Objective: To promote the development of China’s crop seed industry with high quality, guarantee food security and sustainable agricultural development, scientific design of the evaluation index system for high-quality development of the seed industry and conduct of metric analysis are the keys to promoting the revitalization of the seed industry and the construction of a strong agricultural country. Methods: This paper focused on the high-quality development of China’s crop seed industry as the main research object by combining previous research findings of studies based on the connotation of high-quality development of the crop seed industry and constructed the evaluation index system of high-quality development of China’s crop seed industry which covers five dimensions, namely, innovation-driven development, green and sustained development, coordinated and comprehensive development, opening-up and strengthened development, and share-and-promote development, The Entropy method, Dagum’s Gini coefficient, Kernel’s density estimation, and panel regression methods were used to comprehensively analyze the spatial and temporal evolution, regional differences, and driving factors of the level of high-quality development of the crop seed industry in 30 provinces (municipalities and autonomous regions) of China from 2011 to 2020. Conclusions: After systematic analysis, it was concluded that (1) the overall level of high-quality development in China’s crop seed industry has stabilized, and progress has been made. (2) The overall inter-regional differences among the four major regions showed a gradual upward trend, with the inter-regional differences serving as the primary source of the differences and the contribution rate of various inter-regional differences demonstrating an upward trend. (3) Innovation capacity, the cultural and educational level of rural residents, the development of rural infrastructure, national financial support, and market-oriented approach are important factors driving the high-quality development of the crop seed industry in Chinese provinces (districts and municipalities).

This study addresses the crucial question of the macroeconomic impact of investing in railroad infrastructure in Portugal. The aim is to shed light on the immediate and long-term effects of such investments on economic output, employment, and private investment, specifically focusing on interindustry variations. We employ a Vector Autoregressive (VAR) model and utilize industry-level data to estimate elasticities and marginal products on these three economic indicators. Our findings reveal a compelling positive long-term spillover effect of these investments. Specifically, every €1 million in capital spending results in a €20.84 million increase in GDP, a €17.78 million boost in private investment, and 72 new net permanent jobs. However, these gains are not immediate, as only 14.5% of the output increase and 38.8% of the investment surge occur in the first year. In contrast, job creation is nearly instantaneous, with 93% of new jobs materializing within the first year. A short-term negative impact on the trade balance is expected as new capital goods are imported. Upon industry-level analysis, the most pronounced output increases are witnessed in the real estate, construction, and wholesale and retail trade industries. The most substantial net job creation occurs in the construction, professional services, and hospitality industries. This study enriches the empirical literature by uncovering industry-specific impacts and temporal macroeconomic effects of railroad infrastructure investments. This underscores their dual advantage in bolstering long-term economic performance and counteracting job losses during downturns, thus offering valuable public policy implications. Notably, these benefits are not evenly distributed across all industries, necessitating strategic sectoral planning and awareness of employment agencies to optimize spending programs and adapt to industry shifts.