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This paper aims to examine the reaction of energy inflation to geopolitical risks in the European Economic Area between 1990 and 2015.

This study applies the nonparametric time-varying coefficient panel data model with fixed effects. In addition, to further reveal potential tail effects that may not have been captured by conditional mean-based regressions, the method of moments quantile regression was also used.

The findings of this study are as follows: first, as European countries get exposed to geopolitical tensions, it is expected that energy prices will surge. Second, the ability of geopolitical risk to trigger energy inflation in recent times is not as powerful as it used to be. Third, countries with a lower inflation rate, when exposed to geopolitical risks, experience smaller increases in energy inflation compared to countries with a higher inflation rate.

The findings of this study lead us to the conclusion that transitioning from nonrenewable to renewable energy use is one channel through which the sampled countries can battle the energy inflation, which geopolitical risks trigger. A sound macroeconomic policy for inflation control is a complementary channel through which the same goal can be achieved.

Given the increasing level of energy inflation and geopolitical risks in the world today, this study is an attempt to reveal the time-varying characteristics of the relationship between these variables in European countries using a nonparametric time-varying coefficient panel data model and method of moments quantile regression with fixed effects.

This paper examines the role price fluctuations associated with internationally traded commodities play in inflationary conditions and inflation uncertainty among economies in Sub-Saharan Africa.

Using a panel 32 countries from the sub-region from 1996 to 2019, this study employed Two-Step System Generalized Method of Moments (GMM) estimation technique in its analysis.

Empirical evidence demonstrates that fluctuations in forex-adjusted price of crude oil, gold and cocoa have significant positive impact on inflation while forex-adjusted changes in price of cotton tend to have significant negative influence on consumer price inflation among economies in the sub-region. Additionally, the study found that gold, cocoa and cotton price changes on the international market have significant positive impact on inflation uncertainty in the sub-region (rise in price leads to increase rate of inflation uncertainty). Furthermore, improved regulatory quality and growth in output growth (GDP per capita growth) were found to help in stabilizing inflation uncertainty (reduce inflation uncertainty) among economies in the sub-region during periods of persistent growth in general price levels.

The study present a different approach based on individual economy forex-adjusted global prices of internationally traded commodities instead of general prices often used in the literature and assessed the effects such adjusted commodity prices have on inflation and inflation uncertainty. Additionally, the moderating role of regulatory quality and output growth between surmised nexuses are also examined.

Mauritius’s residential real estate sector has undergone an increase in foreign investment over the past decades. This study aims to establish if the increasing level of foreign real estate investments (FREI) has increased land demand and land prices. The study also aims to depict whether the relation between FREI and land prices prevails at an aggregate and/ or a regional level.

Data from 26 regions, classified as urban, rural and coastal is collected on an annual basis over the period 2000 to 2019, and a dynamic panel regression framework, namely, an autoregressive distributed lag model, is used to take into account the dynamic nature of land price modeling.

The findings show that, at the aggregate level, in the long-term, FREI does not have a significant influence on land prices, while in the short term, a positive significant relationship is noted between the two variables. A regional breakdown of the data into urban, rural and coastal was done. In the long term, only in coastal regions, a positive significant link was observed, whereas in urban and rural regions FREI did not influence land prices. In the short term, the positive link subsists in the coastal regions, and in rural regions also land prices are positively affected by FREI.

Unlike other studies which have used quite general measures of FREI, the present research has focused on FREI mainly undertaken in the residential real estate market and how these have affected residential land prices. This study also contributes to research on the determinants of land prices which is relatively scarce compared to research on housing prices.

The price clustering behavior is becoming a core part of the market efficiency theory especially with the development of trading strategies and the occurrence of major and unprecedented shocks which have led to severe inquiry regarding asset price dynamics and their distribution. However, research on emerging stock market is scant. The study contributes to the literature on price clustering by investigating an active emerging stock market, the Muscat stock market one of the Arabian Gulf Markets.

This research adopts the artificial intelligence technique and other statistical estimation procedure in understanding the price clustering patterns in Muscat stock market and their main determinants.

The findings reveal that stock prices are marked by clustering behavior as commonly highlighted in the previous studies. However, we found strong evidence of price preferences to cluster on numbers closer to zero than to one. We also show that the nature of firm’s activity matters for price clustering behavior. In addition, firms with traded bonds in Oman market experienced a substantial less stock price clustering than other firms. Clustered stock prices are more likely to have higher prices and higher volatility of price. Finally, clustering raised when the market became highly uncertain during the Covid-19 crisis especially for the financial firms.

This study provides novel results on price clustering literature especially for an active emerging market and during the Covid-19 pandemic crisis.

In the Netherlands, thesis assessment quality is a growing concern for the national accreditation organization due to increasing student numbers and supervisor workload. However, the accreditation framework lacks guidance on how to meet quality standards. This study aims to address these issues by sharing our experience, identifying problems and proposing guidelines for quality assurance for a thesis assessment system.

This study has two parts. The first part is a narrative literature review conducted to derive guidelines for thesis assessment based on observations made at four Dutch universities. The second part is a case study conducted in one bachelor’s psychology-related program, where the assessment practitioners and the vice program director analyzed the assessment documents based on the guidelines developed from the literature review.

The findings of this study include a list of guidelines based on the four standards. The case study results showed that the program meets most of the guidelines, as it has a comprehensive set of thesis learning outcomes, peer coaching for novice supervisors, clear and complete assessment information and procedures for both examiners and students, and a concise assessment form.

This study is original in that it demonstrates how to holistically ensure the quality of thesis assessments by considering the context of the program and paying more attention to validity (e.g. program curriculum and assessment design), transparency (e.g. integrating assessment into the supervision process) and the assessment expertise of teaching staff.

This paper aims to clarify the impact of information asymmetry on users' payment rates and examine the role of perceived uncertainty (PU) and acceptable price (AP) in the relationship between information asymmetry and users' payment rates.

To test the influences of information asymmetry on users' payment rates, this paper collects 18,489 transaction data from the Chinese knowledge payment platform Zhihu with a Python crawler. This paper constructs a mediation model to define the relationship between information asymmetry and users' payment rates by introducing PU and AP as the mediators.

Information asymmetry negatively affects users' payment rates. In addition, PU and AP mediate the information asymmetry in users' payment rates bond.

This study only explores the mediators of the information asymmetry users’ payment rates bond, ignoring the effect of potential moderators, which would be an important direction for future research.

The findings of this paper suggest that information communication is essential in knowledge market transactions. Knowledge providers, as well as knowledge platforms, should enhance information exchange with consumers in order to increase product sales.

This paper provides a new perspective for understanding how information asymmetry affects users' payment rates and helps to guide suppliers to improve product quality. The research framework of this paper is universal to a certain extent.

This paper is one of the first to propose using PU and AP to construct a mediation model to study the information asymmetry between users' payment rates relationship. It provides a new perspective for understanding the channel of information asymmetry in customer behavior.

Wheat, which is one of the major staple food grain crops in India, continues to depict occasional fluctuation in the prices though Union government has adopted administered price policy for wheat by intervening in its procurement at assured prices and distribution. Such fluctuations in prices are usually attributed to inefficient functioning of the agricultural markets. Since spatially separated markets also play an important role to determine efficiency of the agricultural markets, the study has used market integration as one of the tools to analyze the price transmission across the spatially separated markets to identify causes of price fluctuations and suggest ways to stabilize wheat prices.

The study utilizes monthly wholesale prices for January, 2006 to May, 2016 for dara wheat. First, the study employs augmented Dickey and Fuller (ADF), Phillips and Perron (PP) and Kwiatkowski, Phillips, Schmidt and Shin (KPSS) tests to check stationarity in wheat prices. Second, Johansen's cointegration test is applied to assess the integration of wholesale prices between selected pairs of wheat markets to determine long-run relationship among them. Third, Granger casualty test is used to find the direction of causality between the wheat market pairs. Finally, threshold vector error correction model (TVECM) and likelihood ratio (LR) tests are employed to examine long-run adjustment of prices towards the equilibrium in selected wheat markets.

Since wheat wholesale prices for the selected markets are found to be integrated of the order one, that is [I(1)], Johansen's test of cointegration is employed and its findings reveal that the selected wheat market pairs exhibit cointegration and show a long-run price association among themselves. There exists a bi-directional causality among the wheat market pairs. Since LR test is in favor of threshold model (except for Etawah–Delhi pair), one and two threshold models were also performed accordingly. Findings show that wholesale prices of wheat in Delhi markets remain higher than the prices of all other regional markets as regional markets are found to adjust their prices towards Delhi market. Distance of the wheat markets from each other is directly associated with threshold parameters, which are analogous to the transaction costs. Geographically dispersed wheat markets incorporate high transaction and vice versa.

The study argues that there is need to improve rural infrastructure and connectivity of the agricultural markets and remove market asymmetries through unified market regulating mechanisms across the states. This will enable price adjustment process from primary wholesale markets (in production regions) to the secondary wholesale markets (in scarcity regions) quickly.

The contribution of the study in the existing literature lies in the fact that there are no empirical evidences in the context of India that use price transmission as a tool of market integration among spatially separated wheat markets using TVCEM as this model examines role of transaction costs in efficient functioning of the agricultural markets.

This study aims to test the effect of Seattle’s discontinuous sidewalk requirement, on the number of housing units per construction permit.

This study uses discontinuity linear regression (DLR) on a database of Seattle’s housing construction permits during January-2015 to January-2018, controlled by 51 socioeconomic, planning and geographic variables. The sidewalk requirement is continuous inside the designated urban villages; however, it is spatially and quantitatively discontinuous in the rest of the city: certain blocks at certain locations require sidewalks’ design and construction in permits with six or more housing units. DLR detects the effect of the discontinuity while controlling for a vast array of confounding variables.

The primary finding is that the discontinuous requirement reduces the number of housing units in about 75% of a housing unit per permit, which at the aggregate level amounts to around 335 fewer housing units during the period of analysis.

The database is relatively small, which has limited a more thorough specification process and robustness tests.

Besides directly testing the effect of a discontinuous in-kind development contribution, the research setup allows to discuss a wider, more structural problem: the possibility of contributions avoidance due to spatial substitution. In contrast, spatially continuous (i.e. city-level) contributions cannot be avoided by performing spatial substitution, and they are internalized by the housing supply side (market-neutral).

Investors who can transfer their savings to investments in a well-regulated market benefit not only themselves but also economic development. Hence, it is crucial for fund owners to evaluate their stock market investment decisions. The goal of the study is to understand which model determines the asset returns most efficiently. In this regard, the validity of single and multi-index asset pricing models (capital asset pricing model-CAPM and Fama–French models) has been examined in the Turkish Stock Exchange for 2009–2020, with the quantile regression (QR) approach.

On 18 portfolios comprised of quoted stocks in the Istanbul Stock Exchange 100 (ISE-100/BIST-100), we test the CAPM, the Fama and French three factor model (FF3) and the Fama and French five factor model (FF5). Empirical analyses have been carried out via QR approach regressing the portfolios' average weekly excess returns on risk premium/market factor (Rm-Rf), firm size, book value/market value (B/M), profitability and investments factors. QR estimation has been employed since QR is more effective and provides a better definition of the distribution’s tails.

Our empirical findings have revealed that the average excess weekly returns can be explained more strongly via CAPM. Moreover, Fama and French models are expected to give more reliable result with more data, whereas the market premium would give robust results for the Turkish Capital Market.

Individuals investing in financial assets must find the price model that best fits the market. The return can be approximated in the most appropriate manner using the right variables.

The study differs from other research by comparing the asset pricing models via examining the assets' weekly returns with QR in the Istanbul Stock Exchange 100 (ISE-100).

The city of Quito is a World Heritage Site (WHS) in Ecuador and the city owns one of the best-preserved and extensive historic centers in Latin America for cultural tourism. This study aims to identify the factors that constitute perceived value construct at the WHS of Quito.

This research collects data from tourists who have visited the city of Quito, Ecuador. A total of 381 on-site questionnaires are used. Data have been analyzed using exploratory factorial analysis.

Results regarding the dimensional structural framework of perceived value indicate that perceived value at the WHS of Quito has five factors: (1) monetary and non-monetary costs (MNC), (2) staff service quality (SSQ), (3) tourist offer accessibility (TOA), (4) destination attractiveness (DA) and (5) information accessibility (IA).

Two new factors of accessibility have been proposed in this study for measuring consumer value at a WHS. Perceived value and accessibility have been treated as two separate subjects in academic literature before. However, this article contributes to the understanding of perceived value at WHS, including factors linked to accessibility. Both managerial and theoretical implications for WHS are discussed.