Economic Assessment of Selected Regulatory Ecosystem Services (RES) in the Elgeyo and Nyambene Watersheds Ecosystems in Kenya

Evidence of increased valuation of ecosystem services (ES) globally is significant. However, most of these studies focus on marketed subsets of ES at national and international levels. Ecosystems differ in spatial scale, biophysical and ecological structure, and functionality. This requires conducting studies at the local level to understand how, for example, the watershed ecosystem contributes to humanity locally and nationally. This study focuses on selected regulatory ecosystem services (RES) in Kenya’s catchment area ecosystems (Elgeyo and Nyambene). Field-based sampling and Landsat imagery with secondary information were used to generate biophysical and ecological data. The study used market price-based, cost-based, and unit transfer methods for RES valuation. The study estimates the total value of the six selected regulatory ecosystem services (RES) at KES 41.4 billion (US$386.7 million) and KES 14.73 billion (US$137.71 million) for Elgeyo and Nyambene, respectively. This equates to KES 1.64 million (US$15,331.19) and KES 2.72 million (US$25,375) per hectare per year. Extrapolating the study estimates to the national level, the country’s regulatory ecosystem services would range from US$18.4 billion to US$30.45 billion annually. This equates to between 16.7% and 27.7% of Kenya’s GDP in 2021, underscoring the importance of watersheds to the national economy.

AR Model Based on Time Series Modeling for Predicting Egg Market Price in 2021

Eggs,as a meat consumer product in China,are closely related to the vegetable basket project.Exploring and predicting the future trend of egg market price is of great significance for stabilizing egg price and market supply.In this study,the time series AR model was used for fitting the egg market prices in the 66 d from January 1 to March 7,2021,and the delay operator nlag18 was used for white noise test,giving pr>probability of chisq<0.005.The time series was not a white noise series,and then the stationary series was used for modeling.The optimal model was selected as the AR series(BIC(3,0)),and finally,the egg market price model AM was obtained as X_(t)=9.0556+(1+0.8926)ε_(t),which was the optimal model.The model showed that the egg price fluctuations in 2021 will be clustered,and the later price will be significantly affected by external factors in the previous period.The dynamic prediction results of the model showed that the egg price would stop falling in March 2020,and the egg price would continue to slow down in March.

Rice quality in relation to market prices in Yunnan Province

Factors affecting rice quality and their impacts on market price were investigated in this study. On-farm survey and market survey was undertaken in three selected sites namely Kunming, Dali, and Xishuangbanna in Yunnan Province, China. Market sampling was conducted to determine important rice quality characteristics. Sixty milled rice samples were collected from domestic markets of the three sites during a period of Mar to Apr in 1994. The grain physicochemical properties of the milled rice samples were analyzed on the basis of Chinese Agricultural Ministry Standard for testing rice quality. A hedonic price model (implicit price model) was further employed to quantify relationships between quality characteristics and market prices of rice. The model can be expressed mathematically as the following function (1) This function shows that the average price paid by consumer for different grades of rice with attribute Xj. Using the ordinary least square (OLS) regression of observed market prices on measures

Seminar on“Cotton Price and Market”Outlook and Expectation for 2011

Sponsored by Cotton Council International and co-organized by the Hong Kong Association of Textile Bleachers,Dyers,Printers and Finishers and the Hong Kong Cotton Spinners Association,the seminar on"Cotton Price and Market:Outlook and Expectation for 2011"was held at the Clothing

Pricing to Market: Chinese Export Pricing to the USA after the Peg

In July 2005, the Chinese Government unpegged the RMB from the US dollar. As the RMB has followed a remarkably predictable appreciation over time, I examine the price of Chinese exports to the USA after unpegging the exchange rate. Results suggest that the Chinese industries with greater import market share were able to raise their prices after the removal of the pegged exchange rate regime; however, over time there is a significant deflationary trend. Chinese export prices tended to decrease under an unanticipated RMB appreciation; this effect was more pronounced for industries with more pricing flexibility. This suggests that Chinese exporters are consistently ＂pricing to market＂ and thus creating a significant foreign exchange policy implication. Specifically, a more flexible exchange rate regime will likely have little impact on the prices of Chinese exports to the USA but might increase the profit volatility of Chinese firms.

Impacts of COVID-19 Pandemic on Italian Electricity Demand and Markets

In this paper,the short-,medium-,and long-term effects of the COVID-19 pandemic on the Italian power system,particularly electricity consumption behavior and electricity market prices,are investigated by defining various metrics.The investigation reveals that COVID-19 lockdown caused a drop in load consumption and,consequently,a decrement in day-ahead market prices and an increase in ancillary service prices.

Design and implementation of China Hydrogen Price Index system

Hydrogen will be an important part of China’s energy system in the future and an important carrier for energy-using terminals to realize green and low-carbon transformation.It is important to establish a nationwide hydrogen market to promote the healthy and orderly development of the hydrogen industry chain.The core is to form a complete hydrogen price mechanism and play a decisive role in the process of resource allocation by the market.In this paper,we have developed the framework of the‘China Hydrogen Price Index’system by establishing the‘Assessment+Collection’model,which covers four types of hydrogen:hydrogen,clean hydrogen,renewable hydrogen and high-purity hydrogen.The model considers the raw materials required for hydrogen production,fixed equipment,engineering construction costs and carbon prices,and conducts sensitivity analysis on the trends and influencing factors of national and regional hydrogen prices of multiple categories since 2018.The results show that,with respect to the level of hydrogen prices,fossil-energy-rich and renewable-energy-rich areas have more advantages than other regions.The price of raw materials is the main factor of the hydrogen price change,and the utilization hours of renewable energy and hydrogen production equipment have a key influence on the price of renewable hydrogen.Next,by establishing an index update mechanism,improving the standard system and building a trading platform,we can further exert the role of price signals and continue to promote the efficient and smooth expansion of the domestic hydrogen market.

Linguistic specificity and stock price synchronicity

Linguistic specificity effectively reduces barriers to information cognition,increasing the efficiency of information acquisition,integration and processing.Combining the psycholinguistics theory of the concreteness effect with assetpricing theory,we determine that linguistic specificity in the management discussion and analysis section of a firm’s annual reports is negatively associated with stock price synchronicity,particularly in firms with strong external information demand or insufficient information supply.Furthermore,only specificity of the review section leads to a reduction in stock price synchronicity.Mechanism tests show that specificity reduces information processing costs and enhances information credibility.Additionally,proprietary costs are an essential determinant of linguistic specificity adoption.Our findings suggest that linguistic specificity plays an essential role in improving market pricing efficiency.

A Demand Response System for Wind Power Integration: Greenhouse Gas Mitigation and Reduction of Generator Cycling

A smart grid power system for a small region consisting of 1,000 residential homes with electric heating appliances from the demand side,and a generic generation mix of nuclear,hydro,coal,gas and oil-based generators representing the supply side,is investigated using agent-based simulations.The simulation includes a transactive load control in a real-time pricing electricity market.The study investigates the impacts of adding wind power and demand response(DR)on both greenhouse gas(GHG)emissions and generator cycling requirements.The results demonstrate and quantify the effectiveness of DR in mitigating the variability of renewable generation.The extent to which greenhouse gas emissions can be mitigated is found to be highly dependent on the mix of generators and their operational capacity factors.It is expected that the effects of demand response on electricity use can reduce dependency on fossil fuel-based electricity generation.However,the anticipated mitigation of GHG emissions is found to dependent on the number and efficiency of fossil fuel generators,and especially on the capacity factor at which they operate.Therefore,if a generator(the marginal seller)is forced to use less efficient fossil fuel power generation schemes,it will result in higher GHG emissions.The simulations show that DR can yield a small reduction in GHG emissions,but also lead to a smaller increase in emissions in circumstances when,for example,a generator(the marginal seller)is forced to use less efficient fossil fuel power generation schemes.Nonetheless,DR is shown to enhance overall system operation,particularly by facilitating increased penetration of variable renewable electricity generation without jeopardizing grid operation reliability.DR reduces the amount of generator cycling by an increased order of magnitude,thereby reducing wear and tear,improving generator efficiency,and avoiding the need for additional operating reserves.The effectiveness of DR for these uses depends on the participation of responsive loads,and this study highlights the need to maintain a certain degree of diversity of loads to ensure they can provide adequate responsiveness to the changing grid conditions.

Hot Money Flows, Cycles in Primary Commodity Prices, and Financial Control in Developing Countries

Because the U.S. Federal Reserve＇s monetary policy is at the center of the world dollar standard, it has a first-order impact on global financial stability. However, except during international crises, the Fed focuses on domestic American economic indicators and generally ignores collateral damage from its monetary policies on the rest of the world. Currently, ultra-low interest rates on short-term dollar assets ignite waves of hot money into Emerging Markets （EM） with convertible currencies. When each EM central bank intervenes to prevent its individual currency from appreciating, collectively they lose monetary control, inflate, and cause an upsurge in primary commodity prices internationally. These bubbles burst when some accident at the center, such as a banking crisis, causes a return of the hot money to the United States （and to other industrial countries） as commercial banks stop lending to foreign exchange speculators. World prices of primary products then collapse. African countries with exchange controls and less convertible currencies are not so attractive to currency speculators. Thus, they are less vulnerable than EM to the ebb and flow of hot money. However, Afi-ican countries are more vulnerable to cycles in primary commodity prices because food is a greater proportion of their consumption, and--being less industrialized--they are of their commodity exports. Supply-side more vulnerable to fluctuations in prices shocks, such as a crop failure anywhere in the world, can affect the price of an individual commodity. But joint fluctuations in the prices of all primary products--minerals, energy, cereals, and so on--reflect monetary conditions in the world economy as determined by the ebb and flow of hot money from the United States, and increasingly from other industrial countries with near-zero interest rates.

Priced for the Market

A plan is underway to change the country’s current oil-pricing system from government-controlled to