Studies in Economics and Finance最新文献

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.

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.

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Practical implications

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.

Originality/value

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.

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.

Purpose

This study aims to examine the impact of the beginning of the Russia–Ukraine war and the Wagner Group’s attempted military coup against Putin’s regime on the European defense sector, consisting of weapons manufacturers.

Design/methodology/approach

The authors use the event study methodology to quantify the impact. That is, the authors assume that markets are efficient, and abnormal stock returns around the event dates capture the magnitudes of the impacts of the two events studied on European defense sector companies. The authors use the capital asset pricing model and two different multifactor models to estimate expected stock returns, which serve as the benchmark necessary to obtain abnormal returns.

Findings

The start of the war on February 24, 2022, when the Russian forces invaded Ukraine, was followed by high positive abnormal returns of up to 12% in the next few days. The results are particularly strong if multiple factors are used to control for the risk of the defense stocks. Conversely, the authors find a negative impact of the rebellion initiated by the mercenary Wagner Group’s chief, Yevgeny Prigozhin, on June 23, 2023, on the abnormal returns of defense industry stocks on the first trading day after the event.

Originality/value

To the best of the authors’ knowledge, this is the first study of the impact of the Russia–Ukraine war on the defense sector. Furthermore, this is the first study to measure the financial implications of the military coup initiated by the Wagner Group. The findings contribute to a rapidly growing literature on the financial implications of military conflicts around the world.

Purpose

Over the last few years, the European Central Bank (ECB) has adopted unconventional monetary policies. These measures aim to boost economic growth and increase inflation through the bond market. The purpose of this paper is to study the impact of the ECB’s quantitative easing (QE) on the investor’s behavior in the stock market.

Design/methodology/approach

First, the authors theoretically identify the transmission channels of the QE shocks to the stock market. Then, the authors empirically assess the financial market’s responses to QE shocks in a data-rich environment using a factor augmented VAR (FAVAR).

Findings

The results show that the ECB’s unconventional monetary policy positively affects the stock market. A QE shock leads to an increase in stock prices and a drop in the realized volatility and the implied risk premium. The authors also suggest that the ECB’s QE is transmitted to the stock market through five main channels: the liquidity, the expectation, the portfolio reallocation, the interest rates and the risk premium channels.

Practical implications

The findings help to better understand the behavior of stock market assets in a data-rich economic context and guide investors and policymakers in the presence of unconventional monetary tools. For instance, decision-makers and investors should consider the short-term effect of the QE interventions and the changing behavior of the financial actors over time. In addition, high stock market returns can increase risk appetite. This can lead investors to underestimate the market risk. Decision-makers and market participants should take into consideration the impact of the large injection of money through the QE, which may raise the risk of a speculative bubble in the financial market.

Originality/value

To the best of the authors’ knowledge, this is the first study that incorporates a theoretical and empirical analysis to explore QE transmission to the stock market in the European context. Unlike previous studies, the authors use the shadow rate proposed by Wu and Xia (2017) to quantify the effect of the ECB’s QE in a data-rich environment. The authors also include two key risk indicators – the stock market risk premium and the realized volatility – to capture investors’ behavior in the stock market following QE shocks.