International Journal of Finance & Economics最新文献

This paper presents evidence of the impact of AI investment on firm growth and how the relationship is sensitive to labour market conditions. Using the generalized method of moments (GMM) estimation on 1950 unique American firms over 1996–2016, we show that a 10% increase in AI investment leads to an increase in firm growth by 0.04%. However, this result is highly sensitive to labour market conditions, as labour productivity can positively impact firm growth, but labour cost and labour share negatively influence firm growth. These results offer original insights into an essential channel via which investment in AI may mediate firm growth.

Modern Monetary Theory (MMT) claims that a monetarily sovereign government like the US is never confronted by a real budget constraint since it can always monetise any deficit by printing money; and this need not be inflationary since it can always drain excess money from circulation by taxing. MMT economists claim that their theory is in line with the behaviour of the US data since the Financial Crisis, and argue that policy in the post-COVID recovery period should continue to be guided by MMT principles. We set out the MMT policy rules within a full DSGE model and test this model version against the data by indirect inference, side by side with a standard New Keynesian rival version, to evaluate these claims. We find that the MMT model is rejected by the data, while the standard model is not; and that the MMT policy rules imply a material loss of welfare compared to the standard ones.

While it is known that some elements of the business environment (BE), such as macroeconomic conditions, impact access to finance and the funding choices of SMEs, very little is known whether other elements of the BE—such as the institutional setting and the regulatory business environment (RBE)—influence access to (or supply of) finance and the funding choices of SMEs. Using a World Bank Enterprise Surveys panel sample (2003–2020) from 30 African countries and employing Propensity Score Matching (PSM) methods, it is noted that while an enabling institutional setting and RBE in Africa increases access to external finance for SMEs, SMEs still opt for retained earnings over funding from banking and non-banking financial institutions for their working capital. This funding behaviour can be explained by that SMEs located in enabling RBEs have increased productivity and financial performance and so can employ larger amounts of retained earnings for their operations. Furthermore, even though more accessible in enabling RBEs, external finance remains unaffordable for most SMEs in Africa. These findings indicate the need to tailor interventions to make varied finance more accessible and affordable for SMEs in developing countries.

This study analyses the financialisation of the carbon market and its possible external shocks, with a focus on the European Union Emissions Trading System (EU ETS), by investigating its quantile dependence and influence paths from stage three onwards. To achieve this, we construct a theoretical model of five factors related to the financialisation of the carbon market and empirically investigate the significant influencing factors and their influence paths under different quantiles using quantile group Least Absolute Shrinkage and Selection Operator (LASSO) and quantile regression models. We find that the price of WTI crude oil and the market risk-aversion index have a significant effect on the financialisation of the EU ETS at extremely high quantiles. Factors such as the WTI crude oil price, precipitation, average share price of thermal power companies, and the federal funds rate have a statistically significant impact on the medium quantiles. However, we find no significant influence at extremely low quantiles, indicating that policy instruments are necessary to effectively regulate the operation of the carbon market. Therefore, it is crucial for carbon market stakeholders to pay close attention to these factors and adapt to changing market conditions.

While facilitating people's access to finance and promoting financial coverage, online financing activities involve high capital costs that suppress economic growth. Using 282 Chinese cities during 2011–2020 as the sample, we examine the relationship between online financing and economic growth. Exploiting a variety of models, we find that online financing activities do not have significant effects on economic growth. Further evidence shows that the insignificant relationship between online financing and economic growth also exists in cities with less developed formal financial systems. Our analysis based on the context where borrowers and lenders do not know each other offline implies that the technology intended to promote financial coverage, if not reducing information asymmetry and hence the cost incurred in financial transactions, does not necessarily lead to desirable economic and social outcomes.

This work explores the role of weather shocks, measured as temperature deviations from their normal, in affecting GDP growth through a panel of 148 countries, spanning the period 1960–2019 and a panel quantile approach. The findings show that GDP growth is negatively affected by such deviations at higher quantiles, with the results receiving robust support from three alternative methodologies. The analysis also identifies two channels through which the findings receive further support, such as, the ‘heat-exposed’ sectors effect on labour productivity, and the impact of temperature deviations on the capital accumulation capacity. The results also survive the role of the country development status. Finally, the analysis identifies the role of the countries' geographical location. The results can have substantial merit for policymakers in terms of the role of climate conditions in the growth process, especially in poor countries.

This study endeavours to discern the pivotal factors contributing to the success of initial coin offerings (ICOs) on a global scale. Through a comprehensive analysis of ICO characteristics, we explore the intricate relationship between these attributes and the ultimate success of ICO projects. Our empirical findings show that projects that have secured presale funding, coupled with comprehensive token sale information, exhibit a markedly increased likelihood of achieving ICO success. We also employ the automated machine learning method to offer valuable insights into the potential determinants of ICO success. Furthermore, we delve into the underlying rationale behind ICO success by employing SHAP values to discern the relative importance of various ICO characteristics and examine the correlations among these attributes. This research contributes to a deeper understanding of ICO dynamics and offers empirical evidence regarding the critical factors that shape the success of ICO projects. Such insights hold significant implications for both industry practitioners and policymakers seeking to navigate the evolving landscape of blockchain-based fundraising initiatives.

Banking is one of the highly regulated industries, where a single set of global standards is likely to play a significant role in eliminating double reporting and reducing information asymmetry. Accordingly, we use data on 98 countries over 9 years to examine whether the use of International Financial Reporting Standard (IFRS) drives bank internationalisation. The results show that the use of IFRS is positively and significantly associated with an increase in foreign investment in the banking sector by easing regulatory compliance. However, in developing countries, the benefit of IFRS increasing foreign investment banks is associated with both easing regulatory compliance and reducing information asymmetry between banks and their clients. Our results are consistent across different sub-samplings, including EU versus non-EU, high versus low absence, and divergence between domestic standard and IFRS. These results provide reassurance and clear evidence of how IFRS facilitates the global flow of capital, even in a highly regulated industry such as banks. The results are robust to alternative measurements of variables and endogeneity tests using the Two-Stage Least Square, Two-step System Generalised Method of Moments and Propensity Score Matching.

The study investigates the role of governance (i.e., ‘voice and accountability,’ political stability/no violence, regulatory quality, government effectiveness, corruption-control and the rule of law) in the incidence of short-term debt services on infrastructure development in the perspective of telecommunication infrastructure and access to electricity. The focus of the study is on 52 African countries for the period 2002–2021. The generalised method of moments is employed as estimation strategy and the following findings are established. Debt service has a negative unconditional effect on access to electricity and telecommunication infrastructure. Governance dynamics moderate the negative effect of debt service on infrastructure dynamics. Effective moderation is from regulatory quality and corruption-control for access to electricity and from government effectiveness, regulatory quality, corruption-control and rule of law, for telecommunication infrastructure. Policy implications are discussed.

In this paper, we shed light on the impact of leverage on efficiency by introducing a new banking efficiency indicator that includes efficiency and stability conditions. This indicator relies on the leverage as a proxy of a bank's risk and stability. Banks' leverage played an important role in the last financial crash as well as in the Basel III regulatory rules. The results of the econometric investigation using a large sample of American commercial banks show that profit efficiency indicators including leverage are better predictors of future profits than current indicators, including other measures of bank risk. This is particularly evident for the period during the 2007–2009 financial crisis. Our findings have important policy implications, particularly in light of the recently implemented optimal leverage ratio.