Pub Date : 2024-09-16DOI: 10.1108/sef-04-2024-0255
Yi-Chia Wang, Hong-Lin Su
Purpose
This study aims to investigate the dynamics between exogenous shocks, financial stress and economic performance in the USA from January 1995 to August 2023.
Design/methodology/approach
Granger-causality tests and impulse response analyses are used to examine causal relationships and dynamic responses among crude oil prices, real M2 money supply, financial stress and key economic indicators.
Findings
This study reveals a significant correlation between elevated financial stress and reduced real output, along with disruptions in the labor market, potentially leading to economic recessionary trends. Failure to address these challenges could perpetuate labor market difficulties, weaken capital accumulation within the loanable funds market and ultimately hinder long-term economic growth prospects in the USA.
Practical implications
This study offers insights for policymakers to mitigate financial stress. Recommendations include enhancing financial surveillance, strengthening regulatory frameworks, promoting economic diversification and implementing countercyclical policies to stabilize the economy and support labor markets. In addition, proactive monitoring of financial stress indicators can serve as early warning signals, aiding in timely interventions and effective risk management strategies.
Originality/value
This research provides a comprehensive analysis of how the financial stress index (FSI) mediates the effects of external shocks on the US economy, addressing a gap in existing literature. The integration of the FSI into the analysis enhances the understanding of the transmission channels through which external shocks influence the economy.
{"title":"Unraveling exogenous shocks, financial stress and US economic performance","authors":"Yi-Chia Wang, Hong-Lin Su","doi":"10.1108/sef-04-2024-0255","DOIUrl":"https://doi.org/10.1108/sef-04-2024-0255","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>This study aims to investigate the dynamics between exogenous shocks, financial stress and economic performance in the USA from January 1995 to August 2023.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>Granger-causality tests and impulse response analyses are used to examine causal relationships and dynamic responses among crude oil prices, real M2 money supply, financial stress and key economic indicators.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>This study reveals a significant correlation between elevated financial stress and reduced real output, along with disruptions in the labor market, potentially leading to economic recessionary trends. Failure to address these challenges could perpetuate labor market difficulties, weaken capital accumulation within the loanable funds market and ultimately hinder long-term economic growth prospects in the USA.</p><!--/ Abstract__block -->\u0000<h3>Practical implications</h3>\u0000<p>This study offers insights for policymakers to mitigate financial stress. Recommendations include enhancing financial surveillance, strengthening regulatory frameworks, promoting economic diversification and implementing countercyclical policies to stabilize the economy and support labor markets. In addition, proactive monitoring of financial stress indicators can serve as early warning signals, aiding in timely interventions and effective risk management strategies.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>This research provides a comprehensive analysis of how the financial stress index (FSI) mediates the effects of external shocks on the US economy, addressing a gap in existing literature. The integration of the FSI into the analysis enhances the understanding of the transmission channels through which external shocks influence the economy.</p><!--/ Abstract__block -->","PeriodicalId":45607,"journal":{"name":"Studies in Economics and Finance","volume":"111 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142180338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-27DOI: 10.1108/sef-04-2024-0210
Catalin Gheorghe, Oana Panazan
Purpose
As the onset of the Russia–Ukraine military conflict on February 24, 2022, individuals from Ukraine have been relocating in search of safety and refuge. This study aims to investigate how the influx of Ukrainian refugees has impacted the stock markets and exchange rates of Ukraine's neighboring states.
Design/methodology/approach
The authors focused on the neighboring countries that share a western border with Ukraine and have received the highest number of refugees: Hungary, Poland, Romania and Slovakia. The analysis covered the period from April 24 to December 31, 2022. After this period, the influence of the refugees is small, insignificant. Wavelet coherence, wavelet power spectrum and the time-varying parameter vector autoregressions method were used for data processing.
Findings
The key finding are as follows: a link exists between the dynamics of refugees from Ukraine and volatility of the stock indices and exchange rate of the host countries; volatility was significant in the first weeks after the start of the conflict in all the analyzed states; and the highest volatility was recorded in Hungary and Poland; the effect of refugees was stronger on stock indices than that on exchange rates.
Originality/value
To the best of the authors’ knowledge, it is the first research that presents the impact of refugees from Ukraine on stock markets and exchange rates volatility in the countries analyzed.
{"title":"Influence of Ukrainian refugees on the exchange rate and stock market in neighboring countries","authors":"Catalin Gheorghe, Oana Panazan","doi":"10.1108/sef-04-2024-0210","DOIUrl":"https://doi.org/10.1108/sef-04-2024-0210","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>As the onset of the Russia–Ukraine military conflict on February 24, 2022, individuals from Ukraine have been relocating in search of safety and refuge. This study aims to investigate how the influx of Ukrainian refugees has impacted the stock markets and exchange rates of Ukraine's neighboring states.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>The authors focused on the neighboring countries that share a western border with Ukraine and have received the highest number of refugees: Hungary, Poland, Romania and Slovakia. The analysis covered the period from April 24 to December 31, 2022. After this period, the influence of the refugees is small, insignificant. Wavelet coherence, wavelet power spectrum and the time-varying parameter vector autoregressions method were used for data processing.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>The key finding are as follows: a link exists between the dynamics of refugees from Ukraine and volatility of the stock indices and exchange rate of the host countries; volatility was significant in the first weeks after the start of the conflict in all the analyzed states; and the highest volatility was recorded in Hungary and Poland; the effect of refugees was stronger on stock indices than that on exchange rates.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>To the best of the authors’ knowledge, it is the first research that presents the impact of refugees from Ukraine on stock markets and exchange rates volatility in the countries analyzed.</p><!--/ Abstract__block -->","PeriodicalId":45607,"journal":{"name":"Studies in Economics and Finance","volume":"4 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142180340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-25DOI: 10.1108/sef-05-2023-0218
Josua Tarigan, Monica Delia, Saarce Elsye Hatane
Purpose
This paper aims to investigate the impact of geopolitical events of the Russia–Ukraine conflict on the stock market volatility of G20 countries. Furthermore, the paper also investigates the possible reasons for any similarities or differences in the results of the three sectors.
Design/methodology/approach
This paper measures the impact of the stock market sectoral index price (SIP) by using the daily closing price as a dependent variable. In addition, this study uses three independent variables: geopolitical risk (GPR), commodity price (CP) and foreign exchange rate (FER). Seventeen countries from the G20 are analyzed using a daily timeframe from September 2021 to August 2022 (before and during the Russian invasion).
Findings
The results revealed that FER, CP and GPR all affect SIP, but the level of significance and positive/negative signs vary in all three sectors. The positive FER affects SIP in all sectors, while the negative CP and GPR significantly impact SIP in the energy and transportation sectors.
Research limitations/implications
This study’s research model is more suited for transportation and energy than consumer goods. Future researchers can enhance the research model for the consumer goods sector by incorporating additional variables to understand their relationship with SIP better.
Originality/value
This study explores the impact of the Russia–Ukraine conflict on the stock market in G20 countries, focusing on the top three most affected sectors.
{"title":"Impact of the Russia–Ukraine War: evidence from G20 countries","authors":"Josua Tarigan, Monica Delia, Saarce Elsye Hatane","doi":"10.1108/sef-05-2023-0218","DOIUrl":"https://doi.org/10.1108/sef-05-2023-0218","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>This paper aims to investigate the impact of geopolitical events of the Russia–Ukraine conflict on the stock market volatility of G20 countries. Furthermore, the paper also investigates the possible reasons for any similarities or differences in the results of the three sectors.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>This paper measures the impact of the stock market sectoral index price (SIP) by using the daily closing price as a dependent variable. In addition, this study uses three independent variables: geopolitical risk (GPR), commodity price (CP) and foreign exchange rate (FER). Seventeen countries from the G20 are analyzed using a daily timeframe from September 2021 to August 2022 (before and during the Russian invasion).</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>The results revealed that FER, CP and GPR all affect SIP, but the level of significance and positive/negative signs vary in all three sectors. The positive FER affects SIP in all sectors, while the negative CP and GPR significantly impact SIP in the energy and transportation sectors.</p><!--/ Abstract__block -->\u0000<h3>Research limitations/implications</h3>\u0000<p>This study’s research model is more suited for transportation and energy than consumer goods. Future researchers can enhance the research model for the consumer goods sector by incorporating additional variables to understand their relationship with SIP better.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>This study explores the impact of the Russia–Ukraine conflict on the stock market in G20 countries, focusing on the top three most affected sectors.</p><!--/ Abstract__block -->","PeriodicalId":45607,"journal":{"name":"Studies in Economics and Finance","volume":"18 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141784780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-09DOI: 10.1108/sef-04-2024-0203
Andrés Oviedo-Gómez, Sandra Milena Londoño-Hernández, Diego Fernando Manotas-Duque
Purpose
This study aims to assess volatility spillovers and directional connectedness between electricity (EPs) and natural gas prices (GPs) in the Canadian electricity market, based on a hydrothermal power generation market strongly dependent on exogenous variables such as fossil fuel prices and climatology factors.
Design/methodology/approach
The methodology is divided into two stages. First, a quantile vector autoregression model is used to evaluate the direction and magnitude of the influence between natural gas and electricity prices through different quantiles of their distributions. Second, a cross-quantilogram is estimated to measure the directional predictability between these prices. The data set consists of daily electricity and natural gas prices between January 2015 and December 2023.
Findings
The main finding shows that electricity prices are pure shock receivers of volatility from natural gas prices for the different quantiles. In this way, natural gas price fluctuations explain 0.20%, 0.98% and 22.72% of electricity price volatility for the 10th, 50th and 90th quantiles, respectively. On the other hand, a significant and positive correlation is observed in the high quantiles of the electricity prices for any natural gas price value.
Originality/value
The study described the risk to the electricity market caused by nonrenewable source price fluctuations and provided evidence for designing regulatory policies to reduce its exposure in Alberta, Canada. It also allows us to understand the importance of natural gas in the energy transition process and define it as the fundamental determinant of the electricity market dynamic.
{"title":"Directional connectedness between the electricity prices and natural gas prices: evidence from Alberta’s electricity market","authors":"Andrés Oviedo-Gómez, Sandra Milena Londoño-Hernández, Diego Fernando Manotas-Duque","doi":"10.1108/sef-04-2024-0203","DOIUrl":"https://doi.org/10.1108/sef-04-2024-0203","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>This study aims to assess volatility spillovers and directional connectedness between electricity (EPs) and natural gas prices (GPs) in the Canadian electricity market, based on a hydrothermal power generation market strongly dependent on exogenous variables such as fossil fuel prices and climatology factors.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>The methodology is divided into two stages. First, a quantile vector autoregression model is used to evaluate the direction and magnitude of the influence between natural gas and electricity prices through different quantiles of their distributions. Second, a cross-quantilogram is estimated to measure the directional predictability between these prices. The data set consists of daily electricity and natural gas prices between January 2015 and December 2023.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>The main finding shows that electricity prices are pure shock receivers of volatility from natural gas prices for the different quantiles. In this way, natural gas price fluctuations explain 0.20%, 0.98% and 22.72% of electricity price volatility for the 10th, 50th and 90th quantiles, respectively. On the other hand, a significant and positive correlation is observed in the high quantiles of the electricity prices for any natural gas price value.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>The study described the risk to the electricity market caused by nonrenewable source price fluctuations and provided evidence for designing regulatory policies to reduce its exposure in Alberta, Canada. It also allows us to understand the importance of natural gas in the energy transition process and define it as the fundamental determinant of the electricity market dynamic.</p><!--/ Abstract__block -->","PeriodicalId":45607,"journal":{"name":"Studies in Economics and Finance","volume":"78 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141575927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-05DOI: 10.1108/sef-09-2023-0540
Zbigniew Korzeb, Renata Karkowska, Anna Matysek-Jędrych, Paweł Niedziółka
Purpose
A review of the literature provides a solid reason to believe that an increase in environmental, social and corporate governance (ESG) activities have a positive impact on banks’ default risk (DR). However, the increasing impact of climate risk on credit, operational and market risks, as well as the reduced availability of funding for banks that underperform in terms of ESG risk, is a concern. Therefore, the purpose of this study is to verify the relevance of the implementation of ESG policies to a bank’s DR, against the background of macroeconomic and bank-specific factors.
Design/methodology/approach
Using a data set of 303 commercial banks from 61 countries from 2012 to 2021 and a panel regression methodology, the empirical importance of ESG activities for bank DR is documented. The two-stage generalized method of moments estimator was used to test the research questions.
Findings
Comparing different factors, the results highlight the positive impact of ESG activities on the bank’s DR. However, this relationship varies according to the specific pillars of the bank’s sustainability policies and changes into negative ones.
Originality/value
This paper fits the domain of DR management research, investigating whether ESG performance affects bank DR while controlling macroeconomic and market drivers. Prior literature has shown evidence on the relationship between macro and market forces and a bank’s risk profile while a limited one on the non-market drivers. The main contribution is to consider ESG (in total and as separate pillars) as independent drivers of the bank risk profile.
目的 通过对文献的回顾,我们有充分的理由相信,环境、社会和公司治理(ESG)活动的增加会对银行的违约风险(DR)产生积极影响。然而,气候风险对信用风险、经营风险和市场风险的影响越来越大,而且在环境、社会和公司治理风险方面表现不佳的银行所能获得的资金也会减少,这一点令人担忧。因此,本研究的目的是在宏观经济和银行特定因素的背景下,验证 ESG 政策的实施与银行 DR 的相关性。设计/方法/途径利用 2012 年至 2021 年 61 个国家 303 家商业银行的数据集和面板回归方法,记录 ESG 活动对银行 DR 的经验重要性。研究结果比较了不同的因素,结果凸显了环境、社会和治理活动对银行灾难恢复能力的积极影响。然而,这种关系因银行可持续发展政策的具体支柱而异,并转化为负面关系。先前的文献已经证明了宏观和市场力量与银行风险状况之间的关系,但对非市场驱动因素的研究却很有限。本文的主要贡献在于将环境、社会和公司治理(总体和单独的支柱)视为银行风险状况的独立驱动因素。
{"title":"How do ESG challenges affect default risk? An empirical analysis from the global banking sector perspective","authors":"Zbigniew Korzeb, Renata Karkowska, Anna Matysek-Jędrych, Paweł Niedziółka","doi":"10.1108/sef-09-2023-0540","DOIUrl":"https://doi.org/10.1108/sef-09-2023-0540","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>A review of the literature provides a solid reason to believe that an increase in environmental, social and corporate governance (ESG) activities have a positive impact on banks’ default risk (DR). However, the increasing impact of climate risk on credit, operational and market risks, as well as the reduced availability of funding for banks that underperform in terms of ESG risk, is a concern. Therefore, the purpose of this study is to verify the relevance of the implementation of ESG policies to a bank’s DR, against the background of macroeconomic and bank-specific factors.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>Using a data set of 303 commercial banks from 61 countries from 2012 to 2021 and a panel regression methodology, the empirical importance of ESG activities for bank DR is documented. The two-stage generalized method of moments estimator was used to test the research questions.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>Comparing different factors, the results highlight the positive impact of ESG activities on the bank’s DR. However, this relationship varies according to the specific pillars of the bank’s sustainability policies and changes into negative ones.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>This paper fits the domain of DR management research, investigating whether ESG performance affects bank DR while controlling macroeconomic and market drivers. Prior literature has shown evidence on the relationship between macro and market forces and a bank’s risk profile while a limited one on the non-market drivers. The main contribution is to consider ESG (in total and as separate pillars) as independent drivers of the bank risk profile.</p><!--/ Abstract__block -->","PeriodicalId":45607,"journal":{"name":"Studies in Economics and Finance","volume":"43 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141550640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-05DOI: 10.1108/sef-01-2024-0026
Jin Cai, Gerard Pinto
Purpose
This paper aims to improve how investors can better manage their exposure to bitcoin (BTC), given the growing importance of BTC and the accompanying high volatility of BTC. This paper tests whether altcoins can serve as safe havens and diversifiers against exposure to BTC.
Design/methodology/approach
Using daily returns of altcoins and BTC from 2014 to early 2022, this paper examines the relationship between altcoins and BTC in a GARCH regression framework.
Findings
This paper finds that altcoins act as reliable safe havens during periods of extremely negative BTC returns and provide BTC investors with diversification benefits during normal periods. The safe haven effect of altcoins is superior to that of conventional assets. This paper presents evidence that this safe haven property of altcoins can be attributed to the informational efficiency channel, which arose from the increased adoption of BTC by institutional investors.
Research limitations/implications
The study uses a data set from 2014 to early 2022. While the sample is among the largest samples in the literature on crypto assets and includes adequate BTC tail events to test the hypotheses, it may not capture more recent changes in the crypto markets.
Practical implications
The findings suggest that BTC investors can enjoy diversification and safe haven protections by including altcoins in their portfolios.
Originality/value
This paper’s focus on alternative cryptocurrencies (altcoins) as potential diversifiers and safe havens is original. The hypothesis about altcoins being better alternatives during extreme negative movements in BTC prices is a unique contribution. The test of the role of the information efficiency channel further enhances the paper’s originality.
{"title":"Altcoins as safe havens for bitcoin investors","authors":"Jin Cai, Gerard Pinto","doi":"10.1108/sef-01-2024-0026","DOIUrl":"https://doi.org/10.1108/sef-01-2024-0026","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>This paper aims to improve how investors can better manage their exposure to bitcoin (BTC), given the growing importance of BTC and the accompanying high volatility of BTC. This paper tests whether altcoins can serve as safe havens and diversifiers against exposure to BTC.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>Using daily returns of altcoins and BTC from 2014 to early 2022, this paper examines the relationship between altcoins and BTC in a GARCH regression framework.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>This paper finds that altcoins act as reliable safe havens during periods of extremely negative BTC returns and provide BTC investors with diversification benefits during normal periods. The safe haven effect of altcoins is superior to that of conventional assets. This paper presents evidence that this safe haven property of altcoins can be attributed to the informational efficiency channel, which arose from the increased adoption of BTC by institutional investors.</p><!--/ Abstract__block -->\u0000<h3>Research limitations/implications</h3>\u0000<p>The study uses a data set from 2014 to early 2022. While the sample is among the largest samples in the literature on crypto assets and includes adequate BTC tail events to test the hypotheses, it may not capture more recent changes in the crypto markets.</p><!--/ Abstract__block -->\u0000<h3>Practical implications</h3>\u0000<p>The findings suggest that BTC investors can enjoy diversification and safe haven protections by including altcoins in their portfolios.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>This paper’s focus on alternative cryptocurrencies (altcoins) as potential diversifiers and safe havens is original. The hypothesis about altcoins being better alternatives during extreme negative movements in BTC prices is a unique contribution. The test of the role of the information efficiency channel further enhances the paper’s originality.</p><!--/ Abstract__block -->","PeriodicalId":45607,"journal":{"name":"Studies in Economics and Finance","volume":"34 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141550641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-02DOI: 10.1108/sef-09-2023-0566
Tilahun Emiru, Sara Weisblatt
Purpose
This study aims to examine the long-run relationship between macroeconomic and financial conditions and the aggregate number of mergers and acquisitions (M&As) in the USA, drawing on data spanning from 1928 to 2019.
Design/methodology/approach
The study estimated a Vector Error Correction Model (VECM) encompassing four variables: the aggregate number of M&As, industrial production, the rates on three-month U.S. treasury bills and the closing price of the Dow Jones Industrial Average.
Findings
There exists a long-run relationship among the four variables. An increase in industrial production is associated with a fall in M&A transactions, reflecting a tendency for M&A waves to start during economic downturns. Similarly, contractionary monetary policy, which often happens during good economic and financial times, leads to a decline in M&A activity. When the equilibrium among the four variables is disrupted, the aggregate number of M&As, along with financial conditions, works to restore the equilibrium.
Originality/value
To the best of the authors’ knowledge, this is the first study to examine the long-run relationship between macroeconomic and financial conditions using data spanning nearly a century.
{"title":"Economic tides and merger waves: insights from a long-run perspective","authors":"Tilahun Emiru, Sara Weisblatt","doi":"10.1108/sef-09-2023-0566","DOIUrl":"https://doi.org/10.1108/sef-09-2023-0566","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>This study aims to examine the long-run relationship between macroeconomic and financial conditions and the aggregate number of mergers and acquisitions (M&As) in the USA, drawing on data spanning from 1928 to 2019.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>The study estimated a Vector Error Correction Model (VECM) encompassing four variables: the aggregate number of M&As, industrial production, the rates on three-month U.S. treasury bills and the closing price of the Dow Jones Industrial Average.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>There exists a long-run relationship among the four variables. An increase in industrial production is associated with a fall in M&A transactions, reflecting a tendency for M&A waves to start during economic downturns. Similarly, contractionary monetary policy, which often happens during good economic and financial times, leads to a decline in M&A activity. When the equilibrium among the four variables is disrupted, the aggregate number of M&As, along with financial conditions, works to restore the equilibrium.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>To the best of the authors’ knowledge, this is the first study to examine the long-run relationship between macroeconomic and financial conditions using data spanning nearly a century.</p><!--/ Abstract__block -->","PeriodicalId":45607,"journal":{"name":"Studies in Economics and Finance","volume":"14 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141508692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-28DOI: 10.1108/sef-03-2024-0135
Nicholas Apergis
Purpose
The purpose of this paper is to explore the degree of inflation persistence across all US metro areas over the post-pandemic period.
Design/methodology/approach
Both the Multivariate Core Trend (MCT) model and a fractional integration model, that is the Multivariate Unobserved-Components Stochastic Volatility Outlier-adjusted (MUCSVO) model are estimated.
Findings
The findings provide clear evidence of a significant inflation persistence in ten metro areas and the absence of persistence in the remaining areas, implying that in the former areas, inflation clearly indicates a strong persistent pattern. In other words, in these ten areas, the persistent component dominates the evolution of the trend and stands as a significant driver of inflation.
Research limitations/implications
The findings have important implications for US policymakers to consider implementing more targeted policies to address inflation in specific metro areas to reduce the overall inflation rate, or they may need to consider tailoring fiscal policies to address inflationary pressures in specific metro areas. The findings illustrate the need for targeted policy interventions to address inflationary pressures in specific areas, as well as the importance of understanding the drivers of inflation persistence to develop effective policy responses. The findings also provide insights to firms on how to mitigate the risks of inflation. They may need to diversify their products or supplier base so that they do not rely on areas experiencing persistent inflation.
Originality/value
This paper contributes to the literature by extending the discussion of the impact of the recent pandemic crisis on US regional inflation. The findings have important implications for US policymakers to consider implementing more targeted policies to address inflation in specific metro areas to reduce the overall inflation rate, or they may need to consider tailoring fiscal policies to address inflationary pressures in specific metro areas. The findings illustrate the need for targeted policy interventions to address inflationary pressures in specific areas, as well as the importance of understanding the drivers of inflation persistence to develop effective policy responses. The findings also provide insights to firms on how to mitigate the risks of inflation. They may need to diversify their products or supplier base so that they do not rely on areas experiencing persistent inflation.
{"title":"Inflation persistence: new evidence across US metro areas","authors":"Nicholas Apergis","doi":"10.1108/sef-03-2024-0135","DOIUrl":"https://doi.org/10.1108/sef-03-2024-0135","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>The purpose of this paper is to explore the degree of inflation persistence across all US metro areas over the post-pandemic period.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>Both the Multivariate Core Trend (MCT) model and a fractional integration model, that is the Multivariate Unobserved-Components Stochastic Volatility Outlier-adjusted (MUCSVO) model are estimated.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>The findings provide clear evidence of a significant inflation persistence in ten metro areas and the absence of persistence in the remaining areas, implying that in the former areas, inflation clearly indicates a strong persistent pattern. In other words, in these ten areas, the persistent component dominates the evolution of the trend and stands as a significant driver of inflation.</p><!--/ Abstract__block -->\u0000<h3>Research limitations/implications</h3>\u0000<p>The findings have important implications for US policymakers to consider implementing more targeted policies to address inflation in specific metro areas to reduce the overall inflation rate, or they may need to consider tailoring fiscal policies to address inflationary pressures in specific metro areas. The findings illustrate the need for targeted policy interventions to address inflationary pressures in specific areas, as well as the importance of understanding the drivers of inflation persistence to develop effective policy responses. The findings also provide insights to firms on how to mitigate the risks of inflation. They may need to diversify their products or supplier base so that they do not rely on areas experiencing persistent inflation.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>This paper contributes to the literature by extending the discussion of the impact of the recent pandemic crisis on US regional inflation. The findings have important implications for US policymakers to consider implementing more targeted policies to address inflation in specific metro areas to reduce the overall inflation rate, or they may need to consider tailoring fiscal policies to address inflationary pressures in specific metro areas. The findings illustrate the need for targeted policy interventions to address inflationary pressures in specific areas, as well as the importance of understanding the drivers of inflation persistence to develop effective policy responses. The findings also provide insights to firms on how to mitigate the risks of inflation. They may need to diversify their products or supplier base so that they do not rely on areas experiencing persistent inflation.</p><!--/ Abstract__block -->","PeriodicalId":45607,"journal":{"name":"Studies in Economics and Finance","volume":"27 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141508693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<h3>Purpose</h3><p>This study aims to investigate connections between the development of robotic and artificial intelligence (AI) and green crypto investments. The author also explores the influences of global uncertainty shocks like the COVID-19 pandemic and international conflicts on the role of each channel.</p><!--/ Abstract__block --><h3>Design/methodology/approach</h3><p>In this research, the author uses a cutting-edge model-free connectedness approach to investigate the relationships between the development of Global X Robotics and AI (BOTZ) and the volatility of green crypto investments from November 9, 2017 to March 24, 2023.</p><!--/ Abstract__block --><h3>Findings</h3><p>In the sample duration, the findings reveal a two-way link between AI and green/nongreen cryptocurrencies. Throughout the examined period, BOTZ has been a net receiver of shocks as determined by the net total connectedness. Among the main spillover shock carriers in the system, green cryptocurrencies are the most significant. The net pairwise directional connectivity reveals that green cryptocurrencies controlled BOTZ throughout the analyzed time, particularly during the COVID-19 era as well as the Ukraine–Russia crisis. According to the findings, the proposed system is vulnerable to a high level of indication influence.</p><!--/ Abstract__block --><h3>Practical implications</h3><p>The results have important policy implications for investors and governments, as well as methods from the spillovers across the various indicators and their interconnections. Sharp information on the primary contagions among these indicators aids politicians in designing the most appropriate policies.</p><!--/ Abstract__block --><h3>Originality/value</h3><p>To the best of the authors’ knowledge, this paper is the first to look at the link between AI, technological advancement and green cryptocurrency investing. Second, this study developed a methodology for examining instability links between various factors that is more appropriate for investigating these linkages. This study investigates the links between AI, technical advancement and green digital currencies using a cutting-edge model-free connectivity method. This work is also the first to examine the interconnection between volatility derived from AI, technological development and green cryptocurrency investments in light of unknown events, such as the COVID-19 pandemic and the Ukrainian–Russian conflict. Finally, this study includes a daily database from the BOTZ fund, which attempts to invest in firms that stand to gain from rising robotics and AI use. Cardano (ADA), IOTA, NANO (XNO), Stellar Lumens and Tron are examples of green cryptocurrencies, whereas Bitcoin is an example of a nongreen cryptocurrency. These virtual currencies are being used to investigate the relationship between investor mood and green and nongreen digital currencies. The data set spans the period from November 9, 2017 to March 24, 2023.</p><!--/ Abstra
目的本研究旨在探讨机器人和人工智能(AI)的发展与绿色加密货币投资之间的联系。作者还探讨了 COVID-19 大流行病和国际冲突等全球不确定性冲击对各渠道作用的影响。在本研究中,作者采用了一种前沿的无模型连接性方法,研究了 2017 年 11 月 9 日至 2023 年 3 月 24 日期间 Global X Robotics and AI(BOTZ)的发展与绿色加密货币投资波动性之间的关系。研究结果在样本持续时间内,研究结果揭示了 AI 与绿色/非绿色加密货币之间的双向联系。在整个研究期间,BOTZ 一直是冲击的净接收者,这是由净总连接度决定的。在系统中的主要溢出冲击载体中,绿色加密货币最为重要。净成对方向连通性显示,绿色加密货币在整个分析时间内控制着 BOTZ,尤其是在 COVID-19 时代以及乌克兰-俄罗斯危机期间。根据研究结果,拟议的系统很容易受到高水平的指示影响。实际意义研究结果对投资者和政府具有重要的政策意义,同时也是各种指标的溢出效应及其相互联系的方法。据作者所知,本文是第一篇研究人工智能、技术进步和绿色加密货币投资之间联系的论文。其次,本研究开发了一种研究各种因素之间不稳定性联系的方法,这种方法更适合研究这些联系。本研究采用最前沿的无模型连接方法研究了人工智能、技术进步和绿色数字货币之间的联系。这项工作也是首次根据 COVID-19 大流行病和乌克兰-俄罗斯冲突等未知事件,研究人工智能、技术发展和绿色加密货币投资所产生的波动性之间的相互联系。最后,本研究包含了 BOTZ 基金的每日数据库,该基金试图投资于那些能从机器人和人工智能应用的增长中获益的公司。Cardano (ADA)、IOTA、NANO (XNO)、Stellar Lumens 和 Tron 是绿色加密货币的例子,而比特币则是非绿色加密货币的例子。这些虚拟货币被用来研究投资者情绪与绿色和非绿色数字货币之间的关系。数据集的时间跨度为 2017 年 11 月 9 日至 2023 年 3 月 24 日。
{"title":"In what way can worldwide robotics and artificial intelligence encourage development in green crypto investments? An implementation of a model-free connectedness technique","authors":"Le Thanh Ha","doi":"10.1108/sef-11-2023-0668","DOIUrl":"https://doi.org/10.1108/sef-11-2023-0668","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>This study aims to investigate connections between the development of robotic and artificial intelligence (AI) and green crypto investments. The author also explores the influences of global uncertainty shocks like the COVID-19 pandemic and international conflicts on the role of each channel.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>In this research, the author uses a cutting-edge model-free connectedness approach to investigate the relationships between the development of Global X Robotics and AI (BOTZ) and the volatility of green crypto investments from November 9, 2017 to March 24, 2023.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>In the sample duration, the findings reveal a two-way link between AI and green/nongreen cryptocurrencies. Throughout the examined period, BOTZ has been a net receiver of shocks as determined by the net total connectedness. Among the main spillover shock carriers in the system, green cryptocurrencies are the most significant. The net pairwise directional connectivity reveals that green cryptocurrencies controlled BOTZ throughout the analyzed time, particularly during the COVID-19 era as well as the Ukraine–Russia crisis. According to the findings, the proposed system is vulnerable to a high level of indication influence.</p><!--/ Abstract__block -->\u0000<h3>Practical implications</h3>\u0000<p>The results have important policy implications for investors and governments, as well as methods from the spillovers across the various indicators and their interconnections. Sharp information on the primary contagions among these indicators aids politicians in designing the most appropriate policies.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>To the best of the authors’ knowledge, this paper is the first to look at the link between AI, technological advancement and green cryptocurrency investing. Second, this study developed a methodology for examining instability links between various factors that is more appropriate for investigating these linkages. This study investigates the links between AI, technical advancement and green digital currencies using a cutting-edge model-free connectivity method. This work is also the first to examine the interconnection between volatility derived from AI, technological development and green cryptocurrency investments in light of unknown events, such as the COVID-19 pandemic and the Ukrainian–Russian conflict. Finally, this study includes a daily database from the BOTZ fund, which attempts to invest in firms that stand to gain from rising robotics and AI use. Cardano (ADA), IOTA, NANO (XNO), Stellar Lumens and Tron are examples of green cryptocurrencies, whereas Bitcoin is an example of a nongreen cryptocurrency. These virtual currencies are being used to investigate the relationship between investor mood and green and nongreen digital currencies. The data set spans the period from November 9, 2017 to March 24, 2023.</p><!--/ Abstra","PeriodicalId":45607,"journal":{"name":"Studies in Economics and Finance","volume":"417 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141197324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper aims to examine the relationships among environmental, social and governance (ESG) practices, innovation and economic growth in five Asian countries from 1990 to 2020.
Design/methodology/approach
The study innovatively constructed the ESG index at the country level by using frequency statistics on text mining and factor analysis for each country over time. In addition, this study used the autoregressive distributed lag method to establish a long-term relationship.
Findings
The authors discovered that ESG practices among corporate entities significantly impact economic growth in Malaysia, the Philippines and Singapore. Specifically, the environmental component positively affects the growth of Malaysia, Thailand and the Philippines, while the governance components of ESG contribute to Thailand’s economic growth. The authors also discovered that innovation improves countries’ economic growth, thus offering policy insights into promoting ESG practices and stimulating the ecosystem for innovation.
Originality/value
The paper fills the gap left in previous inconclusive findings on the association between ESG practices and country growth.
{"title":"ESG, innovation, and economic growth: an empirical evidence","authors":"Siti Nurazira Mohd Daud, Nur Syazwina Ghazali, Nur Hafizah Mohammad Ismail","doi":"10.1108/sef-11-2023-0692","DOIUrl":"https://doi.org/10.1108/sef-11-2023-0692","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>This paper aims to examine the relationships among environmental, social and governance (ESG) practices, innovation and economic growth in five Asian countries from 1990 to 2020.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>The study innovatively constructed the ESG index at the country level by using frequency statistics on text mining and factor analysis for each country over time. In addition, this study used the autoregressive distributed lag method to establish a long-term relationship.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>The authors discovered that ESG practices among corporate entities significantly impact economic growth in Malaysia, the Philippines and Singapore. Specifically, the environmental component positively affects the growth of Malaysia, Thailand and the Philippines, while the governance components of ESG contribute to Thailand’s economic growth. The authors also discovered that innovation improves countries’ economic growth, thus offering policy insights into promoting ESG practices and stimulating the ecosystem for innovation.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>The paper fills the gap left in previous inconclusive findings on the association between ESG practices and country growth.</p><!--/ Abstract__block -->","PeriodicalId":45607,"journal":{"name":"Studies in Economics and Finance","volume":"77 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141150660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}