Real Prices Research Articles

Policies for sufficiency: factors influencing acceptance in the Swiss population

Adopting strategies for sufficiency is crucial to meeting climate and sustainability objectives. However, this requires a societal shift which depends on favorable framework conditions pertaining to infrastructure, incentives, regulations, and social and cultural values. Sufficiency policies are essential for influencing and creating such conditions and acceptance by the affected population are important. This article presents two related studies that investigated the acceptance levels of policies supporting sufficiency among the Swiss population and the factors influencing this acceptance. The first study involved a quantitative survey of 834 individuals to assess acceptance of ten policy measures at national and communal levels. The second study entailed interviews with 15 individuals with the same sociodemographic criteria as a critical subgroup identified in the quantitative survey, namely respondents with little environmental affinity, with a low or medium level of education, and from rural or semi-urban areas, and considered on an in-depth basis three of the ten policy measures: the real price of meat, the potential of reduced working hours, and the ban on fossil-fuel powered cars. We further discussed the obstacles and drivers associated with each of these measures with seven experts from relevant fields, leading to recommendations on increasing their acceptance. The findings show that sufficiency policy can gain public support if implemented equitably and seen as effective by the population. When implementing such measures, it is essential to consider fairness and evaluate compensation strategies. Avoiding consideration of sufficiency measures is not advisable and it is crucial to build on existing favorable assessments and counter misleading perceptions with specific arguments and positive framings.

Demographic changes, technology growth, and retirement policy reform: Implications for U.S. housing dynamics

As the population aging process continues, concerns about how this situation impacts the housing market and social security rise. To address this question, this paper presents a developed and calibrated general equilibrium life-cycle model incorporating two production sectors to analyze the impacts of demographic structure changes and retirement policy reforms on housing price fluctuations and household choices. The model calibrated to the U.S. macroeconomic data between 1968 and 2018 suggests that in an economy with unlimited land supply, the housing supply curve exhibits perfect elasticity, rendering demographic changes insignificant in housing price fluctuations, while technological advancements lead to decreased prices. A 1% growth in productivity in both sectors results in a 2.6% decrease in house prices. Furthermore, a 1% decrease in population and a 5-year early retirement led to significant reductions of 25% and 30% in individual social security payments and 9% and 18% in interest rates, respectively. This suggests that during a recession caused by demographic structural changes, households become more conservative and prioritize precautionary saving strategies, increasing savings and investing more in housing assets. Consistent with empirical findings, during an economic boom, a decline in the capital-output ratio and the real housing price suggests a decrease in savings and housing asset investment. The rise in consumption drives the capital demand of the non-housing sector to increase, stimulating business expansion and labor inflow.

The Impact of Unnatural Death Stigmatization on Neighboring Property Prices: Propensity Score Matching and Difference-In-Differences Analysis.

This study primarily investigated the impacts of unnatural in-house deaths on nearby property prices. Propensity score matching was used to assess the homogeneity of experimental and control groups, and the difference-in-differences (DID) method was used for their comparison. Data for real estate transactions in Taipei City from 2012 to 2022 were retrieved from the Ministry of the Interior's real estate actual transaction price registration query system. The DID interaction variable coefficient of 0.066 was significant at the 10% level. A comparison of the experimental and control groups showed a 6.8% property price difference following an unnatural in-house death. This suggests that an unnatural in-house death has a positive impact on property prices nearby. There were four unnatural deaths at the Xining Public Housing from 2003 to 2012 and four at the Jinxing Building from 1984 to 2012. The high incidence of events and the disclosure of information may have depreciated nearby property prices. The study results show that the stigmatization of unnatural in-house deaths reduces nearby property prices. The depreciation of implicit prices reverted and followed a U-shape pattern after several years.

Optimal adaptive heuristic algorithm based energy optimization with flexible loads using demand response in smart grid.

Demand response-based load scheduling in smart power grids is currently one of the most important topics in energy optimization. There are several benefits to utility companies and their customers from this strategy. The main goal of this work is to employ a load scheduling controller (LSC) to model and solve the scheduling issue for household appliances. The LSC offers a solution to the primary problems faced during implementing demand response. The goal is to minimize peak-to-average demand ratios (PADR) and electricity bills while preserving customer satisfaction. Time-varying pricing, intermittent renewable energy, domestic appliance energy demand, storage battery, and grid constraints are all incorporated into the model. The optimal adaptive wind-driven optimization (OAWDO) method is a stochastic optimization technique designed to manage supply, demand, and power price uncertainties. LSC creates the ideal schedule for home appliance running periods using the OAWDO algorithm. This guarantees that every appliance runs as economically as possible on its own. Most appliances run the risk of functioning during low-price hours if just the real time-varying price system is used, which could result in rebound peaks. We combine an inclined block tariff with a real-time-varying price to alleviate this problem. MATLAB is used to do a load scheduling simulation for home appliances based on the OAWDO algorithm. By contrasting it with other algorithms, including the genetic algorithm (GA), the whale optimization algorithm (WOA), the fire-fly optimization algorithm (FFOA), and the wind-driven optimization (WDO) algorithms, the effectiveness of the OAWDO technique is supported. Results indicate that OAWDO works better than current algorithms in terms of reducing power costs, PADR, and rebound peak formation without sacrificing user comfort.

Changes in price, income and e-cigarette affordability for young people in the USA from 2015 to 2021

BackgroundE-cigarette products are the most popular tobacco/nicotine product used among youth and young adults in the USA. While emerging research has shown that e-cigarette taxes increase their price, no study to date has examined e-cigarette tax burdens nor their affordability for youth and young adults.MethodsUsing real (2021 US dollars) prices per mL of e-liquid data from NielsenIQ and annual real (2021 US dollars) personal income data from Integrated Public Use Microdata Series, we calculate relative income prices and examine average annual percentage changes in affordability using Joinpoint trend analysis from 2015 to 2021. In addition, we use tax data to calculate e-cigarette tax burdens as a percentage of price per 1 mL of e-liquid.ResultsIn all states analysed, tax burdens increased from 2015 to 2021. E-cigarette prices decreased considerably from 2019 to 2021; in 2021 the real (2021 US dollars) average price of 1 mL of e-liquid was US$4.45. E-cigarettes on average became more affordable for all age groups and states; however, e-cigarettes tended to be less affordable in states with ad-valorem tax structures. On average, 16–17-year-olds needed 31% of their annual income to purchase 100 mL of e-liquid, whereas 18–19-year-olds, 20–24-year-olds and 25–34-year-olds needed 9%, 3% and 1%, respectively.ConclusionsE-cigarettes have become more affordable for young people, but less so in states with ad-valorem tax structures. Policy efforts should focus on reducing e-cigarette affordability, especially for youth, through tax-induced increases in e-cigarette prices to levels high enough to outpace income growth.

Climate Risks and Real Gold Returns over 750 Years

Using data that cover the annual period from 1258 to 2023, we studied the link between real gold returns and climate risks. We documented a positive contemporaneous link and a negative predictive link. Our findings further show that the predictive link historically gave rise to significant out-of-sample forecasting gains. The positive contemporaneous link is consistent with the view that investors viewed gold as a safe haven in times of elevated climate risks. The negative predictive link, in turn, is consistent with an overshooting scenario in which the real gold price overshot in response to climate risks, only to return subsequently to a lower value. Our findings should provide important implications for investors and policymakers, given that our analysis covered the longest possible data sample involving the gold market, and hence, was independent of any sample selection bias.

Oil Price Uncertainty and Consumer Sentiment in Advanced Economies

How does oil price uncertainty affect consumer sentiment in advanced economies? Is the response of consumer sentiment to exogenous positive and negative oil price shocks symmetric or asymmetric? Motivated to answer these questions, this paper provides a comprehensive examination of the effects of real oil price shocks on consumer sentiment in the G7 economies in the context of two classes of empirical models. With the application of a bivariate structural GARCH-in-Mean VAR model we find that (in general) oil price uncertainty has a negative and statistically significant effect on consumer sentiment in the G7 countries. Moreover, using a test of symmetry, we find that the relationship between oil prices and consumer sentiment is in general asymmetric. JEL Classification: C32, D12, Q43, O57

Brexit and the London housing market: An empirical contribution

This study aims to analyse the impact of Brexit on London’s housing market, exploring socio-economic and regional disparities. By examining property transaction data from 2012 to 2022, the research seeks to understand how Brexit has influenced real housing prices across different boroughs of London. The methodology involves aggregating transaction data from the Her Majesty (HM) Price Paid database and normalizing prices using the Consumer Price Index (CPI) to obtain real price variations. These data were segmented into three distinct periods: pre-Brexit (2012–2016), post-plebiscite Brexit (2016–2019), and post-implementation Brexit (2020–2022). Spatial analysis was conducted using the software Quantum Geographic Information System (QGIS), transforming point data (postcodes) into polygonal data (wards) for better visualization and comparison. The findings reveal significant socio-economic impacts, with traditionally affluent areas such as Westminster, Kensington, and Chelsea experiencing notable declines in real housing prices. Conversely, certain outer boroughs like Newham and Barnet showed resilience, with positive real price variations despite decreased sales. This geographical disparity underscores the uneven distribution of Brexit’s economic consequences, highlighting the critical role of localized economic policies and development projects in mitigating adverse effects. The results confirm existing literature on the polarization and regional inequalities exacerbated by Brexit while providing new insights into the complex interplay of local and global factors affecting housing markets. The findings emphasize the need for targeted policy interventions to address the diverse challenges posed by Brexit, ensuring both affluent and disadvantaged areas receive adequate support. This research is crucial for informing public policy, urban planning, and housing market strategies in a post-Brexit context, promoting equitable and sustainable development across London.

External Shocks, Asset Prices, and Credit Dynamics in Morocco: Insights from Disequilibrium Models

We investigate external shocks and asset price’s impact on the slowdown of business and household credit in Morocco using disequilibrium models. The results show that banks’ fly to quality, driven by a simultaneous decline in interest margins and borrower creditworthiness, is a key factor behind the slowdown of credit supply. On the demand side, slower growth and saturated housing demand have contributed to reduced borrowing and repayment capacity of borrowers. Furthermore, external shocks are transmitted to credit supply through foreign deposits and households’ credit demand through remittances. Additionally, stocks and residential real estate asset prices are closely tied to credit demand. These findings suggest that addressing bank credit barriers could stimulate economic growth. To do so, policymakers may consider employing unconventional monetary policy tools to effectively manage the transmission channels of external shocks and asset prices to bank credit dynamics.

The Positive and Negative Effects of Sustainability on Real Estate Transaction Prices

In last decades, there is a trend to renew buildings and make them more sustainable. Studies have shown that energy measures (as an aspect of sustainability) often increase the value of real estate. The effect of other sustainability measures on real estate values, however, is unknown. This study examines the relationship between multiple sustainability aspects and the transaction prices of different types of real estate. For this study, we used official data on commercial real estate transactions from the Land Registry Office in the Netherlands and sustainability assessment scores from a Dutch sustainability consultant. In total, 10,652 real estate transaction prices between 2012 and 2023 and corresponding sustainability scores were used to perform regressions and hedonic imputation analyses. The results show that, opposed to energy, other aspects of sustainability often correlate negatively with transaction prices in the lower segment of sustainable real estate. These aspects correlate positively in the upper segment of sustainable real estate.

Do Supply Chain Pressures Affect Consumer Prices in Major Economies? New Evidence from Time-Varying Causality Analysis

This study explores the dynamic causality between the consumer price index and supply chain pressure index in two large economies. Despite extensive research into the role of supply chains at the firm level, literature on their impact on time-varying inflation and macroeconomic stability is scarce. Using data from the United States and the European Union from January 2000 to December 2021, we employ novel time-varying causality techniques to examine the evolving relationships among inflation, supply chains, real gross domestic product, interest rates, and oil prices. Our findings show that supply chains have a significant dynamic relationship with consumer prices, particularly during economic crises like the 2008 global financial crisis and the COVID-19 pandemic. Robustness tests including impulse response functions and the autoregressive distributed lag model confirm this causality. These results are critical for policymakers, emphasizing the importance of supply chains in controlling inflation and achieving global economic resilience and stability.

Revisiting the Nexus Between Oil Prices and Economic Activity for Asian Economies Using MIDAS

The objective of this paper is to re-examine the causal relationship between oil prices and economic activity for five Asian economies. We apply the unrestricted MIDAS (U-MIDAS) model using monthly data for real oil prices and quarterly data for real GDP for the period from 1998Q1 to 2019Q4. The causal nexus between oil prices and economic activity is also studied by means of wavelet analysis to investigate whether the relationship between the variables changes over different time scales. The key empirical results under the MIDAS approach show that there is a clear significant causal link from oil prices to economic activity, which is not as clearly found under the standard VAR approach. In addition, our results using impulse response functions suggest that the five Asian economies respond, in general, positively in economic activity to an oil price shock at shorter time horizons (less than two years), while the positive responses switch to mostly negative ones at longer time horizons (from two to four years). Our results, in general, support that the (theoretically) expected negative causal nexus between oil price fluctuations and economic activity for oil importers is dominant over longer time horizons for our dataset. An exception to this pattern is China, which has a dissimilar country profile in terms of its oil market and production structure from the profiles of the other Asian economies in the study. JEL Classification: C32, E32, O53, Q43

The Dynamic Relationship Between Exchange Rate Volatility and Stock Prices in the Egyptian Real Estate Market and the Moderating Effect of Interest Rates

Among different channels of the financial market, the exchange rates and stock markets play a vital role in the domestic and international markets. This study aims to explore the dynamic relationship between the exchange rate (USD/EGP) and the real estate sector listed companies of the Egyptian Stock Exchange (EGX) from 2013 to 2023. Additionally, the study examines the moderating effect of interest rates on the relationship. To achieve this, the study employs several econometric methods such as Augmented Dicky Fuller (ADF) test, Granger Causality test to determine the direction of the relationship, Vector Autoregressive (VAR) model, and more. The results demonstrate that a long-run relationship exists between the variables. Furthermore, there is a significant unidirectional causality that runs from the exchange rate to real estate stock prices; thus, fluctuations in the exchange rate can significantly affect the profitability of investments in real estate stocks. Therefore, investors should closely monitor the movements in the exchange rate level to predict changes in real estate stock prices. When including the interest rate as a moderator, the outcome changes to bidirectional causality, meaning that the exchange rate and real estate stock price movements affect each other at a 1% significance level. Hence, interest rate could be used as an instrument to control demand in both the stock market and foreign exchange market. Finally, it is recommended that policymakers use the monetary policy while considering this bidirectional relationship in the presence of interest rate as a moderating variable.

Volatility Transmission between Oil Price and Exchange Rate

This article presents a study on the transmission of oil price volatility to the exchange rates of 14 countries (net oil exporters and importers) during the period from 02/01/2000 to 31/11/2022. The aim is to compare the effect of oil price fluctuations on exchange rate volatility based on the country's nature. Using ARCH, GARCH, and GARCH-BEKK models, our results reveal that the real effective exchange rate is significantly linked to fluctuations in the real oil price for both categories of countries: oil importers and exporters. These findings have important implications for monetary, fiscal, inflationary, and trade policies for these countries.

Response of legal and illegal cigarette prices to a tax increase in Ethiopia

BackgroundIn 2020, Ethiopia passed a landmark tax proclamation implementing an evidence-based mixed excise system aimed at curbing tobacco use. This study evaluates the impact of the tax increase of more...

Machine Learning-Based Models for Accurate Car Prices Prediction

The used car market is becoming more and more popular in various countries, but some car trading platforms have inaccuracies in predicting prices. So, it is necessary to select machine learning models with high accuracy to predict used car prices for both buyers and sellers. This study selected three factors that have the greatest impact on used car prices, which are: car name, car use year, and car use mileage. In the selection of dataset, this study chooses more than 2000 data from four brands of BMW, Volkswagen, Acura, and Tesla which are very popular in the market to predict. In the part of comparing the accuracy of machine learning models, this paper uses three machine learning models: linear regression, decision tree regressor and random forest regressor. Based on criteria such as root-mean-square error and R-variance, with K-Fold cross validation method to compare the advantages and disadvantages of every model. Through the analysis, all the test criteria consistently show that random forest regressor has the highest performance and can achieve an R-square value of 0.8562. After getting the suitable model, accurate price prediction will be realized in more car trading platforms to help buyers and sellers to understand the real price of used cars.

PRAKTIK BAIK PENGGUNAAN DANA ALOKASI UMUM DI KECAMATAN PAYAKUMBUH SELATAN

The The purpose of this study was to analyze the good practice of using the General Allocation Fund (DAU) in Payakumbuh Selatan Sub-district, Payakumbuh City. Data collection was conducted through semi-structured interviews. Data analysis was conducted using triangulation techniques, namely data reduction, data presentation, and conclusion drawing. The results of the study found that the realization of the use of DAU in the South Payakumbuh Sub-district showed very good performance, with a success rate of 95% in 2023. The process and all activities related to the use of DAU are carried out by the Budget User Authority (KPA), the Activity Technical Implementation Officer (PPTK), the Financial Administration Officer (PPK), the Treasurer, and several personnel who are assigned by each village. Employees in each kelurahan are assigned to succeed in the three focuses of the government through socialization related to stunting, technical guidance related to reducing inflation, and entrepreneurship training. There are several factors that inhibit the use of the DAU program, such as too high a comparison between the unit price listed in the Budget Implementation Document (DPA) and the real price in the field, the lack of personnel in several villages, and the existence of multiple positions that make the work process not optimal.

Influence of daylight on real estate housing prices. A multiple regression model application in Turin

Daylight is crucial in architecture, influencing human health, well-being, energy efficiency, and the post-COVID-19 perception of residential spaces. People often consider daylight among the most important features when buying a home, which potentially affects real estate asset pricing. Within this framework, this study explored the impact of daylight on real estate asset pricing, particularly focusing on its role in the Italian market. The research employed two approaches: (i) simulations of 100 units to determine a large set of daylight metrics and (ii) a statistical approach, applying Hedonic Analysis principles to investigate how house attributes influence pricing. A data sample of 100 housing units was selected in Turin (Italy), including variables such as location, floor area, construction year, façade type, and daylight metrics. By using Multiple Regression Analysis, after Exploratory Analysis and outlier management, we identified significant variables influencing housing listing prices, such as energy class, conservation status, elevator presence, terraces/balconies, and frame type. Notably, two daylight metrics (annual sunlight exposure and useful daylight illuminance) were found to be significant, while others, like average daylight factor and spatial daylight autonomy, were not. The final model was validated by means of a control sample, demonstrating the relevance of daylight in real estate pricing. This research contributes to the literature, providing an in-depth exploration of the impact of daylight on hedonic analysis in a relatively underexplored research space. Precisely, the work contributes to bridging the literature gap about the detection of the influence of daylight on real estate market pricing processes by means of regression analysis.

Tobacco industry pricing strategies during recent tax adjustments in Mexico: evidence from sales data

IntroductionPrevious studies have identified pricing strategies that the tobacco industry employs to try to minimise the impact of tobacco taxation, but these studies are mostly about high-income countries. This research...

The Impact of Indonesian Crude Oil Demand Prices on the Indonesian Biodiesel Industry

Biodiesel is one of Indonesia's potential export commodities as there is a production surplus that occurs every year from 2006 to 2020. The study used the 2SLS method with a validation and simultaneous equation model. Data processing using SAS/ETS version 9.4. The purpose of this study is to analyze the impact of Indonesia's crude oil demand price on Indonesia's biodiesel industry. The findings indicate that the demand for Indonesian biodiesel is positively impacted by a rise in the global real price of crude oil by 0.11%. This increase is due to both the biodiesel industry's and the local market's need for Indonesian palm oil. The local price of Indonesian biodiesel would rise by 0.49% due to the increase in demand for the fuel. The amount of biodiesel produced in Indonesia will increase by 0.87%, this increase in production is due to increasing domestic demand for Indonesian palm oil, and the volume of biodiesel exported to destination countries will increase by 0.01%. Exports of palm oil may be more impacted by the policy of raising the actual world price of crude oil. This implies that the program may potentially result in a rise in raw material exports. On the other hand, the biodiesel industry and other industries also see a spike in palm oil as a result of the strategy of raising the real world price of crude oil.