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The primary aim of this research is to examine the effects of the Renovation, Conversion, and Extension (ROT) tax deduction for renovations on the scope and quality of renovations and its subsequent impact on house prices across various Swedish municipalities.

This study utilises a two-way fixed effect instrument variable (IV) spatial Manski approach, analysing balanced panel data from 2004 to 2020 at the municipal level (290 municipalities) in Sweden. The methodology is designed to assess the impact of the ROT subsidy on the housing market.

The study reveals that the ROT subsidy has significantly influenced house prices, with noticeable variations between municipalities. These differences are attributed to the varying amounts of tax reductions for renovations and the extent to which property owners utilise these subsidies.

The research is limited to the context of Sweden and may not be generalisable to other countries with different housing and subsidy policies. The findings are crucial for understanding the specific impacts of government subsidies on the housing market within this context.

For policymakers and stakeholders in the housing market, this study highlights the tangible effects of renovation subsidies on property values. It provides insights into how such financial incentives can shape the housing market dynamics.

The research underscores the role of government policies in potentially influencing equitable access to housing. It suggests that subsidies like ROT can have broader social implications, including the distribution of housing benefits among different income groups and regions.

This study contributes original insights into the field of applied real estate economics by quantitatively analysing the impact of a specific government subsidy on the housing market. It offers a unique perspective on how fiscal policies can affect property values and renovation activities at the municipal level in Sweden.

This pragmatic investigation examines the dynamic nexus between crude oil prices and food inflation from South and Southeast Asian perspectives.

This study investigates the asymmetric effects of global crude oil prices on food inflation using a nonlinear autoregressive distributed lag (ARDL) model with monthly data covering the period from May 2012 to April 2022.

The empirical evidence reveals that international crude oil has a substantial impact on food prices in the majority of countries. Additionally, the relevant outcome documents that the asymmetric effect of global crude oil on food inflation applies to Sri Lanka and Vietnam, while in the other countries, it is symmetric.

Considering the optimistic outcomes, this empirical investigation is certain to have important shortcomings. Initially, the conclusions drawn from the above findings were based only on detailed assessments of the aforementioned variables' data over a 10-year period. The current scholarly analysis investigates the existence of an asymmetric impact of crude oil on food inflation, limited to six Asian countries. On the other hand, considering a greater number of Asian economies could enhance the analysis’s robustness and precision.

The current research aims to contribute to the existing literature on food inflation and global oil prices in the following ways: First, this study investigates the nexus between global crude oil and food inflation in a novel way, considering the nonlinear relationship between the variables. To figure out the nonlinear relationship or uneven effect of the global oil shock on food prices, we use the nonlinear ARDL model. Secondly, as food inflation is one of the major issues for the South and Southeast Asian economies, this empirical investigation broadens the analysis by incorporating a perspective from South and Southeast Asia, an area largely overlooked by previous researchers. Finally, we are very optimistic about the phenomenal contribution of current analysis to comprehending the conception of oil and food price dynamics from a broader perspective to achieve the Sustainable Development Goal (SDG), which aims for a sustainable resolution to end hunger in all its forms by 2030 and to accomplish food security, especially in emerging economies.

This study aims to investigate the relationship among liquidity, information asymmetry and political risk for non-US stocks listed on the NYSE. Additionally, the study aims to explore the impact of political tension on market quality.

This research adopts a quantitative methodology to examine the interplay between liquidity, information asymmetry and political risk in non-US stocks on the NYSE. A comprehensive analysis encompasses stocks from countries with varying political risk levels, demonstrating a correlation between lower political risk and improved market quality. In assessing the impact of US–China trade conflicts on Chinese stocks, political shocks are scrutinized. Results indicate that heightened political tension exacerbates information asymmetry and diminishes market liquidity, underscoring the susceptibility of stocks in politically strained environments to adverse shocks.

Non-US stocks from countries with lower political risk show higher liquidity and market efficiency, with narrower bid-ask spreads and smaller price impacts of trades. These stocks also demonstrate a higher market quality index, indicating improved overall market performance. In addition, during periods of escalated US –China political tension over trade policy, the liquidity of non-US stocks from China worsens, leading to wider bid-ask spreads and increased information asymmetry.

This study provides novel insights into the impact of political risk on stock market dynamics for non-US stocks listed on the NYSE, with a particular emphasis on the US –China trade conflict's effect on Chinese stocks.

The COVID-19 pandemic was a shock to the food supply chain without modern precedent. Challenges in production, manufacturing, distribution and retailing led to the highest rates of food price inflation in the US since the 1970s. The major goal of this paper is to describe statistically the impact of the pandemic of food price inflation and volatility in the US and to discuss implications for industry and for policymakers.

We use Bureau of Labor Statistics data to investigate food prices in the US, 2020–2021. We apply 16 statistical approaches to measure price changes and volatility and three regression approaches to measure counterfactuals of food prices, had the pandemic not occurred.

Food price inflation and volatility increased substantially during the early months of the pandemic, with a great deal of heterogeneity across food products and geographic regions. Food price inflation was most pronounced for meats, and contrary to expectations, highest in the western US Forecasting approaches demonstrate that grocery prices were about 7% higher than they would have been without the pandemic as of the end of 2021.

The research on COVID-19 and the food system remains in its nascent stage. As findings on food loss and waste, employment and wages, food insecurity and more proliferate, it is vital to understand how food prices were connected to these phenomena and affected. We also motivate several ideas for future work.

The purpose of this study is to discover what attributes of casino buffet restaurants are the most important for customers’ willingness to pay (WTP).

Choice-based conjoint analysis was used in this study to test seven attributes: food, price/value, real price, service, atmosphere, the number of reviews and user-generated star ratings. Sawtooth Software was used to do the conjoint analysis, and a series of significance t-tests were run to determine the significance of each attribute on WTP with Statistical Package for the Social Sciences (SPSS).

Based on a survey of 483 respondents who had visited a buffet at a casino within the last two years, this study found that food is ranked as the most significant attribute of a casino buffet restaurant, followed by real price and service quality.

Theoretically, this work is the first to the authors’ knowledge to apply the antecedents of behavioral intention to willingness-to-pay for niche restaurants. Practically, the results of this study will help casino buffet operators as they re-open after COVID-19. Future studies could collect data in the post-pandemic environment and examine WTP at casino buffets in different geographic locations.

This study aims to show the difference between the two types of oil price volatility resulting from either increases or decreases in oil prices and find evidence of the differential effect of oil price volatility on firms' environmental initiatives.

This paper examines how volatility in crude oil prices affect corporate environmental responsibility among US firms (excluding oil and gas producers) between 2002 and 2020, with a particular focus on the differential impact of oil price volatility.

The authors find that a one standard deviation increase in oil volatility resulting from positive changes in oil prices corresponds to a 12.7% decrease in environmental score, while the same increase in volatility from negative changes in oil prices leads to a 5.5% decrease in environmental score. Financial constraints are identified as a potential channel through which oil price volatility influences environmental activities. Specifically, a one standard deviation increase in oil volatility from positive price changes leads to an 18% decrease in environmental score for firms with high financial constraints, compared to an 8% decrease for firms with low financial constraints.

This study builds on the research of Phan et al. (2021) and Maghyereh and Abdoh (2020). Pan et al. reveal a negative association between oil price uncertainty and corporate social responsibility in the oil and gas sector, yet they overlook 1) the asymmetric impacts of oil price changes and sectoral disparities. Moreover, 2) their inclusion of a year-fixed effect undermines their findings’ reliability, as the oil price volatility variable remains constant across all firm-year observations, and including a year-fixed effect diminishes its explanatory power.

This study aims to quantify the influence of urbanization on housing prices at the district-based level, while also investigating the heterogeneous impacts across different quantiles of housing prices.

The study uses remote-sensed spectral images from the Landsat 7 ETM+ satellite to measure urbanization, replacing prior reliance solely on urban population metrics. Subsequently, the two-step system generalized method of moments is used to evaluate how urbanization influences district-based housing prices through three spectrometries: Urban Index (UI), Normalized Difference Built-up Index (NDBI) and Built-Up Index (BUI). Finally, this study examines the heterogeneous impacts across various housing price quantiles through Dynamic Panel Quantile Regression with non-additive fixed effects under Markov Chain Monte Carlo simulation.

The study demonstrates that urbanization leads to an increase in regional housing prices. However, these impact magnitudes vary across housing price quantiles. Specifically, the impact exhibits an inverse V-shaped curve, with urbanization exerting a more pronounced influence on the 60th percentile of housing prices, while its effect on the 10th and 90th percentiles is comparatively weaker.

This study uses a novel method of remote sensing to measure urbanization and investigates its effects on housing prices. Furthermore, it provides an empirical application of non-additive fixed effect quantile regression for analyzing heterogeneity.

This study aims to analyse the effect of competition on retail fuel prices in a small European Union (EU) country with high market concentration.

The researchers use a panel data set to estimate a fuel price equation that includes supply and demand factors as well as time-fixed effects.

The study finds that more competitors in the local market decrease prices, whereas the high market share of oligopoly brands does not condition this effect. Additionally, independent brands set lower prices than wholesalers, and gas stations located near the borders of almost all neighbouring countries are associated with higher prices.

The study suggests that Slovenia’s retail fuel market maintains competitive pricing despite high oligopolistic shares because of historical regulatory influences that shaped firm behaviour and pricing strategies, along with geographical and economic factors such as Slovenia’s role as a transit country. External competitive pressures from neighbouring countries and high levels of traffic, combined with the remnants of regulatory structures, help prevent market abuses and keep fuel prices lower than in other EU countries.

It also indicates that policy should encourage fiercer competition in the local market by increasing the density of gas stations, especially from independent brands.

These findings may be associated with specific country characteristics. This paper introduces unique findings that shed light on the impact of a small market on competition, with a particular focus on highlighting the effect of oligopolistic brands.

This paper aims to examine the short-term market impact of the beginning of the military conflict between Russia and Ukraine (24 February 2022), the world’s largest oil and gas companies.

The authors examine the world’s 100 largest listed oil and gas companies at and around the beginning of the military conflict between Russia and Ukraine using an event study methodology.

The authors observe a positive and statistically significant stock price reaction at and around the military conflict. These results are consistent with the asset pricing perspective. Conversely, the stock market returns of Russian oil and gas companies, as well as those companies that were “forced” to divest in Russia due to corporate activism, exhibit a negative and statistically significant impact from the conflict. These reactions are reinforced or mitigated by company-specific characteristics such as size, profitability and institutional ownership. Finally, the findings indicate that companies engaged in oil and gas exploration and production report abnormally higher returns compared to firms in the other two subsectors of the industry.

The effect of the war on stock markets has been relatively little examined in the financial theory. This study intends to fill this gap in the literature.

This study aims to evaluate the resource curse hypothesis in an oil-dependent economy, Saudi Arabia, through examining the impact of oil price volatility on foreign ownership among Saudi listed firms.

The study analyzes a unique data set of firm-level data on foreign ownership for the period 2009–2015. A multivariate regression model was applied to analyze the relationships under study.

The analysis reveals a negative association between oil price volatility and foreign ownership in firms with high leverage and low stock volatility.

Policymakers are encouraged to develop policies to control shocks in the supply and demand of oil and enforce economic diversification. Investors can better understand the dynamics of an oil-based economy stock market based on the investment behavior of foreign investors and their response to oil price shocks.

This study adds to the literature by analyzing the relationship understudy in an oil-rich and oil-dependent emerging economy, where its critical economic parameters are influenced by oil price volatility and it has the largest and the most liquid stock exchange in the MENA region.