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The purpose of this paper is to investigate structural changes in the elasticity of demand for wine in the Province of Ontario and in Canada as a whole. It will provide academic researchers and practitioners with a better understanding about structural changes in the levels of wine demand elasticities over time. It will also help the relevant governments and wine business establishments in developing taxation policy and business decisions.

The Kalman filter method, in conjunction with the Chow test, is applied to investigate structural changes in the elasticity of demand for wine. The Chow test is used for primary investigations of structural changes in the elasticity of demand for wine over time, whereas the Kalman filter method provides information about the behavior of the elasticity coefficients over time.

The Chow test reveals that structural changes in wine demand for Ontario are more pronounced than those for Canada as a whole. The Kalman filter results indicate that increased (decreased) government taxation could be an effective tool for discouraging (encouraging) consumption of wine. The analysis of own‐price elasticity suggests that the effects of increased government taxation on wine consumption be totally unexpected. Cross‐price elasticity coefficients change their signs over time, suggesting that some of the goods that are considered to be complements may become substitutes. Income and unemployment levels have different effects on wine consumption in Ontario and in Canada as a whole.

There may be variation in results by wine color (red or white), country of origin (imported or domestic), or price (premium or non‐premium).

Understanding changes in the elasticity of demand structure for wine over time would help policy makers at the provincial and federal levels come up with effective tools for controlling consumption of wine over time, including their taxation policies. For the wine business establishments, the information on consumer response is important for pricing purposes.

The Kalman filter has not previously been used to examine structural changes in the demand for wine in Canada.

The purpose of this paper is to use demand behavior estimation to find the sources of price variability among resort hotels at different Spanish destinations.

This paper estimates online demand functions during high season for seven four-star resort hotels located at different Spanish destinations. Different price elasticity values are compared, and different factors affecting price elasticity are analyzed.

The main findings indicate that most of the high season periods display elastic demands, but factors such as a central location at a resort, recent refurbishments, the availability of additional facilities/services and a hotel targeted at the couples and/or half-board segments make the demand more inelastic; the Tenerife hotels had the most price-elastic demand; during the closest booking periods to the date of stay, the demand is usually more elastic; and a higher number of local competitors pushes down hotel prices.

This paper highlights the managerial implications of focusing on more profitable demand segments for hoteliers. This is especially useful for the development of revenue management software aimed at improving forecasts.

该论文评估了位于西班牙不同目的地的七家四星级度假酒店在旺季期间的在线需求函数。比较不同的价格弹性值, 分析影响价格弹性的不同因素。

本文的目的是使用需求行为估计来找出西班牙不同目的地度假酒店价格变化的来源。

主要调查结果表明：（1）大多数旺季期间的需求弹性, 但诸如度假村的中心位置、最近的翻新、额外设施/服务的可用性以及针对夫妻和/的酒店等因素或半食宿使需求更加缺乏弹性; (2) 特内里费酒店的价格弹性需求最大; (3) 在离入住日期最近的预订期间, 需求通常更具弹性; (4) 更多的本地竞争者压低了酒店价格。

本论文强调了酒店经营者应关注更有利可图的需求细分市场的管理意义。研究发现对于开发旨在改进预测的收益管理软件特别有价值。

This paper aims to estimate electricity demand functions in Japan’s residential sector.

The authors use a partial adjustment model and empirically analyze regional residential electricity demand by using data on 47 Japanese prefectures.

The results reveal that the price elasticity of residential electricity demand during the analytical period (1990-2010) is remarkably different among prefectures, depending on the magnitude of floor space per household. In addition, this study finds that price elasticity is high compared with income elasticity, implying that residential electricity demand changes with rates. Furthermore, an analysis of factors influencing electricity demand in the residential sector shows that increasing electricity demand growth in each region can be attributable mainly to declining electricity rates and increasing number of households.

These results suggest that monitoring the electricity rates and the number of households is important for forecasting future residential electricity demand at region.

The study considers the impact of the number of households on overall electricity demand and identifies other factors contributing to growth in residential electricity demand. The findings can be used to derive projections for future electricity demand.

The demand for alcohol is a well‐researched topic, yet the published literature regarding consumer responses to changes in the price of alcohol includes many conflicting and inconsistent results. This paper seeks to present an analysis of known own‐price elasticity estimates, and to attempt to understand why reported results differ.

The approach taken to analysing the data is the meta‐regression approach. Specifically, the meta‐regression considers 150 beers, spirits, and wines, own price elasticity point estimates, which have been drawn from studies that consider demand responses to changes in the price of alcohol in 18 different countries.

The results of the empirical work reported in this paper suggest that the year of the study, the length of study, the per capita level of alcohol consumption, and the relative ethanol share of a beverage are important factors when explaining variations in consumer demand responses to changes in the price of alcohol. Interestingly, the study also suggests that country‐specific and beverage‐specific effects are not important.

The paper is valuable as it uses the meta‐regression framework to control for study design characteristics and, once these characteristics are controlled for, it becomes possible to identify the underlying trend in the demand for alcohol. Specifically, the trend was shown to be one where the demand for alcoholic beverages became increasingly inelastic up to 1969 and decreasingly inelastic thereafter.

This paper presents a simple alternative measure for the arc elasticity of demand that comes naturally and possesses some attractive properties. In particular, it equals the point demand elasticity at some point inside the interval, thus leading to the exact estimations of demand elasticity when this is constant. It also yields narrower values that Dalton’s, Lerner’s and Allen’s widely used measures, and its relationships with the arc revenue elasticities keep exact analogy with those established for the point elasticity case.

This paper aims to identify the income and price elasticities of demand for residential electricity in Latin America and the Caribbean (LAC) and to verify their main determinants.

Meta-analysis and meta-regression methods were applied. After collecting and filtering journal articles, the authors obtained a sample composed of 76 studies covering 1979–2020.

The results show that the LAC's income elasticity is approximately 0.20 and 0.92 for the short and long term, respectively. The LAC's price elasticity is approximately −0.37 and −0.46 for the short and long term, respectively. Furthermore, the estimates are affected by the data structure, the estimation method used and the sampling period.

The authors close a gap in the literature by analyzing the price and income elasticities of demand through meta-analysis and meta-regression.

A simultaneous equation model is used to estimate export demand and supply functions for US soybeans. Price, income, exchange rate and other effects on exports to four world regions are estimated. Inclusion of export supply relationships have very significant implications for estimated price‐, income‐, and exchange‐rate elasticities of export demand. Results fail to support the usual empirical assumption of infinite supply price elasticity for soybeans.

This paper aims to understand housing demand of urban Indian households in terms of housing and household-level characteristics. Because a house is a bundle of certain characteristics which vary across houses, each characteristic has an implicit price. Finding this implicit price for certain important characteristics is the first objective of this study. The second objective of the paper is to compute the income elasticity and price elasticity of housing demand for these cities.

To achieve comparable estimates, household-level data from India’s National Sample Survey Organisation housing surveys for the years 2002 and 2008-2009 have been used. A hedonic price function is estimated using ordinary least squares (OLS) and Box-Cox functional forms to estimate the implicit prices of housing characteristics. This exercise is attempted for owned and rented houses separately. Demand function required for computing the elasticities, uses the hedonic price index derived from the implicit prices and household characteristics.

The study finds housing demand to be income elastic and price inelastic for the six cities across both the time periods.

Firstly, this study includes housing characteristics such as individual access to drinking water, modern sanitation facility, separate kitchen, condition of the structure, existence of a road with street light and whether the house is in a slum or non-slum area in the hedonic price function. These variables were not used in any of the earlier studies pertaining to India. Secondly, it uses the Box-Cox non-linear form to derive the hedonic price function, a specification not used earlier. Thirdly, this is the first study analysing housing demand across the six largest Indian cities.

This paper aims to better understand if speculative activity is a factor or even the main factor in the run-up of oil prices in the spot market, particularly in the recent price bubble that occurred in the period from mid-2003 to 2008.

The methodology used is based on an existing vector autoregressive model proposed by Kilian and Murphy (2014), which is a structural model of the global market for crude oil that accounts for flow demand and flow supply shocks and speculative demand oil shocks.

From the output of the authors’ structural model, the authors ruled out speculation as a factor of rising oil prices. The authors have found instead that the rapid oil demand caused by an unexpected increase in the global business cycle is the most accurate culprit. Despite the change of perspective in the speculative component, the authors’ conclusions concur with the findings of Kilian and Murphy (2014) and others.

As far as the authors are aware, this is the first time that a study has used as a spread oil variable, a speculative component of the real price, replacing the oil inventories considered by Kilian and Murphy (2014). Another contribution is that the model used allows estimating traditional oil demand elasticity in production and oil supply elasticity in spread movements, casting doubt on existing models with perfect price-inelastic output for crude oil.

Seeks to present a microeconomic model to analyse theoretically BSC, to develop a simplified model version and to apply it empirically.

The model assumes exponential production and demand functions with constant scale factors and elasticities. It is estimated for Nokia's time‐series 1993‐2002 and partly for 35 Compustat firms.

Direct statistical estimates act properly only as initial values iteratively adjusted for the level of the model. Model parameters show in experiments a significant effect on decision variables such as selling price. Most firms show decreasing returns to scale that are found also in a cross‐sectional analysis.

The model assumes constant elasticities and growth which should be relaxed. Most numerical experiments are limited to Nokia's data. Estimates applied in experiments are not fully justified on statistical grounds. More effort should be made to reach a consistent set of estimates at the level of the model.

In growth strategy, price discounts may lead to declining profitability, while productivity is increasing. This results in peculiar causal relationships in strategic mapping of BSC. If strategy is shifted towards revenue maximization, more focus should be given to customer relationships and development and learning in BSC. Firms should in strategic planning pay special attention to rate of discount and planning horizon, because they affect selling price.

This research paper presents a new model specification. It gives novel empirical evidence on parameter estimation and strategic behaviour in BSC framework.