Export Competition in China: Evidence from Data at Provincial Level

18 Halama

Declining Labor Share: Is China's Case Different?

This paper explores why labor share in China has declined since the middle of the 1990s. Existing literature usually ascribes the labor share decline in developed countries to biased technological progress. However, our investigation shows that China's case is different. Using a simultaneous equation model estimated with three-stage least squares, we find that FDI, levels of economic development and privatization have negative effects on the labor share. The negative influence of FDI on labor share results from regional competition for FDI, which weakens labor forces' bargaining power. A U-shaped relationship exists between labor share and the level of economic development, and China is now on the declining part of the curve. The negative effects of privatization on the labor share stem from the elimination of the so-called "wage costs eroding profit" situation and the positive supply shock on the labor market. Copyright (c) 2010 The Authors China & World Economy (c) 2010 Institute of World Economics and Politics, Chinese Academy of Social Sciences.

Does “Going Global” help to restrain enterprises’ financialization: The Belt and Road initiative as a quasi-natural experiment

This paper employs the difference-in-differences (DID) to investigate the impact of “going global” on enterprises' financialization. Baseline estimation shows that the degree of financialization of enterprises participating in the Belt and Road Initiative was lower compared with those not participating in the Initiative. Mechanism analysis reveals that “going global” through Belt and Road Initiative has improved enterprises' profitability of real sector investment and inhibited their motivation of financialization. These findings provide new perspectives for more effectively promoting enterprises to participate in the Belt and Road construction and helping inhibit enterprises’ financialization

Transient signal identification of HVDC transmission lines based on wavelet entropy and SVM

High-voltage DC (HVDC) transmission plays an important role in power transmission projects due to its advantages of large transmission power and good control performance. As the main protection of the DC transmission line, transient protection uses the high-frequency signal generated by fault transient to detect faults, having the characteristics of fast response and high accuracy. However, the HVDC transmission line has complex conditions along the route and is vulnerable to lightning strikes and other accidents, resulting in the occurrence of a variety of transients in the line, which increases the difficulty of fault identification. Being able to reveal signal time-frequency characteristic, wavelet entropy is an effective tool of signal recognition. This study proposes a method of transient signal identification based on the wavelet entropy and support vector machine (SVM). Firstly, the transient processes of three kinds of signals, including unipolar faults, lightning strike faults, and lightning disturbances, are briefly introduced. Then the time−frequency features of three kinds of transient signals under different scenes are analysed by wavelet entropy. Finally, the training set was used to train the SVM classification model with the signal wavelet entropy being taken as the eigenvector, and the test results validate the effectiveness of the proposed method

EU-China Trade and intra-EU Trade: Substitute or Complementary?

This paper examines how EU-China trade affected intra-EU trade. The estimation shows that when a country's share of trade with China increased, its share of trade with EU partners declined. This suggests that stronger trade links with China resulted in weaker trade links among EU countries. Furthermore, the "disintegration" effect of the export to China was stronger than that of import from China, meaning that the influence of China as an export destination was greater than that of China as a source of import. An extended analysis shows that the disintegration effect was most strongly felt in trade links among EU core countries, less strongly felt in trade links between EU core and periphery countries, and least strongly felt in trade links among EU periphery countries. In comparison, we find that EU import from the US and India significantly weakened and strengthened intra-EU trade respectively. Estimation results using product level data demonstrate that the effects depend on the types of products we are concerned with. Whether using gross value or value added, the conclusions remain valid

EU-China Trade and intra-EU Trade: Substitute or Complementary?

This paper examines how EU-China trade affected intra-EU trade. The estimation shows that when a country's share of trade with China increased, its share of trade with EU partners declined. This suggests that stronger trade links with China resulted in weaker trade links among EU countries. Furthermore, the "disintegration" effect of the export to China was stronger than that of import from China, meaning that the influence of China as an export destination was greater than that of China as a source of import. An extended analysis shows that the disintegration effect was most strongly felt in trade links among EU core countries, less strongly felt in trade links between EU core and periphery countries, and least strongly felt in trade links among EU periphery countries. In comparison, we find that EU import from the US and India significantly weakened and strengthened intra-EU trade respectively. Estimation results using product level data demonstrate that the effects depend on the types of products we are concerned with. Whether using gross value or value added, the conclusions remain valid

Entropy SVM–Based Recognition of Transient Surges in HVDC Transmissions

Protection based on transient information is the primary protection of high voltage direct current (HVDC) transmission systems. As a major part of protection function, accurate identification of transient surges is quite crucial to ensure the performance and accuracy of protection algorithms. Recognition of transient surges in an HVDC system faces two challenges: signal distortion and small number of samples. Entropy, which is stable in representing frequency distribution features, and support vector machine (SVM), which is good at dealing with samples with limited numbers, are adopted and combined in this paper to solve the transient recognition problems. Three commonly detected transient surges—single-pole-to-ground fault (GF), lightning fault (LF), and lightning disturbance (LD)—are simulated in various scenarios and recognized with the proposed method. The proposed method is proved to be effective in both feature extraction and type classification and shows great potential in protection applications

Effect of Pricking-bloodletting Therapy Combined with Zhuang-medicine-thread Moxibustion on TLRs/MyD88 Signal Pathway in a Rat Model of Acute Gouty Arthritis

Background With the change of people's environment and diet structure, acute gouty arthritis (AGA) has become a common clinical disease, which is prone to recurrence, causing harm to patients' health. Pricking-bloodletting therapy combined with Zhuang-medicine-thread moxibustion (moxibustion with a threat prepared with Zhuang herbal medicine) has proven to have a definite therapeutic effect on AGA clinically, but the mechanism of action is not very clear. Objective To assess the effect of pricking-bloodletting therapy combined with Zhuang-medicine-thread moxibustion on toll-like receptors /myeloid differentiation factor 88 (TLRs/MyD88) signal pathway in a rat model of AGA to explore the mechanism of action of this treatment in AGA. Methods The experiment lasted from May 2021 to March 2022, sixty SD rats were equally randomized into 6 groups: blank group, model group, pricking-bloodletting group, medicated thread group, colchicine group and pricking-bloodletting with medicated thread group. Except for the blank group, the other groups received sodium urate suspension injected into the right ankle cavity to prepare the AGA model. Twenty-four hours after the modelling, colchicine group received intragastric administration of colchicine suspension, pricking-bloodletting group received bloodletting after pricking the Ashi acupoint with a needle, medicated thread group received Zhuang-medicine-thread moxibustion at the site of lesion, and pricking-bloodletting with medicated thread group first received bloodletting after pricking the Ashi acupoint with a needle, then Zhuang-medicine-thread moxibustion at the site of lesion. The swelling degree of the right ankle joint was observed at 6, 12, 24 h and 72 h after modeling. Hematoxylin-eosin staining was used to observe the pathological changes of the synovium of the right ankle joint. The serum levels of interleukin (IL) -10, IL-8 and cyclooxygenase-2 (COX-2) were determined by ELISA. The expressions of MyD88 and IKK-β in the synovium of the right ankle were detected by western blotting. Results The transverse diameter of right lateral malleolus in model group, pricking-bloodletting group, medicated thread group or colchicine group was larger than that in blank group at 6, 12, 24, 48 h and 72 h after modeling (P<0.05). The transverse diameter of right lateral malleolus in pricking-bloodletting with medicated thread group was larger than that in blank group at 6, 12, 24 h and 48 h after modeling (P<0.05). The transverse diameter of the right lateral malleolus of the pricking-bloodletting group, medicated thread group, colchicine group or pricking-bloodletting with medicated thread group was smaller than that of the model group at 48 h and 72 h after modeling (P<0.05). Compared with model group, the inflammatory cell infiltration of right ankle in pricking-bloodletting group, medicated thread group, colchicine group and pricking-bloodletting with medicated thread group was improved. The blank group had lower levels of IL-8 and COX-2 and higher level of IL-10 than each of the other 5 groups (P<0.05). The model group had higher levels of IL-8 and COX-2 and lower level of IL-10 than colchicine group, pricking-bloodletting with medicated thread group, pricking-bloodletting group or medicated thread group (P<0.05). The colchicine group had lower levels of IL-8 and COX-2 and higher level of IL-10 than pricking-bloodletting group or medicated thread group (P<0.05). The pricking-bloodletting with medicated thread group had lower levels of IL-8 and COX-2 and higher level of IL-10 than pricking-bloodletting group or medicated thread group (P<0.05). The blank group had lower level of MyD88 than each of the other 5 groups (P<0.05). The blank group had lower level of IKK-β than model group, medicated thread group, pricking-bloodletting group or pricking-bloodletting with medicated thread group (P<0.05). The model group had higher IKK-β level than medicated thread group or colchicine group (P<0.05). The model group had higher MyD8 level than medicated thread group, colchicine group, pricking-bloodletting group or pricking-bloodletting with medicated thread group (P<0.05) . Conclusion Pricking-bloodletting with Zhuang-medicine-thread moxibustion is effective in improving the symptoms of AGA by regulating the TLRs/MyD88 signaling pathway, which may be a potential alternative therapy for AGA

Deep learning-based fault location of DC distribution networks

Compared with AC distribution networks, DC ones have a number of advantages. Intensive connections of distributed renewable energy can lead to large amount of power electronic converters and complex models. Underground cable is widely used in DC distribution networks. Accurate location of faults can help engineers find the fault points and shorten the time of maintenance. In DC distribution networks, where only a few measuring units are equipped and low sampling rates are adopted, there is limited data used for fault location. Also, for monopole grounding fault, the fault features are sometimes unobvious for recognition. Deep learning which provides feature hierarchy can learn experiences automatically and recognise raw data as human brain does. It reveals a high potential to solve location problems in DC distribution systems. This paper proposes a depth learning based fault location for DC distribution networks. First, a DC distribution network with radiant topology is modelled, and faults are added with different parameters to simulate various scenarios in practical projects. Then, a deep neural network is generated and trained with normalised fault currents. The parameters of network are discussed according to particular application. Finally, the location performance of deep neural network is tested