This paper uses the Difference-in-Differences method to test the impact of the promulgation of Green Credit Guidelines, a market-oriented environmental regulation, on the enterprise market expansion strategy, based on the panel data of Chinese A-share listed companies from 2008 to 2015. We find that the promulgation of Green Credit Guidelines significantly inhibited the market expansion strategy of high pollution enterprises. Two channels through which the Green Credit Guidelines affect the market expansion strategies of high polluters are increasing the cost of financing and promoting green R&D. Heterogeneity analysis finds that the impact of Green Credit Guidelines on the market expansion of highly polluting enterprises is more significant in non-state-owned enterprises and enterprises without equity incentive. Further analysis shows that the promulgation of Green Credit Guidelines damages the corporate image and profitability of high polluting enterprises, but it doesn’t increase the risk of high polluting enterprises. The results of this research could help relevant government departments to formulate practical environmental regulations and promote sustainable economic development. Over the past decade, China’s contribution to world economic growth has exceeded 30%, ranking first in the world. However, the long-term industrial development model of high investment, high consumption and high pollution has led to a series of problems such as excessive consumption of resources and environmental degradation, which has seriously affected the sustainable and healthy development of economy and social harmony . As the In essence, green finance is a way to guide funds from the pollution field to the green field with the help of the effective allocation of financial resources, so as to realize the sustainable development of ecological environment and economy. Green credit is the main form of green finance in China, which is a bank dominated economy. Since 2007, the Chinese government has been building a green credit policy system and started small-scale pilot projects. In 2012, the China Banking Regulatory Commission issued Green Credit Guidelines, marking the full implementation of green credit policies in China. In recent years, China’s major banking institutions have gradually intensified their implementation of green credit. By the end of the first quarter of 2021, the green balance of 21 major Chinese banks reached 12.5 trillion yuan, ranking first in the world. The non-performing loan ratio of green credit remaining below 0.7% in the past five years, much lower than the overall non-performing level of various loans in the same period. China’s green credit policies are already bearing fruit, and commercial banks are supporting the upgrading of industrial structure and optimizing the allocation of resources through funds. The green credit policies strongly promote the transformation and development of China’s economy.The enterprises, as for-profit organizations, aim to maximize profits. Green credit, a market-based environmental regulation, can only guide high-polluting enterprises to make a green transition by adjusting the amount of funds allocated among different enterprises . HoweverThat such a scenario is logically possible is by now beyond doubt. That such a mechanism is of quantitative importance, however, remains an empirical question. Unfortunately, the ‘micro’ observation that green credit reduces bank lending to high-polluting companies  and promInstead, we examine this mechanism at a relatively macro level by examining the behavior of enterprise market expansion strategy selection. Specifically, this paper takes the promulgation of Green Credit Guidelines in 2012 as a quasi-natural experiment, we assemble a firm-level dataset including 7272 samples from 2008 to 2015 and employ the difference-in-differences (DID) approach to identify causality.We find that high polluting firms reduce the rate of market expansion after green credit guidelines are issued. This implies that even if the government adopts non-coercive environmental regulations, high polluters still adjust their corporate strategies to match the national strategic needs. This paper also provides empirical evidence from China for the validity of Porter’s hypothesis. We are interested in the channels through which green credit guidelines influence the strategic choices of high-polluting firms. We find that the Green Credit Guidelines increase the financing constraints and promote green R&D of high-polluting firms, all of which may inhibit high-polluting firms from adopting market-expanding strategies. We find that the Guidelines would be more influential if the firm is non-SOE or does not have equity incentives.At the same time, we also found that although the green credit guidelines reduced the profitability of highly polluting enterprises, they did not increase the risk of highly polluting enterprises. This shows that a well-designed policy, such as the Green Credit Guidelines, can realize the green transformation of the economy on the premise of stabilizing market risk.This paper contributes to our understanding of the role of the Green Credit Guidelines. We study the impact of green credit policy on the company from the perspective of enterprise strategic deployment. The existing literature mainly investigates the impact of green credit policy on corporate behavior at specific levels , 7. ThisThis paper links the research on the influencing factors of the company’s strategic choice with the national strategy of environmental protection. The external environment and the company’s strategic choice have been discussed for a long time. Existing literature has focused on the impact of political, economic, institutional and other macro-environments as well as the industrial environment on the company’s strategic choices. This article takes the promulgation of China’s Green Credit Guidelines as the starting point, and extends the research on the factors affecting the company’s strategic choices to the fields of environmental protection and world sustainable development.As early as the beginning of reform and opening up, the Chinese government has paid attention to environmental protection issues. In 1995, the People’s Bank of China issued the "Notice on Issues Related to Implementing Credit Policies and Strengthening Environmental Protection Work". The Notice requires financial institutions to include the environmental friendliness of enterprises in credit review conditions. This is China’s first document on green credit policies. However, the primary development goal at that time was economic growth, the contradiction between economic growth and environmental protection was not yet prominent. The green credit was not given enough attention. In 2007, the People’s Bank of China and the environmental protection department jointly issued the "Opinions on Implementing Environmental Protection Policies and Regulations to Prevent Credit Risks". The Opinions clearly stated that commercial banks should support environmental protection and control credit to polluting enterprises as an important part of fulfilling their social responsibilities. However, the green credit policy has not been effectively implemented, due to the lack of corresponding supporting measures and supervision mechanisms.On February 24, 2012, the China Banking Regulatory Commission issued the "Green Credit Guidelines". The Guidelines make specific arrangements for the green credit business of banking financial institutions and the supervision of regulators from six aspects: organization management, policy and system construction, process management, internal control management and information disclosure, supervision and inspection. The Green Credit Guidelines are applicable to policy banks, commercial banks, rural cooperative banks, and rural credit cooperatives legally established in China. The Guidelines require banking financial institutions to formulate their own green credit policies in order to strengthen the management of enterprises’ environmental and social responsibility. The Guidelines also ask banking financial institutions to invest more in key areas such as green economy, low-carbon economy and circular economy. The Guidelines clearly states that the regulatory authorities must comprehensively evaluate the green credit performance of banking financial institutions, and take the evaluation results as an important basis for the regulatory rating, institutional access, business access and senior executives’ performance evaluation of banking financial institutions in accordance with relevant laws and regulations. The "Green Credit Guidelines" is China’s first normative document specifically aimed at green credit policies. It defines the framework of China’s green credit policy system and is of great significance to the development of green credit and green finance.More and more studies have found that environmental pollution will affect climate change and human health –11, so cIn management, there are many ways to divide corporate strategy. Among them, the classification method of Miles and Snow  can coveIn fact, the company’s strategy is neither good nor bad, only suitable or not . If the China’s 14th Five-Year Plan puts forward the long-term goal of basically realizing socialist modernization by 2035: widely forming a green production and lifestyle, steadily decreasing carbon emissions after reaching the peak, fundamentally improving the ecological environment, and basically realizing the goal of building a beautiful China. It shows that environmental protection and sustainable development have been highly valued by the Chinese government. Therefore, environmental protection is also an external environmental factor that cannot be ignored when the management chooses the company’s strategy in recent years.Rational enterprises will make discretionary choices according to their own conditions, facing the constraints brought by market-oriented environmental regulation. The self-selection behavior of enterprises is heterogeneous: reduce production scale or even withdraw from the market, upgrade products to reduce pollution or transform . Due to Hypothesis 1 (H1):The promulgation of the Green Credit Guidelines inhibits the market expansion strategy of high-polluting companies.According to the green credit guidelines, commercial banks strictly control the credit threshold and take the environmental compliance of enterprises as an important condition for granting loans. The supply of credit to highly polluting enterprises decreased. The financing cost of highly polluting enterprises increased, and bank loans, especially long-term loans, decreased significantly , 24. ModHypothesis 2 (H2):The promulgation of Green Credit Guidelines inhibits the market expansion of high polluting enterprises by increasing the financing cost.As a market-based environmental regulation, the Green Credit Guidelines can provide more flexible and effective innovation incentives , 33. TheHypothesis 3 (H3):The promulgation of Green Credit Guidelines inhibits enterprise market expansion by encouraging green R & D of highly polluting enterprises.This paper takes Chinese A-share listed companies from 2008 to 2015 as research samples, and the data required are from the CSMAR database. In this paper, the samples are processed as follows: 1. Eliminate the sample of financial listed companies; 2. Eliminate the sample of companies that have been listed for less than five years, because we need five years of financial data to calculate the company’s market expansion tendency. 3. Eliminate the samples with missing data in variables. 4. Eliminate companies with a leverage ratio of more than 1. 5. Winsorize the continuous variables at the 1% level.The promulgation of the Green Credit Guidelines is a completely exogenous event for enterprises. According to the specific content of the Green Credit Guidelines, the Guidelines only affect the credit policies and corporate social responsibilities of high-polluting companies. Therefore, we take high-polluting companies as the treated group and other companies as the control group, use the DID (Difference-in-Difference) model to analyze the impact of green credit policies on corporate expansion strategies. We consider these companies as high-polluting companies: companies in the 14 high-polluting industries disclosed in the "List of Listed Companies Environmental Inspection Industry Classification Management Directory" issued by the Ministry of Environmental Protection in June 2008. The 14 heavily polluting industries are: thermal power, steel, cement, electrolytic aluminum, coal, metallurgy, building materials, mining, chemicals, petrochemicals, pharmaceuticals, light industry, textiles and tanning. We use the "List of Listed Companies Environmental Inspection Industry Classification Management Directory" promulgated in June 2008 for the following reasons: First, this is the classification issued by the Ministry of Environmental Protection of China, which is authoritative. Second, this is a classification issued before the Green Credit Guidelines and before the sample research time of this article. Using this classification can effectively solve the problem of sample selection.We finally identified 7272 enterprise-annual samples, including 1032 high-polluting enterprise samples and 6,240 control group samples.du is a dummy variable to measure whether enterprises are affected by policies. If firm i is affected by the policy du = 1, otherwise du = 0. dt is a dummy variable representing whether the policy is implemented. dt is 0 before policy is implemented and 1 after policy is implemented. εi,t is the error term, which is assumed to be normally distributed with zero mean value and constant variance according to the existing literature [We use a Difference-in-Differences model to test the influence of Green Credit Guidelines on enterprises’ market expansion strategy, following Liu et al. (2019). A standard Difference-in-Differences (DID) model is as follows: This section may be divided by subheadings. It should provide a concise and precise description of the experimental results, their interpretation, as well as the experimental conclusions that can be drawn.terature –41.du will be absorbed by individual fixed effect, dt will be absorbed by the time fixed effect. Therefore, the DID model is set as follows:When we use the bidirectional fixed effects DID model, Strategy is the variable we use to measure the company’s market expansion strategy. Referring to the existing literature [terature , 43, we Compared with the method of directly using financial indicators, this method has the following advantages: 1. This indicator covers the company’s resource allocation and operating results in the past five years, and reflects the company’s long-term action plan and implemented strategy. 2. Using this indicator can avoid the possible endogenous problems caused by the direct use of financial indicators. 3. We can calculate the corporate strategy of each company, which is conducive to large sample empirical research. In the robustness test part, we also use the market position in the next period and the growth rate of sales scale in the next period to measure the enterprise’s market expansion strategy.Pollute × Policy is the main explanatory variable in the Difference-in-Difference model. Pollute is a virtual variable that indicates whether the company is high-polluting. Pollute = 1 when a company is high-polluting, otherwise Pollute = 0. Policy is a virtual variable that measures the promulgation of Green Credit Guidelines. Policy = 0 if samples are in 2008 to 2011, Policy = 1 if samples are in 2012 to 2015. The coefficient of Pollute × Policy measures the net impact of Green Credit Guidelines on the market expansion strategy choice of high-pollution enterprises.control is the control variable. We control the following main characteristics that may affect corporate strategy in Formula 2: company size (size), leverage (leverage), return on equity (ROE), listing years (age), state owned enterprise (SOE), ownership concentration (Top5Hold) and industry position (Indpos). In addition, corporate strategic decisions are mainly decided by the board of directors and the management. Therefore, we control the variables related to the characteristics of the board of directors and management: board size (Board), proportion of independent directors (Indep) and mean age of the management (MgAge).See Strategy in high polluting enterprises after the promulgation is 2.769, which is significantly lower than 3.126, the mean value before the promulgation. This shows that high polluting enterprises have significantly reduced the market expansion tendency after the promulgation of Green Credit Guidelines. However, there is no significant difference in the Strategy of non-highly polluting companies before and after the promulgation of the policy, only from 3.037 to 3.085. So non-highly polluting enterprises have a slight tendency of market expansion, but the change is not significant. The above information shows that the promulgation of the Green Credit Policy does have a negative impact on the market expansion strategy of the experimental group companies. This impact needs to be further studied using the DID model.Pollute × Policy. The coefficient of Pollute × Policy is -0.2453, statistically significant at the 1% level. This shows that the promulgation of the Green Credit Guidelines has significantly inhibited the market expansion strategy of high-polluting companies. Hypothesis 1 holds. The green credit policy is an effective environmental protection policy. The second to fourth columns are the regression results after adding other control variables, the coefficient of Pollute × Policy is still significantly negative.To verify Hypothesis 1: Green Credit Guidelines will inhibit the market expansion strategy of high-polluting companies, we conduct an empirical study according to Formula 2. The regression results are shown in size is significantly positive, indicating that the larger the scale of the company, the more motivated it is to adopt a radical market expansion strategy. The coefficient of age is significantly negative, which means that the younger the company is, the more likely it is to adopt aggressive expansion strategies. There is a significant positive correlation between leverage and Strategy, which means that external financing is an important source of funds for the market expansion of the Chinese enterprise. The more profitable companies are, the more motivated they are to adopt aggressive strategies, because ROE and Strategy are significantly positively correlated. The Top5hold’s coefficient is significantly positive, that is, a company with a higher degree of equity concentration is more likely to aggressively expand the market. Interestingly, the negative coefficient of MgAge tells us that the older the managements, the more defensive a company’s business strategy, which may be related to the calm and moderate personality of the Chinese elders. Indpos and Strategy are significantly negatively correlated, indicating that companies with a higher market share tend to be more prudent in operation, while companies with a lower market share have a strong tendency to market expansion. The regression results in We can also find from the regression results that the coefficient of The DID method needs to satisfy the parallel trend assumption. That is, the trend of Strategy in the treated group is not statistically significant different from the trend in the control group, while there is a significant difference in the trends of the two after the policy. Refer to Moser and Voena , new timWe also performed a placebo test to exclude other factors. We consider a possibility: the decline in the aggressiveness of enterprise market expansion strategy is caused by the decline of China’s economic growth, rather than the promulgation of Green Credit Guidelines. To eliminate this potential possibility, we constructed a virtual policy occurrence time before the actual policy occurrence (before 2012). Columns 1 and 2 of To ensure the robustness and reliability of the research conclusions, we replace the proxy variables, change the sample, and do PSM-DID (propensity score matching-DID).F. Indpos) and sales scale (F. ln(revenue)) of enterprises in the next period to measure the market expansion strategy of enterprises in the current period. The definition of market position (lndpos) is shown in Pollute × Policy is still significantly negative.Replace the variables that measure the market expansion strategy. In Pollute × Policy is significantly negative, hypothesis 1 holds. The impact of interest rate on the company’s market expansion strategy is also significantly negative, indicating the looser the monetary policy, the more aggressive market expansion strategy is.After the financial crisis in 2008, China launched a series of economic stimulus policies, such as the implementation of the "four trillion" fiscal stimulus policy, the reduction of loan interest rates for five times and deposit interest rates for four times. In order to eliminate the potential impact of macroeconomic factors on the enterprise’s market expansion strategy, we add the SHIBOR (Shanghai interbank offered rate) as the control variable and re estimated formula 2, shown in column (3) of We also try to eliminate the interference of other factors on causal identification in this paper. We consider such a situation: the market expansion strategy of high pollution enterprises is different from that of non-high pollution enterprises. This difference may not be brought about by the green credit policy, but an inevitable choice in the process of enterprise development. Since it is mainly up to the management to decide whether the company will carry out an aggressive market expansion strategy, we use the PSM-DID to try to match individuals similar to the management indicators of high polluting enterprises in non-high polluting enterprises as the control group, and then conduct did test. The regression results are listed in column (4) of The above results show that the promulgation of green credit policy can effectively inhibit the market expansion strategy of high pollution enterprises. What is the specific mechanism of this inhibition? The previous analysis shows that the green credit policy will increase the financing cost of high polluting enterprises and encourage enterprises to carry out emission reduction R & D, so as to reduce the aggressive market expansion strategy in the short term. These two mechanisms will be tested separately below.Similar to Peng et al. , we beliPollute × Policy to cost is significantly positive, which shows that the promulgation of Green Credit Guidelines increases the financial cost of high polluting enterprises.We first measure the financial cost of an enterprise by the ratio of its financial expenses to its operating income. We test whether the promulgation of Green Credit Guidelines increases the external financing cost of high polluting enterprises according to formula 3. The regression results are listed in column 1 of Corporate strategy can be regarded as the rational choice or reasonable action of the company to create earnings for shareholders in the uncertain market environment. Enterprises with high cash flow and low financing constraints are more likely to adopt aggressive market expansion. The promulgation of the Green Credit Guidelines, an exogenous shock, increases the financing difficulty and cost of high-polluting companies. The Guidelines undoubtedly has a greater impact on these companies with more aggressive market expansion. The impact of this guide on companies with defensive market expansion propensity may be smaller or even insignificant. Therefore, we divided the sample into sub-samples according to the level of cash flow and the level of KZ index and re-regressed Formula 2.We use the ratio of cash flow generated from operating activities to total assets to measure the size of corporate cash flow. According to whether the size of the company’s cash flow is higher than the median of the same industry in the same year, the sample is divided into two sub-samples of high cash flow and low cash flow. The regression results are listed in columns (2) to (3) of The calculation method of the KZ indicator is based on Kaplan and Zingales : calculaFrom the regression results, we can see that the promulgation of Green Credit Guidelines significantly inhibits the market expansion tendency of enterprises with high cash flow level and low KZ index, making these companies more conservative in their strategic choices. However, the impact on enterprises with low cash flow holding level and high financing constraints is not significant. This may be related to the defensive market expansion strategy adopted by these enterprises.The theoretical analysis, the R & D innovation is sustainable in the enterprises with strong R & D capability. Due to the limited innovation resources, the R & D investment is uncertain in enterprises with weak R & D ability, these enterprises’ R & D investment is often related to the subsidy policy and the financial situation of the enterprises themselves , 36. TheOn the other hand, both increasing R & D innovation and rapidly expanding the market need financial support. Therefore, enterprises that prefer R & D innovation strategy will appropriately reduce their market expansion tendency to ensure sufficient funds to support R & D. In other words, Green Credit Guidelines have a more significant inhibitory effect on the market expansion strategy of enterprises with strong R & D ability.Based on the above two analysis, we divide enterprises into two sub samples with strong R & D capability and weak R & D capability, and re estimate formula 2. We believe that the amount of R & D investment can measure the R & D capacity of enterprises to a certain extent. Therefore, the R & D capacity is measured by the proportion of intangible assets in total assets and the proportion of R & D expenses in total costs. Column (1) of From the regression results, we can see that the promulgation of Green Credit Guidelines significantly inhibits the market expansion tendency of high polluting enterprises with strong R & D and innovation ability. This shows that the green credit policy has stimulated high polluting enterprises to further increase investment in green innovation. Hypothesis 3 holds.We can also see from In addition, in After the global financial crisis, the $4 trillion stimulus plan led state-owned enterprises to obtain more credit resources than non-state-owned enterprises, exacerbated the difference in resource availability between state-owned enterprises and non-state-owned enterprises . In addiThe promulgation of green credit guidelines is bad for high polluting enterprises. The Guides declare China’s determination to achieve high-quality and sustainable economic development in the future. Therefore, the Guides will increase the managements’ performance pressure of high pollution enterprises. In order to cope with the pressure of market performance and avoid the loss of potential shareholders’ wealth, the management of enterprises with equity incentive may sacrifice some long-term projects , 49 in eROA) and return on equity (ROE). We measure corporate risk by ROE’s volatility (roe_sd) and stock price collapse risk (Ncskew). ROE’s volatility (roe_sd) is the rolling standard deviation of the company’s ROE over three years. Referring to the research of Hutton et al. [Ncskew). First, we calculate the idiosyncratic weekly stock return adjusted by the market return εi,t, according to formula 5. ri,t is the reinvestment return of company i in week t, and rm,t is the weighted average market return of all A-share companies in week t. The residual term εi,t is a unique rate of return that cannot be explained by the market rate of return in time t. Wi,t = ln. Then, we calculate Wi,t, and construct the index Ncskew to measure the risk of stock price collapse according to formula 6. The regression results of the Green Credit Guidelines on economic effects are shown in This paper further examines the economic effects of Green Credit Guidelines on corporate value from three aspects: corporate image, profitability and risk. The regression model is formula 4. We measure the corporate image by negative media sentiment (NEG) and the average earnings per share predicted by analysts (FEPS). Negative media sentiment (NEG) is the ratio between the number of negative financial news and the total amount of financial news of the company in that year. We measure the profitability of the company by return on total assets  and (4) of roe_sd or Ncskew, the impact of the Guidelines on the risk is not significant, as shown in column (5) and (6) of The promulgation of Green Credit Guidelines do not increase the risk of high polluting enterprises. Whether the risk is measured by Based on the quasi-natural experiment of the promulgation of China’s Green Credit Guidelines, we empirically investigate the impact of market-oriented environmental regulation on the choice of company’s market expansion strategy, taking A-share listed companies from 2008 to 2015 as a sample. The results show that the promulgation of Green Credit Guidelines improves the financing constraints of high polluting enterprises, encourages high polluting enterprises to increase the R & D of green projects, and then promotes the company’s market expansion strategy to defensive. Further, the effect of the Green Credit Guidelines on firm’s market expansion strategy is more prominent if the firm is non-SOE or without equity incentive. We also show that although the promulgation of the Green Credit Guidelines reduced the profits of highly polluting enterprises, it does not increase their risk of stock price collapse. In sum, we conclude that the Green Credit Guidelines are market based environmental regulations in line with Porter’s hypothesis. This paper reveals the internal relationship between Green Credit Guidelines and corporate behavior from a deeper level, and supplements literatures about the economic effects of market-oriented environmental regulation and corporate strategic management. It provides an academic basis for governments to steadily and effectively promote environmental protection policies.This study also has some policy implications. First, regulators should actively promote market-oriented environmental regulation. Market-oriented environmental regulation is conducive to promote enterprises to increase the R & D of green projects, protect the environment and achieve sustainable development; It is also conducive to restrict the overly radical business decisions of high pollution enterprises and prevent the occurrence of systemic financial risks. Second, the company’s management should give more consideration to social responsibility and national strategy when deciding the company’s strategy, which will help the company better expand its living space and grasp development opportunities. According to the research conclusion of this paper, if the management does not consider sustainable development and environmental protection when formulating the company’s strategy, it may artificially create obstacles to the survival and development of the company. On the contrary, it will help the management to resolve business risks and ensure the sustainable development of the company. We suggest continued future research on how the green credit policy affects other strategic choices of enterprises, such as talent strategy, M & A strategy or integration strategy, to comprehensively identify green credit policy’s impacts on the transformation of highly polluting enterprises.In the future, we can continue to study whether the Green Credit Guidelines will have an impact on other strategic choices of highly polluting enterprises, such as diversification strategy and market penetration strategy.S1 File(DOCX)Click here for additional data file.


The inversion of the uterus is a rare complication of the puerperium and much rarer during the non-puerperal period. The most common cause of non-puerperal inversion is a submucosa leiomyoma; however, identification can be difficult. Herein, we present a case of pedunculated uterine leiomyoma that causes uterus inversion in a 30-year-old virgin woman with a correct diagnosis; a hysterectomy was prevented for the patient. Uterine leiomyoma (UL) is the most common benign tumor of the female genital tract and has become a major health problem . UL occuUL can have many side effects such as dyspareunia , increasOur case report describes a 30-year-old virgin woman presented at the emergency room of Fatemieh Hospital with vaginal bleeding and a protrusion of a mass from the vagina. The patient had a history of severe bleeding in the form of hypermenorrhea, which had intensified the day before the emergency room visit and also felt a feeling of pressure in the perineum and a mass coming out of the vagina. The patient was conscious during the physical examination.The physical examination revealed a body temperature of 37 °C, a heart rate (HR) of 105 beats per minute, a respiratory rate (RR) of 18 beats per minute, and a blood pressure (BP) of 90/60 mmHg. Pelvic examination revealed the presence of a large mass measuring 6-7 cm in diameter with a necrotic appearance and protruding from the cervix and vagina. Necessary tests were requested for the patient . Due to The vagina was examined in the OR after induction of anesthesia. Due to the abnormal thickness and excessive size of the UL pedicel, the UI was suspected following the protruding of the UL from the vagina, so the patient was asked for an ultrasound. Abdominal ultrasound of the uterus in the pelvic cavity was not observed and the diagnosis of UI was confirmed Figures .Therefore, myomectomy was performed carefully from the fundus level for the patient, and samples were sent for pathological examination . The endThe uterus was returned to the cervix and pelvis, and then the uterine suspension was performed to prevent UI to the round ligament Figures . The abdUI are classified into two groups, including (a) puerperal and (b) non-puerperal inversions . Non-pueThe etiology of UI is not well understood. A thin uterine wall, rapid tumor growth, tumor size, fundic localization of the tumor, tumor attachment to the uterine wall with a thin pedicle, dilatation of the cervix due to uterine cavity distension, and quick expulsion of the tumor are all possible factors . Most noImaging techniques such as ultrasound and magnetic resonance imaging (MRI) help with the diagnosis. However, the diagnostic value of transvaginal ultrasound is limited, especially in cases where large mass protrude into the vagina, because of physical limitations; the probe cannot be inserted into a choked vaginal canal; another issue is that ultrasonic beams could not be transferred beyond the mass, resulting in low-quality sonographic images . TherefoReposition procedures, according to the reproductive desire of the patient, or hysterectomy could be considered for surgical treatment . In our


Surface mount technology (SMT) plays an important role in integrated circuits, but due to thermal stress alternation caused by temperature cycling, it tends to have thermo-mechanical reliability problems. At the same time, considering the environmental and health problems of lead (Pb)-based solders, the electronics industry has turned to lead-free solders, such as ternary alloy Sn-3Ag-0.5Cu (SAC305). As lead-free solders exhibit visco-plastic mechanical properties significantly affected by temperature, their thermo-mechanical reliability has received considerable attention. In this study, the interface delamination of an SMT solder joint using a SAC305 alloy under temperature cycling has been analyzed by the nonlinear finite element method. The results indicate that the highest contact pressure at the four corners of the termination/solder horizontal interface means that delamination is most likely to occur, followed by the y-direction side region of the solder/land interface and the top arc region of the termination/solder vertical interface. It should be noted that in order to keep the shape of the solder joint in the finite element model consistent with the actual situation after the reflow process, a minimum energy-based morphology evolution method has been incorporated into the established finite element model. Eventually, an Improved Efficient Global Optimization (IEGO) method was used to optimize the geometry of the SMT solder joint in order to reduce the contact pressure at critical points and critical regions. The optimization result shows that the contact pressure at the critical points and at the critical regions decreases significantly, which also means that the probability of thermal-induced delamination decreases. Electronic packaging technology not only defines the electrical signal and power path from the chip to the system but also plays the role of mechanical protection for IC components, which improves the environmental adaptability level of the circuit and guarantees continuous high performance. Surface Mount Technology (SMT) is the main form of board-level packaging. Compared with through-hole technology, the packaging size of SMT is greatly reduced, the operation is convenient, the reliability is high, and the installation wiring of the printed circuit board (PCB) is more convenient. It may contain dozens or even thousands of SMT solder joints on a complete board-level package circuit. The shape of SMT solder joints is affected by the pin shape of electronic components. There are many forms of pins, such as gull-wing pin, J pin, I pin and pin-less, as shown in However, electronic products are often in a complex service environment, such as high temperature, low temperature, high humidity, dust, vibration, salt mist and many other adverse environmental effects. When any of the solder joints in the circuit fails, it may cause the circuit to break down, causing the system to crash or the unstable connection of components to fall off. The main failure modes of solder joints are fatigue, creep, brittle fracture and plastic deformation, etc., but all of them are presented on the surface or inside of the solder joints in the form of interface delamination or crack. At present, crack failure analysis of solder joints is mainly carried out by the finite element method or experiments. Xiaoyan Li and Fenghui Li have studied the growth behavior of intermetallic compounds (IMC) in SAC305 solder joints and Cu lands during reflow and isothermal aging. During reflow, the grain size of Cu6Sn5 coarsens rapidly . During The geometric model of SMT solder joints is greatly simplified. The reliability of SMT solder joints depends heavily on their geometry. SMT solder joints are often small in size. A tiny change in the solder joint morphology can lead to different simulation results.Most finite element analysis is assumed to be a plane stress or plane strain problem. The reliability analysis of SMT solder joints is inherently a three-dimensional problem. However, most current studies simplify the problem as a two-dimensional problem, which makes the analysis of the solder joint unreliable.An effective geometric shape optimization process is missing in the solder joint morphology design stage. Some existing studies use the Taguchi method to explore the optimal combination of geometric parameters ,12,13. HAlthough the finite element software can simulate the stress and strain fields of SMT solder joints more accurately and conveniently, the FEA should simulate the actual situation as much as possible. From the existing research, there are the following main problems in the FEA of interface delamination or crack of SMT solder joints:To solve these problems, this paper has established the SMT solder joint model based on the minimum energy, which considers the constraints of external force, gravity and liquid tension when the solder alloy melts into a liquid state, and causes the model to possess the actual shape of the solder joint after the reflow process. It makes up for the imprecise solution caused by the large gap between the traditional simplified model and the actual solder joint shape. At the same time, a three-dimensional finite element (FE) model is established by using the Cohesion Zone Model (CZM), and CZM is used to solve the contact pressure between solder joint and termination, solder joint and land, so as to characterize the delamination trend of the solder joint interface. Finally, an Improved Efficient Global Optimization (IEGO) algorithm is presented, which is an adaptive global optimization algorithm based on the Kriging surrogate model. However, it has the advantage of invoking less expensive calculation times than traditional numerical optimization algorithms. Meanwhile, the improved infill criterion and convergence criterion make the algorithm more resistant to local optimals and converge faster. The framework of this paper is shown in An unknown crack propagation path requires the crack initiation force and crack propagation angle to be calculated by the crack propagation criterion.For a known crack propagation path, only relevant criteria are needed to determine the initiation force.In traditional fracture mechanics theory, for linear elastic materials, the critical strength factor and critical energy release rate are taken as the basis for crack initiation. For nonlinear elastomers, the path-independent J-integral is used as the basis for crack initiation . There aThe CZM is the main method used to study the second type of problem . It avoiThe interaction between microscopic particles within a material is the essence of cohesion . The cohDue to the different properties of materials, the tension–displacement relationship of cohesion elements varies, resulting in a variety of cohesive zone laws, which mainly belong to exponential, trapezoid and bilinear cohesive zone models. Bilinear CZM is used in this paper because of its stability and practicability .The area enclosed by the OAC curve is equal to the rate of energy release from the interface delamination, also known as the critical rate of energy release. When the curve changes from OA to OB, the quantity of delamination at the interface can be accumulated. The maximum subsequent tension can continue to delaminate the interface by only reaching the vertical coordinate of point B, without reaching the maximum tension at point A. The subsequent tension–displacement curve will be enclosed by a straight OB with a smaller slope and a straight BC.The governing equation for the bilinear CZM is as follows:The normal and tangential critical energy release rates in the CZM are The geometry of the solder is constrained by external forces, self-gravity, and liquid tension when it is in a melting liquid state. In order to keep the shape stable during the reflow process, the liquid solder will continuously evolve to the lowest energy state until the total energy is lowest; that is, when the energy of the solder system is lowest, the liquid solder will reach the static balance state. Compared with other mathematical analysis models, the minimum energy method can be used for more diverse, complex, and accurate analysis of solder shaping.http://facstaff.susqu.edu/brakke/evolver/evolver.html, accessed on 16 May 2022) developed by Professor Kenneth. A. Brakke to solve the SMT solder joint shape , y = , and then skip Step 3;Step 11: Output the optimal solution and the true value.This paper uses two benchmark functions, Michalewicz a,b and AFor the Michalewicz function, both the traditional EGO algorithm and the IEGO algorithm have found the global optimal. However, since the Michalewicz function is multimodal and has several local minima, the iteration curve of the algorithm shows that the traditional EGO algorithm has been trapped in the local minima several times and hovered in it, resulting in a very slow convergence rate until the 70th iteration reaches the global optimal c. In conAs mentioned in From the above numerical examples, it can be seen that the IEGO method proposed in this paper has the advantages of fast optimization speed and strong global optimization ability compared with the traditional EGO algorithm.SMT solder joints are easy to be delaminated between pins and lands of components under the thermal load in a service environment. The shape of solder joints has a significant and complex effect on the interface delamination. Therefore, the optimum variables in this paper are the height of solder joints Therefore, the target of optimization is not only the contact pressure Based on the IEGO algorithm proposed in this paper, the above optimization model is solved, and the contact pressure values of each node and critical region in the optimization model are obtained by the high-cost FEA described above. The optimum geometric parameters of the solder joint are shown in The FE model for SMT packaging has been established, in which the geometry of the solder joint was generated based on the minimum energy method, so the geometry and energy constraints in the actual process were considered to make it more conform to the actual shape after reflow. Secondly, the distribution of contact pressure at the solder interface under TC load is analyzed. Due to the different CTE between materials, the maximum contact pressure occurs in the top arc region at interface 1, the corner region at interface 2, and the y-direction side region at interface 3, which means that these regions are prone to interface delamination under TC load. After that, an improved algorithm (IEGO) is presented, which is an adaptive optimization method based on the surrogate model. The benchmark functions prove the superiority of the improved algorithm. The improved algorithm is used to optimize the contact pressure of critical regions  between solder interfaces. The optimal combination of parameters after optimization is


In order to solve the problem of inconsistent state estimation when multiple autonomous underwater vehicles (AUVs) are co-located, this paper proposes a method of multi-AUV co-location based on the consistent extended Kalman filter (EKF). Firstly, the dynamic model of cooperative positioning system follower AUV under two leaders alternately transmitting navigation information is established. Secondly, the observability of the standard linearization estimator based on the lead-follower multi-AUV cooperative positioning system is analyzed by comparing the subspace of the observable matrix of state estimation with that of an ideal observable matrix, it can be concluded that the estimation of state by standard EKF is inconsistent. Finally, aiming at the problem of inconsistent state estimation, a consistent EKF multi-AUV cooperative localization algorithm is designed. The algorithm corrects the linearized measurement values in the Jacobian matrix for cooperative positioning, ensuring that the linearized estimator can obtain accurate measurement values. The positioning results of the follower AUV under dead reckoning, standard EKF, and consistent EKF algorithms are simulated, analyzed, and compared with the real trajectory of the following AUV. The simulation results show that the follower AUV with a consistent EKF algorithm can keep synchronization with the leader AUV more stably. Due to the attenuation of underwater GPS signals and the complex marine environment, it is a challenge for autonomous underwater vehicles (AUV) to obtain high positioning accuracy . TraditiMany multi-AUV (or robot) cooperative localization algorithms have been proposed and successfully implemented in the literature, including standard-based extended Kalman filter (EKF) , particlUnderwater acoustic communication between AUVs is always limited by large delay and low bandwidth. Many kinds of research on homogeneous multi-robots, such as Huang’s work, are not suitable for underwater scenes. The lead-follower multi-AUV cooperative positioning discussed in this paper is less limited by underwater acoustic communication and more suitable for the underwater environments. Based on observability analysis, the measurement Jacobian matrix is obtained under the constraint of relative position. A consistent linearization estimator is designed for cooperative localization. If the motion conditions and alternating communication means are met in this paper, the proposed state estimator can also be applied to cooperative navigation in other situations, such as unmanned aerial vehicles and robots.To sum up, the main contributions of this work are as follows.(1)In this paper, the cooperative localization of heterogeneous AUVs based on underwater acoustic communication is studied. In order to improve the positioning accuracy of the follower AUV, the follower AUV can only alternately obtain the relative range measurement values with the two leading AUVs through OWTT, thus reducing the complexity of acoustic communication. This can result not only in better observability than the single leader with the same communication load, but also in avoiding changing the formation frequently. In addition, the research results can be easily extended to any number of AUV teams and the acoustic communication load will not increase.(2)According to different distance measurement information, the observability matrix of the whole system is decomposed into two independent parts. The whole positioning system is observable, two state estimation and decomposition subsystems related to a single leader are observable, and two ideal decomposition subsystems related to a single leader are not observable. As the rank of observability matrix of decomposition subsystem calculated by standard linearization estimator (such as EKF) is larger than that calculated by the ideal state value, it will lead to inconsistent estimation of the position state of follower AUV.(3)In order to improve the consistency of state estimation, this paper designs a consistent EKF algorithm for multi-AUV cooperative positioning. As the ideal state value cannot be used to calculate the Jacobian matrix, in order to improve the consistency of the standard linearization estimator, the algorithm uses the designed initial zero space vector related to the relative position to construct the constrain conditions of each recursive time step, and then obtain the modified measurement Jacobian matrix under the constraint conditions and prove that the state propagation Jacobian matrix is not affected by the initial zero-space vector.The rest of this paper is organized as follows. 1 starts broadcasting its position at 2 starts broadcasting its position at In this multi-AUV cooperative positioning system, all AUV clocks are synchronized before transmission, as shown in roadcast . As one k is As the actual depth information can be directly measured by the pressure sensor in real-time, the depth does not need to be considered in the system equations and the practical working environment of an AUV can be simplified to a two-dimensional (2D) space . In the Equation  is the Ak can then be expressed via the kinematic Equation  to updaUsing Equations  and 10)10), the Traditionally, system observability is determined by whether the state of a system can be determined from the output (and input) measurements. If the initial state of a system can be uniquely determined for any time in a finite interval, the system is observable, otherwise it is not observable . Thus, iA local observability matrix  can be aThis article will be in the time interval i only. This demonstrates the measurement information of submatrices As such, it is not difficult to determine the submatrices quations  and 8),,O^1 and In the case that the leader AUV remains to maneuver, the control input of the vehicle Equation  and 15)υk≠0. We Equation  to rearrFurthermore, we define ed using  and 17)δp^s=p^s−d using T0H^i,kF^k−tituting  at the sTherefore, the observability matrix Next, the observability of the cooperative position system is analyzed using the ideal state value instead of the estimated value, in this description:By substituting Equation  into EquIts corresponding determinant matrix becomes:i and follower AUVs [By substituting Equations  and 24)24) into wer AUVs . At thisNote: In a large underwater task region, requiring all AUVs to maintain a constant motion formation along the same linear direction is an effective planning strategy to ensure full-region coverage. In addition, due to the sea water resistance, frequently changing the motion formation of AUVs will accelerate energy consumption and require additional time.In comparing the rank expressions  and 25)25), it ir errors . To solvIn practice, it is impossible to acquire ideal state values with noise and errors in the measurement system. As such, we cannot calculate Jacobian matrices using ideal state values, as opposed to the latest state estimate values in a standard linearized estimator. Thus, in this paper, by modifying the state transition matrix and measuring the Jacobian matrix, the observability matching between the actual linearized system and the real system is ensured.To ensure that the rank of the observability matrices is consistent with that of the real state value when calculating the state transition matrix and measuring jacobian matrix with the state estimate value, the observability constraint ull rank ,21. ThisAccording to the constraint expressions  and 27)27) descrWith the definitions provided in , the conIn computing each covariance prediction , we mustFrom this relationship (Equation ), the foWe can further determine:Finally, the constraint expression In expressions  and 35)35), we kquation  systems. The depth information of the follower AUV can be obtained by using the depth sensor, and its projection on the leader AUV can be calculated using the Pythagorean theorem in 3D systems. This method turns a 3D system into a 2D system. Therefore, a similar analytic method can still be applied in the design of consistent estimators for 3D linearized systems.In this section, a series of simulation results will be given to illustrate the effectiveness of the proposed algorithm. In this paper, it is assumed that follower AUV can alternately obtain the distance between two leader AUVs. As acoustic signals cannot carry too much information, it is necessary to minimize the communication frequency under the premise of a stable system. In , the comLocalization results from three different algorithms  are presented to assess the performance of the proposed consistent EKF algorithm and provide a comparison with the true follower AUV trajectory shown in To further demonstrate the advantages of the proposed consistent EKF algorithm, the root-mean-square-error (RMSE) was calculated for two different localization algorithms. The position and heading of the follower AUV at k time RMSE was determined using 100 Monte Carlo simulations:Through the comparison of The normalized estimation error squared (NEES) is the most common criterion for evaluating the consistency of state estimators for dynamic systems. Specifically, the NEES of an N-dimensional Gaussian random variable follows a  freedom . If the In this paper, the observability of cooperative positioning system based on two leaders that broadcast their position information alternately and a consistent EKF multi-AUV cooperative positioning algorithm is proposed. Observability analysis results show that the standard EKF has the problem of obtaining forged measurement information along the unobservable direction, which leads to inconsistent state estimation. The algorithm proposed in this paper adds the zero-space vector as the observability constraint, which improves the consistency of the cooperative positioning system. Simulation results show that the NEES expected values of position and heading angle estimations are 4 m and 1.015 rad, respectively, when using the EKF algorithm, and close to 2 m and 1 rad, respectively, when using the consistent EKF algorithm. Therefore, the consistent EKF algorithm obtained the NEES expected values closer to the real expected values, and its estimated performance is better than the EKF algorithm. Moreover, the consistent EKF algorithm improves the positioning accuracy of the follower AUV, keeps the follower AUV synchronized with the leader AUV, and then keeps the formation in the process of travelling. At present, we have completed the simulation of the algorithm, and some experiments will be carried out in the future. In the future research, we will try to improve the robustness of the system by reducing the communication frequency. We will also study the practical implementation problems in real world applications, such as scanning the seabed with a group of AUV, expanding the working scope and improving the working efficiency.


Since Easterlin pointed out that economic growth in nations does not guarantee increasing happiness for the average citizen, the underlying reason has remained controversial. The present study focuses on income inequality to explain the “Easterlin Paradox,” ignoring the permanent inequality that long-term wealth accumulation brings. Based on social comparison theory, the literature aims to determine how wealth inequality, which accompanies economic growth, diminishes one’s happiness . Specifically, we conduct this study in which we split the wealth inequality into the upward wealth inequality and the downward wealth inequality as measures of upward comparison and downward comparison, respectively. The upward wealth inequality measures the average gap between one and the better-off in wealth while the downward wealth inequality measures the average gap between one and the worse-off in wealth. Furthermore, the heterogeneity of the area of respondent is analyzed and the family life cycle is tested as a moderator. The main findings of the paper are as follows: (1) The empirical test results of hypothesis 1 indicate that the upward wealth inequality aversion  is stronger than the downward wealth inequality inclination . It is due to the psychological preference: loss aversion. As an increase in upward distance implies a loss in relative status and an increase in downward distance implies a gain in relative status, people focus more on loss rather than gain. (2) The empirical test results of hypothesis 2 indicate that residents who live in rural areas do not have a proud effect as much as those who live in urban areas. There is a huge urban-rural wealth gap in China. With the expansion of the social network, people living in rural areas realize that even he is almost the rich in rural areas but still the lower classes in the whole society. It is hard for rural residents to have a proud effect. (3) The empirical test results of hypothesis 3 indicate that family members have the strongest upward inequality aversion in the middle-stage phase of the life cycle (when the family head is approximately 50). During the family life cycle, inequality aversion will be different in different life stages due to the changes in economic status expectations. At the beginning of the family life cycle, family members assume their life has limitless possibilities, and they have high expectations for the future. Logically, they can be easily satisfied by achieving a little more than their peers. In later periods, with increasing age, the members will pay more attention to health instead of wealth. The results shed light on how macroeconomics influence changes in individual psychology. There is a long history of debating the causes of “Easterlin Paradox”. The “Easterlin Paradox” suggests that a positive relationship between inequality and happiness does not exist . The preThe second line of the research explains the social comparison that arises with inequality. Based on social comparison theory , one’s rThe social comparison theory categorized the horizontal social comparison into the upward horizontal social comparison and downward horizontal social comparison . Upward In the field of happiness research, happiness varies with age in U-shape has been proved by a lot of papers . Stone eThe existing literature usually focuses on income inequality’s effect on subjective well-being. However, income inequality is more likely to be transitory than permanent. Permanent inequality could lead to a more marked reduction in happiness than transitory wealth inequality. Since household wealth returns tend to be strongly persistent , it is eBased on the literature reviewed, we next propose three hypotheses: hypothesis 1: wealth inequality would have a significant effect on happiness; hypothesis 2: the effect of wealth inequality on happiness would exhibit urban-rural heterogeneity; hypothesis 3: wealth inequality would affect happiness differently in different family life stages.We contribute to the existing literature by examining the link between split wealth inequality and happiness. Based on the social comparison theory, the Gini index are decomposed into the upward wealth inequality and the downward wealth inequality, and the indexes measures the different economic gap when families compare with different target. The perceived wealth distance for families with both the better-off and the worse-off helps them to complete self-evaluation and social comparison. The wealth Gini coefficient measures the regional inequality and can be defined as the average value across families of personal inequality index in this region. The decomposing wealth Gini coefficient into upward wealth inequality and downward wealth inequality enables us to decompose the regional wealth inequality into personal wealth gap including the average gap between one and the better-off, or worse-off. The upward wealth inequality represents deprivation with respect to being better off while the downward wealth inequality represents advantage with respect to being worse off. The regression of upward wealth inequality and downward wealth inequality makes it possible to capture the families’ affections, respectively. It turns out the upward wealth inequality aversion  is stronger than downward wealth inequality inclination  in general. The remainder of the paper evaluates the inequality aversion model based on a large dataset, verifies the moderating effects of the life cycle and examines the urban-rural heterogeneity of baseline regression. It shows family members have the strongest upward inequality aversion in the middle-stage phase of the life cycle.In the empirical test of hypothesis 1, we examine the effect of wealth inequality on happiness and how the preference for inequality driven by the status between the self and relevant others can lead to two opposite effects. The Gini index measures the total inequality effect but is unable to capture the upward wealth inequality and the downward wealth inequality. Hence, we further divide the wealth inequality into upward relative concern and downward relative concern based on the social comparison thesis. Then, we examine the relationship between relative concern in different directions and happiness. In fact, the upward wealth inequality measures the distance gap between one and one’s richer peers. The “keeping up with the Joneses” effect implies that the larger the relative gap between one and one’s richer peers is, the unhappier one is. The effect of an increase in the wealth of one’s richer peers on one’s happiness is negative since one will envy them .Data that support the empirical analysis come from the China Household Finance Survey (CHFS) conducted by the Southwestern University of Finance and Economics in China. The survey has been conducted every two years since 2011. Since the 2011 sample is the beta version and the 2013 sample have less respondents, we use the sample included in 2015 and 2017. The total sample combines of 2015 and 2017 has 52,348 individuals. All households are randomly selected from 29 provinces in China. From 2015 to 2017, the survey covers 1,396 and 1,428 municipalities nationwide respectively, which is a representative sample of China. We merge the household sample and individual sample to track the fixed households and create cross-sectional data with 2015 and 2017 sample.The data include family assets, happiness, and sociodemographic characteristics. Thus, the data allow us to further include economic characteristics that significantly explain happiness.Happiness is defined as a subjective evaluation of one’s life-as-a-whole. The variable happiness is extracted from the following question: “In general, do you feel like happy now?”. The answers are classified as (1) Very unhappy, (2) Unhappy, (3) Generally, (4) Happy, and (5) Very happy. Happiness is rated by the respondent on a five-point rating scale. We construct a five-point scale  to measure happiness. In this paper, we concentrate on the family, thus, the family head’s happiness is representative of the family’s happiness since the family head is usually the sole decider and emotion can be contagious inside the family.In this paper, we concentrate on inequality that increases permanent inequality. We use wealth inequality to capture permanent inequality since it is relatively stable. Based on social comparison as a consistent psychological phenomenon, we attempt to explain how permanent inequality affects happiness.The wealth Gini coefficient of the population is used to compare wealth inequality across populations. In fact, it can be interpreted as the mean of personal inequality. However, the Gini coefficient is a measure of the wealth distribution of a region’s household, and it uses the sum of all pairwise absolute wealth differences.y_i and y_j is the wealth of household i and j respectively, n > 1, and y1≤y2≤⋯≤yn.where Thus, even though the Gini coefficient is a widely used index for inequality, it cannot be used as the basis for individual or household inequality. To focus on the relationship between household happiness and the inequality among families, we measure inequality at the household level. We regard household inequality from a “top down” or “bottom up” perspective.Based on the easily overlooked fact that the Gini coefficient is the mean value across the household of a particular region:G_i is the average absolute difference between household i and peers in their reference group:where G_i can be rewritten as:y_i and y_i. Excluding household i, G_i can be split into the upward wealth inequality and the downward wealth inequality.Where The upward wealth inequality represents deprivation with respect to being better off. The incessant perception of relative deprivation and positional concern can be a source of envy in the reference group . FeelingWe consider the relevant variables that influence family happiness. Those variables include both demographic characteristics of the family head and family, such as age of the family head, education of the family head, marital status of the family head, gender of the family head, work status of the family head, youth ratio, elderly ratio, pension of family members, family size, average education level of the family and whether they have their own houses. These variables reflect the economic and demographic situation of the family head and family. All variables used in this study are summarized in The similarity criterion for social influence shows that individuals are most influenced by others who are similar. Considering the geographical factor, the basic premise of our model is a reference group with which one is most likely to compare. We established a reference group comprising individuals in the same community.We assume the relative wealth hypothesis that the family cares about the relative wealth level as well as absolute wealth itself.happinessij is latent happiness of household i in community j, wealthij is wealth of household i in community j, gini_j is the Gini index in community j, upij is the upward wealth inequality of household i in community j, downij is the downward wealth inequality of household i in community j, Xij is the vector of control variables, εij is error item follows normal distribution.Where happinessij will be determined based on the latent variable The measurements of happiness, as noted above, are five discrete responses. The discrete variable is difficult to capture the subtle different within the same category since five categories capture a latent continuum. The observed variable happiness We cannot observe the actual level of family happiness, which lies in an ordered categorical range. Some researchers tend to use the ordered response model instead of the ordinary linear model to specify the distribution of the latent variable and avoid arbitrariness of the ordinal scale. Although happiness is always measured as a discrete variable in the survey, sometimes, a continuous latent variable is postulated, which is mapped onto the discrete measurement.Most studies measure happiness using an ordered model rather than ordinary linear square regression (OLS regression). However, p < 0.001), which means that one standard increase in the Gini index in the surroundings decreases the proportion of people reporting themselves as “Very happy” by 0.20 percentage points. Overall, permanent inequality is negatively related to happiness, which means that the persistent gap between people upsets them. To clarify the mechanism of comparison-driven inequality aversion, we decompose the wealth Gini index into the upward wealth inequality and the downward wealth inequality.The regression starts by taking the total effect of wealth inequality into account. The model in p < 0.001), while downward inequality has the opposite effect .The results show an aversion to the upward wealth inequality and an inclination to the downward wealth inequality. However, the two components that the Gini index decomposes display asymmetry: the upward wealth inequality has a greater impact on happiness than the downward wealth inequality does. This trend mirrors people’s psychological preferences, as they would tend to focus on the increases among the rich and neglect decreases among the poor .The inequality aversion mainly comes from the upward wealth inequality, rather than the downward wealth inequality. The empirical results show that a persistent upward distance makes one feel worse and that a persistent downward distance makes one feel better. Compared to the result in temporary advantage that Like many developing countries, the urban-oriented policies in China have contributed to the increasing urban-rural inequality. In particular, there are many aspects that contribute to it: governmental regulation of the price of agricultural products; the segmentation of urban and rural markets; and superior social welfare and social security of city residents. Given the dual-track of urban-rural structure, the residence could affect people’s affection towards wealth inequality.p < 0.001) and rural areas . the downward wealth inequality still decreases happiness significantly among families living in urban areas  as the baseline, but for families living in rural areas, the downward wealth inequality does not have a significant impact on happiness.Based on Equations 7, 8, Considering the dual-track of urban-rural development, the influence of wealth inequality on happiness is next analyzed by the residence of families. The sample is categorized into two: families live in urban areas and families live in rural areas. As shown in With the expansion of the social networks, people can easily obtain the information of others living far away. The huge urban-rural wealth gap caused by house price, labor market return, industrial structure, etc. is apparent. People come to realize that even he is almost the rich in rural areas but still has the lower classes in the overall society. This situation could deter them from being satisfied with their tiny achievement that they are richer in rural areas. Residents in rural area do not perceive the opportunity to narrow the gap to ascend in the social scale, which leads them to manifest non-significant pride for themselves.We further explore the effects of the life cycle on the relationship between wealth inequality and happiness. Since the family head is representative of the family, the family head’ age could reflect the life stage of the family. Then, we explore whether the family life cycle generates a moderating effect on the relationship between wealth inequality and happiness. A lot of literature has shown that in different life stages, the state of mind is different. Some researches prove that the relationship between age and happiness exhibits a U-shaped curve . People’Since the family is a complete economic unit in society, the evolution of the family has been studied. Based on the baseline Equations 7, 8, we consider the moderating effect of the family life cycle. Moderation is typically tested through regression analysis.happinessij is latent happiness of household i in community j, wealthij is wealth of household i in community j, gini_j is the Gini index in community j, upij is the upward wealth inequality of household i in community j, downij is the downward wealth inequality of household i in community j, test of the coefficient on ginij×hageij and upij×hageij is used to infer moderating effect., Xij is the vector of control variables, εij is error item follows normal distribution.where the Where ginij×hageij is used to infer moderation.p < 0.1) is more serious, while the younger group shows non-significant inequality aversion. This outcome might be the offset effect of the upward wealth inequality and the downward wealth inequality. We continue to verify how the life cycle could moderate the effect of the upward wealth inequality and the downward wealth inequality to better capture the offset effect in the Gini index.Regarding the life cycle effect of the family, we categorize the sample into two age groups. Empirically, the turning point of the life cycle effect on happiness usually occurs at the age of 50 . The ageupij×hageij is used to infer moderation. The moderation is significantly positive, which implies that wealth inequality can influence happiness under the impact of the family life cycle. In the young-family-head group, the downward wealth inequality increases happiness significantly , whereas in the old-family-head group, the downward wealth inequality does not have a significant impact on happiness. In contrast, in the young-family-head group, upward inequality does not have a significant impact on happiness, whereas in the old-family-head group, upward inequality significantly decreases happiness .upij×hageij to the moderating framework. Considering that people are more concerned with the upward wealth inequality that dominates inequality aversion, we add the interaction term The results show that age 50 is the breakpoint of social comparison; before the family head reaches 50, the downward wealth inequality slightly increases happiness; however, after the family head reaches 50, people neglect the downward wealth inequality and focus more on the upward wealth inequality with increasing age. Furthermore, on two sides of the breakpoint, the life cycle plays different roles in the relationship between wealth inequality and happiness. As the family head approaches 50, upward inequality aversion deteriorates, while it eases as the family head goes older.Overall, upward inequality aversion reaches a peak when the family head is approximately 50, as visualized in The paper starts with the problem of how permanent inequality influences happiness. Then we find that the main driver of inequality aversion comes from the pain of chasing their richer peers and upward social comparison. The upward wealth inequality is characterized by a process whereby the family’s permanent economic distance with the richer ones. The empirical findings from this paper support that inequality aversion comes from social comparison, specifically, it comes from upward social comparison. As shown in the empirical test of hypothesis 2, unlike urban resident, families who live in rural areas do not have significant proud effect. Moreover, the empirical test of hypothesis 3 implies that during the family life cycle, inequality aversion will be different in different life stages due to the changes in economic status expectations.Unlike the temporary inequality aversion, the permanent inequality aversion comes from desire of higher economic status. In the context of rapid urbanization, the urban-rural gap is increasing. Even the rich in rural areas still the lower classes in the whole society, let alone the others. They feel no sense of achievement but the deprivation from the economic growth. China is fairly representative of other developing countries, which are also experiencing rapid economic growth and urbanization. Even though the economy develops, the negative effects of urbanization should also get noticed by the government. The government should take actions like improving the construction of digital finance, transportation and education to enhance the economic situation of rural residents .the effects of moderating of life cycle show the upward wealth inequality aversion weakens across the life span of family, peaking around the middle stage (family head’s age is around 50) of family life span and decreasing from middle stage to older stage. According to our results, the key aspect of correcting for the negative effects of unequal preparation is focusing on wealth inequality within families of the middle-stage phase of the life cycle (family head’s age is around 50). The upward wealth inequality aversion is strongest among those families. It is due to the change of expected age-graded pattern of potential and the extent of the interpersonal contact. The earlier research shows the prospect develops during the life span . From thThe middle-stage targeting policy not only could modify the middle-stage families but also benefit families of all stages, which explains why the promoting equality policy should be targeted at the middle-stage phase of families. The young families could be more anxious about the upward wealth inequality if they observe the middle-stage families still face the severe inequality and they might struggle harder to catch up with the Joneses. The excessive competition of young families harms social welfare. On the contrary, this policy relieves the young families’ inequality aversion by charting a more equal prospect in their later years and it naturally reduces the inequality for older families.This study has several issues that need to be acknowledged. Firstly, we empirically tested the study using cross-sectional data. Secondly, we use the self-reported happiness as the measure of happiness. Nevertheless, the self-reported happiness could be the instant state of mind when the survey holds. Future research can examine the relationship between using daily data, if available, to link the variations in daily happiness to the permanent inequality. It could change easily. Thirdly, this paper chooses the family in the same community as the reference group, however, one possibility is that one’s self-evaluation might more rely on one’s personal past than others . The choOur findings shed light on the pathway by which macroeconomic inequality affects the psychological movement of individuals. Moreover, mental activities may further influence individual economic behavior. The powerful motivator to promote economic status aroused by the upward wealth inequality might increase conspicuous consumption, especially among young people and the poor. When they are lack money, the desire for unrealistic status could easily get them to over-borrowing. Because conspicuous consumption creates a mismatch between the income and spending level for those low-income groups. Conspicuous consumption worsens the upward gap for them. The upward wealth inequality and conspicuous consumption create a vicious cycle. Thereby, both the mechanism of this vicious cycle and other permanent inequality influences that cause people to take extreme a should be taken into consideration by researchers in the future.https://chfs.swufe.edu.cn/.Publicly available datasets were analyzed in this study. The datasets for this study can be found in the Survey and Research Center for China Household Finance, available at: LG and BS codesigned the study. BS interpreted the data. LG drafted the manuscript. ZD analyzed the data. GL, LG, BS, and ZD revised the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.