This paper evaluates the fit-for-purpose of the monetary policy measures implemented by the Bank of Ghana in response to the COVID-19 pandemic. We examine the effectiveness of the BoG’s policy interventions in the context of vector autoregressions augmented with macroeconomic and financial indicators. We demonstrate that the BoG’s monetary policy measures have had nominal, real, and financial effects. The monetary interventions have been successful, as evidenced by the gradual reduction in the sovereign spread, improved financial stability, and increased real economic activity. Our findings suggest that balance sheet actions are less effective and should be moderated in the conduct of monetary policy in jurisdictions without zero lower bound constraints. However, the analysis indicates that in times of crisis, central banks should deploy both standard and non-standard tools to stabilize dysfunctional financial markets and avoid a deflationary spiral. The historical and variance decomposition of the data reveal that monetary policy shocks have historically made the largest contributions to the targeted macro-financial aggregates during the pandemic episodes.

This research investigates the determinants of women's empowerment within households in a developing country. The investigation specifically focuses on the impact of employment and fertility, considering constraints imposed by family rules that play a pivotal role in shaping women's empowerment. The theoretical framework outlined in this study posits a simplistic model demonstrating that, within the prevailing family structure and household composition, earned income and fertility may bear significant relevance. Utilizing data extracted from the Pakistan Social and Living Standards Measurement Survey, we engage in estimating the level of female empowerment, operationalized as the extent of female authority over household expenditures. Notably, our empirical approach accounts for the endogeneity of employment and fertility through a two-stage estimation process. This involves leveraging information on family rules—representative of a family's cultural norms—pertaining to work and childbearing. Our empirical findings affirm the viability of family-specific rules as instruments to estimate and subsequently predict employment and fertility. Importantly, the evidence gleaned underscores the critical role of selecting valid threat options in theoretical analyses of women's empowerment.

Objective: The paper, specifically examines whether the recently formed Regional Comprehensive Economic Partnership (RCEP) can potentially facilitate minimising the constraints to renewable energy goods exports at the regional level in Asia. Data, Methodology and Findings: Using the panel data from 11 RCEP members from 2006 to 2014, this study has applied the ‘meta frontier stochastic gravity frontier’ methodology and confirms that the establishment of RCEP has the potential to improve trade in renewable energy commodities within the RCEP region. Policy Implications: The policy implication is that when countries work together, it will lead to enormous benefits for national, regional, and worldwide prospects of a more sustainable energy future. Practical Policy Implications: In terms of practical policy implications, the developed RCEP member countries should actively engage in promoting R&D activities and protecting intellectual property rights concerning renewable energy production, which are essential for countries to integrate with the world market and to lift the export frontiers of both the developed and developing RCEP member countries to reach the unrestricted export of renewable energy technology.

This paper attempts to introduce an overlapping generations structure into Paul Krugman's "The world's smallest macroeconomic model" (Krugman (1999)) to examine the implications of fiscal policy, particularly fiscal deficits, in a framework suitable for policy analysis. In that paper, Krugman argued that under the price rigidity assumption, a shortage in the money supply leads to underemployment and recession, so increasing the money supply would eliminate underemployment and restore full employment. But how can the money supply be increased? I show that in order to restore full employment out of a recession, a fiscal deficit is needed to increase the money supply. I also show that in a growing economy, fiscal deficits are necessary to maintain full employment at constant prices or inflation. Fiscal deficits are not only effective in pulling the economy out of recession, they are even necessary for growth to continue without recession or inflation. The fiscal deficit in this paper represents the difference between government spending and government revenues. If this difference is positive, we say that the government is in deficit. Krugman's original model is a one-period static model. I intend to extend this model to a dynamic overlapping generations model.

This study examines the role of news sentiments in the GCC equity markets’ connectedness. We collected news titles for the period from 22nd June 2006 until 31st December 2020 from Gulf News, which is the most widely read English newspaper in the Arab World. We filter these news titles using a carefully designed list of keywords that capture public sentiment on matters related to financial markets. Next, we classify the news titles to compute the geographically distinguished sentiment indexes that allow for a detailed analysis of the source of news sentiment spillovers to compare the impact of domestic versus regional sentiments on the equity markets of GCC countries. Our quantile regression results reveal that equity markets in the GCC are most sensitive to news sentiments when underperforming. Moreover, our results from the connectedness approach suggest that the UAE equity markets are most influenced by domestic sentiments, whilst the KSA equity market is most influenced by regional sentiments from the other GCC countries. Mixed results are found for other countries. The time-varying component of this study also shows that the influence of news spillovers intensified during the major crises events, including the COVID-19 outbreak.

Competitive balance indicates the degree of control participating teams have over a sports competition. Supporters look for excuses to justify their team’s defeat and the triumph of their rivals. If the competition has required a preliminary qualifying group stage, they will argue that the winning team was in an "easy group" from the start, and their team was unlucky to be in a "difficult group". It is therefore of interest to determine what is an "easy group" and what is a "difficult group". This is directly related to the concept of competitive balance. We have a wide range of indices to measure competitive balance. We will use the Distance to Competitive Balance, a standardized index that complies cardinality property. The perfectly unbalanced distribution is the truncated cascade, which allows the maximum value of concentration to be obtained. We focus our attention on the UEFA Champions League, before and after competition, and we measure the competitive balance of the qualifying stage groups between the 1999/2000 and 2022/2023 seasons. The composition of the UEFA Champions League groups seems to be balanced and has no influence on which team will be the champion. A highly competitive group will be more "difficult" in terms of qualifying than a highly concentrated one. Supporters say that their team was unlucky to be in a “difficult” group, but the data does not prove them right.

Electricity price volatility in developing economies, particularly Nigeria, presents a significant challenge to sustainable development. In this paper, we examine the macroeconomic drivers of electricity prices (ELP) in Nigeria based on annual data spanning 1980-2022 and the autoregressive distributed lag (ARDL) procedure. Our model estimates the long-run and short-run impacts of population growth (PG), economic growth (GDP), crude oil price (COPR), and electricity consumption (ELC) on electricity prices (ELP). The empirical findings reveal a positive and long-run effect of PG on ELP, indicating that rising demand from a growing population increases electricity prices. In the short-run, ELC surprisingly co-moved with ELP, which may be attributable to price-sensitive demand within specific consumer segments or periods. Furthermore, GDP and COPR exert positive effects on ELP, indicating that economic growth drives energy consumption and prices, and the cost-driven impact of fossil fuel dependence in electricity generation. These findings shed light on the complex interplay of demographic, economic, and energy market-related forces driving electricity prices in Nigeria. Therefore, the paper proposes some policy suggestions based on the empirical findings.

The paper is motivated by the growth of the electronic payments system and its relevance in enhancing the banking industry's earnings. Consequently, the paper examines the causal relationship between the electronic payments system and the banking industry's returns in Nigeria. The paper offers some important contributions to the literature involving the use of an approach that allows for data-driven identification of the change points in the electronic payments system and the banking industry's returns nexus. The paper discovered three important findings. First, the causal relationship between the electronic payments system and the banking industry's returns in Nigeria changes with time changes. Second, there is evidence of causality between the electronic payments system and returns on assets and equity, however, the causality was more evident under the recursive window. Third, the causal relationship was more evident in some specific periods such as 2020Q4, all quarters of 2015 to 2016, and 2020 to the end of 2023. The paper recommends that policymakers should revisit and reinvigorate the specific cashless policies instituted in 2012-2016 that aided higher returns to the banking industry. Similarly, the Central Bank of Nigeria and other banking industry players should intensify efforts to encourage the use of electronic payments due to their usefulness and ability to enhance the banking industry's earnings.

This paper examines the information content of selected US industries focusing on the dynamic linkages among these industries, the stock market and a number of fundamental variables. The period of investigation spans from January 1960 to December 2021. The empirical strategy includes several methodologies such as regressions, vector autoregressions and volatility models. The idea is to investigate the dynamic linkages among these series at both the mean and the volatility levels. The results point to significant industry returns’ explanatory power for many predictors of economic activity including the stock market. Further, time-varying analysis of the linkages among the industries and the stock market’s returns reveal that certain industries such as Oil and Financials provide consistent information leadership over other industries and across decades. Further, upon assessing the industry–market return volatility spillovers, it was found that a market risk–return profile may not always be economically significant and timely for investors. Finally, crises, financial or otherwise, affect industries but to differing degrees.

The issue of food security has become a global challenge, and it is therefore crucial to seek measures to ensure food security. As an emerging economic model, the digital economy is regarded as the most effective tool for the modernization of agricultural development. As a large food-producing country, China faces serious problems of agricultural non-point source pollution and food loss and waste. The purpose of this study is to explore the impact of digital village construction on food security. We measure the level of digital village construction and food security by entropy method and use the spatial Durbin model to analyze them. In this paper, we found that digital village construction facilitates food security not only in the region but also in neighboring regions. In addition, we found that the promotion effect is significant in main grain producing regions, while the opposite result is found in non-main grain producing regions. We hold that the application of the digital economy in the countryside has played an obvious role in promoting food security in main grain producing provinces, and provides important experimental evidence for reference to ensure food security in the future.

The primary goal of this research is to examine how different types of energy are used in South Asian countries and how they affect the environment and economic growth. From 1990 through 2021, this research employed Panel Data from multiple sources covering the South Asian countries of Pakistan, India, Bangladesh, Sri Lanka, Nepal, Bhutan, Maldives, and Afghanistan. The results are determined by using the Fixed Effect Regression (FEM) technique in both models. Several significant findings are supported by the data. First, while using renewable energy flattens carbon dioxide effusion, using non-renewable energy sources increases it. CO2 emissions are affected negatively by gross domestic product but positively by gross domestic product square. These results provide credence to the idea that South Asian countries do experience an Environment Kuznets Curve. Furthermore, foreign direct investment has a beneficial effect on CO2 emissions, lending credence to the Pollution Haven Hypothesis. Model 2 instead finds that both renewable and non-renewable energy consumption contributes to economic expansion. Gross Fixed Capital Formation and foreign direct investment also contribute to economic growth in this area. Finally, Inflation retards economic expansion.

The Hospital Price Transparency Final Rule aims at reducing the cost of healthcare in the United States by making information about the prices of medical services more readily available to market participants. The economic rationale is that higher price transparency should reduce the level and the dispersion of prices by disincentivizing hospitals from charging higher prices than possible. Using data on 3789 prices for three diagnostic imaging procedures and on the compliance with the rule for 86 acute care hospitals in the Greater Los Angeles area, we test the hypothesis that price levels and price dispersion are lower among hospitals that are more compliant. We do not reject this hypothesis, although we do not observe strictly decreasing relationships in all analyses. Prices are lower at hospitals with high or medium compliance than at hospitals with low compliance, but there is not a clear difference between hospitals with high and hospitals with medium compliance. Prices are less dispersed among hospitals with high compliance than among hospitals with low compliance, but the evidence for hospitals with medium compliance is less clear. We conclude that high compliance with the Hospital Price Transparency Final Rule implies lower prices and less price dispersion among hospitals.

Based on provincial panel data in China, this study is the first to investigate whether industry-university-research collaborative innovation (IURCI) can help to improve factor misallocation. It is found that IURCI can significantly improve capital misallocation and labor misallocation, and the effect has regional differences, which shows that the improvement effect is obvious in areas with factor under-allocation, such as the central and western regions, but not obvious in areas with factor over-allocation, which conforms to the rule of diminishing marginal returns. A regulatory effect model is built to explore the impact of regional heterogeneity, through which we find that after considering three external environmental conditions, including economic development level, academic research level, and marketization degree, the improvement effect of IURCI on factor misallocation undergoes significant changes. The research results show that to deepen the marketization reform of factor allocation, we can start with IURCI. The government should form a sustainable and normalized industry-university-research collaborative innovation ecological mode through pilot cases and adopt measures according to local conditions to ensure the efficient use and reasonable distribution of capital and human resources of enterprises, universities, and scientific research institutions.

This paper evaluates the use of macro-level insurance to finance post-disaster recovery and reinstatement by investigating the case of the National Disaster Insurance policy implemented by Sri Lanka. The national scheme provided cover for all properties in the country against hazards such as flooding and provided compensation for those affected. Analysis of secondary data obtained from the organisations that managed the scheme showed that the scheme has delivered a much higher return compared to the total insurance premium paid, suggesting that the scheme has delivered a net positive benefit compared to the cost of the premium and can be considered a viable option. However, the existing secondary data did not reveal the values of other costs and indirect benefits associated with the scheme to compute a meaningful benefit-to-cost ratio. Further rigorous, evidence-based cost-benefit analysis is required to assess the cost-effectiveness of a scheme of this nature. A cost-benefit analysis approach based on an analytical hierarchy process is proposed as a possible solution to assess the cost-effectiveness of the scheme, which could be used by government organisations as an alternative, where analytical and research resources may be limited, to evaluate a range of disaster recovery financing options using stakeholder opinion.

In his "The World’s smallest macroeconomic model” (Krugman (1999)), Paul Krugman argued that under the assumption of price rigidity, a shortage of money supply leads to underemployment or recession, so increasing money supply can eliminate underemployment and restore full employment. But, how do we increase the money supply? I will show that we need a government deficit to increase the money supply in order to restore full employment from recession. Also, I will show that in a growing economy, if people hold money, a government deficit is necessary to maintain full employment under constant price or inflation. A government deficit is not only effective in pulling the economy out of recession, it is even necessary for continued growth without inviting either recession or inflation. The government deficit in this paper represents the difference between government expenditures and government revenues. When the difference is positive, we say that the government has a deficit. This paper seeks to explore theoretically and normatively the role of government deficits in achieving and maintaining full employment in a growing economy without causing inflation, using a very simple model by Krugman.

The Public Welfare Foundation of a listed company is a non-profit organization with independent legal personality. It is established and funded by a listed company. The purpose of establishing a foundation for a listed company is generally to carry out charitable activities and make important contributions to charitable causes. However, due to the special power separation model, the autonomy of the foundation is poor, and there may be serious agency conflicts, ultimately leading to listed companies becoming beneficiaries of the foundation's charitable activities. We have found from the perspectives of commercial credit, sales, and cooperative relationships that social responsibility initiating organizations (listed companies) can obtain potential benefits from social responsibility fulfilling organizations (listed company public welfare foundations) in supply chain commercial relationships, that is, listed companies that establish public welfare foundations have good supply chain commercial relationships. When a listed company and a public welfare foundation have a close relationship in terms of fund donation, decision-making, business, and naming, the public welfare foundation has a strategic preference in selecting project names, project service areas, project beneficiaries, and project service areas. It prioritizes the interests of the listed company, enabling the listed company to obtain better supply chain business relationships.

Generating output growth by adding more inputs into the production process may not be sustainable in the long run for any economy, given the limited resources. On the other hand, if productivity growth dominates the production process, it will generate more output without excessive increase in input use. Hence, this paper examines whether the output growth in Indonesia’s manufacturing sector is excessive inputs driven or productivity driven. Productivity driven growth is measured by Total Factor Productivity (TFP) growth, which is decomposed into its major components of technological progress and technical efficiency within the framework of varying coefficients stochastic frontier analysis (VSFA) using Indonesia’s annual Large and Medium Manufacturing Industries Survey data over the period 2002–2014. The measurement of the components of TFP growth not only provides more insights and better understanding of the dynamic nature of the production processes, but also has important policy implications. The mean TFP growth during the period 2002-2014 was estimated to be 4.3 per cent and was mostly contributed by technological progress experienced by firms. The policy implication is that technical efficiency could still be improved for the selected technology to reap the full benefit of increasing output from the chosen technology.

Credit scoring remains one of the most important subjects in financial risk management. Although the methods in this field have grown in sophistication, further improvements are necessary. These advances could translate in major gains for financial institutions and other companies that extend credit by diminishing the potential for losses in this process. This research seeks to compare statistical and artificial intelligence (AI) predictors in a credit risk analysis setting, namely the discriminant analysis, the logistic regression (LR), the artificial neural networks (ANNs), and the random forests. In order to perform this comparison, these methods are used to predict the default risk for a sample of companies that engage in trade credit. Pre-processing procedures are established, namely in the form of a proper sampling technique to assure the balance of the sample. Additionally, multicollinearity in the dataset is assessed via an analysis of the variance inflation factors (VIFs), and the presence of multivariate outliers is investigated with an algorithm based on robust Mahalanobis distances (MDs). After seeking the most beneficial architectures and/or settings for each predictor category, the final models are then compared in terms of several relevant key performance indicators (KPIs). The benchmarking analysis revealed that the artificial intelligence methods outperformed the statistical approaches.

In this study, we examined the efficiency of cryptocurrencies Bitcoin (BTC), Ethereum (ETH), Litecoin (LTC), Ripple (XRP), DASH, EOS, and MONERO from March 1, 2018, to March 1, 2023. We separated the sample into four subperiods for this purpose: a Tranquil period that includes the period from March 1, 2018, to December 31, 2019; a First Wave that includes the year 2020; a Second Wave that includes the year 2021; and a fourth subperiod that includes Russia's invasion of Ukraine in 2022-2023. The results are mixed, with some cryptocurrencies exhibiting equilibrium and others exhibiting autocorrelation and predictability in their pricing. When the sample is divided into subperiods, most digital currencies have long memories in their returns during the Tranquil period, BTC, LTC, and XRP exhibit efficiency during the First Wave of the pandemic, while BTC, ETH, and MONERO indicate efficiency during the Second Wave. Most assessed digital currencies showed equilibrium by 2022, with the exception of ETH and MONERO, which exhibit long memories, and LTC, which demonstrates anti-persistence. These results hold significance for investors in these alternative markets, as they suggest that some cryptocurrencies may be more predictable and therefore potentially profitable, whereas others may require greater caution and risk management strategies.

By an endogenous growth model with a two-period overlapping generations structure, I examine the existence of a budget deficit in an economy that endogenously grows by investments of firms. The consumers leave bequests to their descendants and hold money as a part of their savings. I use a Barro-type utility function, where people include the utility of their children in their own utility. The main results are as follows. 1) A budget deficit is necessary for full employment under constant prices. 2) Inflation is induced if the actual budget deficit is greater than the value at which full employment is achieved under constant prices. 3) If the actual budget deficit is smaller than the value which is necessary and sufficient for full employment under constant prices, a recession occurs. Therefore, a balanced budget cannot achieve full employment under constant prices. I do not assume that the budget deficit must later be made up by a budget surplus. I use a Barro-type utility function to prove the necessity (or inevitability) of a budget deficit instead of the neutrality of government debt. In the appendix of this paper, I show that if money, as well as goods, are produced by capital and labor, a budget deficit is not necessary for full employment under constant prices.