This study aims to reveal the network connectedness between the volatilities of Emerging and Growth-Leading Economies (EAGLEs) stock exchanges with the frequency-based TVP-VAR connectedness approach. Connectedness results were obtained in short (1–5 days) and long (5-inf) period frequencies among the volatilities obtained with the Garman–Klass volatility estimator. According to the dynamic TCI results, connectivity peaked during the COVID-19 and Russia–Ukraine War periods. BVSP is the most dominant transmitter of the network and spreads the most effect to the emerging markets. As a result of the pairwise metrics, SSE has the lowest values and is positioned as a relatively independent market in the network. In particular, SSE has almost no connection with BIST in the short term, while it has a more significant effect on BIST in the long term. Moreover, the connectedness metrics show that MOEX is in a neutral position in the network and is largely affected by its internal dynamics.

Research background: As part of the process of structural transformation that countries go through in their development journey, the relative significance of agriculture as a sector typically shrinks over time. Nonetheless, the agricultural sector maintains its significance in terms of its trade potential and global employment prospects to this day. The extant literature largely neglects the impact of countries’ land resources on agricultural trade by emphasizing agricultural farm size and land productivity nexus. This justifies the exploration of the causal nexus between countries’ agricultural land resources and their agricultural exports. Purpose: The study herein aims at investigating the nexus between countries’ total agricultural land resources and agricultural exports for 174 selected countries over the period 1991–2019. Research methodology: Dumitrescu and Hurlin’s (2012) test for Granger non-causality for heterogeneous panels is harnessed. Results: Estimation results evidence the presence of bi-directional causality (feedback) between countries’ agricultural land resources and agricultural exports not only in the whole panel (1991–2019) but also in subpanels too (1991–2000, 2001–2010, and 2011–2019). Overall, the results stress the strategic importance of agricultural land as a significant determinant of agricultural exports. Novelty: Our study takes a unique approach and investigates if there is a cause-and-effect relationship between a country’s agricultural land resources and its agricultural exports by relying on the implications of the factor endowment theory of trade.

This paper studies the volatility connectedness between the stock prices of e-commerce companies. For that matter, we implement the TVP-VAR-Based connectedness procedure to unearth the dynamic structure of volatilities. This approach helps us to determine the volatility spillover between assets that are risk receivers or risk transmitters. We utilize the daily log-return data of the largest e-commerce companies by market cap. The data set consists of the daily open, close, high, and low prices of stocks between 2019-01-02 and 2022-12-23. We obtain the volatility of stocks using the Garman-Klass range-based approach. The findings reveal that the average total connected index is relatively high by 65.45%, which means that the forecasting error variance in the variables is due to the transmission and connectedness between these variables. Furthermore, net pairwise directional connectedness results evidence that the most dominant stock is Amazon within the network. Ultimately, we find the strongest bilateral volatility interconnectedness to occur between the stocks of Alibaba and Jingdong Mall