Using quarterly data for Turkey spanning 1995 Q1-2024 Q4, we estimate closed-and open-economy hybrid New-Keynesian Phillips Curves that allow for time-varying and asymmetric slopes. Controlling for three structural breaks-the **2001 banking crisis, the 2018 currency turmoil, and the 2020-21 pandemic-**a 1-percentage-point positive output-gap shock raises CPI inflation by 0.10-0.14 pp in the short run, while the long-run pass-through from expected to current inflation ranges from-0.02 pp to-0.12 pp. Error-correction coefficients of-0.26 to-0.50 imply that disequilibria vanish within two to four quarters. Robustness checks using state-space time-varying-parameter estimators confirm the post-2021 steepening of the curve. Recent evidence that global forces have flattened-but not eliminated-the Phillips relationship (Kabundi, Poon & Wu 2023) and that Turkey's post-pandemic inflation is increasingly demand-driven (Akarsu & Aktu & gbreve; 2025) supports our results, whereas earlier closed-economy estimates understate the slope by ignoring import-price spill-overs. Our open-economy specification therefore produces a steeper, yet still forward-looking, curve and explains 82 % of in-sample inflation variance. Policy implications. (i) Credible expectation-anchoring could halve the persistence of inflation shocks. (ii) Output-gap management must be pre-emptive, because positive gaps accelerate prices more than negative gaps decelerate them. Consistent communication, demand-smoothing tools, and measures that curb import-price pass-through together give the Central Bank of T & uuml;rkiye the greatest leverage in reaching its 2025-26 inflation target.
Environmental pressures in the Asia-Pacific region have intensified alongside rapid economic growth, structural transformation, and rising energy demand. This study investigates how renewable energy, capital formation, and economic development shape the ecological footprint (EF) across 38 Asia-Pacific economies from 2000 to 2022. Using a dynamic STIRPAT-based empirical framework, we examine both aggregate EF and its six subcomponents. The results show that both renewable energy consumption and production reduce EF, highlighting the environmental benefits of expanding clean-energy capacity. Economic development exhibits a U-shaped relationship with EF: early growth stages improve efficiency and reduce ecological pressures, whereas higher income levels eventually increase EF. Capital formation raises EF, indicating continued investment in resource- and energy-intensive activities, while population is associated with lower EF, likely reflecting demographic transition and efficiency gains. Subcomponent analyses reveal heterogeneous drivers, with the carbon footprint most closely mirroring overall EF dynamics. These findings underscore the need to accelerate clean-energy transitions, redirect investment toward green sectors, and strengthen environmental governance to maintain ecological sustainability as economies develop.
Banks play a vital role in the global economy but face a challenge of complying with regulations regarding board gender diversity and environmental, social, and governance (ESG) practices while maintaining cost efficiency. Applying a two-stage modified Data Envelopment Analysis (DEA) cost efficiency model with Simar-Wilson bootstrap-based truncated regression procedure and the instrumental variable (IV) Tobit robustness checks, this study analyzes the associations among board gender diversity, ESG performance scores, and bank efficiency across 94 Asian banks from 2010 to 2020. The empirical results show that female directors are positively associated with bank efficiency while exhibiting an inverted U-shaped diminishing marginal return. Environmental performance is positively associated with efficiency, whereas social performance is negatively related, and governance performance exhibits an insignificant relationship. Furthermore, the interaction between gender diversity and each ESG performance pillar exhibits a positive relationship with bank efficiency. The findings suggest an optimal threashold of 10%-13% for female board representation. Banks may consider gender diversity as a strategy to implementing ESG initiatives, and ultimately correspond with a positive association with higher cost efficiency.
Today, algorithmic trading (AT) plays a crucial role in financial forecasting. This study explores AT strategies for an emerging market, Borsa & Idot;stanbul (BIST). Analyzing Environmental, Social, and Governance (ESG)-focused stocks from the BIST Sustainability Index, a robotic trading algorithm implemented in C# optimizes trading parameters for return. Key technical indicators; Relative Strength Index (RSI) and Simple Moving Average (SMA) evaluate trends and improve decisions. Results show longer timeframes achieve higher profitability, while shorter intervals face volatility. The study underlines the potential of tailored AT strategies in emerging markets, offering insights for small investors to manage risk and return. Findings emphasize the role of local market dynamics in building robust, algorithm-driven trading solutions.
Drawing on the entropy law, this paper proposes a moving-target model to investigate the long-run convergence of countries' per capita income toward the average income of their reference group. Using evidence from the global economy and the European Union, we show that income convergence follows dynamics consistent with entropy-based physical systems. However, while convergence is observed across countries, regional and sub-regional disparities within countries often widen, indicating that convergence at the macro level may coexist with divergence at lower territorial levels.
