Relevant bibliographies by topics / Home economics Mathematical models

Academic literature on the topic 'Home economics Mathematical models'

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Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Home economics Mathematical models"

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Chen, Hong Jiang, and Yue Hai Wu. "Study of Material’s Creep Relaxation Capability." Applied Mechanics and Materials 121-126 (October 2011): 406–10. http://dx.doi.org/10.4028/www.scientific.net/amm.121-126.406.

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Creep relaxation is an important form of system failure, how to understand and analyze the effect of creep relaxation, to solve system failures and improve economic efficiency are of great significance. The paper describe researches of creep relaxation , mathematical models and theories at home and abroad in detail, and introduce the finite element method applied in this field. By comparing with the mathematical models, finite element Methods with test results, improving current mathematical models and utilizing finite element method is an important trend.
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Fadeeva, A. M. "Risk minimisation methods in shaping the optimal range of treadmills." Vestnik Universiteta, no. 11 (January 7, 2022): 149–56. http://dx.doi.org/10.26425/1816-4277-2021-11-149-156.

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The article presents a solution to the problem of integrating risk minimisation methods in the process of forming the optimal range of treadmill models in a retail enterprise. The problem of multi-criteria optimisation was solved using the generalised criterion method. The formulated problem was therefore broken down into a number of specific tasks, each of which was solved by selecting specific methods. Risks were minimised by mathematical methods, taking into account the economic performance of the enterprise. Recommendations were also offered for customers wishing to purchase one of the treadmill models chosen from the analysis and the best option for ordering via the online shop with home delivery.
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Helander, Mary. "Visitation Access to U.S. Nursing Homes: An Analysis of Facility Locations, Ratings, and Disparities." Innovation in Aging 4, Supplement_1 (December 1, 2020): 114. http://dx.doi.org/10.1093/geroni/igaa057.375.

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Abstract Research findings suggest that family visits to nursing home residents are important for countering depression, increasing residents’ well-being and quality of life (Miller, 2019; Durkin et al., 2014), maintaining physical function (Shankar et al., 2017), and improving general health (Parmenter et al., 2012). Presence by family can directly impact a resident’s care quality, since family members may take a role in monitoring their older relative’s status (Miller, 2019). Unfortunately, regular family visits to nursing homes may be difficult, or impossible, due to challenges that include distance, travel time, lack of transportation, and cost (Fields et al., 2019) (Miller, 2019). These same challenges may translate to socio-economic barriers for families, eliminating long-term-care as an option for older relatives (Ferraro et al., 2017), (Angel and Berlinger, 2018). This paper considers the issue of nursing home visitation access and examines related disparities through spatial and demographic analysis of 15,000+ US facilities monitored by the Centers for Medicare the Medicaid Services. Mathematical models are used to analyze facility and population data, using access measures adapted from the geography discipline (Lou and Wang, 2003; Paez et al., 2019). Analysis explores whether higher rated nursing homes are more likely to be closer to affluent populations, and whether socioeconomic status is a significant factor in overall access. Analysis reveals patterns of access disparity with respect to nursing home ratings and geographies. For example, proximity to higher rated facilities increases monotonically with median household income. Specific policy recommendations are discussed.
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HORIASHCHENKO, S., Yu KRAVCHIK, and O. PIDGORNYI. "MATHEMATICAL MODEL OF HEAT SUPPLY INSTALLATION AS AN OBJECT OF ECONOMIC EFFICIENCY AND AUTOMATION." Computer Systems and Information Technologies 2, no. 2 (November 3, 2020): 69–74. http://dx.doi.org/10.31891/csit-2020-2-12.

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Solar energy is widely used in cases where the inaccessibility of other energy sources in combination with a sufficient amount of solar radiation justifies it economically. With the help of a system of solar collectors, you can significantly reduce energy costs for hot water supply and heating. In addition, the use of this system helps reduce CO2 emissions. The potential of solar energy in Ukraine is quite high. According to the climatic conditions of our region, solar activity is slightly lower than in the southern regions, so the use of flat solar collectors, which use both direct and scattered solar radiation, is effective for our region. The use of heat collectors in the home for water supply and heating of small areas is economically feasible, as it does not require significant costs. Heat supply plants using non-traditional energy sources are promising in terms of fuel savings and reduction of harmful effects on the environment. To increase the service life, economical use of heat and fuel, efficient operation of the installation requires the use of automation. The article considers the development of a mathematical model of a heat supply installation based on a solar collector. For automated control of the heat supply installation, it is necessary to know the properties of this installation as a whole and its individual elements. For this purpose, models of individual elements of the heat supply installation in a linear approximation are considered. The solar collector is conditionally divided into two parts. The model of the ground heat exchanger is developed. Also e battery models and consumer premises. The given matrices of elements of installation of heat supply are united in the uniform system of matrices. The obtained results allow estimating in advance efficiency of their use and economic attractiveness.
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Xu, Lu, and Weijie Chen. "Construction and Simulation of Economic Statistics Measurement Model Based on Time Series Analysis and Forecast." Complexity 2021 (June 23, 2021): 1–9. http://dx.doi.org/10.1155/2021/5963516.

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Time series follow the basic principles of mathematical statistics and can provide a set of scientifically based dynamic data processing methods. Using this method, various types of data can be approximated by corresponding mathematical models, and then, the internal structure and complex characteristics of the data can be understood essentially, so as to achieve the purpose of predicting its development trend. This paper mainly studies the combined forecasting model based on the time series model and its application. First, the application prospects and research status of the combined forecasting model, the source of time series analysis, and the status of research development at home and abroad are given, and the purpose and significance of the research topic and the research content are summarized. Then, the paper gives the relevant theories about the ARIMA model and the basic principles of model recognition and explains the method of time series smoothing. Finally, the paper uses the ARIMA model to identify and fit the time series data and then the gray forecast model to fit and predict the time series data. Finally, by assigning reasonable weights and combining these methods, a combined forecasting model is proposed and carried out.
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Simmons, Cody R., Joshua R. Arment, Kody M. Powell, and John D. Hedengren. "Proactive Energy Optimization in Residential Buildings with Weather and Market Forecasts." Processes 7, no. 12 (December 5, 2019): 929. http://dx.doi.org/10.3390/pr7120929.

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This work explores the development of a home energy management system (HEMS) that uses weather and market forecasts to optimize the usage of home appliances and to manage battery usage and solar power production. A Moving Horizon Estimation (MHE) application is used to find the unknown home model parameters. These parameters are then updated in a Model Predictive Controller (MPC) which optimizes and balances competing comfort and economic objectives. Combining MHE and MPC applications alleviates model complexity commonly seen in HEMS by using a lumped parameter model that is adapted to fit a high-fidelity model. Heating, ventilation, and air conditioning (HVAC) on/off behaviors are simulated by using Mathematical Program with Complementarity Constraints (MPCCs) and solved in near real time with a non-linear solver. Removing HVAC on/off as a discrete variable and replacing it with an MPCC reduces solve time. The results of this work indicate that energy management optimization significantly decreases energy costs and balances energy usage more effectively throughout the day. A case study for Phoenix, Arizona shows an energy reduction of 21% and a cost reduction of 40%. This simulated home contributes less to the grid peak load and therefore improves grid stability and reduces the amplitude of load-following cycles for utilities. The case study combines renewable energy, energy storage, forecasts, cooling system, variable rate electricity plan and a multi-objective function allowing for a complete home energy optimization assessment. There remain several challenges, including improved forecast models, improved computational performance to allow the algorithms to run in real time, and mixed empirical/physics-based machine-learning methods to guide the model structure.
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Çetin, Eyüp, Serap Kiremitci, and Barış Kiremitci. "Developing Optimal Policies to Fight Pandemics and COVID-19 Combat in the United States." European Journal of Pure and Applied Mathematics 13, no. 2 (April 29, 2020): 369–89. http://dx.doi.org/10.29020/nybg.ejpam.v13i2.3700.

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The world has faced many outbreaks and pandemics with hundreds of millions of deaths throughout its history. Those epidemics are global health concerns and as well as serious economic issues. There is certain need to allocate scarce sources efficiently to fight such epidemics in both personal and global dimensions. Here we develop and propose two optimization models to maximize the total protection from any epidemic, pandemic or bioterror attacks; the first one is personal protection model or protocol and the other one is mass protection model that is inspired by the well-known weapon-target assignment problem of operations research. These efforts are optimal allocation of scarce medical and economic resources to save millions of lives- gift of life. We implement our general mathematical programming models with real-world data to fight the coronavirus pandemic for a person and the United States. Our personal protection protocol provides 99.99% protection from COVID-19 for an American through personal strategies when the mass protection model supplies 96.961% protection on average from coronavirus pandemic for the United States through across country policies. The mass protection model which recommends general policy frame for health care policy makers could be applied for any epidemic at any level from county to city, to state and country as well as in global scale. The mathematical relation between the personal protection protocol and the mass protection model also highlights the fact of unus pro omnibus, omnes pro uno (one for all, all for one) for fighting epidemics- particularly the moving enemy, novel coronavirus which is double invisible due to its viral nature and the availability of the high level of asymptomatic cases. Recognize the enemy, as protecting yourself means protecting people, love life, follow the rules and stay at home. That is the greatest ever social impact.
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Zissis, Dimitris, Emel Aktas, and Michael Bourlakis. "Collaboration in urban distribution of online grocery orders." International Journal of Logistics Management 29, no. 4 (November 12, 2018): 1196–214. http://dx.doi.org/10.1108/ijlm-11-2017-0303.

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Purpose Population growth, urbanisation and the increased use of online shopping are some of the key challenges affecting the traditional logistics model. The purpose of this paper is to focus on the distribution of grocery products ordered online and the subsequent home delivery and click and collect services offered by online retailers to fulfil these orders. These services are unsustainable due to increased operational costs, carbon emissions, traffic and noise. The main objective of the research is to propose sustainable logistics models to reduce economic, environmental and social costs whilst maintaining service levels. Design/methodology/approach The authors have a mixed methodology based on simulation and mathematical modelling to evaluate the proposed shared logistics model using: primary data from a major UK retailer, secondary data from online retailers and primary data from a consumer survey on preferences for receiving groceries purchased online. Integration of these three data sets serves as input to vehicle routing models that reveal the benefits from collaboration by solving individual distribution problems of two retailers first, followed by the joint distribution problem under single decision maker assumption. Findings The benefits from collaboration could be more than 10 per cent in the distance travelled and 16 per cent in the time required to deliver the orders when two online grocery retailers collaborate in distribution activities. Originality/value The collaborative model developed for the online grocery market incentivises retailers to switch from current unsustainable logistics models to the proposed collaborative models.
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Riaz, Muhammad, Sadiq Ahmad, Irshad Hussain, Muhammad Naeem, and Lucian Mihet-Popa. "Probabilistic Optimization Techniques in Smart Power System." Energies 15, no. 3 (January 24, 2022): 825. http://dx.doi.org/10.3390/en15030825.

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Uncertainties are the most significant challenges in the smart power system, necessitating the use of precise techniques to deal with them properly. Such problems could be effectively solved using a probabilistic optimization strategy. It is further divided into stochastic, robust, distributionally robust, and chance-constrained optimizations. The topics of probabilistic optimization in smart power systems are covered in this review paper. In order to account for uncertainty in optimization processes, stochastic optimization is essential. Robust optimization is the most advanced approach to optimize a system under uncertainty, in which a deterministic, set-based uncertainty model is used instead of a stochastic one. The computational complexity of stochastic programming and the conservativeness of robust optimization are both reduced by distributionally robust optimization.Chance constrained algorithms help in solving the constraints optimization problems, where finite probability get violated. This review paper discusses microgrid and home energy management, demand-side management, unit commitment, microgrid integration, and economic dispatch as examples of applications of these techniques in smart power systems. Probabilistic mathematical models of different scenarios, for which deterministic approaches have been used in the literature, are also presented. Future research directions in a variety of smart power system domains are also presented.
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Pham, Hoang. "Predictive Modeling on the Number of Covid-19 Death Toll in the United States Considering the Effects of Coronavirus-Related Changes and Covid-19 Recovered Cases." International Journal of Mathematical, Engineering and Management Sciences 5, no. 6 (December 1, 2020): 1140–55. http://dx.doi.org/10.33889/ijmems.2020.5.6.087.

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COVID-19 is caused by a coronavirus called SARS-CoV-2. Many countries around the world implemented their own policies and restrictions designed to limit the spread of Covid-19 in recent months. Businesses and schools transitioned into working and learning remotely. In the United States, many states were under strict orders to stay home at least in the month of April. In recent weeks, there are some significant changes related restrictions include social-distancing, reopening states, and staying-at-home orders. The United States surpassed 2 million coronavirus cases on Monday, June 15, 2020 less than five months after the first case was confirmed in the country. The virus has killed at least 115,000 people in the United States as of Monday, June 15, 2020, according to data from Johns Hopkins University. With the recent easing of coronavirus-related restrictions and changes on business and social activity such as stay-at-home, social distancing since late May 2020 hoping to restore economic and business activities, new Covid-19 outbreaks are on the rise in many states across the country. Some researchers expressed concern that the process of easing restrictions and relaxing stay-at-home orders too soon could quickly surge the number of infected Covid-19 cases as well as the death toll in the United States. Some of these increases, however, could be due to more testing sites in the communities while others may be are the results of easing restrictions due to recent reopening and changed policies, though the number of daily death toll does not appear to be going down in recent days due to Covid-19 in the U.S. This raises the challenging question: • How can policy decision-makers and community leaders make the decision to implement public policies and restrictions and keep or lift staying-at-home orders of ongoing Covid-19 pandemic for their communities in a scientific way? In this study, we aim to develop models addressing the effects of recent Covid-19 related changes in the communities such as reopening states, practicing social-distancing, and staying-at-home orders. Our models account for the fact that changes to these policies which can lead to a surge of coronavirus cases and deaths, especially in the United States. Specifically, in this paper we develop a novel generalized mathematical model and several explicit models considering the effects of recent reopening states, staying-at-home orders and social-distancing practice of different communities along with a set of selected indicators such as the total number of coronavirus recovered and new cases that can estimate the daily death toll and total number of deaths in the United States related to Covid-19 virus. We compare the modeling results among the developed models based on several existing criteria. The model also can be used to predict the number of death toll in Italy and the United Kingdom (UK). The results show very encouraging predictability for the proposed models in this study. The model predicts that 128,500 to 140,100 people in the United States will have died of Covid-19 by July 4, 2020. The model also predicts that between 137,900 and 154,000 people will have died of Covid-19 by July 31, and 148,500 to 169,700 will have died by the end of August 2020, as a result of the SARS-CoV-2 coronavirus that causes COVID-19 based on the Covid-19 death data available on June 13, 2020. The model also predicts that 34,900 to 37,200 people in Italy will have died of Covid-19 by July 4, and 36,900 to 40,400 people will have died by the end of August based on the data available on June 13, 2020. The model also predicts that between 43,500 and 46,700 people in the United Kingdom will have died of Covid-19 by July 4, and 48,700 to 51,900 people will have died by the end of August, as a result of the SARS-CoV-2 coronavirus that causes COVID-19 based on the data available on June 13, 2020. The model can serve as a framework to help policy makers a scientific approach in quantifying decision-makings related to Covid-19 affairs.
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Dissertations / Theses on the topic "Home economics Mathematical models"

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Steeg, Jörg Michael. "Mathematical models and algorithms for home health care services." Tönning Lübeck Marburg Der Andere Verl, 2008. http://d-nb.info/994324375/04.

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Lei, Tianming. "FISCAL MULTIPLIERS IN HOME PRODUCTION MODELS." Miami University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=miami1480542791196421.

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Xotyeni, Zukisa Gqabi. "A study of the existence of equilibrium in mathematical economics." Thesis, Rhodes University, 2008. http://eprints.ru.ac.za/1114/.

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Oladi, Gholamreza. "Three essays in international economics." Thesis, McGill University, 2000. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=36784.

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In international economics literature, different variants of the Nash equilibrium have been used to formulate strategic and retaliative behavior. However, the negotiation process underlying the Nash equilibrium does not capture the notion of retaliation properly. We use the "contingent threat situation" (Greenberg, 1990) to reformulate three different international economic environments.
First, a two-country, two-commodity model of trade is considered to reformulate the tariff retaliations. It is known that tariff retaliations lead to a Nash equilibrium outcome, a non-free trade outcome. We show, in the framework of the "theory of social situations", that the free trade equilibrium is supported by a "stable standard of behavior".
Second, the basic two-country, single commodity model is employed to formulate the interactive and retaliatory policies regarding the choice between foreign investment and immigration. Considering three different strategic environments, we investigate the outcomes supported by "stable standards of behavior" under these strategic scenarios. We also provide a critical examination of Jones-Coelho-Easton's proposition (Jones, Coelho, and Easton, 1986).
Third, a simple model of international debt is formulated using a strategic form game. In the game, a country in financial crisis and on the verge of default is requesting a new loan, and a bank, with exposure to the foreign country's debt, contemplates whether it should issue the new loan. We show that "issue a new loan" and "not default", a Pareto optimum pair of strategies, is stable. Interestingly, we get this result by using a non-cooperative negotiation process, offered by the "individual contingent threat situation".
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Haven, Emmanuel. "The use of fuzzy set theory in economics : applications in micro-economics and finance." Thesis, McGill University, 1995. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=23335.

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This paper attempts to show how fuzzy set theory can be used to weaken some of the stringent, rationality assumptions used in classical micro-economics. The objective of the paper is to see whether by introducing fuzziness we arrive to new results or just only generalizations of classical micro-economic results. We discover that the axiom of completeness is not needed anymore. Using fuzziness will also allow us to better explain the existing gap between delimiting possible choices and making the actual choice. We also introduce the notions of a fuzzy indifference set with a measurable area. The fuzzy utility surface is also discussed. The demand curve is now 'thick'.
In the producer area, the classical hypothesis that maximum profit entails maximum utility of profit is now substantially weakened when introducing fuzziness.
Finally, we consider revealed preference within a fuzzy context.
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Allsopp, Paul, and n/a. "Measuring team performance and modelling the home advantage effect in cricket." Swinburne University of Technology, 2005. http://adt.lib.swin.edu.au./public/adt-VSWT20060713.122306.

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Cricket differs from many team sports in that it is not generally played within easily definable constraints. Thus, it is difficult to compare and contrast team performances. By employing a range of linear and logistic modelling techniques this thesis quantifies the extent to which team quality effects and a range of associated factors such as home advantage have shaped team performance in Test, ODI and domestic cricket. With regards to the latter, the thesis established that, in all forms of cricket, a team?s scoring potential and its capacity to win were both significantly amplified when it played at its home ground. The thesis proposes a method to estimate a projected score for the team batting second in ODI cricket. The method scales up the team?s actual winning scores in proportion to its unused run scoring resources. This creates a projected victory margin when it wins with unused run scoring resources at its disposal and provides a more realistic measure of its relative superiority at the point of victory than the current wickets-in-hand method. Accordingly, the thesis recommends a revised scheme for recording victories in ODI cricket which is consistent across innings and provides a mechanism for all victories to be compared and ranked on an equal footing. The thesis employs linear modelling methods that account for the size of a victory in ODI cricket and the magnitude of the first innings lead in Test and domestic cricket to compute team ratings. The ratings are calculated independently of effects such as home advantage and quantify overall team performance relative to the average rating. They provide a robust measure of team quality and are not sensitive to the extraneous effects that may disproportionately impact on team performance. As a consequence, the thesis recommends that new methods be investigated to officially rate and rank teams in international cricket competitions. The team ratings also form the basis of a proposed outcome prediction model that can be instituted in Test cricket. The thesis established that a surprising trend has emerged in Test cricket, which confirmed that the team batting second, in general, has enjoyed a distinct winning advantage over its opposition. Accordingly, the thesis ascertained that relative strength during the final rather than penultimate innings significantly affected match outcomes and recommends that teams, when winning the coin toss, expose their strongest asset, whether this be batting or bowling, in the final innings.
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Perry, Stanley Foster. "Distributed Economic Systems with Agents that Learn." PDXScholar, 1992. https://pdxscholar.library.pdx.edu/open_access_etds/1271.

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Economic systems are distributed in the sense that economic agents make decisions without any central control. Prices, quantities, wealth, and market structure emerge from the interaction of agents acting in their own self interest. The concepts and language of systems science are used to define economic systems in a manner that captures and articulates the distributed nature of economic systems. Further, the systems definition permits multiple views of the economic system, and in addition, allows the agents to "step outside" the system in order to study it. Economic systems are defined in such a way that it is feasible to construct artificial economic systems, and in particular, ones that are composed of self-interested agents that operate according to principles that are prescribed by the researcher. An artificial economic system was actually constructed and tested in a computer environment. The model was verified with reference to several theoretical models such as static and adaptive expectations. The system constructed allows up to 1000 agents to interact without any central control. A computer "blackboard system" is used as the architecture for providing common information to the agents in the artificial economic system. The blackboard design successfully allows complex agents to compete and trade in an artificial economic system created by the researcher. Prices, quantities, wealth, and market structure emerge naturally in the artificial economy that depend on the characteristics and prescribed strategies of the agents in the system. After a transition period, the trading frequently produces price and quantity time series that have the characteristics of a random walk, a condition that is well known in real world markets. Three classes of producer agents were used in these artificial economic systems: optimizing agents that incorporate neural networks, satisficing agents that incorporate very simple rule-based approaches, and Stackelberg agents that have knowledge about the consumers in the system, but do not have knowledge about their competitor's strategies or intentions. Neural networks are used to model the behavior and strategies of economic agents that can be said to learn, i.e., those agents that develop general principles for adapting to changing market conditions that transfer across markets. The focus of this research was on the producers in the system. The consumption side of the economic system was represented by a set of simple consumers. An important result emerging from this research is that at least one agent out of four in these experiments with accurate knowledge about market demand increases the wealth of the system as a whole. Markets containing a single Stackelberg or neural agent produced far more wealth than markets composed only of satisficing agents. However, the agents with knowledge do not necessarily capture the highest share of the wealth. The success of individual agents depends on the agent's trading strategy, as expected, and in addition depends on the combination of agents in the system. Certain strategies appeared to be flexible while others were brittle, and were easily foiled by changing the agents in the market, or by changing the market conditions. Earlier studies attempted to use neural networks to simulate an entire economic system, but were rejected because the organizing principles of the two systems are not analogous. Additionally, neural networks were successfully tested for solving various economics problems that were not related to the simulation of economic systems. Neural networks were found to effectively solve problems with missing and redundant data that are not directly solvable with well known methods such as least squares.
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Donald, Stephen Geoffrey. "Estimation of heteroskedastic limited dependent variable models." Thesis, University of British Columbia, 1990. http://hdl.handle.net/2429/30691.

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This thesis considers the problem of estimating limited dependent variable models when the latent residuals are heteroskedastic normally distributed random variables. Commonly used estimators are generally inconsistent in such situations. Two estimation methods that allow consistent estimation of the parameters of interest are presented and shown to be consistent when the latent residuals are heteroskedastic of unknown form. Both estimators use recent advances in the econometric literature on nonparametric estimation and deal with the unknown form of heteroskedasticity by approximating the variance using a Fourier series type approximation. The first estimator is based on the method of maximum likelihood and involves maximising the likelihood function by choice of the parameters of the variance function approximation and the other parameters of interest. Consistency is shown to hold in the three most popular limited dependent variable models — the Probit, Tobit, and sample selection models — provided that the number of terms in the approximation increases with the sample size. The second estimator, which can be used to estimate the Tobit and sample selection models, is based on a two-step procedure, using Fourier series approximations in both steps. Consistency and asymptotic normality are proven under restrictions on the rate of increase of the number of parameters in the approximating functions. Finally, a small Monte Carlo experiment is conducted to examine the small sample properties of the estimators. The results show that the estimators perform quite well and in many cases reduce the bias, relative to the commonly used estimators, with little or no efficiency loss.
Arts, Faculty of
Vancouver School of Economics
Graduate
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He, Yumei, and 何玉梅. "Essays on public infrastructure, industrial location and regional development." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B39707313.

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Tian, Huilan 1964. "Three essays on trade, resource and environment." Thesis, McGill University, 2002. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=38525.

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This dissertation comprises three essays under the title "Three Essays on Trade, Resource and Environment".
The first essay develops a model of international duopoly involving competition both in prices and in levels of environmental friendliness, and studies the implications of government policies. It is shown that, contrary to the conventional wisdom, a regulatory increase in the minimum required level of environmental friendliness of the imported goods may harm the home firm, and may result in an increase in the volume of imports. It may also have adverse effects on the environment. Whether consumers lose or gain from such a regulatory increase depends on consumption spillover effects. We also show that, under certain conditions, the duopoly's equilibrium choice of levels of environmental friendliness is socially optimal.
The second essay investigates the properties of the dynamics of population and resource in a model where the objective function is to maximize the utility level of the least advantaged generation. Unlike in models with a utilitarian objective where the typical outcome is a unique steady state, it is found in our model that there is a continuum of steady states. Which steady state will be approached depends on the initial conditions. We show that for relatively large values of the resource stock, each steady state is conditionally stable in the saddlepoint sense; but for small values of the resource stock, the approach path to a steady state is non-monotone in the state space. Along the approach path to a steady state, the implicit discount rate varies over time.
The third essay extends the existing literature on regulation of polluting firms by taking into account the dynamics of investment in pollution abatement capital. It confirms that, under perfect competition, a Pigouvian tax can create the correct incentive for firms to invest and guide firms to achieve the social optimum. This tax path is time consistent. However, when there is a large polluter with price taking behavior, while an efficient and time consistent tax path exists, it is no longer subgame perfect unless the damage cost function is linear in emission. A non-linear taxation rule needs to be designed to achieve the socially optimal outcome. In the case of monopoly, a pair of instruments, an emission tax and a production subsidy, can lead the monopolist to achieve the social optimum. However, if pre-commitment is not possible, it is shown that linear feedback rules cannot achieve the first best outcome.
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Books on the topic "Home economics Mathematical models"

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Wincoop, Eric Van. Is home bias in assets related to home bias in goods? Cambridge, Mass: National Bureau of Economic Research, 2006.

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Richard, Blundell, Preston Ian 1964-, and Walker Ian 1954-, eds. The measurement of household welfare. Cambridge: Cambridge University Press, 1994.

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Berkovec, James Arthur. A general equilibrium model of housing, taxes, and portfolio choice. Cambridge, MA: National Bureau of Economic Research, 1990.

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Hendershott, Patric H. Introducing risky housing and endogenous tenure choice into portfolio-based general equilibrium models. Cambridge, MA: National Bureau of Economic Research, 1989.

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Market demand: Theory and empirical evidence. Princeton, N.J: Princeton University Press, 1994.

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Hildenbrand, Werner. Market Demand: Theory and Empirical Evidence. Princeton, NJ, USA: Princeton University Press, 1994.

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Griffith, Rachel. Is distance dying at last?: Falling home bias in fixed effects models of patent citations. Cambridge, Mass: National Bureau of Economic Research, 2007.

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Griffith, Rachel. Is distance dying at last?: Falling home bias in fixed effects models of patent citations. Cambridge, MA: National Bureau of Economic Research, 2007.

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Donni, Olivier. Labor supply, home production and welfare comparisons. Bonn, Germany: IZA, 2005.

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Fondements de la division du travail dans les modèles économiques du ménage. Paris: AP éditions Arguments, 1992.

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Book chapters on the topic "Home economics Mathematical models"

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Scheinkman, José A. "Dynamic general equilibrium models — Two examples." In Mathematical Economics, 44–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/bfb0078158.

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Vali, Shapoor. "Nonlinear Models." In Principles of Mathematical Economics, 193–223. Paris: Atlantis Press, 2013. http://dx.doi.org/10.2991/978-94-6239-036-2_7.

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Rutsch, Martin. "Models and Methods." In Mathematical Modelling in Economics, 680–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-78508-5_65.

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Vali, Shapoor. "Nonlinear Models." In Principles of Mathematical Economics II, 123–49. Paris: Atlantis Press, 2015. http://dx.doi.org/10.2991/978-94-6239-088-1_7.

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Gleißner, Winfried. "Growth Models in Comparison." In Mathematical Modelling in Economics, 194–206. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-78508-5_19.

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Di Liddo, Andrea. "Counterfeiting Models: Mathematical/Economic." In Encyclopedia of Law and Economics, 418–22. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4614-7753-2_705.

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Di Liddo, Andrea. "Counterfeiting Models (Mathematical/Economic)." In Encyclopedia of Law and Economics, 1–5. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4614-7883-6_705-1.

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Di Liddo, Andrea. "Counterfeiting Models (Mathematical/Economic)." In Encyclopedia of Law and Economics, 1–5. New York, NY: Springer New York, 2021. http://dx.doi.org/10.1007/978-1-4614-7883-6_705-2.

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Simonovits, András. "Continuous-Time Models." In Mathematical Methods in Dynamic Economics, 136–53. London: Palgrave Macmillan UK, 2000. http://dx.doi.org/10.1057/9780230513532_7.

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Zaslavski, Alexander J. "Models with Unbounded Endogenous Economic Growth." In Monographs in Mathematical Economics, 351–70. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9298-7_10.

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Conference papers on the topic "Home economics Mathematical models"

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Moeschlin, Otto. "Von Neumann models and the oeuvre of Jerzy Łoś." In Game Theory and Mathematical Economics. Warsaw: Institute of Mathematics Polish Academy of Sciences, 2006. http://dx.doi.org/10.4064/bc71-0-20.

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Bula, Inese, and Dace Rika. "Arrow-Hahn economic models with weakened conditions of continuity." In Game Theory and Mathematical Economics. Warsaw: Institute of Mathematics Polish Academy of Sciences, 2006. http://dx.doi.org/10.4064/bc71-0-4.

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Arkit, Aleksandra. "The existence of globally stable price mechanisms for pure exchange models with upper semicontinuous multivalued excess demand." In Game Theory and Mathematical Economics. Warsaw: Institute of Mathematics Polish Academy of Sciences, 2006. http://dx.doi.org/10.4064/bc71-0-1.

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Bogomolov, Alexandr. "The effect of expeced events on the results of the forecasts in economic and mathematical models." In System analysis in economics – 2018. Prometheus publishing house, 2018. http://dx.doi.org/10.33278/sae-2018.eng.158-162.

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Gyulov, Tihomir B., Radoslav L. Valkov, George Venkov, Ralitza Kovacheva, and Vesela Pasheva. "Classical and Weak Solutions for Two Models in Mathematical Finance." In APPLICATIONS OF MATHEMATICS IN ENGINEERING AND ECONOMICS (AMEE '11): Proceedings of the 37th International Conference. AIP, 2011. http://dx.doi.org/10.1063/1.3664370.

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Chernyakov, Mikhail K., Maria M. Chernyakova, Irina A. Chernyakova, and Saidmukhtor S. Mokhtarzada. "Mathematical Models for Evaluating the Effectiveness of State Support for the Dairy Industry." In International Conference on Economics, Management and Technologies 2020 (ICEMT 2020). Paris, France: Atlantis Press, 2020. http://dx.doi.org/10.2991/aebmr.k.200509.002.

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Romadhoni, Ita Fatkhur, Luthfiyah Nurlaela, Any Sutiadiningsih, Nugrahani Astuti, and Suhartiningsih. "Re-Create Systematized Interpersonal Skills Learning Models in Millennial Vocational Education and Training." In 2nd International Conference on Social, Applied Science, and Technology in Home Economics (ICONHOMECS 2019). Paris, France: Atlantis Press, 2020. http://dx.doi.org/10.2991/assehr.k.200218.011.

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Suragan, Durvudkhan, and Gulaiym Oralsyn. "Inverse coefficient problems for mathematical models of one-dimensional heat transfer with a generalized condition of preservation of medium temperature." In APPLICATIONS OF MATHEMATICS IN ENGINEERING AND ECONOMICS (AMEE’16): Proceedings of the 42nd International Conference on Applications of Mathematics in Engineering and Economics. Author(s), 2016. http://dx.doi.org/10.1063/1.4968470.

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Klochko, Elena, and Kristina Karpenko. "Mathematical and Analytical Models of the Market of Commercial Real Estate: Monitoring, Analysis and Projected Growth in the Context of Clusterization." In 6th International Conference on Economics, Management, Law and Education (EMLE 2020). Paris, France: Atlantis Press, 2021. http://dx.doi.org/10.2991/aebmr.k.210210.062.

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Liu, Fang, Hao Liang, Hang Yu, and Xiaomei Tang. "Research Development and Application of Solar Thermal Storage With Phase Change Materials." In ASME 2010 4th International Conference on Energy Sustainability. ASMEDC, 2010. http://dx.doi.org/10.1115/es2010-90331.

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Research on efficient and economical thermal storage technology becomes common issue to the scholars. Especially research on PCMs becomes hot spot these years. In view of the discontinuity and instability of solar energy, efficient and economic research on energy storage technology occupies a very important position. This article summarizes and evaluates the research development and applications of solar thermal storage technology with PCMs both in China and the other countries. Including four parts: A review on preparation of new composite phase change materials and its thermophysical properties was carried out. Various heat transfer enhancement technology was overviewed. Including adding metal fill, adding graphite, capsule package, plus fins, adding carbon fiber and composite phase change materials, etc. Mathematical modeling of a latent heat thermal energy storage system (LHTES) was reviewed in recent years which is used for the optimum material selection and to assist in the optimal designing of the systems. The important characteristics of different models and their assumptions used are presented and discussed, the experimental validation of some models are also presented. The applications and prospects of PCMs used in the different fields were summarized, such as industry, agriculture, construction, textiles, electronic products, medicine, transportation etc. Finally, conclusions and perspectives were drawed. Hope to provide references to the other researchers in this field.
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Reports on the topic "Home economics Mathematical models"

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Balyk, Nadiia, Svitlana Leshchuk, and Dariia Yatsenyak. Developing a Mini Smart House model. [б. в.], February 2020. http://dx.doi.org/10.31812/123456789/3741.

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The work is devoted to designing a smart home educational model. The authors analyzed the literature in the field of the Internet of Things and identified the basic requirements for the training model. It contains the following levels: command, communication, management. The authors identify the main subsystems of the training model: communication, signaling, control of lighting, temperature, filling of the garbage container, monitoring of sensor data. The proposed smart home educational model takes into account the economic indicators of resource utilization, which gives the opportunity to save on payment for their consumption. The hardware components for the implementation of the Mini Smart House were selected in the article. It uses a variety of technologies to conveniently manage it and use renewable energy to power it. The model was produced independently by students involved in the STEM project. Research includes sketching, making construction parts, sensor assembly and Arduino boards, programming in the Arduino IDE environment, testing the functioning of the system. Research includes sketching, making some parts, assembly sensor and Arduino boards, programming in the Arduino IDE environment, testing the functioning of the system. Approbation Mini Smart House researches were conducted within activity the STEM-center of Physics and Mathematics Faculty of Ternopil Volodymyr Hnatiuk National Pedagogical University, in particular during the educational process and during numerous trainings and seminars for pupils and teachers of computer science.
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Pritchett, Lant, and Martina Viarengo. Learning Outcomes in Developing Countries: Four Hard Lessons from PISA-D. Research on Improving Systems of Education (RISE), April 2021. http://dx.doi.org/10.35489/bsg-rise-wp_2021/069.

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The learning crisis in developing countries is increasingly acknowledged (World Bank, 2018). The UN’s Sustainable Development Goals (SDG) include goals and targets for universal learning and the World Bank has adopted a goal of eliminating learning poverty. We use student level PISA-D results for seven countries (Cambodia, Ecuador, Guatemala, Honduras, Paraguay, Senegal, and Zambia) to examine inequality in learning outcomes at the global, country, and student level for public school students. We examine learning inequality using five dimensions of potential social disadvantage measured in PISA: sex, rurality, home language, immigrant status, and socio-economic status (SES)—using the PISA measure of ESCS (Economic, Social, and Cultural Status) to measure SES. We document four important facts. First, with the exception of Ecuador, less than a third of the advantaged (male, urban, native, home speakers of the language of instruction) and ESCS elite (plus 2 standard deviations above the mean) children enrolled in public schools in PISA-D countries reach the SDG minimal target of PISA level 2 or higher in mathematics (with similarly low levels for reading and science). Even if learning differentials of enrolled students along all five dimensions of disadvantage were eliminated, the vast majority of children in these countries would not reach the SDG minimum targets. Second, the inequality in learning outcomes of the in-school children who were assessed by the PISA by household ESCS is mostly smaller in these less developed countries than in OECD or high-performing non-OECD countries. If the PISA-D countries had the same relationship of learning to ESCS as Denmark (as an example of a typical OECD country) or Vietnam (a high-performing developing country) their enrolled ESCS disadvantaged children would do worse, not better, than they actually do. Third, the disadvantages in learning outcomes along four characteristics: sex, rurality, home language, and being an immigrant country are absolutely large, but still small compared to the enormous gap between the advantaged, ESCS average students, and the SDG minimums. Given the massive global inequalities, remediating within-country inequalities in learning, while undoubtedly important for equity and justice, leads to only modest gains towards the SDG targets. Fourth, even including both public and private school students, there are strikingly few children in PISA-D countries at high levels of performance. The absolute number of children at PISA level 4 or above (reached by roughly 30 percent of OECD children) in the low performing PISA-D countries is less than a few thousand individuals, sometimes only a few hundred—in some subjects and countries just double or single digits. These four hard lessons from PISA-D reinforce the need to address global equity by “raising the floor” and targeting low learning levels (Crouch and Rolleston, 2017; Crouch, Rolleston, and Gustafsson, 2020). As Vietnam and other recent successes show, this can be done in developing country settings if education systems align around learning to improve the effectiveness of the teaching and learning processes to improve early learning of foundational skills.
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Hlushak, Oksana M., Svetlana O. Semenyaka, Volodymyr V. Proshkin, Stanislav V. Sapozhnykov, and Oksana S. Lytvyn. The usage of digital technologies in the university training of future bachelors (having been based on the data of mathematical subjects). [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3860.

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This article demonstrates that mathematics in the system of higher education has outgrown the status of the general education subject and should become an integral part of the professional training of future bachelors, including economists, on the basis of intersubject connection with special subjects. Such aspects as the importance of improving the scientific and methodological support of mathematical training of students by means of digital technologies are revealed. It is specified that in order to implement the task of qualified training of students learning econometrics and economic and mathematical modeling, it is necessary to use digital technologies in two directions: for the organization of electronic educational space and in the process of solving applied problems at the junction of the branches of economics and mathematics. The advantages of using e-learning courses in the educational process are presented (such as providing individualization of the educational process in accordance with the needs, characteristics and capabilities of students; improving the quality and efficiency of the educational process; ensuring systematic monitoring of the educational quality). The unified structures of “Econometrics”, “Economic and mathematical modeling” based on the Moodle platform are the following ones. The article presents the results of the pedagogical experiment on the attitude of students to the use of e-learning course (ELC) in the educational process of Borys Grinchenko Kyiv University and Alfred Nobel University (Dnipro city). We found that the following metrics need improvement: availability of time-appropriate mathematical materials; individual approach in training; students’ self-expression and the development of their creativity in the e-learning process. The following opportunities are brought to light the possibilities of digital technologies for the construction and research of econometric models (based on the problem of dependence of the level of the Ukrainian population employment). Various stages of building and testing of the econometric model are characterized: identification of variables, specification of the model, parameterization and verification of the statistical significance of the obtained results.
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