This paper provides an overview of the existing literature on the use of artificial intelligence (AI) in various fields, including economics, finance, mining, manufacturing, and innovation. The paper identifies the drivers and effects of AI deployment in the context of innovation and highlights the challenges and opportunities that arise from the use of AI. The studies reviewed in this paper cover various topics related to forecasting, including the impact of AI on professional skills, hybrid forecasting techniques for predicting commodity prices, and novel deep reinforcement learning algorithms for crude oil price forecasting. The paper’s contribution lies in its systematic and comprehensive approach to reviewing the literature, which allows for a better understanding of the impact of AI on various fields and the identification of strategies to address the challenges that arise from its deployment.

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.

I will show that if the propensity to consume from savings satisfies appropriate conditions, the debt-GDP ratio will not grow infinitely large and fiscal collapse will not occur. Using a basic macroeconomic model, with an overlapping generations model in mind, we show the following results: 1) The budget deficit including interest payments on the government bonds equals an increase in the savings from a period to the next period. 2) If the savings in the first period is positive, we need budget deficit to maintain full employment under constant prices or inflation in the later periods. 3) Under an appropriate assumption about the propensity to consume from savings, the debt-GDP ratio converges to a finite value. It does not diverge to infinity. The larger the propensity to consume from savings, the smaller the budget deficit required to achieve full employment. The larger the propensity to consume from savings, the less likely it is that the debt-GDP ratio will become large.

In his 1922 review for Cambridge Magazine of Keynes's A Treatise on Probability, and again in his 1926 review "Truth and Probability" (published in 1931 and republished in Kyburg and Smokler's 1980 edition), Ramsey provided examples critiquing Keynes's logical theory of probability. However, these examples do not disprove Keynes's theory as all of them are flawed. The flaws arise because all the pairs of propositions that Ramsey used to substantiate his criticisms are irrelevant to each other. Such irrelevant propositions are explicitly excluded from Keynes's theory in pages 4-6 of his A Treatise on Probability. This paper highlights that Ramsey's examples, which involve irrelevant propositions, do not disprove Keynes's Boolean, relational logic. The only other defense of Keynes's theory, put forth by Watt in 1989, was found to be deficient by Brady in 2022.

In the behavioral domain, this study discloses the pattern between microblogging-opinionated information and yields on the investment. This phenomenon is particularly related to the political instability in the Pakistan’s economy through the multivariate techniques. Pre-political crisis, the pessimistic sentiments were priced in yields on the investment. In environments of political instability, the intensity of decline in yields was more responsive against an incline in the negative opinions. Meanwhile, the intensity of increase in returns was less responsive against an incline in the positive opinions. The findings were further supported by the Bayesian approach. Before the political instability takes place in the Pakistan’s economy, the occurrence of yields was noted in response to the bearish market period. Post-political instability, there was a higher posterior probability for occurrence of returns against the bearish market period. Conversely, a higher posterior likelihood was noted for occurrence of investment’s yields in response to the bullish market period, but this relevance was not completely probable. From the impulse response analysis, the response of returns was reported against the standard deviation shocks in the microblogging sentiment indicators. The analysis may have potential implications in terms of disclosing the investors’ behavior from a political perspective.

Previous literature shows that the price-discovery ability of options market varies substantially over time. Using data of Shanghai Stock Exchange 50 exchange-traded fund options, this paper shows that options prices contribute relatively less to price discovery during low-sentiment periods, but the price-discovery ability of options market remains unchanged during high-sentiment periods. These results suggest that change in aggregate investor sentiment is an important source of the time variation in options’ price discovery ability. Moreover, the options market experiences greater bid-ask spreads when investor sentiment is lower, supporting a “transaction costs mechanism.” This paper fulfills related literature on the time variation in options’ price-discovery ability.

This paper investigates the impacts of COVID-19 on women’s employment and gender disparity with a longitudinal dataset spanning the pandemic. We exploit the regional intensities of social vulnerability and temporal variation to implement the difference-in-differences (DID) estimation. The results indicate that the pandemic and its associated lockdowns generate a significant and negative impact on women’s employment but not on men’s employment. Moreover, a counterfactual analysis using pre-pandemic data further supports the causal nature of the documented relationships. The evidence suggests that economic downturns caused by public health emergencies, unlike previous economic recessions, have a greater impact on women, and differentiated policies should be designed.

The Oswald hypothesis is that home ownership reduces mobility and through that channel results in poorer labor market outcomes. There has been only limited previous evidence on the Australian case. Here we use data from the first four Australian censuses of the twenty-first century, aggregated at the smallest geographical areas for which statistics are released. We propose testing the Oswald hypothesis by estimating the effect of home ownership on the full-time employment rate. Modelling the unemployment rate, as is often done in testing the hypothesis, produces implausible results with respect to the control variables, most likely due to the limitations of the official definition of unemployment. We find that, in modelling the full-time employment rate, the control variables for educational and demographic factors have the theoretically plausible effects, while variables capturing rates for both outright home ownership and with mortgage home ownership are positively related to full-time employment rates, with the effect of the former stronger than the latter. Our findings strongly contradict the Oswald hypothesis.

This paper estimates panel vector autoregressions to analyze the endogenous connection between COVID-19 and non-communicable diseases (NCDs). Using weekly, US state-level data, the study finds evidence of a significant positive effect of NCD-related mortality on deaths due to COVID-19. I find this effect to be higher for males than females. Results are robust to several sensitivity checks, so large deviations are unexpected.

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.

In this paper, a portfolio analysis is carried out using the Sharpe ratio to identify the optimal market portfolio. The measure of investment performance with a Sharpe ratio is compared to results obtained with bootstrapped resamples of the Sharpe ratio. The results indicate that the choice of the market portfolio is highly affected by the uncertainty regarding the estimation of the expected returns and the variance-covariance matrix between the returns, that is, the estimation risk associated with these parameters.

In this paper, we develop a model in which a monopolistic firm manufactures and sells a digital product, by incorporating digital rights management (DRM), quality degradation of pirated products, and government copyright enforcement into the consumer’s utility function. We determine the monopolist’s optimal pricing strategies and the appropriate DRM protection level through mathematical deduction. Our results show that when the government copyright enforcement is moderate and the quality of pirated products is relatively high, implementing a DRM system is optimal for the monopolist. However, in most other cases, DRM-free is better for the monopolist. This result may explain why DRM is not very popular in some industries. Our results suggest that choosing the right price, focusing on content innovation, and weakening DRM protection may be a better strategy for firms now. The results also indicate that DRM-free may be more prominent in the digital music industry than in the software and video games industries.

This paper intends to analyze efficiency, in its weak form, in the stock markets of Austria (ATX), Poland (WIG), the Czech Republic (PX Prague), Hungary (BUX), Croatia (CROBEX), Serbia (BELEX 15), Romania (BET), and Slovenia (SBI TOP), from February 16, 2018, to February 15, 2023. To achieve the research aim, we intend to answer the following research question: i) Have events in 2020 and 2022 heightened the persistence of Central European stock markets? Results suggest that persistence in returns has increased significantly during the first wave of Covid-19 and the Russian invasion in the year 2023, but we also saw that most stock markets already exhibit long memories, implying that the research question has been partially validated. This research can provide valuable insights to investors, policymakers, and others interested in financial risk management.

Liquidity can be a real phenomenon for execution of the financial holding. Its risk falls in debate to impose a conditional cost on the counterparty. The time-varying liquidity is often linked to the expected fundamental value of an investment. In this work, the microblogging-based informed transaction is examined as a determinant of the liquidity-facilitating cost. Most importantly, this study investigates the economic blockade era and post-pandemic uncertainty. The sentiment indicators were found to be determinants of liquidity. These findings were consistent in the post-pandemic period. However, the investor pessimistic sentiment was a priced risk factor in liquidity during the economic blockade period. Based on the Bayesian theorem, a relativeness was reported between sentiment indicators and the liquidity-facilitating cost. The same findings were depicted in environments of the pandemic era. Nevertheless, the posterior probability indicated an occurrence of the liquidity-associated cost in response to the pessimistic sentiments during the economic blockade period. This quantification may have potential implications in terms of exploring liquidity from the microblogging perceptive.

This study simultaneously tests Wagner’s law on one hand and Keynes proposition on the other hand related both government spending and output in Ivory Coast that experiencing long run economic growth and widened deficit. That challenges the country’s fiscal sustainability. With annual data from 1980 to 2020, results show that Wagner’s law holds, the elasticity of government spending to output is greater than one. There is bidirectional causality between government size and output validating Keynesian idea that public expenditure is an exogenous factor and a policy instrument for increasing national income. Wagner law and public deficit can justify Ivorian over-indebtedness.

With the daily data from Nov 20, 2019 to Oct 31, 2022, this paper examines the dynamic nonlinear effects of RCEP on Dual Circulation and Greater Bay Area stock market from a quantile perspective. The rolling window quantile regressions detect the positive effects of RCEP on Dual Circulation and Greater Bay Area stock markets with significant time-varying characteristics. Meanwhile, QQ results show that the impacts from RCEP index are more significant under extreme conditions. In addition, we further use a nonparametric QC test to provide evidence on the predictive power of RCEP for Dual Circulation and Greater Bay Area with stock market.

The implementation of environmental protection strategy necessarily requires mapping the amount of capital stock of environmental infrastructure. Through the Weibull distribution function and hyperbolic age-decreasing efficiency model, the provincial environmental infrastructure capital stock in China from 1980 to 2018 is measured cautiously, and its spatial dynamics with the generated pollutants is analyzed using the center of gravity method. It is found that: the spatial distribution of environmental infrastructure capital stock is uneven, and the unevenness in the east-west direction is greater than that in the north-south direction, but the unevenness in the east-west direction is narrowing while the north-south direction is widening; the spatial and temporal distribution of environmental infrastructure capital and environmental pollution vary greatly, and the spatial management of environmental pollution is less accurate.

Based on provincial panel data from 1998-2018, this paper estimates research and development (R&D) factors, and a stochastic frontier analysis (SFA) model is constructed to examine the effects of R&D factors on regional total factor productivity (TFP). The results show that both R&D capital stock and R&D personnel can significantly promote regional TFP, but the productivity-enhancing effect of R&D factors is different between regions. Specifically, R&D capital and R&D personnel can promote TFP in eastern and central provinces, and the promotion effect is not significant in western provinces. In addition, compared with investment-driven regions, innovation-driven regions are more likely to enhance TFP by R&D factors.

The vigorous development of the digital economy has brought new opportunities and challenges to the construction of local fiscal revenue efficiency. Based on the panel data from 2011 to 2020, this paper uses the fixed effect model, instrumental variable method and other empirical studies to investigate the impact of the development of the digital economy on the efficiency of local fiscal revenue. The research results show that the development of the digital economy has directly improved the efficiency of local fiscal revenue, and the regression results of instrumental variables are still significant. The mechanism analysis shows that the development of digital economy mainly promotes local fiscal revenue such as efficiency improvement by cultivating tax sources.

Bank deposit is closely related to systemic risks. In addition, considering that resident deposits in China have significant seasonal characteristics, this paper focuses on which component of deposits drives the systemic risk volatility, that is, it can supplement the existing forecast information. We use X-13ARIMA-SEATS to decompose deposit into three subsequences. The research findings show that the forecast effect of subsequence models is better than that of benchmark series. Most importantly, the model with trend component has the best forecast performance.