This paper investigates the effects of an unprecedented education policy called ‘double reduction’ (DR) on students’ performance, with evidence from China. One of the significant changes brought about by this policy is the transition of examination scores from a numerical system to a grading system. We found a junior middle school in a small town in Guangzhou that met the requirements for a natural experiment, and we used such unique data to examine three hypotheses. After the implementation of DR, the ‘rat race’ reflected on the students’ grade is reduced. To examine heterogeneity, we apply quantile regression showing that the high-ability students exert less efforts on the ‘rat race’ than low-ability students. Meanwhile, we also provide possible explanations in terms of this phenomenon. Overall, this study not only does it assess the grading transformation that DR policy induced but also fills the gap in the field of DR from an economic perspective.

Exiting literature and central banks have recently raised concerns about the ominous overlooked threat of growing global debt, and its fundamental role in financial crises and economic instability. This paper develops and models an alternative economic theory that calls for a paradigm shift from the prevailing debt-based financial economy. Through a structured literature review and conceptual analysis, the paper explores the relationship between the traditional interest-based financial economy and economic injustice and instability. The paper then through an econometric analysis of data collected from 189 countries tests its conceptualised theory advocating a gradual transition from the deb-based financial economy. The results provide three important contributions. Firstly, the results contribute to the field of economics and finance by providing a conceptual and theoretical framework for examining the interaction between the financial economy and economic equity. The paper introduces a conceptualisation of what it coins as the Equitable Optimality Economic Theory, which replaces interest rate with profit rate. Secondly, the paper extends the debate in the literature about debt theories and its impact on the financial economy by arguing that a shift towards debt-balanced and eventually debt-free financial economy provides a more equitable and stable economic system. Thirdly, the econometric modelling demonstrates that such a change would lead to improved economic growth, reduced debt levels, enhanced financial stability, and the inherent nature of profit rates provides a natural buffer against economic downturns. The study concludes by proposing a practical roadmap for this economic transition in gradual and steady approach.

Forecasting stock prices remains a fundamental yet complex challenge in financial economics due to the nonlinearity, volatility, and exogenous shocks characterizing market behavior. This paper proposes a hybrid deep learning framework that integrates Long Short-Term Memory (LSTM) networks for time-series modeling with Transformer-based architectures for textual sentiment extraction from financial news. The goal is to enhance predictive accuracy by combining structured historical data with unstructured semantic signals. Using three years of daily data from Apple Inc. (AAPL), the model captures endogenous price dynamics via LSTM and incorporates contemporaneous market sentiment through FinBERT, a Transformer model pretrained on financial text. Empirical results show that the hybrid model outperforms price-only baselines across multiple evaluation metrics, including mean squared error (MSE) and directional accuracy. The incorporation of sentiment features proves particularly valuable around earnings announcements and event-driven volatility regimes. This study contributes to the literature on machine learning in finance by demonstrating the complementary strengths of multimodal learning, offering a more interpretable and robust framework for stock price prediction. The findings also open avenues for future research in real-time forecasting, reinforcement learning integration, and the application of hybrid models across diverse asset classes.

Fintech has revolutionized financial service models, but can it effectively address enterprise financing challenges and provide critical support for technological innovation—a cornerstone of new quality productive forces? Leveraging data from A-share listed companies (2011–2023), this study constructs a regional fintech development index based on the distribution of fintech firms across China and evaluates its impact on enterprise-level productive forces. The findings demonstrate that fintech significantly fosters new productive forces, a conclusion robust to instrumental variables, Heckman two-stage analysis, and alternative variable tests. Mechanism analysis reveals three key channels: mitigating information asymmetry, alleviating collateral constraints, and enhancing market competition. Heterogeneity analysis further indicates that fintech’s impact is more pronounced among private enterprises, high-tech industries, and firms in eastern regions. As China prioritizes the development of new productive forces, sustained fintech advancement, deeper "data empowerment," and targeted policy measures are essential to ensure finance effectively serves the real economy and underpins high-quality economic growth.

This study investigates whether Turkey's per capita primary energy consumption converges to that of high-income countries using linear unit root tests over the period 1965-2023. The analysis applies a variety of methods, including the Lee and Strazicich (2003) test, Narayan and Popp (2010) test, Lumsdaine and Papell (1997) test, and the conventional ADF test. According to the results of the Lee and Strazicich test, the energy convergence series is stationary at the 1% significance level in Model AA and at the 10% significance level in Model CC. These findings suggest that Turkey may exhibit signs of energy consumption convergence with high-income countries. However, the results of other methods, including Narayan and Popp (2010), Lumsdaine and Papell (1997), and the ADF test, reveal that the series has a unit root, indicating non-stationarity. This inconsistency highlights a lack of definitive evidence supporting energy consumption convergence. The divergence in findings among different methodologies underscores the need for more robust and comprehensive analyses to thoroughly evaluate the energy convergence hypothesis. Addressing this issue could contribute to a better understanding of Turkey's energy consumption dynamics relative to high-income countries.

The paper studies Philippine poultry data and revisits the chicken or the egg causality problem to include ducks data. Using quarterly Philippine poultry production time-series from the first quarter of 1980 to the last quarter of 2014, this research finds that chickens came from eggs, which is consistent with the earlier statistical results of Thurman and Fisher (1988), and genetics-based conclusions of Eriksson et al. (2008). However, no conclusive evidence was found using the Philippine duck and duck eggs data. The chicken or the egg conundrum demonstrates the power of Granger causality testing in answering questions of temporal ordering that has various causal applications using macroeconomic, financial, and agricultural time-series data.