Price prediction of polyester yarn based on multiple linear regression model.

China's polyester textile industry is one of the notable contributors to national economy. This paper takes polyester yarn, core raw material in polyester textile industry chain, as research object, and deeply explores its price indicators and risk hedging mechanisms through multiple linear regression models and Holt-Winters approaches. It is worth mentioning that with continuous development of digital technology, digital transformation of production lines and warehouses has become an important development feature in various industries. This study also actively complies with this trend, and innovatively incorporates the upstream and downstream production line start-up rates into price prediction model. Through this initiative, we can more comprehensively consider the impact of supply and demand changes on price of polyester yarn, thus making prediction results more closely reflect the actual market situation. This quantitative analysis method undoubtedly provides new ideas for enterprises to better grasp market dynamics in digital era.

The impact of digital transformation of commercial banks on household income: Evidence from China.

Scholars have focused on the digital transformation of commercial banks, yet there remains a lack of systematic and integrative research at the micro-level of household finance. This article uses data from the China Household Finance Survey (CHFS) and the Digital Transformation Index of Chinese Commercial Banks from Peking University. It employs empirical methods such as mechanism analysis and heterogeneity analysis to explore the impact of the digital transformation of commercial banks on household income. The findings indicate that the digital transformation of commercial banks significantly enhances household income. Second, increasing credit availability, fostering the development of digital inclusive finance, enhancing entrepreneurial possibilities, and increasing the purchase of wealth management products are key pathways through which digital transformation affects household income. Third, heterogeneity analysis reveals that the positive effects of digital transformation on household income are more pronounced in the central and western regions, areas with lower financial industry competition, regions with underdeveloped inclusive finance, rural areas, and among low-income families. This study highlights the significant role that the digital transformation of commercial banks plays in enhancing the welfare of the resident sector.

Willingness to pay for sheep traits and their heterogeneous effects on prices: Evidence from primary livestock markets in Ethiopia.

We test the hypothesis whether levels of key traits of sheep heterogeneously affect market prices of sheep in a rural setting. Feasible generalized least squares and (un)conditional quantile regression estimations were made on a dataset of 1153 sheep transactions in two primary small ruminant markets in the Amhara region of Ethiopia. The empirical results show that animal traits affect the observed prices of sheep differently, but only partly explain the sheep price differences. Our results also reveal that in addition to animal traits, the type of buyers and seasonality of sheep marketing cause heterogeneity in the observed prices. These findings imply that targeting the animal traits demanded by the market and access to price information that enables farmers to respond to the seasonal changes in livestock markets are essential to increase the income of sheep keepers.

The impact of port green competitiveness on the hinterland economy: A case study of China.

In the global trade landscape, ports are not only critical nodes for the transportation of goods but also increasingly recognized as key factors driving sustainable development through their green competitiveness. This paper takes a green competitiveness perspective to delve into the interactive relationship between port development and the hinterland economy, aiming to provide a theoretical foundation and policy recommendations for the green development of ports. An evaluation index system for green competitiveness of ports was constructed, and a combination of the Slacks-Based Measure (SBM) and the Entropy Weighted-Technique for Order Preference by Similarity to Ideal Solution (EW-TOPSIS) method was employed to quantitatively measure and assess the 25 major coastal ports and their hinterland economic systems in China. The study reveals that the overall green competitiveness of these major coastal ports is on the rise, yet notable disparities exist among individual ports. Regionally, the green competitiveness of the Yangtze River Delta port group stands out, while that of the Bohai Rim, southeastern, Pearl River Delta, and southwestern coastal port groups is relatively low. Empirical analysis conducted in this paper demonstrates the positive impact of port green competitiveness on the hinterland economic system, particularly its significant role in enhancing the total and quality aspects of the hinterland economy. Furthermore, it was found that the green competitiveness of ports exerts a more pronounced promotional effect on the hinterland economies of the Yangtze River Delta and Pearl River Delta port groups compared to that on the Bohai Rim, southeastern, and southwestern coastal port groups. The results of this paper also hold important guiding value for optimizing the allocation of port resources, promoting port technological innovation, and improving port environmental management, contributing to the harmonious coexistence and long-term development of ports and their hinterlands.

Parametric seasonal-trend autoregressive neural network for long-term crop price forecasting.

Crop price forecasting is difficult in that supply is not as elastic as demand, therefore, supply and demand should be stabilized through long-term forecasting and pre-response to the price. In this study, we propose a Parametric Seasonal-Trend Autoregressive Neural Network (PaSTANet), which is a hybrid model that includes both a multi-kernel residual convolution neural network model and a Gaussian seasonality-trend model. To compare the performance of the PaSTANet, we used daily data from the Garak market for four crops: onion, radish, Chinese cabbage, and green onion, and performed long-term price forecasts for one year in 2023. The PaSTANet shows good performance on all four crops compared to other conventional statistical and deep learning-based models. In particular, for onion, the (mean absolute error (MAE) for the long-term forecast of 2023 is 107, outperforming the second-best Prophet (152) by 29.6%. Chinese cabbage, radish, and green onion all outperform the existing models with MAE of 2008, 3703, and 557, respectively. Moreover, using the confidence interval, the predicted price was categorized into three intervals: probability, caution, and warning. Comparing the percentage of classified intervals about the true prices in our test set, we found that they accurately detect the large price volatility.

Consumer Out-Of-Pocket Drug Prices Grew Faster Than Prices Faced By Insurers After Accounting For Rebates, 2007-20.

The rising price of branded drugs has garnered considerable attention from the public and policy makers. This article investigates the complexities of pharmaceutical pricing, with an emphasis on the overlooked aspects of manufacturer rebates and out-of-pocket prices. Rebates granted by pharmaceutical manufacturers to insurers reduce the actual prices paid by insurers, causing the true prices of prescriptions to diverge from official statistics. We combined claims data on branded retail prescription drugs with estimates on rebates to provide new price index measures based on pharmacy prices, negotiated prices (after rebates), and out-of-pocket prices for the commercially insured population during the period 2007-20. We found that although retail pharmacy prices increased 9.1 percent annually, negotiated prices grew by a mere 4.3 percent, highlighting the importance of rebates in price measurement. Surprisingly, consumer out-of-pocket prices diverged from negotiated prices after 2016, growing 5.8 percent annually while negotiated prices remained flat. The concern over drug price inflation is more reflective of the rapid increase in consumer out-of-pocket expenses than the stagnated inflation of negotiated prices paid by insurers after 2016.

Impact on beer sales of removing the pint serving size: An A-B-A reversal trial in pubs, bars, and restaurants in England.

BACKGROUND: Smaller serving sizes could contribute towards reducing alcohol consumption across populations and thereby decrease the risk of 7 cancers and other diseases. To our knowledge, the current study is the first to assess the impact on beer, lager, and cider sales (hereafter, for ease, referred to just as "beer sales") of removing the largest draught serving size (1 imperial pint) from the options available in licensed premises under real-word conditions. METHODS AND FINDINGS: The study was conducted between February and May 2023, in 13 licensed premises in England. It used an A-B-A reversal design, set over 3 consecutive 4-weekly periods with "A" representing the nonintervention periods during which standard serving sizes were served, and "B" representing the intervention period when the largest serving size of draught beer (1 imperial pint (568 ml)) was removed from existing ranges so that the largest size available was two-thirds of a pint. Where two-third pints were not served, the intervention included introducing this serving size in conjunction with removing the pint serving size. The primary outcome was the mean daily volume of all beer sold, including draught, bottles, and cans (in ml), extracted from electronic sales data. Secondary outcomes were mean daily volume of wine sold (ml) and daily revenue (£). Thirteen premises completed the study, 12 of which did so per protocol and were included in the primary analysis. After adjusting for prespecified covariates, the intervention resulted in a mean daily change of -2,769 ml (95% CI [-4,188, -1,578] p < 0.001) or -9.7% (95% CI [-13.5%, -6.1%] in beer sold. The daily volume of wine sold increased during the intervention period by 232 ml (95% CI [13, 487], p = 0.035) or 7.2% (95% CI [0.4%, 14.5%]). Daily revenues decreased by 5.0% (95% CI [9.6%, -0.3%], p = 0.038). CONCLUSIONS: Removing the largest serving size (the imperial pint) for draught beer reduced the volume of beer sold. Given the potential of this intervention to reduce alcohol consumption, it merits consideration in alcohol control policies. TRIAL REGISTRATION: ISRCTN.com ISRCTN18365249.

Digital transformation and corporate tax avoidance: An analysis based on multiple perspectives and mechanisms.

Promoting the seamless integration of the digital economy with the real economy, mitigating the adverse impacts of widespread corporate tax avoidance, and optimizing tax governance are critical imperatives in the era of digital economy. This study examines all A-share listed companies from 2007 to 2022 as research samples. It utilizes multiple perspectives including signal theory, information asymmetry theory, and the T-O-E (Technology-Organisation-Environment) framework to investigate the primary impacts of digital transformation on corporate tax avoidance, along with the intermediate mechanisms and foundational conditions that influence its effectiveness. After conducting both theoretical and empirical analyses, this paper presents the following conclusions. (1) The implementation of digital transformation significantly reduces corporate tax avoidance, a conclusion supported by rigorous robustness tests. Moreover, digital transformation enhances corporate productivity through the suppression of tax avoidance. (2) Digital transformation diminishes corporate tax avoidance through enhanced innovation and efficiency in resource allocation (technology level), improved quality of internal controls (organization level), and decreased industry competition (environment level). (3) The impact of digital transformation in reducing tax avoidance is significantly greater for enterprises in their growth phase, experiencing lower financing constraints, particularly those situated in the central and western regions. (4) Lower business risk is essential for maximizing the effectiveness of digital transformation and reducing corporate tax avoidance. This is crucial for governments seeking to improve tax administration, guide market and regional development, and enhance the impact of corporate digital transformation on mitigating tax avoidance.

Why is welfare pork so expensive?

Specialty (niche) pork products may provide societal benefits in terms of e.g. higher animal welfare, reduced use of antibiotics, and lower environmental impact. At the same time, they offer a business opportunity for farmers, slaughterhouses, meat processers, and retailers, who can capitalise on consumer segments willing to pay a price premium. However, the added cost of delivering niche products and a limited willingness among consumers to pay the higher prices may negate the benefits of this approach, particularly as niche products typically have high substitutability with standard pork. One way to ensure the success of the niche pork products is to drive down costs across all parts of the value chain. Inspired by data from the Danish pork market, the present study seeks to identify cost drivers in the value chain. We found two promising approaches to reduce the costs associated with niche products. First, the pricing strategy can be altered so that mainstream pork is replaced entirely by specialty pork products in the chiller section, thereby making niche the new standard. Second, with improved carcass balance, the price premium paid to farmers can be assigned to a larger proportion of the pig, thus enabling the retail price to be lowered. For example, we found that improved carcass balance had the potential to halve the necessary retail price increase, regardless of the pricing strategy employed. The conclusion is that it is possible to drive down costs across all parts of the value chain to enable further production and profitable sale of welfare pork.

Methods and data needs to estimate the economic market value of livestock at different spatial scales.

Assessing the economic value of livestock such as cattle, goats, sheep, pigs, chickens and fish can offer information about their financial performance and economic importance at farm, national and global scale. Such information is needed for decision-making surrounding livestock finance, investment and strategic development. The aim of this study was to provide an overview of the key livestock valuation methods and associated data requirements. The study was conducted using a literature review. Five key livestock valuation methods were identified and described: historical costs, net current market value, replacement costs, net present value and cost of production. The findings of this study may be of interest to livestock scientists, veterinarians, policy-makers and other stakeholders who aim to assess the economic value of livestock herds. The Global Burden of Animal Diseases programme relied on the outcomes of this study to identify methods for the estimation of the economic value of livestock at the global scale and for its Ethiopia and Indonesia case studies.

L'estimation de la valeur économique des animaux d'élevage (bovins, caprins, ovins, porcins, poulets et poissons d'élevage) peut apporter un éclairage sur leurs performances financières et leur intérêt économique à l'échelle d'une exploitation, d'un pays ou du monde. Ces informations sont indispensables pour étayer les décisions de financement, d'investissement et de développement stratégique des élevages. L'étude présentée par l'autrice vise à donner une vue d'ensemble des principales méthodes d'estimation de la valeur des animaux d'élevage et des exigences qui leur sont associées en termes de données. L'étude repose sur un examen de la littérature sur le sujet. Cinq méthodes principales d'estimation de la valeur des animaux d'élevage y sont répertoriées et décrites : coûts historiques, valeur marchande courante nette, coûts de remplacement, valeur actuelle nette et coûts de production. Les résultats de cette étude pourraient intéresser les spécialistes de l'élevage, les vétérinaires, les décideurs politiques et d'autres parties prenantes qui cherchent à évaluer la valeur économique des cheptels. Le programme " Impact mondial des maladies animales " s'est appuyé sur les résultats de cette étude pour retenir les méthodes d'estimation de la valeur économique des animaux d'élevage appliquées à l'échelle mondiale ainsi que dans les études de cas conduites en Ethiopie et en Indonésie.

Evaluar el valor económico del ganado, como vacas, cabras, ovejas, cerdos, pollos y peces, puede ofrecer información sobre su desempeño financiero y su importancia económica tanto a nivel de la explotación como a escala nacional y mundial. Esta información es necesaria para la toma de decisiones en materia de financiación, inversión y desarrollo estratégico de la ganadería. El objetivo de este estudio era ofrecer una visión general de los principales métodos de valoración del ganado y de las necesidades de datos conexas. Para ello, se llevó a cabo una revisión bibliográfica y se distinguieron y describieron cinco métodos fundamentales de valoración de la ganadería: costes históricos, valor actual de mercado neto, costes de reposición, valor actual neto y costes de producción. Las conclusiones de este estudio pueden ser de interés para científicos que trabajan en el ámbito de la ganadería, veterinarios, responsables de la toma de decisiones y otras partes interesadas en la evaluación del valor económico del ganado. El programa sobre el Impacto Global de las Enfermedades Animales se basó en los resultados de este estudio para definir métodos de estimación del valor económico del ganado a escala mundial y para sus estudios de caso de Etiopía e Indonesia.

Can good ESG performance of listed companies reduce abnormal stock price volatility? Mediation effects based on investor attention.

Today, with a growing emphasis on sustainable economic development, corporate environmental, social and governance (ESG) performance is attracting increasing attention and favor from investors. This triggers a question: can good ESG performance of listed companies mitigate the "up and down" of the stock market by drawing investor attention? This paper utilizes the data from China's A-share listed companies from 2011 to 2020, with investor attention as a mediating variable, to explore how the ESG performance of listed companies influences abnormal stock price volatility. The findings suggest that stronger ESG performance of listed companies significantly reduces abnormal stock price volatility, in which investor attention plays a partial mediating role. This paper confirms the robustness of the findings through multiple robustness and endogeneity tests. Heterogeneity analysis reveals that listed companies with good ESG performance during the growth period are more likely to significantly mitigate abnormal stock price volatility. Similarly, firms that maintain commendable ESG performance in bear markets significantly reduce abnormal stock price volatility. These findings enrich the theoretical research on the impact of ESG performance on abnormal stock price volatility, provide empirical evidence for listed companies to emphasize ESG investment and encourage investors to consider ESG ratings. Additionally, the study provides a new perspective for government agencies to utilize corporate ESG performance to maintain the sound development of the capital market.

Asymmetric dynamic linkage between consumer sentiment, inflation expectations, and international energy prices: Evidence from time-frequency wavelet and nonlinear analysis.

This study investigates the relationship between consumer sentiment (CONS), inflation expectations (INEX) and international energy prices, drawing on principles from behavioral. We focus on Brent crude oil price and Henry Hub natural gas prices as key indicators of energy market dynamics. Based on the monthly data from January 2003 to March 2023, three wavelet methods are applied to examine the time-frequency linkage, while the nonlinear distributed lag model (NARDL) is used to verify the asymmetric impact of two factors on energy prices. The results highlight a substantial connection between consumer sentiment, inflation expectations and international energy prices, with the former in the short term and the latter in the medium to long term. Especially, these correlations are particularly pronounced during the financial crisis and global health emergencies, such as the COVID-19 epidemic. Furthermore, we detect short-term asymmetric effects of consumer sentiment and inflation expectations on Brent crude oil price, with the negative shocks dominating. The positive effects of these factors on oil prices contribute to observed long-term asymmetry. In contrast, inflation expectations have short-term and long-run asymmetric effects on natural gas price, and both are dominated by reverse shocks, while the impact of consumer sentiment on natural gas prices appears to be less asymmetric. This study could enrich current theories on the interaction between the international energy market and serve as a supplement to current literature.

A multi-level multi-product supply chain network design of vegetables products considering costs of quality: A case study.

Effective logistics management is crucial for the distribution of perishable agricultural products to ensure they reach customers in high-quality condition. This research examines an integrated, multi-echelon supply chain for perishable agricultural goods. The supply chain consists of four stages: supply, processing, storage, and customers. This study investigates the quality-related costs associated with product perishability to maximize supply chain profitability. Key factors considered include the network design, location of processing and distribution centers, the ability to process raw products to minimize post-harvest quality degradation, the option to sell the excess produce to a secondary market due to unpredictable yields, and the decision not to fulfill demand from distant customers where significant quality loss and price drops would be involved, instead diverting those products to the aforementioned secondary market. Quantitative methods and linear mathematical programming are employed to model and validate the proposed supply chain using actual data from a real-world case study on vegetable supply chains. The main contribution of this research is the incorporation of quality costs into the objective function, which allows the supply chain to prioritize meeting nearby customers' demands with minimal quality loss over serving distant customers where high quality loss is unavoidable. Additionally, deploying a faster transportation fleet can significantly improve the overall profitability of the perishable product supply chain.

Does managerial myopia promote enterprises over-financialization? Evidence from listed firms in China.

This paper analyzes the potential shortsightedness of enterprise managers through annual reports. Additionally, we use corporate financial statement data to measure enterprises over-financialization in terms of resource allocation. After testing with a causal inference model, we find that firms with managerial myopia significantly contribute to over-financialization. It remains robust even after the instrumental variable of whether the manager has experienced a famine is used. Furthermore, financial distress and financing constraints amplify the inclination of short-term-focused managers to amass greater financial assets.

Can digital technology innovation contribute to firms' market value?

With the rapid development of digital technology, digital technology innovation has become a core driver of China's economic development. Thus, this study uses A-share listed companies from 2003 to 2021 as the research sample. The digital patents of firms are identified to portray the level of digital technology innovation by matching the digital economy industry classification code, national economy industry classification code, and IPC number. Considers the economic effect of digital technology innovation from the perspective of firm market value. It is found that digital technology innovation significantly contributes to the increase in firm market value, and this finding still holds when robustness tests are performed. Mechanistic tests have shown that digital technology innovation affects firm market value by driving digital transformation, promoting productivity, and enhancing market profitability. Further analysis reveals that digital technology innovation has a more significant effect on increasing firm market value for large, non-state, capital-intensive, technology-intensive and low internal control costs firms. This study verifies the enabling effect of digital technology innovation on the development of the real economy at the micro level, and provides insights for the optimization of China's digital technology innovation policies and the formulation of firms' digital development strategies.

Drug Prices After Patent Expirations in High-Income Countries and Implications for Cost-Effectiveness Analyses.

Importance: Understanding how patent expirations affect drug prices is crucial because price changes directly inform accurate cost-effectiveness assessments. This study investigates the association between patent expirations and drug prices in 8 high-income countries and evaluates how the changes affect cost-effectiveness assessments. Objective: To analyze how the expiration of drug patents is associated with drug price changes and to assess the implications of these price changes for cost-effectiveness evaluations. Design, Setting, and Participants: This cohort study performed an event study design using data from 8 high-income countries to assess the association between patent expiration and drug prices, and created a simulation model to understand the implications for cost-effectiveness analyses. The simulation cost-effectiveness model analyzed the implications of including or ignoring postpatent price dynamics. Exposure: Drug patent expiration. Main Outcomes and Measures: Change in drug prices and differences in incremental cost-effectiveness ratios when considering vs ignoring postpatent price dynamics. Results: The sample comprised 505 drugs undergoing patent expiration in Australia, Canada, France, Germany, Japan, Switzerland, UK, and US. Price decreases were statistically significant over the 8 years after patent expiration, with the fastest price declines observed in the US: 32% (95% CI, 24%-39%) in year 1 after patent expiration and 82% (95% CI, 71%-89%) in the 8 years after patent expiration. Estimates for other nations ranged from a decrease of 64% in Australia to 18% in Switzerland in the 8 years after expiration. The cost-effectiveness simulation model indicated that not accounting for generic entry into the market may produce biased incremental cost-effectiveness ratios of 40% to -40%, depending on the scenario. Conclusions and Relevance: The findings of this cohort study demonstrate that drug prices were reduced substantially after patent expirations in high-income countries. Therefore, incorporating information on patent status and pricing dynamics in cost-effectiveness assessment analyses is necessary for producing accurate economic evaluations of new drugs.

Credit risk contagion of supply chain finance: An empirical analysis of supply chain listed companies.

With the gradual rise of the supply chain financial model and the expansion of scale, credit risk and contagion effects are gradually strengthened as business and financial links between upstream and downstream enterprises in the supply chain. The traditional credit risk contagion assessment model based on the financial status of an enterprise and the pledging of fixed assets has been unable to meet the basic needs of modern supply chain companies and financial institutions for risk control. Therefore, this paper introduces the Cox-Copula model to comprehensively assess a company's financial situation and the business health of upstream and downstream companies in the supply chain from the perspective of actual transactions between companies and fixed asset pledges. The study found that credit risk has a contagion effect in supply chain enterprises, and this contagion effect of credit risk has certain dynamic characteristics. At the same time, it was found that the impacts of macroeconomic factors and microfinance factors on credit risk contagion of supply chain finance have differences in the two dimensions of degree and direction of action.

On the role of government spending, trade openness and terms of trade in Iran's agricultural growth.

Agriculture is recognized as the driving force of economic growth, especially in developing economies. It plays a crucial role in Iran's economy especially during economic sanctions as it is a source of income for rural people, food security, job creation, and foreign exchange earnings. The present study investigates the impact of government spending, trade openness, and terms of trade on agricultural growth in Iran using annual data for the period 1978-2021 by application of the nonlinear autoregressive distributed lag model (NARDL). The results confirmed asymmetry in the impact of all three variables of interest on agricultural growth. In other words, the superiority of the nonlinear specification in explaining the relationships between variables was confirmed. To be specific, a positive and negative shock to government spending affects sector growth by 0.18 and -0.05 percent, respectively in the long run. The same finding was found for trade openness with 0.22 and -0.11 impact coefficients for positive and negative shocks, respectively. Moreover, we could not find significant impact for terms of trade.

The effect of avian influenza outbreaks on retail price premiums in the United States poultry market.

This study analyzes the effect of avian influenza outbreaks on retail price premiums in the US poultry market. We estimate hedonic price models for eggs, chickens, and turkeys, controlling for quality characteristics, unobserved time, and regional factors. To measure the impact of avian influenza outbreaks we use 2 proxies. The first proxy is a measure of the number of new bird infections at the production level. The second proxy measures online search queries related to the outbreak. The results show that, on average, prices increase across product categories, that is, egg, broiler, and turkey markets, during avian influenza outbreaks. Furthermore, we observe price convergence and reduced dispersion within product categories, which is consistent with the economic theory of asymmetric substitutability between conventional and premium products. Our analysis finds that the HPAI outbreak caused a reduction of the price gap between conventional and premium products.