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AbstractUsing a unique firm‐level dataset from 2007 to 2015, we investigated the characteristics and trends of China's economic development from the perspective of firm performance. We found that China's economic development in the recent decade has made the following achievements: less reliance on investment for growth, enterprises' deleveraging, a more competitive market environment and improvement in labour income distribution. Yet, it still faced severe challenges, such as increasing tax and fee burdens, high employment pressure, low total factor productivity (TFP) growth rate, and how to realize the coordinated development of the economy and environment.

Chinese companies have become major technology producers, with the largest share of their output exported. This paper examines the development of solar PV and wind energy technology component (WETC) exports from China and the competitive position of the country`s renewable energy industry. We also describe the government's renewable energy policy and its success in renewable electricity generation as well as increasing renewable energy innovation and foreign knowledge accumulation, which may drive export performance. We aim at empirically identifying determinants of Chinese solar PV and WETC exports. We estimate an augmented gravity trade model using maximum likelihood estimation. Besides controlling for standard variables derived from the gravity literature, we consider additional explanatory factors by accounting for market, policy and innovation effects steaming from both importing countries and China. We use a panel dataset representing annual bilateral trade flows of 43 countries from the developed and developing world that imported solar PV and WETCs from China between 1996 and 2008. The analysis shows that while the national market remained small for solar PV, the industry successfully entered foreign markets. The export performance of firms producing WETC increased but remained relatively small while the country developed a large home market. Empirical results indicate that high income countries, with a large renewable energy market and demand side policy support scheme, in terms of incentive tariffs, are increasingly importing solar PV components from China. We show that trade costs have a negative impact on exports of solar PV components but not WETC. Additionally, we find a positive impact of research and development (R&D) appropriation growth, especially from provincial governments in China, but no evidence that bilateral knowledge transfer and indigenous innovation affect exports.

Precise and timely information on crop spatial distribution over large areas is paramount to agricultural monitoring, food security, and policy development. Currently, automatically classifying crop types at a large scale is challenging due to the scarcity of ground data. Although previous studies have indicated that transductive transfer learning (TTL) is a promising method to address this problem, it performs poorly within regions where crop compositions and phenology differ largely. Here we transferred random forest classifiers trained in limited regions with diversified growing conditions and land covers to the rest of the study area where ground data are scarce, with more than 130,000 Sentinel-2 images processed using the Google Earth Engine (GEE) platform. We established the 10 m crop maps for four major crops (i.e., maize, rapeseed, winter, and spring Triticeae crops) across 10 European Union (EU) countries from 2018 to 2019. The final crop maps had a high accuracy with overall accuracy generally greater than 0.89, with user's accuracy and producer's accuracy ranging from 0.72 to 0.98. Moreover, the resulting maps were consistent with the NUTS-2 level official statistics, with R2 consistently greater than 0.9. We further analyzed the crop rotation patterns and found that the rotation intervals across these EU countries were generally at least one year. Maize was dominantly rotated with winter Triticeae crops or converted to other land covers in the following year. Rapeseed was generally grown in rotation with winter Triticeae crops, whereas the rotation patterns of winter and spring Triticeae crops were more diversified. Red Edge Position (REP) and Normalized Difference Yellow Index (NDYI) played significant roles in crop classification across the EU. This study highlights the potential of the developed TTL method for crop classification over large spatial extents where labeled data are limited and the differences in crop compositions and phenology are relatively large.

AbstractWe study firm investment in abatement technology under a heterogeneous‐firm framework. We find that more‐productive firms make more (less) investment in abatement technology if investment and productivity are complements (substitutes). Under linear demand, firms' abatement investments exhibit an inverted U‐shape with respect to productivity level. This finding is in contrast to results in existing studies. We also find that in response to tightened environmental regulations, more‐productive firms raise their respective investments in abatement technology, whereas less‐productive firms do the opposite. More‐productive firms have lower pollution emission intensity. The key theoretical predictions are confirmed by empirical tests using Chinese data.