Impact Of Price Increase Research Articles

주택유형별 가격변화 간의 파급효과 분석

This study analyzed the interrelationship and lead-lag relationship between price changes by housing type with the TVP-VARX model and Wavelet Phase Difference. As a result of the empirical analysis, the price of all housing types has a strong tendency to decrease after 2020 due to rising interest rates. The interrelationship between price changes by housing type is time-varying, and the impact of increase in apartment price on the price of detached and row houses increases over time. On the other hand, the impact of increase in detached house prices on prices of other housing types increases and then decreases sharply after August 2020. The impact of increase in row house price on prices of other types of housing generally remains constant, but temporarily increases around August 2020. At this time, in the interrelationship between prices by housing type, the impact of increase in apartment price on the price of other housing types is the largest on average. Next, it is confirmed that the impact of increase in the price of detached and row houses has a large impact on other housing types. The lead-lag relationship between price changes by housing type, which is detached → row → apartment, clearly has made after 2019. However, the interrelationship, influence, and lead-lag relationship between price changes by housing type by region are different. Accordingly, this study suggests that it is necessary to discriminately select housing types and policies to be supplied for price stabilization in the housing market according to the time and region.

Between online and offline markets: A structural estimation of consumer demand

While the literature on comparing the online and offline markets from the supply-side perspective is extensive, fewer researches have focused on the demand-side. Using a large-scale point-of-sales (POS) dataset on consumer packaged goods, we estimate a structural demand model and conducted counterfactuals of the price change or product stockouts. Our key findings are: 1) the own-price elasticity of demand is higher offline (i.e., –1.74 on average) than online (i.e., –0.87 on average). 2) The cross-price elasticity is also higher offline (i.e., 0.17 on average) than online (i.e., 0.04 on average). 3) When a product is out-of-stock, a larger portion of the loss of the market share is recovered more in the common products in the offline markets than that in the online markets. Specifically, 6.55 % of the loss of the market share goes to common products offline on average, while 6.05 % of the loss of the market share goes to the common product online on average. Our further analyses show that, when considering substitute products, the impact of price increases is surprising. The retailer may not be worse off by increasing prices because the gains in the revenue from the substitute products can make up more than the losses. The manufacturers may lose revenue by increasing prices or product stockouts. However, consumers are hurt more in the offline markets following the price increases of the common products because the offline market is more concentrated on the common products.

Changes in the affordability of tobacco products in India during 2007/2008 to 2017/2018: a price-relative-to-income analysis.

Increasing the price of tobacco through taxation is a very effective means of reducing tobacco use. However, the impact of price increases can be diluted if consumer incomes are growing strongly. The affordability of tobacco products has, therefore, become an important indicator for tobacco control. This study asks whether tobacco products in India became more or less affordable during 2007/2008 to 2017/2018. Survey data on the retail price of chewing tobacco, bidis and cigarettes were used to measure affordability at state and national levels. We adapted the price relative to income measure by calculating the percentage of net state domestic product (NSDP) per capita needed to purchase 1000 g of tobacco in each form and then calculating the average annual percentage change (AAPC) in affordability. We used ordinary least squares regression analysis to test for any changes. In 2017/2018, it took 1.72% and 1.18% of NSDP/capita to purchase 1000 g of tobacco in the form of bidis and chewing tobacco respectively. The affordability of bidis remained unchanged, while chewing tobacco became more affordable (AAPC = -1.83%, 95% confidence interval -2.87 to -0.80, P = 0.003). For cigarettes, it took 7.56% of NSDP/capita to purchase 1000 g of tobacco in 2017/2018; although affordability decreased in many states, national average affordability was unchanged. Tobacco products, especially indigenous forms such as bidis and chewing tobacco, have not become measurably less affordable over the past decade. India should raise taxes on all tobacco products to significantly reduce the affordability of these products and to promote public health.

Financing elderly people's long-term care needs: Evidence from China.

SummaryConfronted by accelerated population aging, China is establishing a long‐term care (LTC) system. This study discusses challenges and recommendations for financing China's LTC system. On the basis of the data on elderly people's self‐care ability from the Chinese Longitudinal Healthy Longevity Survey, we calculate the size of the elderly population that need LTC for the period from 2015 to 2030 and analyse the increasing tendency of LTC expenses by considering the impact of price increase. We also analyse the local governments' financial capacity for LTC support by comparing the expense level to the fiscal revenue. The study found that aging will double the LTC expenses by 2030. Therefore, this study suggests the establishment of an LTC insurance system that allocates LTC expenses, which are currently borne by individuals and families, more fairly among the government, individuals, and families. Moreover, with the current LTC reforms, implemented primarily by local governments in China, we believe that the central government should bear some of the fiscal responsibility by conducting fiscal transfers to partially support undeveloped regions that are establishing an LTC system.

Consumer reaction to price increase: an investigation in gasoline industry

Purpose – The aim of this study is to investigate the impact of increase in price of an essential product (i.e. gasoline) toward the focal product and other seemingly non-related products. Design/methodology/approach – A self-administered survey was used to collect data from the drivers at a large metroplex in Southwest USA. Multiple regression and scanning electron microscope procedures were used to analyze and test the proposed hypotheses. Findings – When consumers notice the increase in gas prices, they become very anxious. This anxiety is positively associated with average gas bought in gallons and negatively associated with threshold price. Further, this consumer anxiety has the strongest influence on lifestyle changes, followed by automobile technology change and transportation mode change, and has the weakest influence on gasoline brand/type change. Research limitations/implications – We focus on only anxiety as a mediator between increase in gas prices and the behavioral outcomes, and collect data from only one location. Practical implications – Managers must be cognizant that a price increase in essential goods not only influences the demand for focal products but also for products that may not seem related to the focal products. Social implications – Increase in gasoline price will not only affect the demand for gasoline, but also the demand for alternate forms of transportation, fuel efficient vehicles, and other aspects of life. Originality/value – This study is the first to look at the role of anxiety as a mediator and looks at the effects of increase in gas prices in a holistic manner.

Price Changes and Customer Loyalty & Defection in Consumer Insurance: A Test of ‘Prospect Theory’ - And Why Regression Modeling Should Use Multiple Datasets

This paper examines the relationship between price changes and customer defection levels in a ‘subscription’ type market, namely car insurance. Two regression models are constructed to estimate this relationship, one model for younger customers and another for older customers. The regression models fit well to the defection rates associated with different levels of price changes. The analysis also shows that the impact of price decreases on defection rates is less than the impact of price increases, consistent with ‘loss aversion’. The paper notes that models of this type should offer true predictive ability and therefore tests the ability of the model to predict defection rates for new data. That is, rather than fitting new models to the new data, the analysis fits the original models to new data. The models performed comparatively poorly when fit to new data, particularly for price increases. The paper concludes that multiple sets of data are needed to develop and validate predictive models.

Price changes and defection levels in a subscription‐type market: can an estimation model really predict defection levels?

This paper examines the relationship between price changes and customer defection levels in a “subscription”‐type market, namely car insurance. Two regression models are constructed to estimate this relationship, one model for younger customers and another for older customers. The regression models closely estimate the defection rates associated with different levels of price changes. The analysis also shows that the impact of price decreases on defection rates is less than the impact of price increases, extending previous research. The paper notes that models of this type should offer true predictive ability and therefore tests the ability of the model to predict defection rates for new data. The models performed comparatively poorly in this regard, particularly for price increases. The paper concludes that multiple sets of data are needed to develop and validate predictive models.