Relevant bibliographies by topics / Price elasticity

Academic literature on the topic 'Price elasticity'

Author: Grafiati
Published: 4 June 2021
Last updated: 11 March 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Contents

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Price elasticity.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Price elasticity"

1

Syirah Murandawi, M. Luthfi, Fajri Jakfar, and Mustafa Mustafa. "Analsisi Elastisitas Permintaan Konsumen Rumah Tangga Terhadap Telur Ayam Ras di Kota Banda Aceh." Jurnal Ilmiah Mahasiswa Pertanian 3, no. 3 (August 1, 2018): 54–65. http://dx.doi.org/10.17969/jimfp.v3i3.8108.

Full text
Abstract:
Abstract. Chicken Eggs Demand race in Banda Aceh city influenced by the price of eggs, the price of fish, cooking oil prices, income and number of dependents. This study aims to look at the demand for chicken eggs dipengaruhhi by the price of eggs, the price of fish, cooking oil prices, income and number of dependents, and to see the price elasticity, cross elasticity and income elasticity. Withdrawal of samples obtained by the method of proportional stratified random samplingin Banda Aceh where for high income states 25, middle 65 and lower 33 samples. The technique is passed on this peneitian with Multiple Linear Regression. The results of this study show the price of eggs, the price of fish, cooking oil prices, income and number of dependents significant effect simultaneously, and the price elasticity of its elastic for medium and low, while high-inelastic, the cross elasticity of substitution for fish and complementary to cooking oil, and for its income elasticity of eggs belonging to inferior goodsAnalysis of elasticity of demand for eggs in banda aceh cityAbstract. Demand for Chicken Eggs in the city of banda aceh is influenced by the price of eggs, the price of the egg, the price of cooking oil, the income and the number of dependents. This study aims to see the demand for chicken eggs influenced by the price of eggs, the price of the village egg, the price of cooking oil, the income and the number of dependents and to see the price elasticity, cross elasticity and income elasticity. Sampling was obtained by multi stage cluster random sampling method in Kota Banda Aceh with a sample of 46 family heads. Techniques performed on this study with Multiple Linear Regression. The results of this study indicate the price of eggs, the price of eggs, the price of cooking oil, the income and the number of dependents have a significant effect simultaneously, while partially only the price of eggs, the price of cooking oil and the number of dependents that have real effect, and elasticity of its price elastic , cross-substitution elasticity for chicken eggs and complementary for cooking oil, and for his income elasticity of chicken eggs belonging to normal goods.
APA, Harvard, Vancouver, ISO, and other styles
2

Chai, Jian, Huiting Shi, Xiaoyang Zhou, and Shouyang Wang. "The Price Elasticity of Natural Gas Demand in China: A Meta-Regression Analysis." Energies 11, no. 12 (November 22, 2018): 3255. http://dx.doi.org/10.3390/en11123255.

Full text
Abstract:
Since natural gas has become a new star in China’s energy mix, a reliable estimation of the price elasticity of natural gas demand is crucial if we are to understand how energy price changes affect natural gas consumption. In this paper, we conduct a Meta-regression analysis to quantitatively synthesize empirical estimates of the price elasticity of natural gas demand reported in previous studies, provide true underlying values, and explain the heterogeneity of the aforementioned estimates. The Fixed-effects model and ordinary least squares (OLS) are applied to estimate the regression models. As a result, this paper reports a mean elasticity of −1.521 and 0.410 for the short- and long-run own-price elasticity, separately; −0.762 and 0.008 for the short- and long-run cross-price elasticity-coal to natural gas, respectively; 2.122 and 1.884 for the short- and long-run cross-price elasticity-electricity to natural gas, separately; and 2.267 and 1.275 for the short- and long-run cross-price elasticity-oil to natural gas, respectively. Our results suggest that natural gas consumption increases with the decrease of its own and coal prices in the short term and rise of electricity and oil prices. It also shows that almost all heterogeneity can be explained by the type of data, sample period, models of analysis, geographical region, and type of consumer.
APA, Harvard, Vancouver, ISO, and other styles
3

Juswadi, Juri, and Pandu Sumarna. "Elastisitas Transmisi Harga Komoditas Buah Pepaya Di Kabupaten Indramayu Jawa Barat." Paspalum: Jurnal Ilmiah Pertanian 10, no. 2 (September 30, 2022): 259. http://dx.doi.org/10.35138/paspalum.v10i2.464.

Full text
Abstract:
This study aims to analyze the elasticity price transmission of papaya fruit at the farmer level (producer) and at the consumer level (retailer) in Indramayu Regency. Papaya is one of the fruits favored by the public because of its vitamin content, fresh taste, and low price. The price transmission elasticity (Et) analysis uses a simple regression between two prices, namely prices at the farm level and at the retailer level. The research data uses time series data on monthly papaya prices at the farmer level and at the consumer level in Indramayu Regency during the 2014-2020 period. The results of the analysis show that the price elasticity of papaya fruit in Indramayu Regency is inelastic (Et < 1). This shows that price changes at the farmer level are smaller than the price changes at the retail level. This means that farmers have not received good prices from traders.
APA, Harvard, Vancouver, ISO, and other styles
4

Kusumaningrum, Stranti Nastiti. "The Sensitivity of Residential Electricity Demand in Indonesia." Signifikan: Jurnal Ilmu Ekonomi 7, no. 2 (March 25, 2018): 247–66. http://dx.doi.org/10.15408/sjie.v7i2.6048.

Full text
Abstract:
Since 2013, the residential electricity price for High VA (Volt-Ampere) households has changed due to changes in pricing policies. This paper analyzes the responsiveness of residential electricity demand to the change in electricity prices and income among two different household groups (Low VA and High VA) in 2011 and 2014. Using an electricity consumption model and the Quantile Regression method, the results show that residential electricity demand is price and income inelastic. Income elasticity is lower than price elasticity. Furthermore, the effects on price elasticity also found in the Low VA group, whose rate remained stable. At the same time, evidence proves the impact of the change in pricing policy on income elasticity remains unclear. This result implies that the government has to be more careful in regulating electricity prices for the low VA group, while maintaining economic stability.DOI: 10.15408/sjie.v7i2.6048
APA, Harvard, Vancouver, ISO, and other styles
5

Frondel, Manuel, Delia A. Niehues, and Stephan Sommer. "Wasserverbrauch privater Haushalte in Deutschland: Eine empirische Mikroanalyse." Zeitschrift für Wirtschaftspolitik 70, no. 3 (November 29, 2021): 230–54. http://dx.doi.org/10.1515/zfwp-2021-2061.

Full text
Abstract:
Abstract Germany is a rather water-rich country. Nevertheless, climatic changes might make it necessary to use water resources carefully in the future, especially in times of drought. Against this background, this paper estimates the price elasticity of household water consumption, differentiating between households that have a rough knowledge of water prices and households that do not. Based on about 1,100 observations for households living in single-family houses and using the sum of cubic meter prices for water and wastewater as price measure, we find a moderate but statistically significantly non-zero price elasticity of -0.102. Households that have knowledge of water prices tend to exhibit a higher elasticity, while households without price knowledge do not show a statistically significant response in their water consumption. Prices can thus only be used to a limited extent as a means of controlling water consumption.
APA, Harvard, Vancouver, ISO, and other styles
6

Fadhlan Syihabuddin, Elinur, and Sisca Vaulina. "PERMINTAAN DAGING SAPI DI PROVINSI RIAU." DINAMIKA PERTANIAN 35, no. 1 (September 15, 2021): 33–40. http://dx.doi.org/10.25299/dp.2019.vol35(1).7684.

Full text
Abstract:
The husbandry sub-sector is a source of supporting energy for human needs, especially beef. Beef is a food commodity that has had an impact on improving public nutrition, especially animal protein. This study aims to analyze the development of beef demand and variables that influence it in Riau, the factors that influence beef demand in Riau Province, and the price elasticity, income elasticity, and cross elasticity of factors affecting meat demand beef in Riau Province. This research used the literature study. The data used in this research was data time series from 1999 to 2015. Data were analyzed using descriptive statistics, multiple linear regression, and elasticity. The results showed that the overall average development of beef demand, beef prices, chicken meat prices, rice prices, population income, and the population increased during the period. The factors that significantly influence the demand for beef were the price of beef and the price of rice. Meanwhile, the price of chicken meat, the income of the population, and the population had no significant to the demand for beef. The results of the elasticity calculation of demand showed that beef prices, rice prices, and population income were responsive to beef demand. This indicates that changes in beef prices, rice prices, and population income had a major impact on changes in demand for beef.
APA, Harvard, Vancouver, ISO, and other styles
7

Stalon, Charles G. "More price elasticity desirable." Natural Gas 16, no. 3 (January 9, 2007): 24–29. http://dx.doi.org/10.1002/gas.3410160306.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Gao, Dan, Zheng Li, Cheng Gang Yang, Pei Liu, Lin Wei Ma, and Hong Xu. "China Oil Price-GDP Elasticity Coefficient and Optimal Strategic Petroleum Reserve Scale Analysis." Advanced Materials Research 347-353 (October 2011): 98–102. http://dx.doi.org/10.4028/www.scientific.net/amr.347-353.98.

Full text
Abstract:
The rising international oil prices will cause the loss of national GDP and the establishment of strategic petroleum reserves (SPR) could avoid this loss as much as possible. The oil price-GDP elasticity coefficient is an important parameter in calculating strategic petroleum reserve, but since it is difficult to obtain, it is also hard to calculate. This paper provides the fitting formula of oil price-GDP elasticity coefficient based on the regression analyzing of literature data. China’s oil price-GDP elasticity coefficient in recent years has been analyzed and predictions for future trends in different situations have been made. Finally, the predicted oil price-GDP elasticity coefficient is used to calculate the size of China's strategic petroleum reserve and its earnings.
APA, Harvard, Vancouver, ISO, and other styles
9

Saidin Nainggolan, Yanuar Fitri, Riri Oktari Ulma, and Cynthia Cleantha br. Sinuraya. "Estimation of the profit function of Trans log and the elasticity of input demand in rice farming in Jambi province." GSC Advanced Research and Reviews 13, no. 1 (October 30, 2022): 169–75. http://dx.doi.org/10.30574/gscarr.2022.13.1.0266.

Full text
Abstract:
This study aims to analyze the development of input and output prices, the translog profit function, and the elasticity of demand for lowland rice farming inputs in Jambi Province. The function model used is the Transcendental Logarithmic (Translog) profit function. The study results show that · The development of input prices has increased significantly every year. · The production input factors that affect the profitability of lowland rice farming are the price of seeds, TSP fertilizer, and other chemical fertilizers (KML). Other production factors such as urea fertilizer prices, pesticide prices, labor wages, and land rental costs are determinant factors. · The value of the elasticity of demand for inputs to their prices is elastic. All cross-price elasticity of demand is complementary and elastic. The value of the elasticity of input demand which is influenced by the price of rice shows a positive and elastic value. From the results of the study, it is expected that there will be capital assistance for farmers so that farmers can allocate optimal use of inputs.
APA, Harvard, Vancouver, ISO, and other styles
10

Chelwa, Grieve, and Corne van Walbeek. "Does cigarette demand respond to price increases in Uganda? Price elasticity estimates using the Uganda National Panel Survey and Deaton’s method." BMJ Open 9, no. 3 (March 2019): e026150. http://dx.doi.org/10.1136/bmjopen-2018-026150.

Full text
Abstract:
ObjectiveTo provide the first published estimates of the price elasticity of demand for cigarettes in Uganda and thereby contribute to growing the evidence base of the likely impact of excise taxes on cigarette consumption and tax revenues in Sub-Saharan Africa.MethodWe use a linear approximation of the Almost Ideal Demand System along with expenditure data from the Uganda National Panel Survey and exploit the fact that prices of cigarettes vary across geographical space in Uganda.ResultsWe find that cigarettes are price inelastic in Uganda with elasticity estimates ranging between −0.26 and −0.33. That is, we expect that cigarette demand will decline by between 2.6% and 3.3% every time cigarette prices rise by 10%. These elasticity estimates are in line with international evidence and are robust to outliers in the data.ConclusionOur estimates of the price elasticity of demand for cigarettes suggest that the authorities in Uganda can reduce cigarette consumption and simultaneously increase tax revenues by increasing the excise taxes on cigarettes.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Price elasticity"

1

Emir, Akin. "Delivery pricing for different demand price elasticity functions." [Gainesville, Fla.] : University of Florida, 2002. http://purl.fcla.edu/fcla/etd/UFE1001138.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Joslyn-Battaglia, Kari. "The Relationship Between an Industry Average Beta Coefficient and Price Elasticity of Demand." Thesis, North Texas State University, 1986. https://digital.library.unt.edu/ark:/67531/metadc500999/.

Full text
Abstract:
The price elasticity of demand coefficient for a good or service is a measure of the sensitivity, or responsiveness, of the quantity demanded of a product to changes in the price of that product. The price elasticity of demand coefficients were generated for goods and services in nine different industries for the years 1972 to 1984. A simple linear demand function was employed, using the changes in the Consumer Price Index as a proxy for changes in price and Personal Consumption Expenditures, taken from the National Income and Product Accounts, as a proxy for quantity. Beta measures the sensitivity, or responsiveness, of a stock to the market. An industry average beta coefficient was generated for each of the nine industries over the time period, using the beta coefficients published by Value Line for firms which met certain criteria. In order to test the relationship between the price elasticity of demand and an industry average beta coefficient, a simple regression was performed using the beta coefficient as the dependent variable and the price elasticity of demand coefficient as the independent variable. The results broke down into 3 basic categories: those industries for which there seemed to be no relationship, those industries where there was a fairly strong probability that a relationship exists and the price elasticity of demand explains at least part of the variation in beta coefficients, and those industries where there was a very high probability that a relationship does exist and the variation in the price elasticity of demand coefficients substantially explained the variation in the industry average beta coefficients. The first category includes the food at home, tobacco, and shoe industries. The second category includes the men's clothing, the women's clothing, and the alcoholic beverages industries, and the third includes the automobile, airline, and fast-food restaurant industries.
APA, Harvard, Vancouver, ISO, and other styles
3

Ahmed, Sadeq Mohamed, and Kamran Vaziri. "Price elasticity of demand for cigarettes : The Case of Sweden." Thesis, Högskolan Dalarna, Nationalekonomi, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:du-14649.

Full text
Abstract:
Due to health problems and the negative externalities associated with cigarette consumption, many governments try to discourage cigarette consumption by increasing its price through taxation. However, cigarette, like the other addictive goods, is viewed as that it is not sensitive to demand rules and the market forces. This study analyses the effect of price increase on cigarette consumption. We used Swedish time series data from 1970 to 2010. Our results reveal that though cigarette is addictive substance its demand is sensitive to changes in the price. Estimates from this study indicate short-run price-elasticity of -0.29 and the long run price elasticity of -0.47.
APA, Harvard, Vancouver, ISO, and other styles
4

Jonák, Ondřej. "Odhad cenové elasticity poptávky po ropě." Master's thesis, Vysoká škola ekonomická v Praze, 2009. http://www.nusl.cz/ntk/nusl-15857.

Full text
Abstract:
Objective of this diploma thesis is estimation of price elasticity of crude oil demand. In order to calculation of such elasticity crude oil demand is estimated with econometrical methods. The choice of suitable model, which sufficiently and accurately models crude oil demand, is initial position of analysis. Consequently, crude oil demand is estimated from market data obtainable from public sources. This estimated model is verified from economic, statistic and econometric point of view. Consequently, price elasticity of crude oil demand is calculated from such model.
APA, Harvard, Vancouver, ISO, and other styles
5

Huang, Yikun, and 黃逸昆. "Land supply elasticity and the housing price sensitivity to interest rate." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hdl.handle.net/10722/197542.

Full text
Abstract:
In Hong Kong, housing prices have increased significantly in recent years. Amongst all the reasons for such significant increase, low interest rate has been recognized as one of the major reasons. Many studies have provided empirical evidence to support the negative relationship between interest rate and housing prices. However, in the US, recent studies (Glaeser, Gottlieb and Gyourko, 2010; Kuttner, 2012) show that the observed effect of interest rate changes on housing prices is much less than that predicted by the standard user cost model. According to the Glaeser et al. (2010), there are three potential explanations for the low housing price sensitivity to interest rate fluctuation. First, increase in land (and therefore housing) supply elasticity can reduce the effects of the demand-side variables, including interest rate. Second, high risk premium for long term mortgage rate in the US makes housing prices less sensitive to changes in interest rates. Third, the long-term mortgage contracts in the US cannot reflect the impact of frequent short term interest rate fluctuation. Among these three potential hypotheses proposed to explain the lower than expected housing price sensitivity to interest rate changes, land supply elasticity is more relevant to Hong Kong. By focusing on Hong Kong’s housing market, this thesis examines the relationship between land supply elasticity and the sensitivity of housing prices towards interest rate changes. When demand shift due to interest rate change, land supply (and therefore housing supply) may respond accordingly to reduce the impact of interest rate change. The more elastic the supply is, the weaker the housing price sensitivity to interest rate may be. Alternatively, housing prices are more sensitive to interest rate change when land supply is inelastic. To be more precisely, this study provides an empirical test on whether land supply elasticity reduces housing price sensitivity towards interest changes. Two approaches are applied to provide clear pictures of housing price sensitivity. First, data from different housing subsectors with different land supply elasticity are used for the empirical tests. The results show that prices of large units in the Hong Kong Island are significantly more sensitive to interest rate change, compared to those of small units in the New Territories. This is consistent with the implication of our hypothesis because new land for building luxurious units in Hong Kong Island is limited while there are relatively more lands available in the New Territories for smaller mass residential units. Second, in Hong Kong, all new land supply comes from the government in the form of leasehold land. Hence, government’s land supply policy has a major impact on land supply elasticity. For example, there was a period of restricted land supply before the handover in 1997, which effectively reduced land supply elasticity. On the other hand, the Application List land sales system adopted by the Hong Kong government from 2000 to 2013 should increase the flexibility in land supply. Therefore, this study makes use of these policy changes as nature experiments to investigate the effect of land supply elasticity on housing price sensitivity towards interest fluctuation. The results show that housing prices are more sensitive to interest rate change during the land supply restriction period and more insensitive when the Application List was used for land sales.
published_or_final_version
Real Estate and Construction
Doctoral
Doctor of Philosophy
APA, Harvard, Vancouver, ISO, and other styles
6

SILVA, LEONARDO LUIZ ROCHA E. "APPLICATION OF PRICE AND CROSS ELASTICITY OF SMARTPHONES USING TIMES SERIES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2017. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=32914@1.

Full text
Abstract:
O mercado de smartphones é muito sensível a preços devido à alta competitividade comercial e à constante evolução tecnológica. A elasticidade de preços e a elasticidade cruzada são fundamentais para ajustes de previsões de vendas para evitar rupturas e/ou altos volumes de estoques. Este trabalho apresenta uma proposta de modelagem para cálculo de elasticidade de preços e elasticidade cruzada utilizando variáveis causais abordando aspectos internos e externos de uma empresa operadora de serviços de telecomunicações com várias lojas próprias. A escolha das variáveis é resultante da parceria entre profissionais de Logística, Marketing e Vendas fornecendo apoio técnico aos Planejadores de Demanda. Para se calcular a elasticidade de preços, a modelagem baseada em Regressão Dinâmica indicou utilização das variáveis: preços de concorrentes internos (representando a canibalização), disponibilidade (para lançamento e phase-out de produtos), loja aberta (diferenciando dos dias de lojas fechadas com vendas nula) e fator diário (cadenciando as vendas diárias), proporcionando resultados satisfatórios e demonstrando aplicabilidade comercial do modelo proposto.
The smartphone market is very price sensitive due to high commercial competitiveness and constant technological evolution. Price elasticity and cross-elasticity are critical for adjusting sales forecasts to avoid disruptions and / or high inventory volumes. This work presents a modeling proposal for calculation of price elasticity and cross elasticity using causal variables, addressing the internal and external aspects of a telecommunications service operator with several own stores. The variable s choice is the result of a partnership between professionals in Logistics, Marketing and Sales providing technical support to Demand Planners. In order to calculate price elasticity, modeling based on dynamic regression indicated the use of variables: internal competitors prices (typifying cannibalization), availability (for launching and phase-out of products), open store (differentiating from the days of closed stores with zero sales) and daily factor (daily sales rhythm), providing satisfactory results and demonstrating commercial applicability of the proposed model.
APA, Harvard, Vancouver, ISO, and other styles
7

Dubihlela, Dorah. "An analysis of the poor's demand patterns during rising prices : the case of Bophelong / Dorah Dubihlela." Thesis, North-West University, 2012. http://hdl.handle.net/10394/10120.

Full text
Abstract:
This study investigated the demand patterns of poor households during a period of rising prices. Focus was on three main constructs namely the poor, rising prices and the demand patterns. The study was on Bophelong, a township in South Africa. This study was conducted from an empirical, quantitative approach which was preceded by a literature review. The main objective of conducting the literature review was to provide a theoretical framework for questionnaire design and empirical work. Cross sectional data was collected at Bophelong households. On completion of the survey, the poor were selected from the non-poor by means of a poverty line. The poor were further divided into two categories, namely moderately poor and the very poor. Moderately poor households were categorised by an income ranging 50% to 99% inclusively of their household poverty line. The very poor households were categorised by an income in the range of 0 to 49% inclusively of their poverty line. Using the above division, the total poverty rate was 56% of the total sample, 26% being moderately poor and 30% very poor. The poverty gap ratio for all the poor in the sample was 0.48, meaning that on average, the poor needed 48% of their current income to reach their poverty line. This ratio was 0.29 for the moderately poor households and 0.69 for the very poor households. A logistic regression done on the determinants of poverty in Bophelong showed that household size, age of the household head, monthly household income and the employment status of the household head were significant in determining poverty. The monthly average household income in Bophelong was R2 910. For the moderately poor households it was R1 641 for the and R932 for the very poor households. Household size was 3.96 for the whole sample size, 2.97 for the non-poor households, 4.2 for the moderately poor households and 4.7 for the very poor households. The study revealed that demand patterns of the poor differ from those of the non-poor. In addition the moderately poor households‟ demand patterns differ from the very poor An analysis of the poor‟s demand patterns during rising prices: the case of Bophelong household. The greatest part of income of the poor is spent on basic food stuffs. The very poor spent more than half of their income (53%) on food. The study indicated that bread is a giffen good only to the very poor households where quantity demanded moves in the same direction with price. In the non-poor households, bread is regarded inferior. A commodity can be overly a necessity, but the degree of necessity differs with a households‟ economic status. In some cases, a commodity was a necessity in the very poor households but a luxury in the non-poor. The way households substitute one good for another depends on their income levels. In conclusion, the study recommends that for poverty alleviation policies to effectively target the very poor in reducing malnutrition and hunger, these very poor should be studied separetely from the poor households. This is because households of different poverty levels face different challenges. A more detailed and deeper study relating to the demand structure of the poor is recommended. There is also a need to explore the survival means of the poor as to direct policy actions aimed at alleviating poverty among the poor in general.
Thesis (PhD (Economics))--North-West University, Vaal Triangle Campus, 2013
APA, Harvard, Vancouver, ISO, and other styles
8

Huang, Min-Hsin. "Price competition between store brands and national brands determinants of price elasticities for cheese products /." Columbus, Ohio : Ohio State University, 2004. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1083621040.

Full text
Abstract:
Thesis (Ph. D.)--Ohio State University, 2003.
Title from first page of PDF file. Document formatted into pages; contains xiv, 169 p.; also includes graphics (some col). Includes abstract and vita. Advisor: David E. Hahn, Dept. of Agricultural, Environmental & Development Economics. Includes bibliographical references (p. 164-169).
APA, Harvard, Vancouver, ISO, and other styles
9

Mousinho, Guilherme Filipe Palma. "Modelling renewal price elasticity : an application to the motor portfolio of Ocidental." Master's thesis, Instituto Superior de Economia e Gestão, 2016. http://hdl.handle.net/10400.5/12840.

Full text
Abstract:
Mestrado em Ciências Actuariais
O aumento da competitividade no mercado segurador automóvel em Portugal tem levado as seguradoras a considerar uma abordagem de tarifação mais assente na procura, como um complemento à tradicional abordagem baseada no risco. As companhias de seguros querem actualmente saber mais sobre como evitar a saída dos seus clientes, durante o período de renovação de apólice, sem prejudicar a rentabilidade. Este relatório é o resultado de um estágio curricular que teve lugar junto da Ocidental Seguros, tendo como principais objectivos modelar a taxa de anulação na renovação do seguro automóvel da companhia e analisar como diversas variáveis influenciam as renovações. Considerámos a regressão logística, um caso particular dos Modelos Lineares Generalizados, para modelar a variável de resposta binária renovação/anulação. Modelando a variável de resposta como uma função da variação do prémio e de outras variáveis explicativas, é possível estimar a probabilidade de anulação por valor da alteração do prémio para cada cliente. Como a variação do prémio é a única variável que a companhia pode controlar directamente, obter tal informação sobre a elasticidade preço de cada cliente permitirá à seguradora tomar melhores decisões, com o objectivo de aperfeiçoar o equilíbrio entre o grau de satisfação dos clientes e a rentabilidade. A capacidade do modelo em prever que clientes irão anular as suas apólices foi também examinada. Para converter as probabilidades obtidas pelo modelo em classificações binárias, foram comparados vários critérios de optimização de ponto de corte, de modo a encontrar o valor que resulta na melhor capacidade discriminatória global.
The increase in competition in the Portuguese Motor insurance market has lead insurers to consider a more demand-based approach to ratemaking, as a complement to the usual risk-based approach. Insurance companies now want to have a better understanding of how to prevent their clients from leaving the company, during the policy renewal period, while maintaining profitability. This report is the result of a curricular internship that took place at Ocidental Seguros, with the main goals of modelling the company's Motor insurance lapse rate during the renewal period and studying how different covariates influence renewals. We considered logistic regression, a special case of Generalized Linear Models, to model the binary response variable renewal/lapse. By modelling the response as a function of premium change and other covariates, the lapse probability for each client per amount of premium variation can then be estimated. As premium change is the only covariate the company has direct control over, obtaining such knowledge on each client's price elasticity will allow the insurer to make better decisions, so that a finer balance between customer satisfaction and profitability can be achieved. The model's capacity to predict which clients will cancel their policy was also analysed. In order to transform the output probabilities into binary classifications, several threshold optimisation criteria were compared, to find the threshold generating the best overall discriminatory performance.
N/A
APA, Harvard, Vancouver, ISO, and other styles
10

Farhadikashi, M. (Mahboobeh). "Demand response for residential customers:based on real-time price elasticity of electricity." Master's thesis, University of Oulu, 2017. http://urn.fi/URN:NBN:fi:oulu-201710042940.

Full text
Abstract:
This study surveyed the impacts of the expanding Real-Time Price (RTP) scheme on residential electricity consumption when households shift from fixed price to hourly spot prices. A unique and detailed data of electricity consumption had been used. The data are based on working days of winter and summer for Swedish detached houses from 2005 to 2008. Solar power is valuable energy with low emission, which can be achieved by installing solar panels on the household’s roof. Also, it reduces the system cost and provides quick access to energy for customers. The preliminary photovoltaic production evaluated through HARMONIE Numerical Weather Prediction data. Four types of households are analyzed based on various patterns of prices, elasticities, and the share of households in RTP program with and without solar panels. The results of this study demonstrate that putting more residential customers on RTP contracts will shift load, decrease electricity demand, total capacity, and increase economic welfare. The simulations show that the social welfare gained from increasing the share of customers on RTP are notable. Also, the estimated cost saving indicates that the effect of shifting from a flat rate to RTP is positive. Furthermore, the effect of small-scale solar production on electricity consumption is considered. The combination of RTP with solar energy would lead to a significant decrease in electricity consumption during off-peak periods in winter and both peak and off-peak load in summer.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Price elasticity"

1

Gardiner, Walter H. Price elasticity of export demand: Concepts and estimates. Washington, D.C: U.S. Dept. of Agriculture, Economic Research Service, 1987.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Gardiner, Walter H. Price elasticity of export demand: Concepts and estimates. Washington, D.C: U.S. Dept. of Agriculture, Economic Research Service, International Economics Division, 1986.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Gruber, Jonathan. Estimating price elasticities when there is smuggling: The sensitivity of smoking to price in Canada. Cambridge, MA: National Bureau of Economic Research, 2002.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Roe, Terry L. Price responsiveness of world grain markets: The influence of government intervention on import price elasticity. Washington, DC: U.S. Dept. of Agriculture, Economic Research Service, 1986.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

Roe, Terry L. Price responsiveness of world grain markets: The influence of government intervention on import price elasticity. Washington, DC: U.S. Dept. of Agriculture, Economic Research Service, 1986.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

Roe, Terry L. Price responsiveness of world grain markets: The influence of government intervention on import price elasticity. Washington, DC: U.S. Dept. of Agriculture, Economic Research Service, 1986.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Parker, Philip M. Price elasticity dynamics over the adoption lifecycle: An empirical study. Fontainebleau: INSEAD, 1990.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

Devinney, Timothy Michael. Advertising and price elasticity in a model of dominant firm markets. Brussels: European Institute For Advanced Studies in Management, 1988.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

United States Postal Service. Office of Inspector General. Analysis of postal price elasticities. Arlington, VA: Office of Inspector General, United States Postal Service, 2013.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

Gu, Yiquan. Product variety, price elasticity of demand, and fixed cost in spatial models. Essen, Germany: Ruhr Graduate School in Economics, 2009.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "Price elasticity"

1

Hoyer, Daniel, Eric P. Zorrilla, Pietro Cottone, Sarah Parylak, Micaela Morelli, Nicola Simola, Nicola Simola, et al. "Cross-Price Elasticity." In Encyclopedia of Psychopharmacology, 362. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-68706-1_496.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Yang, Jan Y. "Behind the Scenes of Price Elasticity." In The Pricing Puzzle, 97–102. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50777-0_16.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Funk, Burkhardt. "Exploring Price Elasticity to Optimize Posted Prices in e-Commerce." In Communications in Computer and Information Science, 71–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20077-9_5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Zhang, Bingsong, and Zhaoxia Kang. "China Railway Freight Price Reform Analysis: Based on Price Elasticity of Freight Demand." In IEIS2019, 573–85. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5660-9_43.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Bhaduri, Saumitra N., and David Fogarty. "Estimating Price Elasticity with Sparse Data: A Bayesian Approach." In Advanced Business Analytics, 113–29. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0727-9_9.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Eshchanov, Bahtiyor, Mona Grinwis, and Sanaatbek Salaev. "Price and Income Elasticity of Residential Electricity Consumption in Khorezm." In Cotton, Water, Salts and Soums, 155–67. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-1963-7_10.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Galvin, Ray, and Minna Sunikka-Blank. "How Fuel Price Elasticity Affects the Economics of Thermal Retrofits." In A Critical Appraisal of Germany's Thermal Retrofit Policy, 117–33. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5367-2_8.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Saloojee, Yussuf. "Price and Income Elasticity of Demand for Cigarettes in South Africa." In Tobacco and Health, 235–39. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-1907-2_51.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Santos, Eleonora, and Jacinta Moreira. "Price Elasticity of Overnight Stays: Testing Veblen’s Conjecture Across Portuguese Regions." In Advances in Tourism, Technology and Systems, 25–34. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1040-1_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Guerrero García Rojas, Hilda R., Faustino Gomez-Santiz, and Erandi Maldonado-Villalpando. "Industrial Water Use in Mexico: Analysis of Efficiencies Using Water Price Elasticity." In Water Policy in Mexico, 89–113. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76115-2_5.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Price elasticity"

1

Kouhpaei, Mah. "Airfare price elasticity over non-business passengers." In 2010 2nd IEEE International Conference on Information and Financial Engineering (ICIFE). IEEE, 2010. http://dx.doi.org/10.1109/icife.2010.5609484.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Yi Wang. "Price-load elasticity analysis by hybrid algorithm." In 2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. IEEE, 2008. http://dx.doi.org/10.1109/drpt.2008.4523409.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Zhengwei Sun and A. E. Abbas. "Bayesian updating on price elasticity of uncertain demand." In 2013 7th Annual IEEE Systems Conference (SysCon). IEEE, 2013. http://dx.doi.org/10.1109/syscon.2013.6549886.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Yang, Wenxian, Xiaoming Bao, and Rongshan Yu. "Modeling price elasticity of electricity demand using AIDS." In 2014 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT). IEEE, 2014. http://dx.doi.org/10.1109/isgt.2014.6816392.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Wu, Tong, Gengfeng Li, and Zhaohong Bie. "Charging Price Determination and Energy Management of EV Parking Lot Considering Price Elasticity." In 2019 IEEE 8th International Conference on Advanced Power System Automation and Protection (APAP). IEEE, 2019. http://dx.doi.org/10.1109/apap47170.2019.9224866.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Dan Ton, M. A. Biviji, E. Nagypal, and Jianhui Wang. "Tool for determining price elasticity of electricity demand and designing dynamic price program." In 2013 IEEE PES Innovative Smart Grid Technologies Conference (ISGT 2013). IEEE, 2013. http://dx.doi.org/10.1109/isgt.2013.6497848.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Yayar, Rüştü, Yunus Emre Birol, and Yusuf Demir. "Analysis of Turkey’s Export and Import Demand Functions within the Context of Foreign Trade with Russia." In International Conference on Eurasian Economies. Eurasian Economists Association, 2013. http://dx.doi.org/10.36880/c04.00783.

Full text
Abstract:
The main purpose of this study is to analyze the foreign trade of Russia and Turkey. Considering the foreign trade volume between the two countries, an experimental study was carried out to determine export and import demand functions of Turkey. The Russian Federation has been one of the countries having an important part in export of Turkey. Whereas textile products have taken the first place within the export of Turkey, petroleum gas and natural gas have taken the first place in import. The data used in the study covered the period between 1995 and 2010 quarterly. The data were obtained from Turkish Republic Central Bank, International Money Fund, Russian Central Bank and Russian Federal Statistics Service databases. According to obtained results, export of Turkey to Russia has affected more from the income of Russia rather than the relative prices, and import of Turkey from Russia has affected more from the income of Turkey rather than the relative prices. When income and price elasticity of export and import demands were analyzed, income and price elasticity of the export demand was noticed as being greater than the income and price elasticity of the import demand.
APA, Harvard, Vancouver, ISO, and other styles
8

Kuang, Weida, and Hua Zhou. "Property Tax, Supply and Demand Elasticity and Housing Price." In 2010 International Conference on Information Management, Innovation Management and Industrial Engineering (ICIII). IEEE, 2010. http://dx.doi.org/10.1109/iciii.2010.325.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Juan, Su, Fang Shu, Xing Guangjin, Du Songhuai, and Chen Zhiwen. "Eleceticity Price Elasticity Model under Electricity Market Transaction Mode." In 2021 3rd Asia Energy and Electrical Engineering Symposium (AEEES). IEEE, 2021. http://dx.doi.org/10.1109/aeees51875.2021.9403135.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Jia, Yuelong, Haifeng Zheng, Songtai Yu, and Chuanlong Xu. "User Price Elasticity Analysis Based on Power Load Characteristics." In 2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA). IEEE, 2022. http://dx.doi.org/10.1109/icdsca56264.2022.9988479.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Price elasticity"

1

Fujita, K. Sydny. Estimating Price Elasticity using Market-Level Appliance Data. Office of Scientific and Technical Information (OSTI), August 2015. http://dx.doi.org/10.2172/1236368.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

King, M., and E. Renedo. Estimating the price elasticity of demand for NPL's services. National Physical Laboratory, August 2020. http://dx.doi.org/10.47120/npl.iea6.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Bernstein, M. A., and J. Griffin. Regional Differences in the Price-Elasticity of Demand for Energy. Office of Scientific and Technical Information (OSTI), February 2006. http://dx.doi.org/10.2172/877655.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Coglianese, John, Lucas Davis, Lutz Kilian, and James Stock. Anticipation, Tax Avoidance, and the Price Elasticity of Gasoline Demand. Cambridge, MA: National Bureau of Economic Research, February 2015. http://dx.doi.org/10.3386/w20980.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Wambalaba, Francis. Price Elasticity of Rideshare: Commuter Fringe Benefits & Parking Cash-Out. Tampa, FL: University of South Florida, June 2004. http://dx.doi.org/10.5038/cutr-nctr-rr-2003-01.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Fujita, Kimberly, Larry Dale, and K. Sydny Fujita. An Analysis of the Price Elasticity of Demand for Household Appliances. Office of Scientific and Technical Information (OSTI), January 2008. http://dx.doi.org/10.2172/929429.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Pauly, Mark, Kate Withers, Krupa Subramanian-Viswana, Jean Lemaire, and John Hershey. Price Elasticity of Demand for Term Life Insurance and Adverse Selection. Cambridge, MA: National Bureau of Economic Research, August 2003. http://dx.doi.org/10.3386/w9925.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Davis, Lucas. Estimating the Price Elasticity of Demand for Subways: Evidence from Mexico. Cambridge, MA: National Bureau of Economic Research, December 2020. http://dx.doi.org/10.3386/w28244.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Hughes, Jonathan, Christopher Knittel, and Daniel Sperling. Evidence of a Shift in the Short-Run Price Elasticity of Gasoline Demand. Cambridge, MA: National Bureau of Economic Research, September 2006. http://dx.doi.org/10.3386/w12530.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

JOHNSON, MEGAN M. Meta-Analysis of the Oil Price Elasticity of the GDP for Policy Analysis: Documentation. Test accounts, August 2017. http://dx.doi.org/10.2172/1376319.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Price elasticity' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography