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We use a co-authorship network analysis to describe and examine the social network of researchers studying physical education content knowledge worldwide. Co-authorship network analysis is a method for determining the scope, trend, and focus of research around a topic. It provides a way to evaluate both the growth of a field and to examine the extent of research collaboration. Our review consists of 101 articles that were examined in our network analysis. Our results show that the research on content knowledge occurs within and among 13 high-income economies. Research productivity in this area is on an upward trajectory since 1990. The research in physical education occurs in a distributed network with some authors serving as key hubs for research collaboration. From a global perspective, there is a need to create links to low-income economies to strengthen their research capacity. [ABSTRACT FROM AUTHOR]

The paper presents evidence on the relationship concerning military spending among Southeast Mediterranean countries (Greece – Turkey, Israel – Egypt, Israel – Turkey) over the period 1962–2020. We account for the presence of nonlinearities in the bilateral relationships of defence spending by applying Threshold Autoregressive methodologies and utilize kink regression analysis to detect the existence of a country's military spending threshold that signals a threat to another country of the region. Our empirical results show: First, there is a nonlinear strategic interaction between the countries examined, in the sense that their defence spending policy is cointegrated. Second, there is no arms race among the countries examined, but only unilateral effects. Third, there is consistent evidence of a possible military spending equilibrium, in the absence of friction between the countries involved (peace threshold). Our findings have important policy implications as they indicate, first, that each country in the region should not determine its level of military spending considering only operational factors, but also considering the signaling of its military spending on its neighboring countries and, second, that there is space for peaceful solutions regarding disputes in the Southeast Mediterranean region. [ABSTRACT FROM AUTHOR]

An effective feature vector generation approach is herein presented based on the cointegration concept and the signal processing methods in order to improve varying speed bearing troubleshooting. Initially, each vibration signal is decomposed into its intrinsic mode functions (IMFs) using ensemble empirical mode decomposition method. Then, the cointegration relations are extracted by applying the Johansen trace test method to the obtained components. In order to form the feature matrix, the cointegration relations are analyzed by wavelet packet transform and the time-domain features are calculated for the wavelet packet coefficients. Consequently, by using a hybrid feature selection approach based on compensation distance evaluation technique, support vector machine, and binary particle swarm optimization algorithm, the optimal hybrid features were identified. The experimental results show that the optimal features are composed of the first cointegration relation, the third level of wavelet packet coefficients, the third IMF, Teager–Kaiser energy, energy, and root mean square. Also, the number of optimal features obtained from the first cointegration relation was less than other relationships. The results reveal that when the optimal feature set is computed for the first cointegration relationship, the identification accuracy of the proposed approach increases considerably. The result analysis also shows the efficiency of the proposed technique in detecting the condition of the bearing in time-varying rotational speed. [ABSTRACT FROM AUTHOR]

Conventional pairs trading strategies (PTS) exploit the mean-reverting nature of stock pairs with stationary value processes. This paper elevates PTS by integrating trend-stationary value processes, thereby enhancing profitability and expanding trading opportunities. Our asymptotic analysis reveals that the value process, adjusted for the derived slant asymptote, adheres to a stationary distribution. By capitalizing on price deviations and value trends, the strategy profits by longing undervalued or shorting overvalued processes based on their respective upward or downward slopes. Positions are strategically closed when they revert to the asymptote, thus securing profits and avoiding counterproductive trades against prevailing trends. In this context, conventional stationary-based PTS can be considered a specific instance of our broader approach when the asymptote is non-trended. To refine trade selection, we evaluate the mean-reversion velocity, monitoring the frequency at which the portfolio's value crosses the slant asymptote to exclude high-risk pairs. Empirical evidence underscores our method's superiority over conventional stationary PTS, delivering higher average returns per trade, improved Sharpe ratios, and increased trading opportunities, even amidst the financial uncertainties of the COVID era. [ABSTRACT FROM AUTHOR]

Corruption has been one of the challenging topics in public economics for years, prompting extensive discussions from various perspectives. In this study, we investigate the causal relationship between government size and corruption in Turkey, where the anticorruption performance has been getting worse over time until recently. By utilizing a long-span news-based corruption index spanning approximately three-quarters of a century, we conclude that government size serves as the long-term driving force behind corruption in Turkey from 1950 to 2019. This conclusion is robustly reached through a battery of dynamic time series analyses. [ABSTRACT FROM AUTHOR]

This note presents insights on the Jordan structure of a matrix which are derived from an extension of the I(1) and I(2) conditions in Johansen (1996). It is first observed that these conditions not only characterize, as it is well known, the size (1 or 2) of the largest Jordan block in the Jordan form of the companion matrix but more generally the geometric multiplicities, the algebraic multiplicities and the whole Jordan structure for eigenvalues of index 1 or 2. In the context of the Granger representation theorem, this means that the Johansen rank conditions do more than determine the order of integration of the process. It is then shown that an extension of these conditions leads to the characterization of the Jordan structure of any matrix. [ABSTRACT FROM AUTHOR]

The intricate relationship between economic growth, environmental quality, and energy consumption has been extensively debated and studied on a global scale. The impacts of ecological quality on economic growth have been observed to be both positive and negative, particularly about human health as a result of pollutant emissions. It is essential to examine the compatibility between economic growth and environmental improvement, particularly through the reduction of emissions. This study aimed to investigate the connection between economic growth in forested areas and the corresponding impact on carbon dioxide (CO2) emissions in Nepal (Rose and Fisher, 1970). The analysis utilized time series data from 1990 to 2020, employing the dynamic ordinary least squares (DOLS) method. The DOLS results demonstrated a positive and statistically significant relationship between economic growth and CO2 emissions (Shafik and Bandyopadhyay, 1992). Specifically, an increase of Rs. 10 million in gross domestic product (GDP) corresponded to a 0.6112 kiloton increase in CO2 emissions. In contrast, the long‐term coefficient for forested areas exhibited a substantial association, indicating that a reduction of one square kilometer of forested area (deforestation) resulted in an increase of 68.37 kilotons in CO2 emissions in Nepal. These findings accentuate the divergent effects of economic progress and deforestation on carbon emissions in Nepal, with GDP growth contributing to a greater increase in emissions. Therefore, the implementation of effective strategies and economic measures, such as afforestation and reforestation, forest protection, sustainable forest management, and mechanisms like REDD+ (reducing emissions from deforestation and forest degradation plus), can play a vital role in mitigating carbon emissions while simultaneously addressing deforestation and ensuring long‐term economic progress in Nepal. [ABSTRACT FROM AUTHOR]

Data-driven models have become powerful tools for structural and condition monitoring of engineering systems, particularly wind turbines. This paper presents a comparative analysis of common machine learning (ML) algorithms (artificial neural networks, linear regression, random forests, and gradient boosting) and a cointegration-based approach for fault detection using Supervisory Control and Data Acquisition (SCADA) data. While ML models offer early fault prediction, the cointegration method is simpler, requires less training data, and has lower computational costs. However, it is less effective for early detection. To balance these trade-offs, we propose a cascading monitoring framework, where the ML model provides long-term predictions (outer monitoring process) and the cointegration model offers short-term verification (inner monitoring process). The cointegration model serves to confirm anomalies flagged by the ML model. By combining both models in a cascade structure, the system reduces the risk of false alarms triggered by uncertainties in the ML model alone. Furthermore, the short-term cointegration-based prediction model helps pinpoint immediate risks and mitigate the issue of prolonged downtime. This combination enhances both accuracy and reliability, as demonstrated through testing on a five-year SCADA dataset from a commercial wind turbine with a known gearbox fault. [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM AUTHOR]

Although considerable discussion has been devoted to the macro determinants of labor market variables across genders, comparatively little attention has been given to the contribution of the informal economy to this market. This study was aimed at empirically investigating the impact of the size of the shadow or informal economy (IE) on labor market variables across genders in 12 Middle Eastern countries. The study used quarterly time series data on each country under investigation, covering 1991 to 2015. Phillips–Perron unit root tests were carried out to verify the stationarity of the examined economic series. An autoregressive distributed lag approach was adopted to conduct cointegration tests and estimate long-run regression coefficients and error correction terms. The results indicated that the IE served men and women differently across countries. Whereas this economy had a long-run positive relationship with men's employment rates in Bahrain, Iran, Qatar, and Turkey, this relationship existed among women only in Israel. IE activities matter in the employment of men and women in Middle Eastern countries. The sizes of IEs in the labor market are a significant factor that favors men's employment rather than that of women. [ABSTRACT FROM AUTHOR]

The study attempts to measure RMB real effective exchange rate (REER) equilibrium and its associated degree of misalignments for China using the behavioral equilibrium exchange rate (BEER) and permanent equilibrium exchange rate approaches. We use a range of economic fundamentals and employ yearly data covering the period 1980–2020, and apply the Johansen Cointegration test and other econometric methods for the study purpose. We find evidence of the existence of RMB real effective exchange rate equilibrium, and for most of the periods, the RMB REER is closer to its equilibrium level. We also find that the RMB REER misaligned with its equilibrium producing episodes of undervaluation and overvaluation, but the magnitude of the misalignments is small and the BEER approach produces a lower degree of misalignments. This suggests that the RMB undervaluation is moderate and not as exaggerated. We identify that the economic fundamentals used in this study are important determinants of RMB real effective exchange rate equilibrium. In line with the above, the study recommends that China may continue using its RMB exchange rate as its policy tool, but the policymakers should focus on the core fundamentals that derived the equilibrium exchange rate. [ABSTRACT FROM AUTHOR]

Using high-rate (1 Hz) global positioning system (GPS) data, coseismic displacement estimates are obtained for the 2023 Mw 7.8 Pazarcik and Elbistan Mw 7.5 Türkiye earthquakes. The estimated largest displacements caused by the Mw 7.8 event are observed at station ante with an eastward component displacement of 31cm and at station mly1 with a southward component displacement of 39cm. The displacements caused by the Mw 7.8 Pazarcik event show left-lateral displacements along the nodal plane, which is consistent with the focal mechanism. The largest displacements caused by the Mw 7.5 event are a westward component displacement of 450 cm and a northward component displacement of 97cm at the station ekz1 which is only 6 km from the epicenter of the event. Based on high-rate GPS time series, the surface wave propagation of the Mw 7.8 Elbistan earthquake is preliminarily estimated at an overall speed of approximately 2.9 km/s, with a slightly higher speed of 3.1 km/s along the northeast direction and 3.0 km/s along the east direction. High-rate GPS measurements show a prominent advantage of temporal resolution for earthquake sequences with short intervals, and preliminary displacement estimates could be made with only a few hours of observations. The displacement estimation provides constraints for the inversion of the rupture process and seismic source mechanisms. [ABSTRACT FROM AUTHOR]

This paper explores empirical evidence for a connection between income inequality and skill (advanced-level educated workers share) using panel data methods that take into account cross-section dependency and heterogeneity. To assess the income inequality associated with skill, we run a data set for 24 developed the Organisation for Economic Co-operation and Development (OECD) countries from 1995 to 2018. In order to determine the stationary characteristics of the variables, we employ the Cross-Sectionally Augmented Im, Pesaran and Shin (CIPS) test approach. Following this, we employ Westerlund (2007), and Gengenbach, Urbain, and Westerlund (2016) Panel Cointegration tests, and then the Panel Dynamic Ordinary Least Squares (PDOLS) estimator. Our empirical test results conclude that there is a relationship between inequality and skill in the long-run and the PDOLS estimator findings show that as the skill level in employment increases, inequality decreases. In addition, according to the findings, this negative relationship is more pronounced in the United States, whereas it is more moderate or not valid in European countries. The results obtained are primarily consistent with the framework presented by Acemoglu (2002, 2003). These findings constitute one of the main contributions of the study in terms of supporting Acemoglu’s (2003) thesis that the skill premium is more pronounced in the United States. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Finance Letters / Maliye Finans Yazıları Dergisi is the property of Maliye Finans Yazilari Yayimcilik Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We consider whether government bonds, through the term structure, or corporate bonds, through the default yield, provide predictive power for output, consumption and investment growth in the United States. Such predictive power will allow policy‐makers to use the information as a leading indicator for macroeconomic performance and will improve our understanding of the links between real and financial markets. Full sample results suggest that both interest rate series exhibit predictive power for each of the macroeconomic growth series. Time‐variation in the predictive coefficient reveals the waning influence of the term structure and the rising influence of the default yield. Forecast results, which are obtained from a rolling window approach, likewise suggest both series have information content for macroeconomic conditions, but there is a change in their relative strengths. These results may arise as interest rates have declined since the highs of the early to mid‐1980s thus reducing the information content of government yields, whereas corporate bonds respond more to investor views of macroeconomic risk, which affects a firm's ability to repay its debt. Furthermore, short‐term rates are largely held unprecedently low since the dotcom crash. [ABSTRACT FROM AUTHOR]

This empirical work analyzes the impact of tourism arrivals, tourist receipts, tourist expenditure, active population, and population density on environmental quality. Unlike previous studies, this study employed a consumption-based indicator of environmental quality, which is the material footprint. Given the significance of major tourist destination countries, a sample of the top ten tourist destinations has been selected for the analysis over the period 1995–2018. The study applies econometric tools that consider the issues of cross-sectional dependence and heterogeneity. The findings of cointegration show a significant long-run relationship between the variables. Similarly, pooled mean group results indicate a positive impact of tourist arrivals, tourist expenditure, and active population on the material footprint, while a negative impact is observed in the case of tourist receipts and population density. The robustness of long-run results has been examined with the help of Panel corrected standard errors. Moreover, the Dumitrescu-Hurlin panel causality test shows unidirectional causality from tourist arrivals and tourist receipt to the material footprint and unidirectional causality from the material footprint to tourist expenditure in the long run. According to our results, some policy implications have also been highlighted. [ABSTRACT FROM AUTHOR]

Purpose: This study presents time-series data estimations on the association between the indicators of institutional environment and inward foreign direct investment (FDI) in India utilizing a comprehensive data set from 1996 to 2021. Design/methodology/approach: The study employs the nonlinear autoregressive distributive lag (NARDL) model. The asymmetric ARDL framework evaluates the existence of cointegration among the factors under study and highlights the underlying nonlinear effects that may exist in the long and short run. Findings: The significance of coefficients of negative shock to "control of corruption" and positive shock to "rule of law" is greater when compared to "government effectiveness, regulatory quality, political stability/absence of violence." The empirical outcomes suggest the positive influence of rule of law, political stability and government effectiveness on FDI inflows. A high "regulatory quality" is observed to deter foreign investment. The "voice and accountability" index and negative shocks to the "rule of law" are exhibited to have no substantial impact on the amount of FDI that the country receives. Originality/value: This study empirically examines the institutional determinants of FDI in India for a comprehensive period of 1996–2021. The study's findings imply that quality of the institutional environment has a significant bearing on India's inward FDI. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0375 [ABSTRACT FROM AUTHOR]

Over the past three decades, Pakistan's energy consumption has surged due to industrialization, population growth, and development activities. To meet the escalating energy demands, the country has primarily relied on thermal power projects, which are financially burdensome and environmentally detrimental, compared to hydropower projects. This reliance exposes Pakistan to global oil price shocks and environmental degradation. To address this dilemma, this empirical research investigates the impact of both non-energy factors (labour and capital) and energy-specific factors (renewable and non-renewable) on Pakistan's aggregate output, using annual time-series data from 1980 to 2021. The analysis employs the newly established Residual Augmented Least Square (RALS) cointegration test and the Autoregressive Distributed Lag (ARDL) methodology to estimate the long-term cointegrating relationship among the examined variables. The empirical findings demonstrate that both non-energy and energy-specific factors positively and significantly influence Pakistan's long-term aggregate output. However, petroleum consumption exerts a positive but insignificant influence on Pakistan's long-term aggregate output. The study recommends diversifying the energy supply mix to include more hydroelectricity, non-hydroelectric renewables (mainly solar and wind), and natural gas. Specifically, transitioning from imported, expensive, and more greenhouse gas (GHG)-generating petroleum products to domestically produced natural gas could potentially reduce Pakistan's trade deficit and its vulnerability to global oil price shocks. Besides the economic benefits, shifting from non-renewable energy sources (specifically oil) to renewable energy would enhance Pakistan's image and increase its geopolitical influence over neighboring countries. Additionally, the study emphasizes the need to encourage private sector participation in renewable energy projects and suggests implementing effective carbon tax policies to mitigate CO2 emissions and foster economic growth. [ABSTRACT FROM AUTHOR]

Structural damage can affect the long-term operation of equipment. Real-time damage warning for structures can effectively avoid accidents caused by structural damage. In this paper, a real-time warning method of structural plastic damage based on the cointegration theory is proposed. This method calculates the cointegration relationship between the strain signals at different measuring points, and the stability of the strain signal relationships is also evaluated. The problem of inaccurate detection caused by the error of strain measurement and environmental influence can be eliminated by the comprehensive judgment of strain between asymmetrical measuring points. A real-time damage sensing system is developed in this paper. In order to improve the real-time and practicability of the system, this paper proposes and determines the residual warning coefficient by analyzing the proportion of the strain residuals exceeding the residual threshold. The research on this sensing system has certain value for the engineering application of damage monitoring methods. [ABSTRACT FROM AUTHOR]

Our study assesses the performance of a threshold vector error correction model (TVECM) for the analysis of spatial price transmission. We specifically determine how inference about price regimes and the process of price adjustment to the established long-run equilibrium is affected when the stochastic transaction cost is exogenously or endogenously determined in fixed and flexible threshold models. The study first generates non-stationary but cointegrated price series and transaction costs based on true price transmission parameters: percentage of violations of spatial equilibrium, speed of price adjustment, threshold and inaction band using Monte Carlo simulations. Then, the generated data are used to estimate TVECMs under various assumptions on transaction cost variation and threshold specification. Finally, estimates of price transmission parameters are compared with the true parameters to evaluate the performance of model specifications. Our results indicate that the flexible TVECM accounting for transaction cost variation outperforms the standard fixed TVECM, which is consistent with findings from many previous studies in the literature. Our study also finds that although the flexible TVECM performs better than the fixed TVECM, it may not fully address the limitation of linear models when a real-world data represents a complex nonlinearity in the spatial price transmission. [ABSTRACT FROM AUTHOR]

We investigate the impact of exchange rate volatility on exports and imports between South Africa and its main trading partners, namely the United States and China, across 22 import and export industries. The study employs the quantile autoregressive distributive lag (QARDL) model using quarterly data from the period spanning from 1994Q1 to 2022Q4. Our initial ARDL estimates establish that currency volatility does not significantly harm most trade sectors with both countries. In fact, many industries exhibit an insignificant or positive correlation with currency volatility. Nevertheless, upon re-estimating the regressions using the QARDL model, we uncover 'hidden cointegration' relationships existing at quantiles beyond the mean and median estimates, which are undetectable by traditional ARDL models. By considering these location-based asymmetries, we conclude that trade activities with China benefit more from exchange rate volatility compared to those with the United States. Overall, our findings imply that monetary authorities may not need to intervene in currency markets to stimulate trade with the top trading partners, as firms appear to be willing to bear the currency risks associated with the volatile Rand exchange rate. [ABSTRACT FROM AUTHOR]

Fractional cointegration in time series data has been explored by several authors, but panel data applications have been largely neglected. A previous study of ours discovered that the Chen and Hurvich fractional cointegration test for time series was fairly robust to a moderate degree of heterogeneity across sections of the six tests considered. Therefore, this paper advances a customized version of the Chen and Hurvich methodology to detect cointegrating connections in panels with unobserved fixed effects. Specifically, we develop a test statistic that accommodates variation in the long-term cointegrating vectors and fractional cointegration parameters across observational units. The behavior of our proposed test is examined through extensive Monte Carlo experiments under various data-generating processes and circumstances. The findings reveal that our modified test performs quite well comparatively and can successfully identify fractional cointegrating relationships in panels, even in the presence of idiosyncratic disturbances unique to each cross-sectional unit. Furthermore, the proposed modified test procedure established the presence of long-run equilibrium between the exchange rate and labor wage of 36 countries' agricultural markets. [ABSTRACT FROM AUTHOR]

The G7 countries, which represent a significant portion of global energy consumption and have a major impact on the World economy, consider energy to be of utmost importance. These advanced economies have a significant influence on global oil dynamics. Oil will continue to be a significant component of the global energy system, with an anticipated consumption of 70-80 million barrels per day by 2035. This study aims to investigate the causal relationship between oil consumption and economic growth in G7 countries from 1990 to 2022 using panel data analysis methods. The analysis employed Gengenbach et al.'s (2016) cointegration test and Emirmahmutoğlu and Kose's (2011) causality methods. The results indicate a cointegration relationship and a positive effect of oil consumption on economic growth. However, no causality relationship was detected between the variables, which supports the neutrality hypothesis in the literature. [ABSTRACT FROM AUTHOR]

Foreign investments, viewed as a matter of social responsibility, can improve environmental quality in the host country. In addition, although foreign investors promote economic development because they prefer countries where environmental policies are not stringent, they may increase environmental degradation by transferring dirty industries to host countries. However, in EU countries, environmental policies are strictly implemented, and incentives are offered to increase investments in clean sectors. In this context, there is a widespread opinion that greenfield investments will be environmentally friendly thanks to environmental regulations in EU countries. Despite this, no study has been found that analyzes these views empirically. In this study, the effect of greenfield investment and investment freedom on environmental quality in EU countries for the period 2003–2022 is investigated with panel cointegration and long-run estimators within the framework of the EKC hypothesis. According to the results of the study, while greenfield investment increases environmental quality in Italy and Romania, investment freedom increases environmental quality in Belgium, Croatia, Denmark, Italy and Spain. The EU should set a standard in order to attract environmentally friendly foreign investments, taking into account its strategic location and infrastructure. RESEARCH HIGHLIGHTS: The effects of greenfield investment and investment freedom on the ecological footprint are investigated. The environmental Kuznets curve (EKC) hypothesis is tested for EU countries. Greenfield investment positively influences environmental quality in Italy and Romania, while investment freedom has a positive impact in Belgium, Croatia, Denmark, Italy, and Spain. The study suggests that the EU can serve as a model by establishing standards to attract environmentally friendly foreign investments. [ABSTRACT FROM AUTHOR]

Supply chain instabilities and inflated material prices have had a disruptive impact on cost estimating of construction projects. While several research efforts used national macroeconomic indicators to forecast the prices of domestically produced construction materials, none of the existing studies investigated whether the lagged macroeconomic indicators of the main trading partners could enhance the predictability of the prices of cement, steel, and lumber in the US construction sector. This paper fills this knowledge gap. The authors adopted a multi-step methodology that included: (1) collecting data on the target variables and the candidate leading indicators; (2) identifying the structural breaks in the collected data sets; (3) conducting causality tests to identify short-term associations and cointegration tests to examine long-term relationships; (4) developing vector error correction (VEC) models to forecast the prices in the short and long terms; and (5) evaluating the performance of the proposed models against existing forecasting models in the literature. Results of the Granger test and Johansen test indicate that Canada's overall producer price index (PPI) is a consistent leading indicator of the prices of cement, and Mexico's overall PPI is a consistent leading indicator of the prices of steel. Findings indicate no statistical evidence to suggest that neither Canada's PPI nor Mexico's PPI can be leading indicators of lumber prices. Over an 18-month ahead of sample horizon, the presented VEC models of cement and steel prices outperformed existing models, particularly beyond the 1-year-ahead forecasts. Utilization of the proposed forecasting models can significantly enhance the accuracy of cost estimates and feasibility studies of construction projects. This provides proactive financial planning for construction contractors and project owners through improved short- and long-term forecasting of the prices of main construction materials. [ABSTRACT FROM AUTHOR]

In most cases, researchers assume that control of corruption, rule of law, accountability, and government expenditure tend to have a positive impact on government effectiveness. Nonetheless, recent theoretical and empirical evidence supports a mixed relationship between these variables. The paper, therefore, seeks to answer the extent to which corruption, the rule of law, accountability, and government expenditure affect government effectiveness. We employed Johansen method of cointegration and vector error correction model to examine the long-run and short-run relationship between the variables under study. By using Sri Lankan data covering the period from 1996 to 2020, we find a significant and positive relationship only between the control of corruption and government effectiveness both in the long run and in the short run. Yet, rule of law has a positive and significant impact on government effectiveness only in the long run. Voice and accountability, and government expenditure affect the government's effectiveness negatively in the long run and positively in the short run. The article demonstrates that weak anti-corruption mechanisms and weak legal and criminal justice systems seem to have a detrimental impact on government effectiveness in developing countries. [ABSTRACT FROM AUTHOR]

It is prominently stated in the literature that local asymptotic power properties serve as a useful indicator for the performance of residual‐based no‐cointegration tests in finite samples. However, this article comes to an opposing conclusion. In particular, we show that Breitung's (2002, Journal of Econometrics 108, 343–363) nonparameteric variance ratio unit root test applied to regression residuals serves as a no‐cointegration test but is inferior to its competitors from a local asymptotic power perspective. Nevertheless, in finite samples, the variance ratio test has good size properties, competitive power, and the convenience of being tuning parameter free. In general, we find that short‐run dynamics in the error process can have considerably larger detrimental effects on the performance of residual‐based no‐cointegration tests in finite samples than changes in the only nuisance parameter affecting local asymptotic power of the tests. The results serve as a warning for practitioners and lead to interesting directions for future research. [ABSTRACT FROM AUTHOR]

Ethiopia has experienced years of robust economic growth, with an average annual growth rate of 6%. However, the country continues to grapple with food insecurity, which is exacerbated by high food prices. The objective of this paper is to examine the effects of output level and inflation on Ethiopia's food security situation. The researchers utilized quarterly interpolated time-series data from the first quarter of 2005 to the fourth quarter of 2019. The data was analyzed using an autoregressive distributive lag framework for cointegration. The study's significant findings unequivocally demonstrate that a high output level has a positive effect on Ethiopia's food security situation in both the short and long terms, while showing a weak coefficient in the long run. However, unpredictable political contexts, rising food prices, and fluctuations in global pricing negatively affect this impact. The paper suggests that, alongside the level of output, sustaining improvements in Ethiopia's food security status necessitates enhancing production capacity, restoring stability, mitigating food price inflation, and strengthening disaster management. [ABSTRACT FROM AUTHOR]

This paper presents the ARDL package for the statistical language R, demonstrating its main functionalities in a step by step guide. Some of its main advantages over other related R packages are the intuitive API, and the fact that includes many important features missing from other packages that are essential for an in depth analysis. Additionally, it is designed in such a way that it can be combined with other packages for post regression diagnostics and tests. These characteristics are shown through an example, where we showcase part of the application demonstrated in the seminal work of Pesaran et al. (J Appl Econom 16:289–326, 2001). [ABSTRACT FROM AUTHOR]

This study aims to measure the elasticity of pension revenues from the General Social Security Regime (RGPS) in relation to the Gross Domestic Product (GDP) in Brazil, considering monthly data from January 1997 to July 2023. Based on a rigorous analysis of stationarity, co-integration and temporal causality, considering the presence of structural breaks, the results obtained from the estimation of an autoregressive vector model with an error correction mechanism (VECM) indicate that social security revenues are elastic in relation to GDP in the long term. [ABSTRACT FROM AUTHOR]

Copyright of OPUS Journal of Society Research is the property of OPUS - International Journal of Society Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Financial Politic & Economic Reviews / Finans Politik & Ekonomik Yorumlar is the property of Journal of Financial Politic & Economic Reviews / Finans Politik & Ekomomik Yorumlar and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

By sustaining the required capital and investment, the financial sector plays a critical role in achieving economic growth and stability. This paper conducts a comprehensive examination of the relationships between stock market development and economic growth in 11 post-socialist countries and China. Unbalanced panel data from selected countries from 1995 to 2020 were used for this study. We wanted to disclose the cointegration of crucial variables in assessing Granger causalities using the Vector Auto-Regressive (VAR) model. Our findings confirm the Neutrality Hypothesis (NLH) when we investigated the existence of an independent association between Economic Growth (EG) and the Composite Index of Stock Market Development (SMD). The study's recommendations emphasize the significance of changing economic policies to account for disparities in economic growth and stock market development to ensure sustainable development in the selected countries. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to analyze the relationship between the consequences of the pandemic and the housing sector with econometric tests that allow for structural breaks. Design/methodology/approach: Study data were collected weekly between March 9, 2020, and February 4, 2022, and analyzed for Turkey. In the model of the study, housing loans were used as a housing market indicator, and the number of new deaths and new cases were used as data related to the pandemic. The exchange rate, which affects the use of housing loans, was added to the model as a control variable. This study was analyzed to examine the relationship between the pandemic and the housing sector, time series analysis techniques that allow structural breaks were used. Findings: Based on the result of the analyses, it was concluded that there is a long-run relationship between the pandemic stages and housing markets along with structural breaks. As a result of the time-varying causality test developed to determine the causality relationship between the variables and its direction, a bidirectional causality relationship was identified between all variables at certain dates. Research limitations/implications: Study data were collected weekly between March 9, 2020, and February 4, 2022, and analyzed in the case of Turkey. Practical implications: Based on results of the study, it is recommended that policy makers and market actors take into account extraordinary situations such as pandemics and create a budget allocation that is always ready to use for this purpose. Originality/value: The empirical examination of the relationship between the pandemic and the housing sector in Turkey provides originality to this study in terms of its topic, sample, methodology, contribution to the literature and potential policy recommendations. [ABSTRACT FROM AUTHOR]

The current research delves into the implications of exchange rate fluctuations on commodity trade between Pakistan and Japan, utilizing the nonlinear autoregressive distributed lag method. While prior studies have predominantly utilized the symmetric cointegration approach, the current study posits that the limited assumption of symmetry between the exchange rate and the trade flows could have hindered the empirical findings. The research investigates both the symmetric and asymmetric effects of exchange rate fluctuations on 102 Pakistani industries that import from Japan and 62 industries that export to Japan at the industry level from 1980 to 2020. The outcomes indicate that in nearly half of the importing and exporting industries that engage in trade with Japan, there is evidence of a significant impact of asymmetric exchange rate fluctuations on trade flows in both the short and long term. The study suggests that policymakers should consider the industry-specific impact of exchange rate fluctuations on trade flows and implement targeted policies accordingly. Particularly, industries that benefit from currency depreciation should be encouraged through export incentives, while industries negatively affected by currency volatility should be provided with hedging mechanisms and other forms of support to mitigate their losses. [ABSTRACT FROM AUTHOR]

A general conception is that investment induces economic growth, but there is still debate over which type of investment contributes more to economic growth. The disaggregation of investment into public and private components allows estimation of the impact of the two types of investments on economic growth. This research, therefore, empirically estimates the relationship between each investment component against economic growth by constructing panel data for Ghana and Kenya from 1991 to 2O22. The empirical strategy adopted in this study can be divided into three major stages. First, the LLC unit root test in the panel series is undertaken. Second, if integrated in the same order, a Kao co-integration test is conducted. Finally, if the series is co-integrated, the vector of cointegration in the long run is estimated using the dynamic ordinary least squares (DOLS) method. Our estimation results, based on the panel cointegration approach confirm a long-run relationship between the study variables. Further analysis shows that public investment can promote economic growth in the long run. In contrast, the results indicate that private investment can obstruct growth. The study has shown that private investment did not always increase economic growth in Ghana and Kenya. The study findings indicate that public investment is more efficiently allocated in Ghana and Kenya than private investment, suggesting the best economic strategy is for private investment to be complementary and promote higher public investment to improve public sector productivity. Therefore, policymakers should focus on creating a favourable investment climate, providing fiscal stimulus and promoting public-private partnerships to enhance infrastructure development and stimulate private -sector investment, which can sustain long-term economic growth. [ABSTRACT FROM AUTHOR]

The application of machine learning in the medical field has resulted in significant advancements in computer-aided pathological diagnosis. Multiple instance learning (MIL) has emerged as a promising approach for pathological image classification, particularly in scenarios where local annotations are lacking. However, current MIL models often overlook the importance of feature weights in the channel dimension and struggle with imbalanced positive and negative data. To address these limitations, an integration of a channel attention (CA) module and an augmented data (AUG) mechanism into the MIL model is proposed, resulting in improved performance. The CA module dynamically assigns weights to example features in the channel dimension, enhancing or suppressing features adaptively. Additionally, the AUG mechanism effectively balances the distribution of positive and negative data, significantly reducing false negatives. Through ablation experiments, the contributions of the CA module and AUG mechanism in enhancing the overall model performance are analyzed. Experimental validations on the CAMELYON16/17 public pathological image datasets demonstrate that the proposed model and method outperform existing approaches, with particular emphasis on reducing false negatives. Highlights: While multiple instance learning (MIL) models address scarce local annotations in pathological images, existing methods often neglect feature weights in the channel dimension and struggle with imbalanced data. This study introduces a novel approach by proposing a channel attention (CA) module and data augmentation mechanism for integration into the MIL model, significantly improving its performance. By conducting carefully designed ablation experiments, this study probes into the precise contributions of the introduced CA module and data augmentation mechanism towards enhancing the performance of the MIL model. Through validation on public datasets reveals that the proposed method excels over the latest methods by notably reducing false negatives, thereby enhancing sensitivity metrics. [ABSTRACT FROM AUTHOR]

Exchange rate modeling has always fascinated researchers because of its complex macroeconomic dynamics. This study documents the exchange rate dynamics of major emerging economies after accounting for their macroeconomic cycles and explores the Bayesian Vector Error Correction Model (VECM) Markov Regime switching model, which uses time‐varying transition probabilities. The main objective is to study the exchange rate dynamics of Brazil, Russia, India, China, and South Africa (BRICS) vis‐à‐vis the US dollar. The Bayesian setup uses two hierarchal shrinkage priors, the normal‐gamma (NG) prior and the Litterman prior, for parameters' estimation. These shrinkage priors allow for a more comprehensive assessment of the regime‐specific coefficients. The model performed well in differentiating between the two regimes for all currencies. The Russian ruble was identified to be the most depreciated currency, whereas the African Rand was the most appreciated. The evaluation of model features revealed that many regime‐specific coefficients differed significantly from their common mean. A forecasting exercise was then performed for the out‐of‐sample period to assess the model's performance. A significant improvement was observed over the basic random walk (RW) model and the linear Bayesian vector autoregression (BVAR) model. [ABSTRACT FROM AUTHOR]

The aim of this paper is to develop a model of the real equilibrium CZK/EUR exchange rate with all relevant explanatory variables. Emphasis will be placed on examining the longest possible time horizon, with a period of real convergence, but also economic stagnation. The model is based on the theoretical BEER approach using a cointegration or error correction model that distinguishes between short-term and long-term relationships. The results show that the Czech koruna strengthens when the productivity differential, terms of trade differential or gross fixed capital formation increase, while the koruna weakens when the VIX index representing global risk aversion increases. For the real interest rate differential, the hypothesis that the koruna strengthens in the short run during the improvement but weakens in the long run probably due to the country's risk premium, was confirmed. Moreover, it turned out that the start of the European Central Bank's quantitative easing led to strengthening of the Czech koruna, while the start of the CNB's foreign exchange interventions in 2013 led to weakening of the Czech koruna.

This study aims to test hypothesis of Environmental Kuznets Curve (EKC) in Algeria using the Autoregressive Distributed Lag (ARDL) bounds testing methodology. The objectives include examining the long-term relationship between economic growth and CO2 emissions, investigating the impact of structural breaks on this relationship’s stability, and offering policy recommendations informed by the findings. The research utilizes annual data related CO2 emissions and GDP per capita from 1962 to 2014 in Algeria. The data are analyzed through the ARDL bounds test to ascertain the existence of a long-term equilibrium relationship. The study incorporates structural breaks to account for potential changes in the economic-environmental relationship over time. The findings confirm the presence of an EKC pattern in Algeria, showing a reverse U-shaped nexus between economic growth and CO2 emissions. The Inclusion of structural breaks in the analysis led to the stability of the model compared to the case of their absence that led to a variability in the model coefficients. Thus, it provides a more accurate and reliable understanding of this relationship. The threshold at which economic growth starts to decrease CO2 emissions, is identified at a GDP per capita of approximately $4125.58 (constant 2010 $), which Algeria reached in 2005. Furthermore, if disequilibrium between CO2 emissions and economic growth is occurred due to a possible short-term shock, the return toward the steady state requires three years approximately. While the results validate the EKC hypothesis for Algeria, the paper is limited to the period from 1962 to 2014 and may not capture more recent economic and environmental changes. Furthermore, the study aims to enrich the EKC literature in Algeria, which is characterized by scarcity, by using the recent ARDL bounds test methodology and addressing basic assumptions that were violated in previous studies. This study highlights the importance of considering structural breaks in environmental- economic analyses to avoid biased estimations and incorrect policy recommendations. Future research should explore additional determinants of CO2 emissions, such as biofuel use, advanced technologies, environmental awareness, urbanization, foreign direct investment, and employment. Policymakers should promote clean energy and sustainable economic practices to ensure continued environmental improvements alongside economic growth.

This paper examines the difference between pure contagion and financial interconnection by studying the U.S. and some American and Asian markets in the subprime crisis context. These markets are affected by the mortgage crisis, with data available from January 1, 2003 to December 30, 2011. The paper first identifies the turmoil period via the wavelet technique and adopts cointegration and Granger causality approaches by estimating vector autoregressive (VAR) and vector error correction models (VECM) models. Based on daily returns from stock market indices in five American countries (Mexico, Brazil, Canada, Argentina, and the U.S.) and eight Asian ones (Hong Kong, Japan, India, Indonesia, Malaysia, Singapore, Korea, and China), the results show eight cases of pure contagion and 10 cases of financial interconnection. In addition, there were high co-movements in the short term and low co-movements in the long term for financial interconnection cases. These findings have several implications for investors looking to diversify their portfolios internationally and for portfolio managers to expect and limit market risk. The results provide additional guidance to regulators and policymakers.

Purpose: The main purpose of this paper is to analyse the influence of capital efficiency on the economic growth of Bangladesh using the Harrod-Domar (H-D) model. Design/methodology/approach: We use annual data from 1980 to 2019 for this paper. Three steps are taken in the data analysis. First, to check the existence of a unit root, we use the augmented Dickey-Fuller (ADF) test and to determine co-integration among the variables, we use the Johansen-Juselius co-integration test. Next, for long-run estimation, we use the dynamic ordinary least square (DOLS) estimator. The sensitivity of the long-run estimations is further checked by the fully modified OLS (FMOLS) and autoregressive distributed lag (ARDL) estimators. Lastly, we use the Granger causality test to determine the long-run causality among the variables. Findings: The long-run co-integration test validates the co-integrating relationship among the variables. DOLS estimations reveal that the economic growth of Bangladesh is negatively associated with the incremental capital output ratio (ICOR), validating the notion that capital efficiency matters for achieving higher economic growth. On average, an increase in ICOR by a unit tends to reduce economic growth in the long term by 0.75 percent. Our results also reveal no significant relationship between savings and economic growth when the model is extended. Finally, causality results indicate unidirectional causality between ICOR and economic growth. Practical implications - Based on the results obtained, we argue that the enhancement of capital productivity could bring efficiency because ICOR is an inverse of capital productivity. Since Bangladesh's capital productivity is considerably low compared with other neighbouring countries, it is suggested that firms should gradually move towards technological advancement and enhance economies of scale, etc. in the long run. Moreover, policies in favour of continuous skill development programmes could be highly effective in increasing capital productivity given that capital follows a vintage structure. Originality/value: This is the first paper to analyse the economic growth pattern of Bangladesh using the traditional H-D model by incorporating variables such as savings and ICOR and also by relaxing the assumption of time-invariant (i.e. fixed) data of the variables. Moreover, this paper extends the traditional H-D empirical model by introducing key indicators and time breaks for Bangladesh's economy through a stepwise regression process. [ABSTRACT FROM AUTHOR]

The effect of real exchange rate volatility on real exports is explored empirically in this article. The study uses disaggregated Indian manufacturing sector data consisting of seven categories: leather & leather manufactures, chemicals and related products, engineering goods, electronic goods, textiles (excluding readymade garments), readymade garments and other manufactured goods. The analysis is focused on India's quarterly data from 2004Q2 to 2018Q2 using the ARDL bound test procedure. The ARDL bound test results show that real exports are co-integrated with fluctuations in real exchange rates and world real GDP. The study also reveals that exchange rate volatility has mixed effects on manufacturing exports both in the long run and short run. The impact of real-world GDP (WGDP) on real exports has been found positive and significant in the long run except for leather and leather manufacturers where it is negative and significant. In the case of the short-run, real-WGDP has mixed effects on exports. JEL Classification: C22, F14, F31, F1 [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate and evaluate the impact of public spending on inflation in Algeria from 1973 to 2022. The data used are obtained from the official website of world Bank (WDI) and the Finance Ministry of Algeria. This study is conducted by applying the Auto-Regressive Distributed Lag model (ARDL)-(bounds testing approach) using eviews13 software. The time series of the data were subjected to statistical tests by applying the Augmented Dickey-Fuller (ADF) test. The cointegration tests were also applied for a common relationship and the Model Stability: The Bounds Test for confirming the existence of a stable long-term relationship, the Breusch-Godfrey serial correlation LM test to test the absence of serial correlation, Test Breusch-Pagan-Godfrey to test the Heteroskedasticity; and the CUSUM and CUSUM Squares test for the stability of the model as well as the estimation of the model’s short- and long-term parameters. The results obtained confirm the hypothesis posed in the introduction on the existence of a cointegration relationship between public expenditure and inflation the indicate that there exists a cointegration relationship between public expenditure and inflation, such that a 1% increase in public spending leads to a 0.23% rise in the inflation rate. It is important to mention that this percentage is relatively low compared to the short term, having reached 2%. As regards the other control variables, we found a positive and statistically significant correlation between the inflation rate and the percentage of broad money to GDP and the percentage of imports to GDP. However, we found an inverse relationship between the inflation rate and GDP per capita at constant 2015 prices, which serves as a measure of inverse economic growth. Based on these results, we can suggest Moving forward, policymakers in Algeria must prioritize measures aimed at curbing inflation while ensuring sustainable economic growth. This may involve reassessing public spending priorities, implementing effective monetary policies, and enhancing fiscal discipline. Furthermore, fostering economic diversification and promoting investment in sectors with high growth potential can contribute to reducing reliance on public expenditure as a driver of inflation.

Despite the importance of financial development-international trade nexus and its implication for growth, studies have yet to look at the impact of new financial development indicators developed by the International Monetary Fund on international trade performance in Nigeria. This is one of the few attempts made to examine the elasticity of trade to financial development, given the inconclusive findings that permeate the literature. Therefore, this paper investigates the effect of financial development on aggregate trade performance in Nigeria using annual data from 1980 to 2021. The empirical framework is based on the ARDL approach to cointegration and error correction model. The findings revealed that (i) The ARDL bound test revealed the existence of a long-run equilibrium association between the variables; (ii) We find that a unit improvement in financial development induces a 1.1%-1.2% increase in trade performance in the short-run short term and a 9.7% in the long-run; (iii) The results show that a 1% increase in the exchange rate (depreciation) leads to a 0.01% improvement in trade performance in the short-term. The findings have important policy implications. The paper concludes that financial development contributes to trade performance.

The purpose of this study is to find empirical evidence of long-run equilibrium relationship between the personal savings ratio and several factors that, in the author’s opinion, determine this ratio. To achieve this purpose, a panel for 82 regions of the Russian Federation for the years 2000–2022 was assembled on the basis of official statistics data. In the descriptive part of the paper, we examined theories of personal savings, saving behavior of the population, the impact of personal savings on economic growth and the reasons why regional authorities should improve the climate for personal savings and growth of the working-age population in their regions. We used the PMG method to estimate our empirical ARDL model and found that the personal savings ratio is mainly determined by the age composition of the regional population and regional inflation, while money income and household final consumption are robust control variables. There is a long-run equilibrium relationship between these variables.