the Nigerian transmission network, which has challenges relating to the environment's terrain and a long-distance transmission line of about 20,000 km. The different approach of fault classification, detection and location was analyzed and critically summarized. This review paper proposes a hybrid artificial neural network (ANN) and distance protection scheme that can automatically identify, locate, isolate, predict, correct faults, and real-time monitor and control the entire network. It can also detect the shortest possible trip time of 0.02 s and 0.03 s of line current and fault losses, respectively, during fault to avert damage on the line. However, this method has its challenges, such as the volume of data generated from load flow analysis, training time, and the total distance covered by the network. However, these can be averted by segmenting the entire network for easy evaluation and monitoring to achieve set goals. [ABSTRACT FROM AUTHOR]

In the real world, economic covariates follow asymmetric and time-varying patterns. Therefore, it is imperative to integrate these effects while estimating environmental and economic relationships. Although prevailing literature reveals various emissions-deriving and eliminating factors, however, there is a dearth of empirical evidence that estimates the asymmetric and time-varying effect of globalization, natural resources, and financial development from a multidimensional perspective in China. In doing so, we employ the nonlinear autoregressive distributed lag (NARDL) and cross-wavelet modeling framework to explore the long- and short-run nonlinear and time-variant association between globalization, natural resources, financial development, and carbon emissions from 1980 to 2017. The NARDL method has the benefit of discriminating the long-term and short-term asymmetric carbon emission responses due to a positive and negative shock in our primary variables of interest. Mainly, the findings of NARDL estimations confirm that positive shocks in globalization and financial developments have a significant positive impact on carbon emissions, whereas negative shock in natural resources has a significant positive impact on carbon emissions. Similarly, the outcomes of continuous wavelet transformation and wavelet transformation coherence confirm the causal linkages between covariates; however, this effect varies across different time and frequency domains. These results imply that environmental researchers should consider asymmetric transmission channels and time–frequency associations among variables to devise long-term sustainable policies. [ABSTRACT FROM AUTHOR]

The current study investigates the connectedness between US COVID-19 news, Dowes Jones Index (DJI), green bonds, gold, and bitcoin prices for the period 22 January 2020-3 August 2021. The study has employed wavelet coherency, the continuous wavelet transform, and the waveletbased Granger causality methods to obtain the dependence result. The continuous wavelet transform (CWT) analysis reveals that the United States equity market prices are extremely sensitive with regard to spreading coronavirus (USCOVID-19) news and changes in the oil price. Green bonds, gold, and bitcoin have minimal connectedness with the equity market, which might lead to the hedge and safe haven role of these assets during the COVID-19 crisis period. Lastly, very strong comovement was found between bitcoin and gold during the entire sample. The results of the present study offer a number of fresh and noticeable policy implications for international investors and asset managers. [ABSTRACT FROM AUTHOR]

This study aims to investigate the relationship between the tourism activities and price level in Pakistan by using monthly data set from 1972 to 2016. In this study, aggregated as well as disaggregated price level have been considered. Co-integration results suggest significant long-run relationship between tourism and all price level of goods and services except fuel and lightning. Results of the wavelet transformation show a strong variation in short-run. The results of the wavelet transformation coherence also show an in-phase as well as out-phase both associations between the prices and tourism receipts in the mid-term and long-term periods. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate the dynamics of the co-movements of energy and banking sector credit default swaps (CDS) spreads with global financial and economic policy uncertainty and risk factors in the United States and Europe. We first employ the standard quantile regression approach to examine the co-movement dynamics under different credit market conditions. The empirical results show that the standard quantile regression fails to capture the co-movement between the U.S. and European CDS spreads and the economic policy uncertainty and risk factors for all quantiles. However, after decomposing the raw series at various scales of resolution, using the wavelet approach to capture the structure, we find that the financial and energy related CDS spreads co-move with the economic policy uncertainty and stock market risk in the intermediate and lower frequency domain. That is, there is a dependency in the intermediate and higher time scales or the intermediate and long investment horizons for both the United States and Europe. However, there are positive effects of the stock market risk index on the U.S. banking CDS spreads, which remain almost similar across quantiles, but the effects are asymmetric for the European banking spreads. The study also provides policy implications. [ABSTRACT FROM AUTHOR]

In this study, the continuous wavelet transformation approach is employed to test the dynamics of the causality between two principal inflation indices i.e. consumer price index (CPI) and producer price index (PPI) based on monthly data from 1990:5 to 2013:12 for the Iranian economy. Analyzing the dynamics of causality between these two inflation indices could provide significant policy implications. One of the dominant aspects of this approach compared with the conventional causality tests is that it has a higher ability in analyzing dynamics of causality between time series. The wavelet, as a band pass filter to the time series, is stretched in time by varying its scale, which makes it possible to show the short run and long run causalities between the time series. In this paper, we apply the continuous wavelet transformation to study the inflationary cycles of the Iranian economy. The results confirm both demand-pull and cost-push nature of inflation by indicating bidirectional causality between the CPI and PPI. In fact, the causality directions vary over time depending on different economic conditions.

• Dynamic nexus between the carbon emission price and climate change. • Novel measures of physical and transitional climate risks. • Wavelet coherence approach to European and North American cap-and-trade programs,. • Strong correlation between carbon prices and transitional climate risks since 2019. • Positive relationship between carbon prices and physical climate risks before Paris agreement. We examine the dynamic nexus between the carbon emission price and climate change concerns using novel measures of alternatively both physical and transitional climate risks. We apply a wavelet coherence approach to European and North American cap-and-trade programs, highlighting strong correlation between carbon prices and transitional climate risks since 2019. We also reveal a positive relationship between carbon prices and physical climate risks before the Paris Agreement, with this relationship becoming negative in February 2022. Our findings show the important role of climate change concerns on the dynamics of the carbon market. [ABSTRACT FROM AUTHOR]

The gravest challenge for economic sustainability is the undetermined growth in the financial and economic risks of the nation, which need to be overcome with adequate measures without compromising economic growth. The uncertainty of economic factors produces fluctuations in the financial sector and makes them more vulnerable. However, the existing literature has not significantly focused on the economic and financial risk challenge for sustainable economic growth. Therefore, to fill the gap, an in-depth study is imperative to explore the association between these risks. To do so, this study incorporates both economic and financial risk to determine how risks are interconnected across time (frequency) and how they are linked by utilizing quarterly data from 1984-Q1 to 2020-Q4 and by applying both the "wavelet power spectrum (WPS)" and "wavelet coherence (WTC)" approaches, to examine the time-frequency dependency of each variable on the other. The findings of WTC revealed that the economic and financial risks have a positive dependency on each other in India at high, medium, and low frequencies. Likewise, the wavelet power spectrum outcomes reflect the high economic and financial risks vulnerability during 1991, 1992, and 1996. In addition, for the robustness check, the study employed both the "quantile regression (QR)" and "quantile-on-quantile regression (QQR)". Both the QQR and QR endorsed the positive association between FR and ER. Hence, our paper is the first research of its kind for the Indian economy, and it extends to the existing literature by examining the link between the two most significant indicators in terms of both time and frequency dependency. The findings in our paper offer excellent perspectives for investors and policymakers to assess prospects for investment and policy changes if necessary., (© 2023 The Authors. Published by Elsevier Ltd.)