In the last two decades, major emerging economy blocs, such as BRICS, have gained importance as alternative poles of global growth and economic coordination. However, an economically comparable and globally integrated country, Turkey, remains institutionally positioned outside formal bloc membership. Despite the inexistence of formal entry rules, the members share some similarities. Therefore, this study examines whether Turkey’s income dynamics align with those of BRICS economies and, importantly, what form such convergence takes. By using the purchasing power parity adjusted GDP per capita data from 2005 to 2024 for Turkey, from core and newly admitted BRICS member states, this paper investigates both β- and σ-convergence and examines the relative income gap. This allows distinguishing between convergence in growth paths and convergence in income level and helps interpretation of convergence beyond standard catching-up, which is clearly not the case in the Turkish economy. Both β- and σ-convergence tests results show clear evidence of alignment in growth dynamics between Turkey and BRICS member states. On the other hand, relative income gap tests show no evidence of “catching down”: Turkey’s per capita income remains persistently above the BRICS average throughout the sample period. This finding differs from conventional convergence interpretations and points to a case of convergence from above, where growth trajectories converge despite persistent income gaps. By separating growth convergence from income-level convergence, the study demonstrates that Turkey’s alignment with BRICS reflects economic compatibility rather than income convergence. More broadly, the findings suggest that Turkey’s exclusion from BRICS cannot be explained on economic grounds alone, highlighting the role of institutional design and political-economy considerations in bloc formation.
Bu çalışma, Avrupa’da gelir yakınsamasını incelemek amacıyla uzamsal ekonometrik yöntemlere yenilikçi yaklaşımlar önermektedir. Çalışmanın temel hedefi, komşuluk ilişkilerine dayanarak oluşturulan uzamsal ağırlık matrisini her komşunun etkisinin aynı olmaması durumuna göre şekillendirerek tahminlerde daha uygun sonuçlara ulaşabilmektir. Çalışmada önerilen uzamsal ağırlık matrisleri kullanılarak “yakınsama hipotezi” çerçevesinde Avrupa ülkeleri için 2000-2021 dönemi itibariyle uygulama yapılmıştır. Uygulamada “vezir”, “eşik”, “iki eşikli” ve “komşu yönünden asimetrik” ağırlık matrisleriyle kurulan “sabit etkili” ve “tesadüfi etkili” panel veri modelleri ile “uzamsal gecikme modeli”, “uzamsal hata modeli”, “uzamsal Durbin model” ve “genel uzamsal model” kullanılmıştır. Modellerin çoğunda “komşu” ağırlık matrisi ile oluşturulan modellerin en iyi performansa sahip olduğu görülmektedir. Bu matris ile yapılan çözümlemeye göre, Avrupa’da gelir ıraksaması mevcuttur. Gelir ıraksamasının bulunması, Avrupa’da gelişmekte olan ülkelerin gelişmiş ülkeleri yakalamasından ziyade, aralarındaki ekonomik gelişmişlik farkının giderek açıldığını göstermektedir. Başlangıç anında düşük gelire sahip olan ülkeler, zamanla başlangıç anında yüksek gelire sahip olan ülkelere yakınsamamış, aksine onlardan daha düşük bir büyüme gerçekleştirmişlerdir. Bu durum, Avrupa’da var olan eşitsizlik durumunun devam ettiği veya daha kötü bir duruma geldiğini göstermektedir. Politika yapıcılar için yerel ekonomik koşulların ve sosyal yapıların dikkate alınması, gelir eşitsizliklerini azaltmaya yönelik stratejilerin geliştirilmesinde kritik bir unsur olarak öne çıkmaktadır. Bu çalışmada herhangi bir birimin kendi değerinden daha yüksek ya da daha düşük değerli komşu gözlem değerlerinin uzamsal etkisinin diğer komşu birimlerden daha faklı olabileceği gösterilmiştir. Bu sebeple, daha yüksek log-olabilirlik değerleri elde ederek daha iyi tahminlerde bulunmak adına, bu çalışmada önerilen komşu yönünden asimetrik uzamsal ağırlık matrisinin yapılacak olan uzamsal ekonometrik çalışmalarda kullanılması faydalı olacaktır.
This study analyzes the LCF convergence of the world's ten largest polluters-Brazil, the United States, Germany, South Korea, India, China, Indonesia, Japan, Mexico, and France-using data for the period 1961-2024. The research goes beyond the static framework and the heterogeneous findings of the linear, structural-break, and nonlinear unit root tests. As an analytical contribution, it applies the Nahar-Inder (2002) methodology to the LCF literature for the first time. This approach models convergence towards the leading country (Brazil) as a dynamic polynomial function of time, thereby relaxing the restrictive assumption of stationarity. With the contribution of Bentzen and Tung (2021), changes in the speed of convergence (acceleration or deceleration) are also captured through second-derivative analysis. The findings stand in sharp contrast to those obtained from unit root tests: the Nahar-Inder methodology identifies strong convergence for seven countries (the United States, India, Japan, Indonesia, Germany, France, and South Korea), while China and Mexico exhibit divergence. This result indicates that economies appearing to be divergent under traditional tests (e.g., the U.S., Germany, France) are, in fact, dynamically converging. The results emphasise the necessity of differentiated policy trajectories for converging and diverging countries.
The degree of efficiency in financial markets plays a crucial role in shaping investment strategies and analysing market behaviour. This study evaluates the weak-form efficiency of 27 sector indices traded on Borsa Istanbul by applying Bahmani-Oskooee, Chang ve Ranjbar (2017) Fourier Quantile Unit Root Test. While the Fourier approach accounts for unknown structural breaks in the time series, the quantile-based analysis allows for the examination of stationarity patterns across different segments of the distribution. Using monthly data spanning the period from January2000 to March 2025, the empirical results reveal thatthe unit root hypothesis is rejected in only nine indices, suggesting that in certain market conditions, past price movements may have predictive power for future prices. For the remaining 18 indices, the unit root could not be rejected, implying that the weak-form efficiency holds under most circumstances. Furthermore, findings based on the constant coefficients indicate that some sectors exhibit wider shock intervals, reflecting higher sensitivity to market fluctuations. In contrast, some sectors demonstrated more stable price behaviour. The autoregressive coefficients reveal that stationarity patterns vary across quantiles, indicating heterogeneous market dynamics. While some indices show significant stationarity across all quantiles, others display significance only in the extreme quantiles. These results give that market efficiency in Borsa Istanbul is not homogeneous across sectors or market conditions, and that investment decisions should account not only for sectoral characteristics but also for the volatility environment.
The sharing economy is an economic model that facilitates access to goods and services by eliminating the need for individual ownership, thereby enabling a more efficient use of resources. This model is closely aligned with the sustainable developmentgoals and fosters environmental, social, and economic benefits. This study aims to analyze the factors influencing attitudes toward and intentions to participate in the sharing economy among individuals aged 18 and over living in the provinces of Istanbul, Adana, and Aksaray. Accordingly, the study thoroughly examines attitudes toward the sharing economy and participation intentions as dependent variables, along with three main motivational factors affecting them: environmental benefit, social benefit, and economic benefit. The study used factor analysis, reliability analysis, and logistic regression analysis methods. The findings indicate a high level of agreement among participants regarding statements about the sharing economy. Social and economic benefits motivate behavior, though less strongly than environmental benefits. Participation intention is driven primarily by social benefit, followed by environmental and economic benefits, and overall the sharing economy is viewed positively with strong potential for sustainable development. Based on these findings, it can be argued that economic, social, and environmental benefits should be more effectively highlighted to encourage broader adoption of the sharing economy. Adopting this model, which significantly contributes to sustainability, as a development tool that balances economic growth with environmental and social well-being, can play a crucial role in achieving global sustainability goals.
This paper investigates the volatility spillovers between exchange rates and stock returns across three major developed economies: the United States (US), the Euro area (EA), and the United Kingdom (UK). Using daily data from January 1, 2010, to December 31, 2019, this study employs the Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroscedasticity (DCC-GARCH) framework to capture time-varying conditional correlations and inter-market volatility spillovers across financial asset classes. The analysis further computes optimal hedge ratios and portfolio weights to support risk-minimising investment strategies across asset return pairs within each market. The results reveal that volatility spillovers are not significant between foreign exchange markets; however, they are evident across stock markets. Moreover, dynamic correlations amongstock markets are consistently positive, whereas correlations in foreign exchange markets are negative over time. Dynamic hedge ratio estimates indicate that short positions are only feasible in the currency markets. Lastly, the portfolio optimisation analysis reveals that, for a $1 portfolio of exchange rate (stock) returns, the US (UK) asset should dominate the portfolio. These findings offer valuable insights for both academics and practitioners, particularly international investors seekingto understand cross-market volatility dynamics among key global financial centres.
The rise in global carbon emissions has become a critical issue, accelerating climate change and contributing to the deterioration of ecosystems. Environmental degradation is closely linked to changes in economic activity, making it essential to examine the relationship between macroeconomic performance and the environment. This study investigates the effects of macroeconomic indicators on environmental degradation in T & uuml;rkiye by analysing annual data from 1990 to 2020. To capture both short-and long-term dynamics, the autoregressive distributed lag (ARDL) bounds test and the dynamic ARDL approach were applied. Dynamic analysis reveals that economic-environmental relationships can be temporary or cyclical, that the results must be interpreted with caution. Therefore, ARDL outcomes should be evaluated togetherwith dynamic simulations to gain a more comprehensive understanding.The comparative results of the two models highlight several important findings. In the ARDL model, both foreign direct investment(FDI) inflows and gross fixed capital formation significantly affect environmental degradation in the short and long term. However, in the dynamic ARDL model, these variables show significant effects only eventually. The simulation results further demonstrate that a 10% positive shock in FDI inflows leads to higher environmental degradation, supporting the pollution haven hypothesis. In terms of economic growth, the ARDL model results indicate short-term increase in environmental degradation, although this relationship is not statistically significant in the dynamic ARDL framework Overall, the findings underline the long-run risks of rising gross fixed capital formation, highlighting the need for Turkiye to adopt a green economy perspective, integrating environmental concerns into investment and growth policies.
In this study, the spatial effects of aviation data and economic variables on airport terminal revenues in T & uuml;rkiye were investigated using spatial panel data models. This study is the first study to model airport revenues in T & uuml;rkiye spatially. Based on previous studies, the variables that are thought to affect terminal revenues were as follows: number of passengers, cargo volume, annual exchange rate, real gross domestic product (GDP), and number of foreign visitors. Four different spatial panel data models were applied in the analysis: Spatial Autoregressive Model (SAR), Spatial Error Model (SEM), Spatial Autoregressive Combined Model (SAC) and Spatial Durbin Model (SDM). Statistical tests and model fit criteria were used to determine the most appropriate model. The Hausman test was performed to decide between fixed and random effects, and the Akaike information criterion (AIC) and Bayesian information criterion (BIC) were evaluated to compare model performances. Because of the Hausman test, fixed-effects models were more appropriate than random-effects models. Among the fixed effects models, the SDM model was determined to be the best fit according to the AIC and BIC values. According to the findings of the SDM model, the number of passengers had a statistically significant and positive effect on terminal revenues, and the number of foreign visitors in neighbouring cities had a statistically significant but negative effect on terminal revenues.
Informal employment constitutes a significant socio-economic challenge both globally and within the context of T & uuml;rkiye. As conceptualised by the International Labour Organisation, informal employment encompasses work activities that fall outside the purview of national labour legislation, taxation systems, and social security frameworks. This phenomenon not only erodes workers' access to fundamental rights and protections but also undermines public revenues, distorts labour market dynamics, and hampers overall economic efficiency. This study aims to analyse the macroeconomic determinants of informal employment in T & uuml;rkiye, with a specific focus on the regional and temporalvariations observed over the period 2009-2021. Employingthe spatial Durbin error model, the research identifies significant relationships between informal employment and key economic indicators. The results indicate that higher levels of GDP per capita, increased public expenditure, unemployment rates, and COVID-19 are correlated with a decline in informal employment. Notably, the findings reveal that neither the tax burden nor the inflation exerts a statistically significant impact on informal employment within the Turkish context during the examined period.This demonstrates that the influence ofthese factors may be context-specific or mitigated by other prevailing economic and institutional dynamics in T & uuml;rkiye. The results also demonstrate that GDP per capita, unemployment, public expenditure and inflation of neighbouring regions have spillover effects on the IFE. The methodological approach adopted in this study underscores the importance ofspatial and regional interactions in shaping informal employment trends.
Cities referred to as metropolitan areas or megacities serve as the economic, commercial, and socio-cultural engines of countries. However, some cities may not concurrently possess all these characteristics due to political decisions, leading to economic, administrative, social, and cultural imbalances and injustices among the cities within a country. This study identifies the factors beyond the legally defined population size criterion that may influence the attainment of metropolitan status in Turkiye. In this context, a logistic regression model was designed using 13 socio-economic independent variables. The results of the logistic regression analysis revealed that only three variables were statistically significant, yet a model with relatively high explanatory power was achieved. The findings obtained from the binary logistic regression model indicate that the export and importvariables positively influence the attainment of metropolitan status, while the per capita gross domestic productvariable has a negative effect. In other words, increases in exports and imports enhance a city's likelihood of gaining metropolitan status, whereas an increase in per capita gross domestic product decreases this likelihood. This suggests that cities with metropolitan status generally have large economic and commercial capacities, but due to high population levels, the per capita income is lower. Consequently, this research demonstrates that, in addition to political decisions, certain economic criteria can also be influential in determining the metropolitan status of cities.
The primary aim of this research is to examine the factors influencing Turkiye's exports of medium-technology automotive products and to test the validity of the Linder Hypothesis in this context. The research compares both supply-side approaches, relying on cost and productivity differences, and demand-side approaches that emphasise similarities in consumer preferences and income levels. A balanced panel dataset coveringTurkiye's exports to 118 countries between 2007 and 2023 is analysed using an extended gravity model. The findings indicate that while the economic size (GDP) of both Turkiye and its trading partners positively influences export performance, geographical distance has a negative effect. Regarding the main question, the LINDER variable proved statistically insignificant, whereas the similarity index (SIM) was positive and significant. This finding suggests that Turkiye exports more to countries with similar income levels, thus providing empirical support for the Linder Hypothesis in the automotive sector. The study further emphasises that targeting markets with similar demand structures, particularly in Europe and regional neighbours, may enhance Turkiye'sexport capacity. This will both maintain the sector's competitiveness and ensure sustainable export growth
