This paper provides a thorough review of the shifting landscape of economic analysis, spotlighting recent trends and predicting future paths. While traditional economic models remain key for interpreting economic activity, they are being supplemented by fresh methods and cross-disciplinary viewpoints. The increased attention to inequality studies, using advanced statistical techniques and unique data sources, underscores the growing emphasis on fairness and distribution within economic analysis. The incorporation of behavioral elements into economic models also expands our comprehension of economic decision-making and market results. Notably, the emergence of computational economics-integrating artificial intelligence (AI), big data, and machine learning into economic scrutiny-represents a major development. Often referred to as ’smart economics,’ this field employs technology to formulate, address complex economic dilemmas, and perceive economic activity in unconventional ways. Yet, the application of AI and machine learning in economics introduces new hurdles around data privacy, algorithmic bias, and the transparency of model outcomes. The impact of the digital revolution on economic analysis is significant, as the advent of computational economics and the surge of big data are transforming research techniques and policy implications. Concurrently, the advent of the circular economy indicates a radical shift in our perspective on economic sustainability, carrying considerable implications for environmental policy and business tactics.  In the future, it’s anticipated that these trends will further modify the realm of economic analysis, with AI and machine learning integration, emphasis on sustainability and fairness, and the influence of big data becoming more pronounced. As these changes take place, it’s imperative for researchers, policymakers, and practitioners to remain adaptable and flexible, prepared to capitalize on the opportunities and tackle the challenges these trends present.

There must be a better match between the supply of financial news graduates in colleges and the media's demand for financial news talents. Based on 300 questionnaires and in-depth interviews from three universities, namely Shanghai University of Finance and Economics, Nanjing University of Finance and Economics, and Jiangxi University of Finance and Economics, this paper uses the interview method to excavate the professional quality improvement path for majoring in financial news students. Results reveal that undergraduates majoring in financial news have problems such as low professional identity, insufficient recognition of the discipline system, poor sense of professional identity, common matching between job selection and majors, and worrying about the status quo of professional literacy. Therefore, the improvement of the professional quality of students majoring in financial news and the reform of the training program needs to drive the professional quality of students in multiple dimensions, change their professional cognitive problems, strengthen their professional identity, and achieve an effective match between supply and demand of financial media professionals.

Liquidity and its associated issues are one of dominant strands in the market microstructure. In this study, microblogging-based behavioral perspective on economic unrest is linked to the market liquidity. The concept of liquidity is examined in terms of price dispersion relative to the quantity traded. The analysis contains the quantification of multiple linear regression, Gaussian distribution technique, and vector error correction methodology. In the economic stability period, the investor’s mood, either in positive manner or pessimistic context, had an influential role on the price impact volume-based liquidity. Meantime, the probability was higher for occurrence of price impact volume-based liquidity in response to the sentiment indicators. In the economic unrest environments, the positive bias investor’s mood was not vigorous enough to influence the dispersion of asset’s prices and trading quantity. Most importantly, the negative bias investor’s emotion was linked to increase the dispersion of asset’s prices relative to the quantity traded. Investors with a lower amount of trading quantity had declined the liquidity in the market. Additionally, there was a higher probability for occurrence of illiquidity in the pessimistic market periods. However, changes in past sentiment series were not associated with changes in pervious liquidity series, either in short run or long run. The findings may be potentially applicable to manage the behavioral perspective of liquidity risk.

The study investigates the impact of COVID-19 on African exchange rates, employing a panel dataset over the period 2016-2022 from 13 African economies and employing pooled OLS estimator. The findings reveal a noteworthy positive correlation between COVID-19 levels and exchange rates within the region. However, this association necessitates deeper exploration due to its multifaceted implications, including economic disruptions, government interventions, global market interconnections, regional stability perceptions, and investor behavior. Economic indicators, such as GDP, inflation rate, real interest rate, and unemployment rate, significantly influence exchange rates. While GDP positively impacts exchange rates through economic growth, investor confidence, and trade strength, controlled inflation fosters investor confidence and export competitiveness, positively affecting exchange rates. Moreover, a pronounced positive impact of the real interest rate indicates economic stability, attracting investment and contributing to currency appreciation. Conversely, high unemployment negatively affects exchange rates, signaling economic weaknesses and eroding investor confidence. These findings emphasize nuanced policy responses for managing health crisis-induced economic disruptions and suggest future research directions focusing on specific country-level analyses and multifaceted factors influencing currency valuations within African economies.

We employ the joint production decomposition model to conduct a full decomposition of CO2 emission among 36 industrial sectors in China from 1998 to 2011, under the framework of growth accounting. The results show that: (1) the average CO2 emission increases at an annual rate of 3.01%, and production technology progression is the main driving force, while the transformation toward clean production effectively curb the rapid growth of CO2 emissions; (2) the effect of technology changes on CO2 emission is larger during the "10th Five-Year Plan" compared with the "11th Five-Year Plan", which makes the annual growth rate of CO2 emission during the "11th Five-Year Plan" 1% lower than its counterpart; This study has important theoretical and practical significance for understanding the driving factors of CO2 emission and the corresponding emission reduction measures.

I examine the problem of budget deficit in a growing economy in which consumers hold money as a part of their savings in the case where consumers live forever. For simplicity and tractability I use a discrete time dynamic model and Lagrange multiplier method. In the appendix I briefly explain the solution using a discrete time version of the Hamiltonian method. I will show the following results. 1) 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, balanced budget cannot achieve full employment under constant prices. I do not assume that budget deficit must later be made up by budget surplus.

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.

Based on the empirical data of 6110 listed export companies in China from 2010 to 2019, this paper studies the impact of China's economic policy uncertainty (EPU) index on the profitability of listed companies from the specific perspective of export companies, and analyzes the moderating effects of different factors on this impact. The results show that China's EPU index has a significant negative impact on the profitability of listed export companies, and the increase in R&D investment and wage returns will aggravate this negative impact. In addition, listed export enterprises with different enterprise characteristics have different responses to EPU. State-owned enterprises and enterprises located in coastal areas are relatively less negatively affected by EPU.

By introducing time to build, which creates a time-lag between government investment and the accumulation of productive capital, into an analysis of fiscal stimulus to the economy with financial frictions, we find that the effectiveness of fiscal policy is dampened. While the weakening effects of time to build become significantly weaker alongside with a higher fraction of government bonds allocated to leverage-constrained banks, which can be explained by a high correlation between time to build and financial frictions in both worsening balance sheet conditions of banks. Furthermore, the stimulus effects of public investment become stronger associated with shorter time-to-build period.

The relation between fund flows and returns in the Australian ETF industry is assessed in this study. Daily data from 43 equity ETFs over the period 2019-2023 are used. The main research objective is to accentuate whether past returns can predict future fund flows and in what way and vice versa. According to the results of the applied regression analysis, past flows and past returns can predict to some extent concurrent flows. This is also the case about concurrent returns. However, in both cases, the results are not unanimous and depend on the specification of the applied regression model.

Banks operating within a free economic environment and with constructive regulatory frameworks can function with enhanced efficiency, augmenting their profitability. This study aimed to examine the influence of economic freedom and financial restrictions on banks' profitability within the Organization of Islamic Cooperation member nations. The study used a sample of 1453 banks, collecting panel data spanning 13 years. The System-GMM methodology was justified based on the enduring characteristics of the data and the profitability metrics. The dependent variables, namely the Net Income Margin, Return on Average Assets, and Return on Average Equity were individually examined. The research findings indicate that most economic freedom indicators, except for investment freedom, harm bank profitability. The influence of the rule of law on profitability indicators is mostly adverse, although regulatory quality within the financial system has a comparatively favorable effect on profitability. Furthermore, bank-specific performance indicators had a negative impact on profitability, except for bank size. Moreover, country-specific variables substantially impact banks' profitability, including inflation, tax, and interest rates. The presence of Islamic banking has been shown to substantially impact the profitability performance of banks within the Organization of Islamic Cooperation. OIC banks' profitability is adversely impacted by the ongoing health crises, including the Covid-19 pandemic.

This paper examines the efficiency, in its weak form, of the clean energy stock indices, Clean Coal Technologies, Clean Energy Fuels, and Wilderhill, as well as the cryptocurrencies classified as "dirty", due to their excessive energy consumption, such as Bitcoin (BTC), Ethereum (ETH), Ethereum Classic (ETH Classic), and Litecoin (LTC), from January 2020 to May 30, 2023. In order to meet the research objectives, the aim is to answer the following research question, namely whether: i) the events of 2020 and 2022 accentuated the persistence in the clean energy and dirty energy indices? The results show that clean energy indices such as digital currencies classified as "dirty" show autocorrelation in their returns; the prices are not independent and identically distributed (i.i.d). In conclusion, arbitrage strategies can be used to obtain abnormal returns, but caution is needed as prices can rise above their real market value and reduce trading profitability. This study contributes to the knowledge base on sustainable finance by teaching investors how to use forecasting strategies on the future values of their investments.

Since 2011, the conflict in Syria left the country with a devastating energy sector and fragile economy. The residents struggle daily to live with only two hours a day of electricity. The crisis encouraged some Syrians to assemble photovoltaic (PV) panels to generate energy. Unfortunately, the geopolitical risks, the inflation, and displacement are making the situation worse. The geopolitical risks are complex and multifaceted due to the ongoing war and the involvement of various regional and international actors. In this letter, we focus on the situation in war-torn Syria, its economy, and the opportunities for renewable energy development in the country. We also give some recommendations for academics and policy makers.

The sensitive nature of interest rate has spurred empirical interests on the factors that determine it. This paper examined the joint impact of exchange rate and foreign direct investment inflows on interest rate in Nigeria over the period from 1981-2022. The study made use of the auto regressive distributed lag (ARDL) bounds test and results of findings reveal that in both the short-run and the long-run the impact of the interaction between FDI inflows and exchange rate on real interest rate was negative and significant. Also, while credit to the private sector was found to have significant positive impact on real interest rate in both the time horizons, the impact of consumer price index was negative only in the short. Oil revenue was found to impact positively on real interest rate only in the long-run, but the impact of broad money supply was negative and significant in both the short-run and the long-run. The study suggests that policies to regulate domestic interest rate should focus on joint regulation of both exchange rate and FDI inflows and this requires a synergy between monetary and fiscal policies.

This paper investigates the effect of economic policy uncertainty (EPU) on the systemic risk of the fintech industry. To achieve this goal, we first estimate the evolution of system-wide systemic risk using the CatFin method. We further examine whether EPU significantly affects systemic risk. Our findings demonstrate that the systemic risk of the fintech industry is time-variant and sensitive to major crisis events. Systemic risk tends to increase after major crises, especially the outbreak of the COVID-19 pandemic. EPU has a considerable impact on systemic risk, notably during periods of turmoil.