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The issue of volatile food prices is a consistent problem for American consumers, as rising prices make it challenging to afford nutritious food that meets dietary standards. Various complex factors influence this price volatility, including economic conditions, weather patterns, global trade, energy prices, and more. Notably, the impact of food price increases is not equal for everyone. Low-income individuals and those in rural areas are disproportionately affected. A comprehensive understanding of the driving factors is essential to tackle this issue effectively. We employ advanced time-series techniques such as Vector Error Correction Models (VECM) and modern causal inference methods such as probabilistic graphical models implemented via machine learning and artificial intelligence approaches on monthly data from 2000 to 2021 to investigate the U.S. food price inflation issue. These methods help unravel the intricate dynamics among key variables driving food price inflation. The study aims to achieve several objectives. It intends to (1) clarify how factors influencing food price inflation in the U.S. change over time using VECM models, (2) establish causal relationships among interconnected variables to develop probabilistic graphical models using innovative search algorithms, and (3) create and validate forecasts related to U.S. food price inflation. The end goal is to provide actionable insights for policy design. Results show that food price inflation is heavily tied to commodity pricing and pricing for medical services. Additionally, historical decompositions for COVID-19 show ties between food price inflation and energy inflation. [ABSTRACT FROM AUTHOR]

This article examines how fluctuations in macroeconomic indicators influence companies’ propensity to invest, gauged by the investment intensity index – defined as the ratio of investment expenditures to total revenue. The analysis focuses on the five most revenue-generating sectors within Poland’s manufacturing industry, as defined in the Polish Classification of Activities (PKD). Using unpublished Statistics Poland (GUS) quarterly panel data from 2008 to 2022, sourced from the F-01 and F-02 reports, the research targets medium and large companies. Cointegration analysis and the Vector Error Correction Model (VECM) are employed to identify macroeconomic indicators that consistently impact the propensity to invest in specific sectors, while also assessing the presence of investment seasonality. The findings reveal a strong long-term correlation between corporate investments and macroeconomic indicators, capturing both enduring equilibria and transient fluctuations. Significantly, the research uncovers varied macroeconomic impacts on investment decisions, with GDP and SP emerging as pivotal in the chemical sector (PKD-20), and temporal and inter-sectoral dynamics notably influencing the computer and electronics sector (PKD-26). These insights highlight the complexity of macroeconomic effects on investment strategies within Poland’s industrial landscape.

This research paper attempts to test the applicability of the Purchasing Power Parity theory to the Algerian economy. Annual data from 1990 to 2023, specifically concerning the official exchange rate and the consumer price index, were used. By conducting a series of econometric tests, such as stationarity tests, cointegration tests, and causality studies, the study concludes that there is a long-term equilibrium relationship between the official exchange rate and the consumer price index. Hence, it can be inferred that the PPP theory holds true for the Algerian context. This implies that purchasing power parity is maintained in the long run, and therefore, this theory can be relied upon to determine and interpret the exchange rate of the Algerian dinar in the current scenario. The results of the error correction model estimation from the joint integration test also showed a direct relationship between the nominal exchange rate and the consumer price index, such that a relative change in the exchange rate by one unit leads to a relative change in the consumer price index by 0.14. The error correction model coefficient, estimated at 0.024, reveals the speed of the return to the equilibrium position and is a relatively weak correction coefficient. Based on the R² value, it can be said that exchange rates represent 69% of the changes in the consumer price index. The Granger causality test revealed a causal relationship running from the official exchange rate to the consumer price index for the Algerian economy.

This paper examines and forecasts the impact of foreign direct investment (FDI) on industrialization and industrial performance in Tanzania by using World Bank data spanning 1960 to 2020. The admixture time series analysis of Vector Autoregressive (VAR) and Vector Error Correction Model (VECM) has been extensively explored in order to provide accurate estimation. The need to examine FDI inflows is enormously based on domestic macroeconomic parameters that are stuck in many developing countries, including Tanzania, implying that FDI is necessary for growth and development now and in the future. According to the findings, FDI granger causes industrialization, and the more the sector thrives, the more granger causes FDI inflow. In the long run, FDI has a significant impact on Tanzanian industrialization growth, whereas the exchange rate (EXR) has a significant impact on industrialization growth in the short run. The study recommends the Bank of Tanzania to take appropriate measures to control poor-performing economic parameters such as the exchange rate, inflation, and the improvement of the money market in order to enhance capital availability and accessibility. [ABSTRACT FROM AUTHOR]

Copyright of Polish Journal of Economics / Gospodarka Narodowa is the property of SGH Warsaw School of Economics 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.)

Forecasting the flow of rivers is an essential task in water management resources. However, the flow changes significantly at the seasonal variation of the year, so it is difficult to predict the flow because of its complex nature. The study aims to find a predictive model for forecasting the inflow of the Indus River. Two multivariate models, the autoregressive distributed lag (ARDL) model and vector error correction model (VECM), are compared to examine whether there is any long‐ or short‐run association between variables. It is observed that the ARDL model shows long‐ and short‐run associations between inflow, outflow, and levels. In contrast, VECM shows only a long‐run association between the variables. It is concluded that the ARDL model performs better in predicting the future inflow of the Indus River than VECM based on the stability test or accuracy of the models. [ABSTRACT FROM AUTHOR]

AbstractThe Dutch Disease, initially associated with natural resource discovery, has evolved to include various capital inflows. This study investigates the relationship between remittance inflows and the Dutch Disease in Ethiopia, focusing on the real effective exchange rate. Using a 30-year time series (1991–2020) and a Vector Error Correction Model, the study finds a robust long-run relationship among remittances, official development assistance, money supply, terms of trade, domestic credit, and real gross domestic product. The empirical results reveal that remittances, along with other variables, significantly affect the real effective exchange rate in both the short and long run. Contrary to the Dutch Disease hypothesis, remittance inflows did not lead to real effective exchange rate appreciation in the long run. Trade liberalization and government consumption of non-tradables were also identified as influential factors. The short-run dynamics indicate a significant speed of adjustment towards equilibrium, emphasizing the importance of understanding the macroeconomic impacts of remittances on real effective exchange rate. Policy implications include managing real effective exchange rate through targeted interventions, considering trade liberalization to enhance export competitiveness, and designing remittance policies to utilize capital for economic development without fearing Dutch Disease consequences. The study also recommends the disaggregation of foreign aid data for more nuanced policy insights. Overall, this research contributes valuable insights for policymakers in navigating the complexities of remittances, economic variables, and the real effective exchange rate in Ethiopia, facilitating informed and effective policy decisions.

The problem of dynamic relationships among the price indices of 10 major steel products – the rebar, steel wire, plate, hot rolled coil, cold rolled plate, galvannealed sheet, seamless tube, welded tube, section and narrow strip – is addressed in the present work for the Chinese market from 2011M7 to 2021M4. For examination of contemporaneous causal links among the 10 series, we use data on a daily basis and combine the vector error correction model and directed acyclic graph. This analysis is done using both the Peter and Clark and linear non-Gaussian acyclic model algorithms. With the exception of the price series for steel wire, each of the 10 series is part of cointegration relationships according to the vector error correction model, and all save the price series for thin strips respond to long-run equilibrium disturbances. The linear non-Gaussian acyclic model method allows us to achieve causal routes that allow for the examination of innovation accounting, but the Peter and Clark algorithm prevented us from reaching an acyclic graph. We categorise complex dynamics among price adjustment processes after shocks based on impulsive responses, for which the price indices of the plate, seamless tube and thin strip are predominating in comparison to the other seven items. Our findings show that these three goods should get the most consideration when designing long-term strategies for steel prices. [ABSTRACT FROM AUTHOR]

This research study evaluated the dynamics and competitiveness of Nigeria's sesame (Sesamum indicum) production in international trade. Secondary data were used, in the data period of 1982 to 2022 (41 years). The data used were sourced from NBS, CBN, FAO, World Bank publication, and General Household Survey-Panel (GHS-P) in conjunction with Federal Ministry of Agriculture and Rural Development. The econometric tools used were Augmented Dickey-Fuller (ADF) unit root test, Johansen co-integration test, Zivot - Andrews (Z-A), Lee Strazicich (LM) structural break unit root tests, and vector error correction model (VECM). The result of the ADF unit root test shows that all the test variables were stationary at first difference I (1). The results of the Johansen co-integration test for the time series data shows that the trace test statistics indicate 2 co-integrating equations, the Max-Eigen values also indicates 2 cointegrating equations. The estimated long run effect using VECM shows that area, yield, and world trade in oilseed, were positively and significantly related to the dynamics and competitiveness of Nigeria's sesame seed in international trade. The real exchange rate had a negative coefficient and was non-significantly related to the dynamics and competitiveness of Nigeria's sesame seed in international trade. The coefficient of the error correction term (ECM) is with the expected negative sign and statistically significant at 1% level of probability, this is an indication of a move back towards equilibrium with a magnitude of -0.95. Policies that would encourage exportation of sesame should be pursued and enhancing research activities on improving quality of sesame produced. [ABSTRACT FROM AUTHOR]

AbstractThe recent upsurge in food prices in Sri Lanka has raised significant concerns, posing a threat to the food and nutritional security of the population. However, the causal factors driving this inflation still need to be better understood. Our study, utilizing Cointegration and Vector Error Correction Models (VECM), investigates the role of supply and demand-side determinants of food inflation. The study identified changes in exchange rate, agricultural wages, fuel prices, money supply, and fertilizer prices as key drivers of food inflation in Sri Lanka. Expansion of the money supply exerted the most substantial influence on food inflation in the long run. At the same time, changes in world market prices were found to be the most influential determinants of food inflation in the short run. Findings underscore the need for a comprehensive strategy that combines supply-side enhancements and demand-side management to control food inflation in Sri Lanka. [ABSTRACT FROM AUTHOR]

The objective of this study is to analyse the impact of Zakat distribution, inflation, consumption, and international trade on the economic growth of Indonesia using the Vector Error Correction Model (VECM) analysis. The VECM analysis comprises several tests, including the unit root test, stability test, cointegration test, and Granger causality test. This study found that consumption, exports, imports, and Zakat exert a favourable influence on economic growth; however, inflation has an adverse impact on economic growth. Zakat expenditure indicated a positive relationship with gross domestic product level in the long term. The results of the Granger causality test implied a two-way causal interconnection between Zakat expenditure and economic growth. Zakat can trigger the country's economic expansion by increasing consumption, investment, or government spending, and an increase in national income will encourage an increase in Zakat distribution. Moreover, the augmentation of national income will foster an upsurge in the distribution of Zakat. The future tax potential is immense because the total population of Indonesian Muslim residents in 2022 is predicted to be 241.7 million people, or the equivalent of an 87.02 per cent increase. [ABSTRACT FROM AUTHOR]

This research paper attempts to test the applicability of the Purchasing Power Parity theory to the Algerian economy. Annual data from 1990 to 2023, specifically concerning the official exchange rate and the consumer price index, were used. By conducting a series of econometric tests, such as stationarity tests, cointegration tests, and causality studies, the study concludes that there is a long-term equilibrium relationship between the official exchange rate and the consumer price index. Hence, it can be inferred that the PPP theory holds true for the Algerian context. This implies that purchasing power parity is maintained in the long run, and therefore, this theory can be relied upon to determine and interpret the exchange rate of the Algerian dinar in the current scenario. The results of the error correction model estimation from the joint integration test also showed a direct relationship between the nominal exchange rate and the consumer price index, such that a relative change in the exchange rate by one unit leads to a relative change in the consumer price index by 0.14. The error correction model coefficient, estimated at 0.024, reveals the speed of the return to the equilibrium position and is a relatively weak correction coefficient. Based on the R² value, it can be said that exchange rates represent 69% of the changes in the consumer price index. The Granger causality test revealed a causal relationship running from the official exchange rate to the consumer price index for the Algerian economy. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power is the property of Electric Power Editorial Office 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.)

Every economic sector is susceptible to the direct or indirect effects of weather variability, and the tourism sector is no exception. In fact, the tourism industry is considered to be more vulnerable to the effects of weather variability than the general economy, with changes in weather patterns, extreme events, and environmental degradation offering substantial obstacles. Ethiopia's tourism industry, like many others, faces challenges from weather variability. This study investigates the short- and long-term effects of weather variability on Ethiopia's international tourism receipts. Utilizing data from 1995 to 2019, the research employs a vector error correction model to analyze the relationships between weather variables (temperature, rainfall), economic factors (GDP growth, inflation), political stability, and tourist arrivals. The findings reveal that in the long run, higher temperatures, rainfall, and inflation have negative impacts on tourism receipts, while political stability and past tourist arrivals have positive effects. Short-term trends mirror these, with the addition of GDP growth not showing a significant impact. To ensure the sustainability of tourism in Ethiopia, the study emphasizes the importance of understanding weather's influence, developing adaptation strategies, and promoting sustainable tourism practices. [ABSTRACT FROM AUTHOR]

Dollar exchange rate and Indian stock market are leading economic indicators. The present study investigates the relationship between the two economic indicators during the period April 2005 to December 2019. Analysis of Johansen cointegration test reveals that positive long-run cointegrating relationship exists between the variables. The vector error correction mechanism shows that INR/USD exchange rate influences the Indian stock prices negatively in the short-run. The study also observes the presence of bidirectional causality between the variables in the short-run. The variance decomposition analysis further reveals that the Indian stock market is driven to considerable extent by innovations in INR/USD exchange rate. The close relationship that the study found between INR/USD exchange rate and Indian stock market will be an important factor in the decision making of both individual and institutional investors. Furthermore, the study recommends the Indian government to adopt a cautious approach in implementing the foreign currency exchange rate policies. [ABSTRACT FROM AUTHOR]

Every economic sector is susceptible to the direct or indirect effects of weather variability, and the tourism sector is no exception. In fact, the tourism industry is considered to be more vulnerable to the effects of weather variability than the general economy, with changes in weather patterns, extreme events, and environmental degradation offering substantial obstacles. Ethiopia’s tourism industry, like many others, faces challenges from weather variability. This study investigates the short- and long-term effects of weather variability on Ethiopia’s international tourism receipts. Utilizing data from 1995 to 2019, the research employs a vector error correction model to analyze the relationships between weather variables (temperature, rainfall), economic factors (GDP growth, inflation), political stability, and tourist arrivals. The findings reveal that in the long run, higher temperatures, rainfall, and inflation have negative impacts on tourism receipts, while political stability and past tourist arrivals have positive effects. Short-term trends mirror these, with the addition of GDP growth not showing a significant impact. To ensure the sustainability of tourism in Ethiopia, the study emphasizes the importance of understanding weather’s influence, developing adaptation strategies, and promoting sustainable tourism practices.

While investing in the stock market can generate profits, it can also generate losses. Understanding the impact of certain important components on stock prices can help investors make more profitable investment decisions. The study investigated the key components that influenced the price of sharia bank Indonesian shares. Secondary data used for research. The information comes from monthly financial statements compiled from June 2018 to December 2020. The study looked at the impact of the shock and long-term response of each variable on the stock price using the Vector Error Correction Model (VECM). In the long run, PER and ROE variables have a positive effect on the stock price, but EPS has a negative effect. Unlike other variables, DER and PBV do not affect the stock price. The main factor is the EPS, which has a big and positive impact on the stock price in the short term. DER and PER have a very negative impact on the value of stocks. PBV has a negative but non-significant impact, while ROE has a positive but not significant impact. [ABSTRACT FROM AUTHOR]

Copyright of International Economics / Economia Internazionale is the property of Camera di Commercio di Genova 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.)

Efficient management of working capital in the realm of trade serves to bolster a company's liquidity by meticulously handling cash, receivables, and inventory. This approach emphasizes the optimization of sales, upkeep of inventory, and the implementation of judicious customer payment policies. Challenges inherent within the cash cycle can exert considerable influence on liquidity, compelling heightened borrowing practices that could potentially impact the overall performance of the company. The research delves into analyzing how different aspects of working capital and the level of liquidity impact the profit performance of a trading company. The empirical analysis is centered around the case study of PT XYY, spanning from 2016 to 2021. The research methodology entails examining monthly time series data and applying the vector error correction model (VECM) to comprehend the long-term relationships among the variables. Days of sales in outstanding (DSO), days of sales in inventory (DSI), days of payable outstanding (DPO), and cash conversion cycle (CCC). Liquidity is also measured by the current ratio and cash ratio with the sales growth control variable. The Principal aim of the study is to fathom how these elements collectively impact the company's profitability, gauged by return on assets (ROA). ROA assesses the company's capability to derive profit from its assets. The research findings indicate that DPO and current ratio notably positively influence ROA. DSO, cash ratio, and CCC significantly negatively impact ROA. Meanwhile, the DSI variable has no significant effect. The Implications of these findings underscore the importance of skillfully managing commitments to suppliers to uphold profitability. Companies can leverage these outcomes to fine-tune their operational policies, particularly concerning payment terms with suppliers within purchase agreementsas well as maintaining optimal cash availability in liquidity security. [ABSTRACT FROM AUTHOR]

There is no consensus in the economics theory about the determinants of household saving. The article composes vector error correction (VEC) models to identify the determinants of household saving in the East Central European countries from 2005–2020. Its novelty is that it identifies push and pull factors in accordance with the Keynesian and neoclassical theories whose mixed approach has not been included in the methodology of relevant papers in relation with East Central European countries. The examined countries are indicated to be homogenous from macroeconomic perspective. Results confirm that household saving increases because of decreases in consumer confidence, unemployment, and inflation rates. Increases in the deposit rate and real house price index are related to these pull factors, while decreases in the official share index correlates withincreases in household saving. Results can serve as guidelines for policy makers about incentives which stimulate household saving most effectively in the region. [ABSTRACT FROM AUTHOR]

Research Highlights • An assessment of institutional quality, innovation, and economic growth in developing countries. • Long-run causality from innovation and institutional quality to economic growth is present. • Short-run directions of causality are varied among variables of interest. • Innovation and institutional quality generally positively impact economic growth. Continuous innovation is the lifeblood of a competitive economy. Furthermore, and arguably, the existence of institutions of governance of quality can be a catalyst for emerging economies to transition up the universal innovation value chain. In this context, we investigate temporal causal interactions among institutional quality, innovation, and economic growth for developing countries (DCs) spanning the period of 2005–2020. Employing a vector error-correction model (VECM), we find that for each case and specification (49 instances), there is evidence of the long-run causality from institutional quality and innovation to economic growth. Stated another way, in the long run, institutional quality and innovation Granger-cause economic growth. However, the short-run causality results differ depending on the specific measures of innovation and institutional quality. The strongest short-run conclusion is support for the feedback hypothesis for economic growth and innovation where there is a strong endogenous relationship between innovation, institutional governance, and economic growth. The empirical analysis shows over 70% of our observations support that economic growth and innovation jointly determine each other in the short run. The results suggest that DCs should develop and pursue long-term growth strategies that simultaneously develop innovation and improve institutional governance. [ABSTRACT FROM AUTHOR]

In this study, we aim at investigating dynamic relations among steel price indices of all seven regional markets in China, spanning the period of 2010M1–2021M4. With daily data, we apply techniques of vector error correction modeling and the directed acyclic graph to analyze the issue of contemporaneous causality among the seven indices, the latter of which is facilitated through the LiNGAM algorithm. We find via vector error correction modeling that each of the seven indices is part of cointegration relations and responses to long-run equilibrium disturbances. We arrive at causal paths via the LiNGAM algorithm for enabling innovation accounting analysis. With this analysis, we find sophisticated dynamics in price adjustment processes following shocks, for which east and northeast regions have the most significant impacts on other regions, followed by south and north regions, followed by the southwest region. Central south and northwest regions are not found to have significant impacts on others. These results suggest that policies on regional steel prices in the long run might be designed with most attention paid to five of the seven regions, particularly east and northeast regions. [ABSTRACT FROM AUTHOR]

COVID-19 and SARS are epidemics which have influenced the largest global economic crisis in recent years. This research reveals that both SARS and COVID-19 have led to fluctuations in the prices of gold and the US dollar index; however, there is no direct causal relationship be-tween COVID-19 and the price of bitcoin. The USD index saw a significant increase during the SARS outbreak, while gold prices surged during the COVID-19 pandemic. The notion that cryptocurrency will surpass the value of gold or traditional currencies seems improbable, given the lack of evidence linking bitcoin prices to COVID-19. Gold is expected to maintain its value in the long term, offering lower risk compared to other currencies. [ABSTRACT FROM AUTHOR]

Economic growth’s theories suggest that a developed financial sector can promote the economy growth. However, the ability of financial sector to boost the economic growth depends on its ability to finance the economy. This paper investigates the relationship between Morocco's economic growth and financial development (FD). We base our study on the crucial role of banking sector in economic growth in developing countries through their financial intermediation. In order, to verify this relationship the vector error correction model (VECM) is used on secondary data: real GDP per capita (GDP) and a set of explanatory variables representing the financial development sector, specifically the ratio of private sector credit (CPS) and control variables including the share of government consumption (PC), the real interest rate (IR), trade openness (TO), and the inflation rate (INF). Our secondary data comes from the Central Bank of Morocco database and covers 56 quarters from 2007Q1 to 2020Q4. The findings support the long- and short-term benefits of financial sector development for economic growth in Morocco.

Research in recent years has shown that Bitcoin is a virtual asset that is used as a medium of exchange and investment tool other than shares and bonds, the development of the digital era has opened up opportunities for Bitcoin to be chosen as part of an investor’s portfolio. The focus of this study is to examine the impact of nine key determinants on Bitcoin price. The data used in the study are daily data starting from January 1, 2018 to January 1, 2022. The main data source is taken from Investing.com, and the estimation method applied is the Vector Error Correction Model (VECM). The main finding shows that Bitcoin Volume impacts Bitcoin Price negatively, which is in line with the demand theory. Another finding is related to the substitute effect of Ethereum Volume, Litecoin Volume, and Gold Volume, each of which influences Bitcoin Price positively, suggesting that these three commodities are substitutes to Bitcoin. In contrast, whereas Oil Volume has an insignificant effect on Bitcoin price in the short term, it has a negative significant impact in the long term. In addition, LQ45 stock index Volume influences Bitcoin Price positively in the short term, suggesting that LQ45 stock index and Bitcoin substitute for each other. Moreover, Google Trends impacts Bitcoin price positively in the long term. In terms of the income effect, either the Indonesian GDP or US GDP has a strong positive effect on Bitcoin price in both the short and long term.

In order to adopt the appropriate fiscal policy, one should know the correct relationship between the revenues and expenses of the government. The main goal of this study is to offer appropriate policy recommendations to reduce the budget deficit and resolve the imbalance between the government's revenues and expenses. In this research, the dynamic relationship and mutual effects between government revenues and government expenditures have been tested using the vector error correction (VEC) model. The results confirm the Tax-and-Spend Hypothesis for Iran. The political consequence of this hypothesis for Iran is that higher tax revenues lead to higher expenditures, which can cause an increase in the inflation rate and financial illusion in addition to the government's failure to resolve the budget deficit. Therefore, the government's efforts should be accompanied by appropriate reforms in public spending to enable productive investments and, as a result, sustainable economic growth. With increasing economic growth in the long term, it will be possible to increase tax revenues in order to compensate for the budget deficit.

BACKGROUND AND OBJECTIVES: Coronavirus-19 has affected carbon emissions, which was declared as a pandemic by World Health Organization. Unprecedented environmental effects are being caused by Bangladesh's strict lockdown policies, which were implemented to stop the spread of Coronavirus-19. However, it is still unclear how the temporary halting and restart of industrial and commercial activities will affect the environment. In this study, it has been identified how Coronavirus-19 determinants like lockdown, daily confirmed cases, and daily confirmed deaths affect greenhouse gases. METHODS: From March 18, 2020 to February 4, 2022 the data series is used for Bangladesh. To ensure that the data series were stationary, the Augmented Dickey–Fuller and Phillips–Perron tests were utilized. Johansen co-integration test was utilized to determine co-integration among variables. The Granger causality test was utilized to identify directional causes and effects between Coronavirus-19 determinants and carbon emissions and the Vector Error Correction Model was employed to determine short-run and long run connections. FINDINGS: The study finds a bidirectional relationship between lockdown, carbon emissions and daily confirmed deaths, while a unidirectional association exists among Coronavirus-19 confirmed cases according to the Vector Error Correction Model. The Granger causality test also established the relationship between variables, except for daily confirmed cases. The pandemic's onset and subsequent lockdown resulted in decreased carbon dioxide emissions. The short-run link of carbon dioxide emissions with newly confirmed cases was corroborated by the directional relationship of variables, whereas there was a long-term and short-term association between confirmed deaths and lockdown. CONCLUSIONS: The reduction in carbon emissions during the pandemic will not be long-lasting because it is anticipated that global economic activity will gradually return to the pre- Coronavirus-19 state. The directional and relational nature of lockdown offers the potential to connect carbon dioxide emissions to regular lives. During a lockdown, there is a connection between the atmosphere's changes and how natural organisms behave. Importantly, there is a room for investigation into how communities of organisms and the atmosphere would function without humans. The essential point is to stress that during the lockdown, the ecosystem is self-healing. Environmental activists and business people will find this study useful in developing future sustainable improvement strategies.

An increasing trend in cryptocurrency prices shows the investors’ attention towards digital currency, but the carbon emission effect due to cryptocurrency is also gaining importance. However, no study has investigated the relationship between these two variables. The study’s objective is to investigate the relationship between Bitcoin energy consumption and the prices of Bitcoin. This paper uses Johansen’s cointegration test, the Vector error correction model, Granger’s causality, Impulsive response, and variance decomposition on daily frequency data. It indicates the existence of long-run cointegration between energy consumption and Bitcoin prices. On the other hand, VEC Granger causality indicates that one time series does not cause the other one and vice versa. Variance decomposition and impulsive response function also indicate that shocks in energy consumption insignificantly affect the Bitcoin prices and vice versa. Policymakers and regulators should pay attention to renewable energy resources in cryptocurrency mining.

During the past two decades, two global events highlighted the importance of household savings to economies and individuals, and their relation to economic activity and growth. First, the Global Financial Crisis of 2008 reminded the world that household savings are essential for economic recovery and sustainable economic development. Second, the recent COVID-19 pandemic showed how vulnerable household savings are to various external shocks. This paper investigates the relationship between household savings rates and real GDP in the four countries of the Visegrád Group, namely the Czech Republic, Hungary, Poland, and Slovakia, for the period 1996–2021. Our empirical analyses indicate short-run Granger causality from real GDP to household savings rates, and from household savings rates to real GDP, in both the Czech Republic and Hungary. Additionally, we also report significant long-run relationships between household savings rates and real GDP, particularly in Hungary. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny 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.)

Urban agglomerations are becoming increasingly important in driving economic development in China. Accurate representation of the economic development status and spillover effects of cities within an urban agglomeration is the foundation of and an effective approach for promoting the coordinated development of that agglomeration. However, current studies of economic spillovers tend to focus on urban agglomerations as a whole, and there is a lack of scrutiny and validation of research data. Therefore, this study proposes a framework for detecting economic spillover effects within an urban agglomeration based on a prolonged night-time light dataset. Firstly, we explored the most suitable night-time light index to characterize the economic status. Then, we used this index to construct the economic network and hierarchical structure of the urban agglomeration. Finally, we explored the heterogeneity of spillover effects under the hierarchical structure. The results of a case study in the Pearl River Delta (PRD) urban agglomeration show that (1) the total night-time light in built-up areas (BNTL) has the highest Pearson correlation coefficient with GDP, which is 0.82; (2) there is an obvious hierarchical structure within the PRD; (3) there are significant and sustained economic spillover effects among the core cities, with Guangzhou–Foshan and Shenzhen–Dongguan having more obvious spillover effects; and (4) the economic spillover effects within the three metropolitan areas have different characteristics. The Guangzhou–Foshan–Zhaoqing metropolitan area is closely linked, to apparent differences in the pace of spillover effects. The Shenzhen–Dongguan–Huizhou metropolitan area has strong close linkages, with strong synchronization of spillover effects. The Zhuhai–Zhongshan–Jiangmen metropolitan area has not yet formed a stable synergistic development relationship. Overall, the framework can effectively reveal the hierarchical structure and different characteristics of economic spillovers within urban agglomerations, which can provide a scientific reference for policy making related to the coordinated development of such agglomerations. [ABSTRACT FROM AUTHOR]

A key criticism of Uganda's macroeconomic modelling frameworks is the lack of accounting for the effects of climate change. As a result, the demand for sustainable climate change evidence-based policy actions is higher than ever, making this a key issue in policy discussions. However, climate change research in Uganda has been piecemeal, with a few using case studies of agricultural commodities, regions, or agriculture. Thus, using the endogenous economic growth framework, this study estimated the long-term and short-term direct and indirect-sectoral effects of climate change on Uganda's economic growth using the vector error correction model and Johansen cointegration econometric analysis methods. The results show that climate change (precipitation) affects agriculture and industry sectoral output growth in a positive direction, and service sectoral output growth in a negative direction. Further, climate change (temperature) affects agriculture and industry sectoral output growth in a negative direction, and service sectoral output growth in a positive direction. The study's main conclusion is that an increase in temperature by 1.0 degrees Celsius accounts for a reduction in economic growth by approximately 2.5 percentage points, keeping all other factors constant. The study recommends accounting for climate change effects in macroeconomic growth frameworks, and implementing key sectoralspecific climate sustainability measures. [ABSTRACT FROM AUTHOR]

Time series data usually exhibit non-stationary behavior and involve interrelated variables. Thus, we need a model that can obtain good forecasting results from non-stationary time series data with multivariate variables. The Vector Error Correction Model (VECM) is a multivariate time series model which is a vector form of Vector Autoregressive Regression (VAR) for time series data that are non-stationary and have a cointegration relationship. This research was conducted to model the cointegration relationship in providing clarity on the long-term relationship of the influence of future prices and the Covid-19 pandemic on price movements of gold futures commodities and to predict spot price prediction modeling for gold futures commodities. The results of the research using the VECM (2) model, which is the best model, show that the future price of the gold commodity is quite dominant in influencing the value of the spot price of gold. The Covid-19 variable does not have a significant effect on the spot gold price variable.

Afghanistan has been plagued by decades of conflict, but the last two decades' movements toward peace offer the opportunity for a new era of human development. The government was committed to achieving the 2030 Agenda and the Sustainable Development Goals. Due to repeated wars and conflicts, the country relies heavily on foreign aid to support its development goals and fill budget gaps. The Human Development Index (HDI) serves as a widely utilized measure of individual well-being, and foreign aid is one of the most effective tools for the development of impoverished nations. In this study, we analyzed the impact of foreign aid on Afghanistan's Human Development Index and its three core components from 1990 to 2019.We achieved our objective through the implementation of the Vector Error Correction Model (VECM). Our study uncovered a reciprocal association between ODA and HDI, including its three aspects. Through our observations, we have discovered that foreign aid plays a crucial role in enhancing human development in the long term. Specifically, for every one percent increase in ODA, we have observed a 0.0007 percent improvement in HDI. In addition, our findings have revealed that human development serves as a driving force in attracting foreign aid. Looking at Afghanistan as a case study, we have observed a significant improvement in overall human development, which we attribute to the influx of foreign aid during our study period.

The development of non-cash payments is predicted to have an effect on real money demand, not only in Indonesia. The use of electronic money in Indonesia itself continues to increase especially in the covid-19 pandemic and it supported by technological developments. The purpose of this study was to analyse the effect of non-cash payments on real money demand in Indonesia. The method used is Vector Error Correction Model (VECM) using secondary data from Januari 2019 to December 2022. The independent variable is the amount of money circulated by Bank Indonesia, and the independent variables used are the value of debit / ATM card transactions, credit cards, and e -money. The results indicate that in the long run debit cards and emoney have a significant negative effect on money supply, while credit cards have positive effect on money supply but it’s not significan. While in the short term, all variables debit cards, credit cards and e-money are not significant on money supply. [ABSTRACT FROM AUTHOR]

In 2019, Ireland was the third-largest exporter of butter in the world butter market but Irish butter prices have been more volatile compared to other Irish dairy products. Yet, empirical research that examines the market price dynamics and international competitor behavior in the butter market remains scarce. The Vector Error Correction Model was applied to data from 1970–2019, to test the extent to which changes in competitor butter prices and Irish farm milk prices had an impact on Irish butter prices. The results provide evidence of asymmetric price transmissions, Irish butter prices were more responsive to shocks in New Zealand (NZ) butter prices and Irish farm milk prices in the long-run. Declining world milk prices over time, related to milk supply, perishability and storability factors, may prevent symmetric response of Irish milk prices to changes/shocks in Irish butter prices. Moreover, different target markets and EU/NZ policies for Ireland and NZ butter may prevent symmetric response of Irish butter prices to changes/shocks from NZ butter prices. Essentially, the take home message for the butter industry is that Irish butter prices must not be studied in isolation, NZ is a major butter competitor to Ireland in the world market and NZ butter prices play a significant role on how Irish butter prices change. [ABSTRACT FROM AUTHOR]

Objective To investigate how economic development and health resource input impact infant mortality in Shanghai. Methods Data on GDP per capita, the number of health facility beds per 10,000 population, and the infant mortality rate in Shanghai from 1991 to 2020 were selected and analyzed using the vector error correction model. Results A long-term equilibrium relationship existed between infant mortality, GDP per capita, and the number of health beds per 10,000 persons, with the elasticity coefficient of infant mortality being-2. 83 (95% CI:-3. 86-1. 80) for GDP per capita and-3. 02 (95% CI: -5. 03-- 1. 01) for the number of health beds per 10,000 persons. The maximum value is reached in the 5th and 6th year respectively and has a long-term negative impact. Conclusion The improvement of infant health cannot be achieved without the two-way promotion of socio-economic and health resource investment. It is necessary to promote the effective combination of investment in health resources and economic development, improve the construction of the maternal and child healthcare service system, strengthen the leading role of the Government, and build an efficient mechanism for the investment of health resources. [ABSTRACT FROM AUTHOR]

This empirical paper aims at investigating the dynamic impact of sustainable development on tourism growth for the case of the small island developing state of Mauritius. The study is done for the period 1980–2018. The vector error correction model is being used and the results point out that sustainable development variables, notably economic, social and environmental, have influenced tourism development. Furthermore, the results also endorse the presence of bi-directional causality and feedback effects in the tourism-economic growth model hence supporting both the tourism-led growth hypothesis and the economic-driven tourism growth hypothesis. Furthermore, tourism development is observed to contribute towards environmental degradation. [ABSTRACT FROM AUTHOR]

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The COVID-19 pandemic has had a devastating impact on the world at large with over 750 million cases and almost 7 million deaths reported thus far. Of those, over 100 million cases and 1 million deaths have occurred in the United States of America (USA). The mental health of the general population has been impacted by several aspects of the pandemic including lockdowns, media sensationalism, social isolation, and spread of the disease. In this paper, we examine the associations that social isolation and COVID-19 infection and related death had with the prevalence of anxiety and depression in the general population of the USA in a state-by-state multiple time-series analysis. Vector Error Correction Models are estimated and we subsequently evaluated the coefficients of the estimated models and calculated their impulse response functions for further interpretation. We found that COVID-19 incidence was positively associated with anxiety across the studied period for a majority of states. Variables related to social isolation had a varied effect depending on the state being considered.