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The purpose of this study is to reveal the dynamics of house prices and sales in spatial and temporal dimensions across British regions.

This paper incorporates two empirical approaches to describe the behaviour of property prices across British regions. The models are applied to two different data sets. The first empirical approach is to apply the price diffusion model proposed by Holly et al. (2011) to the UK house price index data set. The second empirical approach is to apply a bivariate global vector autoregression model without a time trend to house prices and transaction volumes retrieved from the nationwide building society.

Identifying shocks to London house prices in the GVAR model, based on the generalized impulse response functions framework, I find some heterogeneity in responses to house price changes; for example, South East England responds stronger than the remaining provincial regions. The main pattern detected in responses and characteristic for each region is the fairly rapid fading of the shock. The spatial-temporal diffusion model demonstrates the presence of a ripple effect: a shock emanating from London is dispersed contemporaneously and spatially to other regions, affecting prices in nondominant regions with a delay.

The main contribution of this work is the betterment in understanding how house price changes move across regions and time within a UK context.

Since 1966, the Severn crossing has been connecting England and Wales. In January 2018, its ownership returned to the UK Government, and this marked the start of a toll-free journey across the two countries and made commuting between the regions more affordable. In this paper, we examine the impact of the toll removal on the property market.

We employ property-level data from the Land Registry and a difference-in-differences (DiD) empirical model for the periods 2016–2018 and 2019–2021 to capture the pre- and post-toll removal dynamics. The DiD estimation allows us to examine the causal relationship between policy changes and property prices.

Our findings suggest that property prices in Newport and Monmouthshire (South East Wales) are positively affected by the policy, which results in a statistically significant increase of 5.8% more than those located in the South West England (Bristol and South Gloucestershire) region in the period 2019–2021. The impact can reach up to 13.1% for properties located in a 10 km radius of the bridge. The results indicate that the toll removal enables the ripple effect across the two markets by reducing commuting costs.

This is the first paper that examines the Severn Crossing case study. Its contribution is significant since we provide empirical evidence on how reduced transportation costs increase property prices in the lowest income region and have the opposite effect on the area with higher incomes and economic activity levels.

This paper aims to examine the dynamics of house prices in metropolitan cities in an emerging economy. The purpose of this study is to characterise the house price dynamics and the spatial heterogeneity in the dynamics.

The author explores spatial heterogeneity in house price dynamics, using data for 35 Indian cities with a million-plus population. The research methodology uses panel econometrics allowing for spatial heterogeneity, cross-sectional dependence and non-stationary data. The author tests for spatial differences and analyses the income elasticity of prices, the role of construction costs and lending to the real estate industry by commercial banks.

Long-term fundamentals drive the Indian housing markets, where wealth parameters are stronger than supply-side parameters such as construction costs or availability of financing for housing projects. The long-term elasticity of house prices to aggregate household deposits (wealth proxy) varies considerably across cities. However, the elasticity estimated at 0.39 is low. The highest coefficient is for Ludhiana (1.14), followed by Bhubaneswar (0.78). The short-term dynamics are robust and show spatial heterogeneity. Short-term momentum (lagged housing price changes) has a parameter value of 0.307. The momentum factor is the crucial dynamic in the short term. The second driver, the reversion rate to long-term equilibrium (estimated at −0.18), is higher than rates reported from developed markets.

This research applies to markets that require some home equity contributions from buyers of housing services.

Stakeholders can characterise stable housing markets based on long-term fundamental value and short-run house price dynamics. Because stable housing markets benefit all stakeholders, weak or non-existent mean reversion dynamics may prompt the intervention of policymakers. The role of urban planners, and local and regional governance, is essential to remove the bottlenecks from the demand side or supply side factors that can lead to runaway prices.

Existing literature is concerned about the risk of a housing bubble due to relaxed credit norms. To prevent housing market bubbles, some regulators require higher contributions from home buyers in the form of equity. The dynamics of house prices in markets with higher owner equity requirements vary from high-leverage markets. The influence of wealth effects is examined using novel data sets. This research, documents in an emerging market context, the observations cited in low-leverage developed markets such as Germany and Japan.

Previous studies demonstrate that market-oriented reform has contributed significantly to China's economic growth from the efficiency-based economic view. But some argue that state-owned firms have access to policy information, scarce resources, and government support, and thus state-owned firms might foster innovation. This study tries to find out either market force or state ownership helps improve firms' R&D efficiency.

Using data from China's high-tech industry, we employed the fixed-effect stochastic frontier model and the spatial panel Han-Philips linear dynamic regression model to investigate the relationship between market-oriented reform and the dynamic evolution of R&D efficiency in both temporal and spatial dimensions. Moreover, we examined whether the relationship is affected in a state-owned economy and an industry protection environment.

The results indicate the following: (1) the R&D efficiency of China's high-tech industry has improved steadily and has converged gradually across its regions during the market-oriented reform; (2) the marketization degree is positively correlated with R&D efficiency and its regional convergence; (3) the state-owned economy and industry protection have significantly weakened the ability of market forces to shape R&D efficiency — i.e. they reduce, rather than enhance, R&D efficiency.

This investigation helps understand the drivers of R&D efficiency in transition economies, and the findings are also helpful in defining the boundaries and constraints of market forces.

Vertical electrical sounding (VES) and Rayleigh wave exploration are widely used in the exploration of near-surface structure, but both have limitations. This study aims to make full use of the advantages of the two methods, reduce the multiple solutions of single inversion and improve the accuracy of the inversion. Thus, a nonlinear joint inversion method of VES and Rayleigh wave exploration based on improved differential evolution (DE) algorithm was proposed.

Based on the DE algorithm, a new initialization strategy was proposed. Then, taking AK-type with high-velocity interlayer model and HA-type with low-velocity interlayer model near the surface as examples, the inversion results of different methods were compared and analyzed. Then, the proposed method was applied to the field data in Chengde, Hebei Province, China. The stratum structure was accurately depicted and verified by drilling.

The synthetic data and field data results showed that the joint inversion of VES and Rayleigh wave data based on the improved DE algorithm can effectively improve the interpretation accuracy of the single-method inversion and had strong stability and large generalizable ability in near-surface engineering problems.

A joint inversion method of VES and Rayleigh wave data based on improved DE algorithm is proposed, which can improve the accuracy of single-method inversion.

The purpose of this paper is to investigate the trend of transatlantic strategic convergence and policy coordination in response to Chinese trade practices and technological competition, specifically in the critical minerals sector.

The research draws on primary and secondary source material to identify evidence of and examine the drivers, manifestations and prospects for effective US-European efforts to advance the shared aim of reducing vulnerabilities in critical minerals supply chains.

The interests of the USA and Europe would be best served by prioritizing their own security, diversification and resilience strategies while seeking areas of common ground and constructive engagement with China.

The research offers a fresh perspective on the growing alignment and persistent gaps in US and European perspectives on China’s rising influence and assertive behavior.

The research highlights the vital role of critical minerals in national security, economic competitiveness, technological advancement and sustainable resource management. It underscores the shared recognition on both sides of the Atlantic that securing a stable supply of critical minerals – essential for maintaining strategic capabilities, driving innovation and ensuring long-term economic prosperity – necessitates tighter transatlantic coordination as well as constructive engagement with China.

This study aims to assess how real income, oil prices and gold prices affect housing prices in China from 2010 to 2021.

This study uses a novel bootstrap autoregressive distributed lag (ARDL) testing to empirically analyze the short and long links among the tested variables.

The ARDL estimations demonstrate a positive impact of oil price shocks and real income on housing market prices in both the phrases of the short and long run. Furthermore, the results reveal that gold price shocks negatively affect housing prices both in the short and long run. The result can be attributed to China’s housing market and advanced infrastructure, resulting in a drop in housing prices as gold prices increase. Additionally, the prediction of housing market prices will provide a base and direction for housing market investors to forecast housing prices and avoid losses.

To the best of the authors’ knowledge, this is the first attempt to analyze the effect of gold price shocks on housing market prices in China.

This study probes the psychological interplay between investor sentiment and the returns of cryptocurrencies Bitcoin and Ethereum. Employing the Granger causality test, the authors aim to gauge how extensively the Fear and Greed Index (FGI) can predict cryptocurrency return movements, exploring the intricate bond between investor emotions and market behavior.

The authors used the Granger causality test to achieve research objectives. Going beyond conventional linear analysis, the authors applied Smooth Quantile Regression, scrutinizing weekly data from July 2022 to June 2023 for Bitcoin and Ethereum. The study focus was to determine if the FGI, an indicator of investor sentiment, predicts shifts in cryptocurrency returns.

The study findings underscore the profound psychological sway within cryptocurrency markets. The FGI notably predicts the returns of Bitcoin and Ethereum, underscoring the lasting connection between investor emotions and market behavior. An intriguing feedback loop between the FGI and cryptocurrency returns was identified, accentuating emotions' persistent role in shaping market dynamics. While associations between sentiment and returns were observed at specific lag periods, the nonlinear Granger causality test didn't statistically support nonlinear causality. This suggests linear interactions predominantly govern variable relationships. Cointegration tests highlighted a stable, enduring link between the returns of Bitcoin, Ethereum and the FGI over the long term.

Despite valuable insights, it's crucial to acknowledge our nonlinear analysis's sensitivity to methodological choices. Specifics of time series data and the chosen time frame may have influenced outcomes. Additionally, direct exploration of macroeconomic and geopolitical factors was absent, signaling opportunities for future research.

This study enriches theoretical understanding by illuminating causal dynamics between investor sentiment and cryptocurrency returns. Its significance lies in spotlighting the pivotal role of investor sentiment in shaping cryptocurrency market behavior. It emphasizes the importance of considering this factor when navigating investment decisions in a highly volatile, dynamic market environment.

This research aims to determine the ideal fare for various aircraft itineraries by modeling prices using a neural network method. Dynamic pricing has been studied from the airline’s point of view, with a focus on demand forecasting and price differentiation. Early demand forecasting on a specific route can assist an airline in strategically planning flights and determining optimal pricing strategies.

A feedforward neural network was employed in the current study. Two hidden layers, consisting of 18 and 12 neurons, were incorporated to enhance the network’s capabilities. The activation function employed for these layers was tanh. Additionally, it was considered that the output layer’s functions were linear. The neural network inputs considered in this study were flight path, month of flight, flight date (week/day), flight time, aircraft type (Boeing, Airbus, other), and flight class (economy, business). The neural network output, on the other hand, was the ticket price. The dataset comprises 16,585 records, specifically flight data for Iranian airlines for 2022.

The findings indicate that the model achieved a high level of accuracy in approximating the actual data. Additionally, it demonstrated the ability to predict the optimal ticket price for various flight routes with minimal error.

Based on the significant alignment observed between the actual data and the tested data utilizing the algorithmic model, airlines can proactively anticipate ticket prices across all routes, optimizing the revenue generated by each flight. The neural network algorithm utilized in this study offers a valuable opportunity for companies to enhance their decision-making processes. By leveraging the algorithm’s features, companies can analyze past data effectively and predict future prices. This enables them to make informed and timely decisions based on reliable information.

The present study represents a pioneering research endeavor that investigates using a neural network algorithm to predict the most suitable pricing for various flight routes. This study aims to provide valuable insights into dynamic pricing for marketing researchers and practitioners.

It is critical for those who are engaged in the work of resisting the movement of academically restrictive policy to understand that it is a deliberate act on the part of conservatives to outlaw critical race theory (CRT) specifically, because it is a theoretical mechanism for discrediting the rhetorical foundations of their policy movement. The knee-jerk institutional courses of action to now defund initiatives and curriculum related equity, diversity and inclusion (EDI) represent what has always been a deeply rooted investment in white supremacy on the part of the institutions (Baldwin, 2021; Patel, 2021; Squire, 2021).

The author explores and defines the CRT tenets of interest convergence (Bell, 1980) and whiteness as property (Harris, 1993) in relation to EI (Fricker, 2007; Dotson, 2011) as frameworks for examining three EGOs in the region where these policies have become most dominant. All three are critical tools of analysis for understanding the stake the White conservative political elite have in EGOs, and the magnitude of EI these policies represent, and stand endorse in their rhetoric. Definitions of EI often rely on the work of Amanda Fricker’s (2013) text on the subject, but this paper is invested in the expansions of this theorization for speaking to the nature of the injustice that EGOs represent as a matter of historical trend, with grave implications for futures marked by continued oppression. Whiteness as property and interest convergence are points for explicating the dialectic and material aspects of issues of race and equity in this country; namely, how knowledge processes inherent to higher education sound even more alarms as EGOs become commonplace for college campuses.

To support the arguments laid out, the author provides a historical review of the settler-colonial foundations of higher education as an american institution. This is meant to provide contour to the image of postsecondary education that exists today. In accordance with this paper’s allegiance to CRT, many of the texts would be considered revisionist history (Delgado and Stefancic, 2023), which stray from dominant narratives of american comfort and speak more accurately to the experiences of minoritized populations. The author then applies the same analysis to the sociopolitical contexts of EGOs, and to policy language itself. Each section is closed with an explanation of its connection to tenets of CRT and EI so as to provide a thread to follow into the subsequent discussion section.

In the first presentation of the early writings of this work, the author was lucky enough to be in community with Barbara Applebaum at the annual meeting for the American Educational Studies Association and engage in discourse surrounding EI and CRT applications to EGOs. In conversations surrounding the will in the willful ignorance that is exemplified in the movement of EGOs, the author had shared with Dr Applebaum the early thinking on how that will was the same force that brought together converging interests, which have continually forecasted interest divergence. This is commonly referred to as “political backlash.” The author had said something along the lines of: “if we follow the interest convergence, we can get in front of the subsequent political moves to turn the clocks on what was once celebrates progress.” This conversation planted the seed for what is the thesis of this paper. Interest convergence and divergence happen at the will of white populations because of the american truth of whiteness as property. In the context of higher education, this means that because educational pursuit has largely been white property, it has served as an arena for white populations to converge and diverge their interests with those of the minoritized. For example, the policies that drained federal funding for higher education in the 1970s were passed on the tails of a Civil Rights Movement that shook the very foundation of this country and expanded access to postsecondary education for racially minoritized groups (Berret, 2015).

Ensuring that this social construction is a matter of status quo has largely been the work of postsecondary institutions, and EGOs represent the most recent attempt at epistemically imposed inferiority. Explicit attention to the fact of higher education’s complicity and overall investment in the socialization of oppression is necessary to engage in transformative practice that resists anachronism. If higher education researchers and practitioners do not recognize the stake in both the presence and resistance to EGOs, there would likely be acts of resistance that will belie an act of interest convergence – and later divergence – on the part of the state.