Consumption Function Research Articles

Immigration of Medical Workers and Variable Labour Supply

This paper studies the effects of immigration policy on the immigration of foreign medical workers on the welfare and income distribution of home medical workers and labourers. We set up a simple small open economy with two traded goods and non-traded medical care services. In the economy, there exists a constant rate of labourers who get ill health and must leave their jobs and thereby lose part of their income. But they can reduce the loss of working time and income by consuming medical services. There are two channels that consumption of the medical service affects the welfare of consumers: (i) consumption of medical service raises the state of health and increases utility, and (ii) consumption of medical service reduces the leave period of labourers and raises their wage income (labour supply-enhancing effect). We see that the above second effect makes the effective price of the medical service for the consumer lower than its market price and causes consumption bias towards the consumption of medical services. To introduce the above properties of consumption of medical service, we define the effective expenditure function of the labourers and examine its properties and conduct comparative static analyses. JEL codes: F13, F22

An experimental investigation of the affect regulating properties of sugar consumption: Examining the roles of socially-oriented positive and negative affect

Obesity is a major public health concern, and sugar consumption is a key risk factor for obesity. Thus, there is a need to identify factors that may increase motivation to consume sugar. One such factor may be negative affect, as research has shown that negative affect increases motivation for and engagement in appetitive behaviors, including sugar consumption. The goal of the present study was to extend past research on the role of negative affect in sugar consumption by examining: (a) the effect of a socially-oriented negative affect induction (i.e., social rejection) on the consumption of flavored beverages with varying levels of sugar, and (b) the negative and positive affect regulating properties of varying levels of sugar consumption. Undergraduate students (N = 116) were randomized to receive either a neutral or socially-oriented negative affect induction. Participants were then presented with three flavored beverages with varying levels of sugar (low, medium, high). Negative and positive affect were assessed prior to and following the affect induction procedure, as well as following consumption of the beverage. Participants exposed to the negative affect induction consumed a larger volume of the high sugar beverage (as well as a larger volume of all sugary beverages) relative to participants in the neutral induction condition. Moreover, these findings could not be attributed to a greater preference for the high sugar beverage among participants in the negative affect condition. Additionally, lower levels of positive affect post-induction across all participants (regardless of condition) were associated with greater consumption of the high sugar beverage, and high sugar beverage consumption was significantly positively associated with post-consumption positive affect. Results provide evidence for an affect-regulating function of sugar consumption following social rejection.

Glucagon-like peptide-1 receptor differentially controls mossy cell activity across the dentate gyrus longitudinal axis.

Understanding the role of dentate gyrus (DG) mossy cells (MCs) in learning and memory has rapidly evolved due to increasingly precise methods for targeting MCs and for in vivo recording and activity manipulation in rodents. These studies have shown MCs are highly active in vivo, strongly remap to contextual manipulation, and that their inhibition or hyperactivation impairs pattern separation and location or context discrimination. Less well understood is how MC activity is modulated by neurohormonal mechanisms, which might differentially control the participation of MCs in cognitive functions during discrete states, such as hunger or satiety. In this study, we demonstrate that glucagon-like peptide-1 (GLP-1), a neuropeptide produced in the gut and the brain that regulates food consumption and hippocampal-dependent mnemonic function, might regulate MC function through expression of its receptor, GLP-1R. RNA-seq demonstrated that most, though not all, Glp1r in hippocampal principal neurons is expressed in MCs, and in situ hybridization revealed strong expression of Glp1r in hilar neurons. Glp1r-ires-Cre mice crossed with Ai14D reporter mice followed by co-labeling for the MC marker GluR2/3 revealed that almost all MCs in the ventral DG expressed Glp1r and that almost all Glp1r-expressing hilar neurons were MCs. However, only ~60% of dorsal DG MCs expressed Glp1r, and Glp1r was also expressed in small hilar neurons that were not MCs. Consistent with this expression pattern, peripheral administration of the GLP-1R agonist exendin-4 (5μg/kg) increased cFos expression in ventral but not dorsal DG hilar neurons. Finally, whole-cell patch-clamp recordings from ventral MCs showed that bath application of exendin-4 (200 nM) depolarized MCs and increased action potential firing. Taken together, this study adds to known MC activity modulators a neurohormonal mechanism that may preferentially affect ventral DG physiology and may potentially be targetable by several GLP-1R pharmacotherapies already in clinical use.

Sugar-sweetened beverages consumption is associated with worse cognitive functions in older adults: from the national health and nutrition examination survey and food patterns equivalents database

ABSTRACT Objectives: This study aimed to investigate the association between sugar-sweetened beverages (SSB) consumption (including individual SSB) and cognitive function from the National Health and Nutrition Examination Survey (NHANES) and Food Patterns Equivalents Database (FPED) and whether it is age-dependent. Methods: Older adults aged 60 years old and over were included during the NHANES 2011–2014. SSB consumption was defined as the amount of added sugar obtained by connecting the NHANES and FPED. Cognitive function tests included the consortium to establish a registry for Alzheimer's disease test, Animal Fluency Test and Digit Symbol Substitution Test. We calculated z-score using the average of the total standardized scores on three cognitive tests to estimate the level of whole cognition. Multi-variable linear regression models and interaction analysis were conducted in this study. Results: For individual SSB types, increased carbonated soft drinks, sweetened tea, fruit drinks, energy drinks, and sport drinks were all significantly linked to declined cognitive function (P < 0.05), respectively. Nevertheless, interaction effects by age groups were not significant (P for interaction > 0.05). Discussion: SSB consumption (including individual SSB) was negatively associated with cognitive function, which was not age-dependent. Future studies may advance the knowledge in the field considering the association between SSB consumption and cognitive function.

Energy-Dependent Particle Size Distribution Models for Multi-Disc Mill.

Comminution is important in the processing of biological materials, such as cereal grains, wood biomass, and food waste. The most popular biomaterial grinders are hammer and roller mills. However, the grinders with great potential in the processing of biomass are mills that use cutting, e.g., disc mills. When it comes to single-disc and multi-disc grinders, there are not many studies describing the relationships between energy, motion, material, and processing or describing the effect of grinding, meaning the size distribution of a product. The relationship between the energy and size reduction ratio of disc-type grinder designs has also not been sufficiently explored. The purpose of this paper was to develop models for the particle size distribution of the ground product in multi-disc mills depending on the variable process parameters, i.e., disc rotational velocity and, consequently, power consumption, and the relationship between the grinding energy and the shape of graining curves, which would help predict the product size reduction ratio for these machines. The experiment was performed using a five-disc mill, assuming the angular velocity of the grinder discs was variable. Power consumption, product particle size, and specific comminution energy were recorded during the tests. The Rosin–Rammler–Sperling–Bennet (RRSB) distribution curves were established for the ground samples, and the relationships between distribution coefficients and the average angular velocity of grinder discs, power consumption, and specific comminution energy were determined. The tests showed that the specific comminution energy increases as the size reduction ratio increases. It was also demonstrated that the RRSB distribution coefficients could be represented by the functions of angular velocities, power consumption, and specific comminution energy. The developed models will be a source of information for numerical modelling of comminution processes.

A Novel Method for Estimating Parameters of Battery Electric Vehicles

In this study, an artificial neural network was employed to calculate and simulate the inverse functions of battery electric vehicle parameters. One of the objectives of this work is to develop a model that can accurately estimate up to nine parameters at once, given nine variables. Datasets from manufacturers of battery electric cars were employed in this study to generate direct functions using an artificial neural network. In this case, a direct function model was developed. The output of the direct function model was now combined with virtual or dummy functions to form the input variables for the inverse function model. In this case, an inverse function model was developed. Nine variables were calculated and simulated as the outputs by the inverse function model at the same time. The procedure was completed for the nine cases where each of the augmented input variables of the inverse function model was the output of the direct function model. The results of the inverse function model with virtual functions were compared with those of the model without virtual functions. For all the nine cases considered, the inverse function model with virtual functions had greater or better accuracy than the model without dummy functions. Accuracy was 145.7 times higher in terms of mean square error when electrical charge consumption and virtual functions were employed as input variables into the inverse function model. This implies that the proposed approach, which involves the augmentation of the input of the inverse function model, is more efficient and accurate than the one without virtual functions. Augmentation with virtual functions improved the simulating capability of the inverse function model.

The Impact of the COVID-19 Pandemic on Household Financial Well-being

Purpose: The current research is one of the few studies investigating the impact of COVID-19 on shattered households' financial well-being in light of Friedman's Theory of Consumption Function. It explored if there are statistical differences in the impact of COVID-19 due to the demographic variables of the study.&#x0D; Design/methodology/approach: The study is descriptive and analytical. It used an online survey that targeted respondents representing 387 Palestinian households randomly selected from the community of the Gaza Strip.&#x0D; Findings: The results showed a negative impact of the COVID-19 pandemic on households' financial well-being. It also revealed these households' lack of financial resilience due to the combined effect of the pandemic and the concurrent siege and its economic drawbacks. The statistical results demonstrated no statistically significant differences in the households' mean financial well-being scores due to gender before and during the COVID-19 pandemic. In contrast, it was found that there are statistically significant differences in the households' mean scores of financial well-being due to the (education level, number of household members, employability status, and the number of households' breadwinners) before and during the COVID-19 pandemic.&#x0D; Research limitations/implications: The researcher conducted an online survey among the general population in the Gaza Strip during the COVID-19 pandemic between the 2nd and 5th of June 2021. Although the results of this study are based on the Palestinian context, the main hypotheses can be tested in other countries to assess the impact of COVID-19 on household financial well-being, especially in emerging countries.&#x0D; Originality/value: This study is the first to address the financial and economic effects of the COVID-19 pandemic on households already shattered and torn by suffrage political and economic inequalities. It also demonstrates how people in emergencies tend to respond to the resulting conditions of the pandemic in the light of Friedman's Theory of the Consumption Function.

Wildfire impacts on western United States snowpacks

Mountain snowpacks provide 53–78% of water used for irrigation, municipalities, and industrial consumption in the western United States. Snowpacks serve as natural reservoirs during the winter months and play an essential role in water storage for human consumption and ecosystem functions. However, wildfires across the West are increasing in severity, size, and frequency, progressively putting snowpacks at risk as they burn further into the seasonal snow zone. Following a fire, snow disappears 4–23 days earlier and melt rates increase by up to 57%. In a high burn severity fire in the Oregon Cascades, the black carbon and charred woody debris shed from burned trees onto the snowpack decreased the snow albedo by 40%. Canopy cover loss causes a 60% increase in solar radiation reaching the snow surface. Together, these effects produce a 200% increase in net shortwave radiation absorbed by the snowpack. This mini-review synthesizes the implications of wildfire for snow hydrology in mountainous watersheds with the primary aim to characterize wildfires' varied influences on the volume and timing of water resources across time scales (daily to decadal), space (plot to watershed) and burn severity (low to high). The increase in the geographical overlap between fire and snow poses unique challenges for managing snow-dominated watersheds and highlights deficiencies in research and operational snow hydrologic modeling, emphasizing the need for additional field and remote-sensing observations and model experiments.

Association of sugar-sweetened beverages with executive function in autistic children

The association between sugar-sweetened beverages (SSBs) consumption and executive function (EF) among typically developing (TD) children has been investigated in previous studies but with inconsistent results. Furthermore, this relationship has been less investigated among autistic children who perform worse in EF compared with TD children. In this study, we aimed to investigate the association between SSB consumption and EF in autistic children, and whether the association between SSB and EF in autistic children is different from that in TD children. We recruited 106 autistic children and 207 TD children aged 6–12 years in Guangzhou, China. Children’s EF was assessed by using the Chinese version of parent-reported Behavior Rating Inventory of Executive Function, Stroop Color–Word Test, and working memory subscales of the Chinese version of Wechsler Intelligence Scale for children, Fourth edition. Meanwhile, we assessed children’s dietary intake and SSB consumption with a validated Food Frequency Questionnaire. In this study, 70 (66.0%) autistic children consumed SSB and 20 (18.9%) of them consumed more than two servings SSB a week. Among autistic children, over two servings per week SSB consumption was associated with poorer performance in emotional control [β = 7.20, 95% confidence interval (CI): 0.94–13.46] and plan/Organize (β = 6.45, 95% CI: 0.27–12.63). The association between over two servings/week SSB consumption and emotional control among autistic children was significantly different from that among TD children (βASD = 7.20; βTD = −3.09, Z = 2.72, p = 0.006). Results of this study show that SSB consumption was associated with an impairment in some subscales of EF in autistic children. Furthermore, the association between SSB and EF in autistic children might be different from that in TD children.

Dynamic ARDL Simulations Effects of Fiscal Decentralization, Green Technological Innovation, Trade Openness, and Institutional Quality on Environmental Sustainability: Evidence from South Africa

Fiscal decentralization and green innovation are important to a country’s economic progress, but the externalities of increased pollution as a result of a rise in the energy used and economic growth must not be overlooked. The destruction of the environment presents a serious threat to human existence. South Africa, like several nations, has been working on reducing its dependence on fossil fuels such as coal by utilizing modern energy-efficient technologies that allow to establish a more carbon-neutral economy. Several attempts have been made to identify the major sources of environmental deterioration. Within the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) framework from 1960 to 2020, this study aims to check empirically the effect of fiscal decentralization (FD), green technological innovation (GI), trade openness (OPEN), population size (POP), per capita GDP (GDP), per capita GDP squared (GDP2), institutional quality (INS), and energy consumption (EC) on carbon emissions (CO2) in South Africa, as given its fast economic progress the country is facing problems with CO2 emission. The recently developed novel dynamic autoregressive distributed lag (ARDL)-simulations framework has been used. The outcomes of the analysis indicate that (i) FD, GI, and INS improve environmental sustainability in both the short and long run; (ii) OPEN deteriorates environmental quality in the long run, although it is environmentally friendly in the short run; (iii) per capita GDP increases CO2 emissions, whereas its square contributes to lower it, thus validating the presence of an environmental Kuznets curve (EKC) hypothesis; (iii) POP and EC contribute to environmental deterioration in both the short and long run; and (iv) FD, GI, OPEN, POP, GDP, GDP2, INS, and EC Granger cause CO2 in the medium, long, and short run, suggesting that these variables are important to influence environmental sustainability. In light of our empirical evidence, this paper suggests that the international teamwork necessary to lessen carbon emissions is immensely critical to solve the growing trans-boundary environmental decay and other associated spillover consequences. Moreover, it is important to explain responsibilities at different tiers of government to effectively meet the objectives of low CO2 emissions and energy-saving fiscal expenditure functions.

Estimation of Consumption Functions Using Savings Motive Hypothesis (SMH)

In this paper a new consumption function is derived based on savings motive hypothesis (SMH). The major theory behind the SMH is that households save part of their income in period 1 and transfer it to period 2. Implying that consumption in period 1 is the addition of autonomous consumption and variable consumption in period 2. The validity of the SMH is tested by using data from India, Kenya, South Africa, Saudi Arabia, UK and USA for the period 1970 to 2018. The data analyses are performed by using World Bank Data and generalized least squares (GLS) method. The paper demonstrates that estimation of the consumption function could be done more accurately by using SMH of the consumption function. The MSH is based on the psychological savings motive theory. Some results in the paper can be used in making both household and national welfare decisions e.g. making use of the short run global marginal propensity to consume that is found to be 0.43.

The New Economic Era Analysis of the Structure System of Chinese Household Consumption Expenditure Based on the ELES Model.

In recent years, the new economy has entered a phase of rapid development and upgrading China's service consumption is driving the continuous optimization of the population's consumption structure. To realize the rationalization of the Chinese household consumption structure, the ELES model is used to analyze the structure system of Chinese household consumption expenditure. This article constructs the ELES model, divides the types of Chinese household consumption expenditure structure systems, establishes consumption expenditure function, analyzes the influencing factors of the consumption expenditure structure system, and obtains the analysis results from static and dynamic aspects. Based on the statistics of Chinese household consumption expenditure data in recent years, this article obtains the analysis results of the consumption expenditure structure system: the basic consumption demand and marginal consumption tendency of food are in the first place, and the consumption expenditure structure system has gradually changed into the development-type and enjoyment-type consumption mode. Through increasing the income of rural residents, guiding reasonable consumption concept, optimizing consumption environment, and so on, we can promote the proposal and implementation of the optimization of China's household consumption expenditure structure system to improve the rationalization of China's household consumption structure system.

Economic growth and global warming effects on electricity consumption in Spain: a sectoral study

This paper analyzes the effect of certain factors on electricity consumption in Spain at a sectoral level. An electricity consumption function has been estimated by using panel data, depending on gross value added (GVA), temperatures, capitalization, and human capital. This function is obtained for total productive electricity consumption and for the agricultural, construction, industrial, service, and public administration sectors, referring to the 17 Autonomous Communities of Spain for the 2000–2013 period. The obtained results show important sectoral differences in the effect that GVA has on electricity consumption, indicating a positive and increasing effect of temperatures above 22 °C in the total economy and in the tertiary sector, and a negative effect of temperatures below 18 °C in some sectors. These results may indicate that global warming may induce an electricity demand growth in Spain, especially related to cooling needs. The results also highlight the positive effects of capitalization in all sectors, and the negative effects of human capital, except for the public administration sector. In this context, it may be appropriate to carry out policies that mitigate this consumption growth, reinforcing energy efficiency measures, and human capital investments.

Hidden Figures: A New History of the Permanent Income Hypothesis

Abstract This article uses archival sources to reconstruct an alternate history of Milton Friedman's A Theory of the Consumption Function, spotlighting the contributions of his collaborators Margaret Reid, Dorothy Brady, and Rose Friedman. Although Milton Friedman offered public credit to his wife and their two close friends, none received formal recognition or reward for their contribution to the permanent income hypothesis. The article documents this hypothesis as an example in professional economics of the well-known “Matilda effect,” in which women's intellectual contributions are systemically devalued, while arguing it is important to distinguish between formal and informal credit. Further, the article connects the lower status of women's consumption economics to broader shifts in the economics discipline across the twentieth century.

Response of China's electricity consumption to climate change using monthly household data.

Intensifying climate change significantly impacts residential electricity consumption, especially in developing countries, such as China, that are experiencing rapid income growth. By combining meteorological and monthly household consumption survey data, this study explores the response function of residential electricity consumption to temperature in China from a micro perspective. Future residential electricity demands and related CO2 emissions are then forecast under different climate scenarios. Overall, the response function is U-shaped, and one additional day above 34 °C will increase monthly residential electricity consumption by 2.11%. Global warming will more likely increase the electricity burden on low-income groups. There will be notable seasonal changes in electricity demand in the future, and the largest increase will occur in August. The total demand for residential electricity caused by temperature change will show a fluctuating growth trend, from 0.8% and 1% in 2025 to 2% and 2.9% in 2060 under the RCP4.5 scenario and RCP8.5 scenario, respectively; meanwhile, this demand will be accompanied by a cumulative increase in carbon dioxide emissions.

Driving Robot for Reproducible Testing: A Novel Combination of Pedal and Steering Robot on a Steerable Vehicle Test Bench

Shorter development times, increased standards for vehicle emissions and a greater number of vehicle variants result in a higher level of complexity in the vehicle development process. Efficient development of powertrain and driver assistance functions under comparable and reproducible operating conditions is possible on vehicle test benches. Yet, the realistic simulation of real driving environments on test benches is a challenge. Current test procedures and new technologies, such as Real Driving Emission tests and Autonomous Driving, require a reproducible and even more detailed simulation of the driving environment. Due to this, the simulation of curve driving in particular is gaining in importance. This results from its significant influence on energy consumption and Autonomous Driving functions with lateral guidance, such as lane departure and evasion assistance. Reproducibility can be additionally increased by using a driving robot. At today’s vehicle test benches, pedal and shift robots are predominantly used for longitudinal dynamic tests in the performed test procedures. In order to meet these new test automation requirements for vehicle test benches, the cooperative operation of pedal and steering robots is needed on a test bench setup suitable for this purpose. In this publication, the authors present the setup of a vehicle test bench to be used in automated and reproducible vehicle-in-the-loop tests during steering events. The focus is on the test-bench-specific setup with steerable front wheels, the actuators for simulating the wheel steering torque around the steering axle and the robots used for pedals and steering wheel. Results from various test series are presented and the potential of the novel test environment is shown. The results are reproducible in various test series due to the closed-loop operation without human driving influences at the test bench.

The impact of liquidity constraints and cashflows on the optimal retirement problem

In this work we analytically solve an optimal retirement problem, in which the agent optimally allocates consumption, leisure rate and invests in a risk-free and risky asset to maximize a gain function characterized by a power utility function of consumption and leisure, through the duality method. The model is general enough to be compatible with both lifetime debt repayments and pension plans. We impose different liquidity constraints and cashflows over different time spans and conduct a sensitivity analysis to discover the effect of this kind of constraint. We show that pre- and post-retirement constraints have opposite effects on optimal wealth threshold of retirement. Moreover, pre-retirement constraints do not impact on post-retirement control strategies, while the opposite does not hold true.

Resource-controlled stochastic customer order scheduling via particle swarm optimization with bound information

PurposeCycle time reduction is important for order fulling process but often subject to resource constraints. This study considers an unrelated parallel machine environment where orders with random demands arrive dynamically. Processing speeds are controlled by resource allocation and subject to diminishing marginal returns. The objective is to minimize long-run expected order cycle time via order schedule and resource allocation decisions.Design/methodology/approachA stochastic optimization algorithm named CAP is proposed based on particle swarm optimization framework. It takes advantage of derived bound information to improve local search efficiency. Parameter impacts including demand variance, product type number, machine speed and resource coefficient are also analyzed through theoretic studies. The algorithm is evaluated and benchmarked with four well-known algorithms via extensive numerical experiments.FindingsFirst, cycle time can be significantly improved when demand randomness is reduced via better forecasting. Second, achieving processing balance should be of top priority when considering resource allocation. Third, given marginal returns on resource consumption, it is advisable to allocate more resources to resource-sensitive machines.Originality/valueA novel PSO-based optimization algorithm is proposed to jointly optimize order schedule and resource allocation decisions in a dynamic environment with random demands and stochastic arrivals. A general quadratic resource consumption function is adopted to better capture diminishing marginal returns.

The Mental Health Education Management of Higher Vocational Students Based on Fractional Differential Equations

Abstract Based on fractional differential equations, this paper proposes an optimization modeling method for the mental health quality of vocational students. This article quantifies the psychology of higher vocational students from the perspective of fractional differential equations. At the same time, we use alertness to characterize the risk of mental fatigue and propose a mental health energy equation. We propose a mental health energy replenishment function and consumption function and describe mental health energy during sleep. Finally, we use fractional differential equations to reason about the model deductively. The research shows that it is feasible for us to apply fractional differential equations to predict the mental health problems of vocational students.

The effect of industrialization, militarization, and government expenditure on carbon dioxide emissions in Ghana.

The need to attain lower carbon dioxide emissions has become a topical issue in recent times. The effect of a number of economic variables on carbon dioxide emissions has been empirically assessed. Rising government expenditure, industrialization, and militarization have characterized many developing countries including Ghana. While it is undeniable that such situation has socio-economic importance to offer developing countries, their environmental effects have become a matter of debate among researchers. This study assesses the carbon dioxide emissions effect of industrialization, government expenditure, and militarization in Ghana. Based on the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) framework, the study models Ghana's carbon emission as a function of income, population, industrialization, government expenditure, and military expenditure. Time series data over the 1971-2018 period was used for investigation. The techniques employed to analyze the data were unit root test, cointegration test, and regression analysis. The autoregressive distributed lag (ARDL) regression approach reveals there is an inverted U-shaped relationship between income and carbon emission confirming the environmental Kuznets curve hypothesis. Also in the long run, carbon emissions are positively influenced by population, industrialization, and militarization but reduced by government expenditure. Similar outcome was obtained in the short run. The paper concludes that the level of income, industrialization, militarization, and population matters to deal with carbon dioxide emissions in Ghana. Policy implications of the findings include the urgent need for authorities to promote the use of eco-friendly production methods for military and industrial activities to sustain the economic growth without harming the environment.