In terms of the development of the manufacturing industry, the Chinese government has carried out environmental regulations and set up production standards for related industries. This is an environmentally-friendly and economic action, which is also in line with the requirements of building a green economy for China. Meanwhile, whether from the micro regulatory measures or the macro government policies, carbon emission is an inevitable problem in the study of environmental problems. This paper will explore the impact of environmental regulation on the green economy based on carbon emissions and study the optimal environment regulation intensity that relates to a direct carbon footprint under the maximum green economic benefits. A SBM-MALMQUIST model is established to measure the green total factor productivity according to 27 Chinese manufacturing industries through the MAXDEA software. It is found that the intensity of environmental regulation has a significant impact on green total factor productivity, and direct carbon footprint also exhibits a partial intermediary effect, participating in the mechanism that affects green total factor productivity. Combined with the industrial characteristics and the above research results, this paper puts forward the adjustment strategy of reasonable environmental regulation for the manufacturing industry, which conforms to the national policy guidance, and will be beneficial in promoting the economic development of the green manufacturing industry.
In: Political analysis: PA ; the official journal of the Society for Political Methodology and the Political Methodology Section of the American Political Science Association, S. 1-5
Abstract A recent paper by Häffner et al. (2023, Political Analysis 31, 481–499) introduces an interpretable deep learning approach for domain-specific dictionary creation, where it is claimed that the dictionary-based approach outperforms finetuned language models in predictive accuracy while retaining interpretability. We show that the dictionary-based approach's reported superiority over large language models, BERT specifically, is due to the fact that most of the parameters in the language models are excluded from finetuning. In this letter, we first discuss the architecture of BERT models, then explain the limitations of finetuning only the top classification layer, and lastly we report results where finetuned language models outperform the newly proposed dictionary-based approach by 27% in terms of
$R^2$
and 46% in terms of mean squared error once we allow these parameters to learn during finetuning. Researchers interested in large language models, text classification, and text regression should find our results useful. Our code and data are publicly available.
In: Political analysis: PA ; the official journal of the Society for Political Methodology and the Political Methodology Section of the American Political Science Association, Band 31, Heft 4, S. 662-668
AbstractSupervised topic classification requires labeled data. This often becomes a bottleneck as high-quality labeled data are expensive to acquire. To overcome the data scarcity problem, scholars have recently proposed to use cross-domain topic classification to take advantage of preexisting labeled datasets. Cross-domain topic classification only requires limited annotation in the target domain to verify its cross-domain accuracy. In this letter, we propose supervised topic classification with pretrained language models as an alternative. We show that language models fine-tuned with 70% of the small annotated dataset in the target corpus could outperform models trained using large cross-domain datasets by 27% and that models fine-tuned with 10% of the annotated dataset could already outperform the cross-domain classifiers. Our models are competitive in terms of training time and inference time. Researchers interested in supervised learning with limited labeled data should find our results useful. Our code and data are publicly available.1
Cet article explore le parcours de deux discours coloniaux à la fin du XIX e et au début du XX e siècle en Chine : le discours colonial évolutionniste et étatique et le discours colonial développemental et commercial. Plus précisément, il s'intéresse à la façon dont Timothy Richard a mobilisé ces discours en lien avec le concept de Minben , l'une des idées fondamentales de la pensée politique chinoise, d'abord dans ses divers écrits sur l'Inde des années 1880 jusqu'à sa traduction chinoise du chapitre sur l'Inde du livre de Robert Mackenzie, The Nineteenth Century: A History publié en 1895. S'appuyant sur un corpus substantiel de traductions, de commentaires, de journaux personnels non publiés et d'un large éventail d'écrits bilingues de Timothy Richard, cet article soutient que sa pratique translinguistique n'a pas seulement créé une plate-forme pour que les discours coloniaux migrant entre différents systèmes de connaissances et de culture, mais a également fourni aux intellectuels chinois des concepts pour construire une compréhension hybride localisée des discours coloniaux. L'émergence et le déclin de ces discours éclairent la dynamique du savoir qiaoyi , en particulier en ce qui concerne la façon dont les intellectuels dans des conditions politiques défavorables ont manifesté un grand niveau d'autonomie et de flexibilité dans la réception et la réinterprétation des connaissances alimentées par un réseau culturel ayant reçu une nouvelle impulsion dans le contexte de l'impérialisme et de l'expansion coloniale.
This paper takes the Zhejiang traditional garden museums as research object, elaborates their historical causes, generalizes the garden types and characteristics, analyzes the issues existing in the museumification process, explores the practical significance of development of Zhejiang traditional garden museums, proposes the protection and development strategies, and expects to provide reference and pathway for promoting the Zhejiang traditional garden museumification.
Despite the extensive theoretical connections between defense budget growth and inflation, empirical findings based on traditional time-domain methods have been inconclusive. This study reexamines the issue from a time–frequency perspective. Applying continuous wavelet analysis to the U.S. and Britain, it shows empirical evidence in support of positive bilateral effects in both cases. In the bivariate context, U.S. defense budget growth promoted inflation at 2- to 4-year cycles in the 1840s and at 8- to 24-year cycles between 1825 and 1940. Conversely, inflation accelerated defense spending growth at 5- to 7-year cycles in the 1830s and at 25- to 64-year cycles between 1825 and 1940. Similarly, British defense budget growth spurred inflation at 8- to 48-year cycles between 1890 and 1940 and at 50- to 65-year cycles between 1790 and 1860. Inflation fueled the growth of defense spending at 7- to 20-year cycles between 1840 and 1870, in the 1940s, and in the 1980s. Preliminary results from multivariate analyses are also supportive, though there is a need for further research that is contingent on advancements in the wavelet method in the direction of simulation-based significance tests.
Existing international relations literature on the United Nations Security Council (UNSC) paints a picture where the United States proactively lobbies other UNSC members using carrots and sticks, whereas China is quiet, content with its veto power, and acts only to punish other members when its core interests are hurt. We add nuance to the picture and present a different perspective where China actively promotes its agenda among UNSC members. Using newly collected data from 2000 to 2020, we show that when Chinese leaders visit Africa, they are three times more likely to visit a sitting UNSC member country than a nonmember country. We obtain similar results when we replicate our models on the seminal work by Dreher et al. (2018).
This study examines the effect of bargaining power on the allocation of U.S. military assistance. Conceptualising U.S. military assistance as an aid-for-policy deal, it applies a two-tiered stochastic frontier model to a data sample of the post-Cold War era. It shows that the bargaining effect accounts for a huge variation in U.S. military aid distribution. The volume of U.S. military assistance in equilibrium is lower than the baseline volume by 4% at the mean and by 6% at the median. The donor U.S. extracts a slightly larger portion of the transaction surplus at these central points. However, the game of surplus division is not always about equally strong hagglers as it may first appear. In fact, the quartile values show substantial variance in bargaining performance and, hence, an outcome of surplus division across transactions. The bargaining effect is highly significant in the allocation of U.S. military assistance in the post-Cold War era. The donor U.S enjoys a bargaining advantage at the mean and median, but rich variations are noticeable.