Synchronisation among short-term rental markets, co-movements and cycles in 39 European cities

This paper presents new evidence of the short-term rental market's prices and transactions from a daily time -series perspective in 39 European cities from 2015 to 2020. It uses Airbnb micro datasets to build time-series cycles by extracting the original observations containing total bookings (rent transactions), rental units sup-ply, and asking rent, with a daily periodicity. The cycles show the periods in which short-rental activity was more relevant for each city, and the level of rents across Europe. The paper provides empirical evidence of a long-term relationship among the city variables (tested via mean and variance). Causality supporting co-movements across cities was found by estimating a short-term naive market equilibrium model using the vector error correction model approach, supporting the hypothesis that the short-term rental market performs according to housing -market principles. Short-run elasticities among rents and contracts across the 39 cities show causal evidence of co-movements among rents and the supply and demand of properties. The market adjustment on the supply side estimates new units responding to changes in prices within 15 lags (days) and longer (350 lags) from the demand side, equivalent to eight to nine months. Evidence of the pandemic's limited effect on housing supply and prices' positive effect is also provided. A robust negative weekend impact on prices was found, suggesting stronger market relevance on weekdays.

COVID-19 and domestic trade in Bulgaria

Domestic trade is an essential contributor to economic growth and an indicator of the people's welfare. It is vulnerable to the COVID-19 crisis due to the pandemic itself and the government's measures against it. An accurate estimation of the pandemic influence on domestic trade is needed for effective economic intervention in support of the economic recovery and improvement of the well-being of the population. The aim of this paper is to estimate the magnitude and timing of the COVID-19 impact on domestic trade in Bulgaria. The data used in the study covered the period 2000-2020 with monthly data for the indicator “Turnover for wholesale and retail trade and repair of motor vehicles and motorcycles in Bulgaria.” This paper employed unit root tests, autocorrelation function analysis, building, estimating, forecasting ARIMA and ARCH models, and intervention analysis. The results revealed that Bulgarian domestic trade followed the difference-stationary process as unit root tests failed to reject the random walk hypothesis. The COVID-19 impact on domestic trade proved to be long-lasting and has permanently decreased its level since March 2020. The timing of the impact coincided with the government's measures against the pandemic. The drop in the volume of domestic trade was substantial and estimated at 19.3%. Following the nature of domestic trade, determined and decisive intervention is necessary if the Bulgarian government seeks to expand domestic demand and successfully procure economic recovery. © Lyubomir Todorov, 2022.

Impact of Sustainable Development Goals on Economic Growth in Saudi Arabia: Role of Education and Training

Sustainable development goals (SDGs) are intended to be attained as a balanced whole. However, significant interactions (the synergies and trade-offs) between the SDGs have caused the need, especially in developing economies, to identify and pursue them in line with their particular developmental needs. The research intends to empirically investigate the relationship between selected UN SDGs and GDP growth rate as a proxy for economic well-being in Saudi Arabia. We also investigate the role of education and training in achieving SDGs in accordance with the Saudi Vision 2030, which places emphasis on the knowledge economy. This research employs multiple regression analysis to explore the relationship between the SDG variables and the GDP. The results show that education and training, gender equity/women's empowerment, greenhouse gas emissions, and decent employment are positively and significantly related to the GDP growth, whereas poverty, hunger, and health appear to be negatively related. The research indicates that education and training can promote economic, socioeconomic, and health goals without compromising environmental goals. Consequently, the Saudi government should invest more in education and training to maximize synergies and minimize tradeoffs between the SDGs. This will help to promote sustainable employment generation, build human capital, improve socioeconomic empowerment through technology, and boost economic growth.

On the effects of COVID-19 on food prices in India: a time-varying approach

Since the inception of the novel coronavirus, immense research efforts have been made to understand how several economic indicators, including food security, would be affected. With India racing behind the United States in terms of daily infection rate and being a country with challenging food security issues, it is important to investigate how the presence of the pandemic has influenced the dynamics of food prices in the country. This paper considers seven price series from 167 markets across the five regions in India as well as the growth rate of COVID-19 infection. The paper uses a time-varying autoregressive model to investigate the nonlinear dynamics of food prices in relation to the pandemic in India. The resultant models reveal strong asymmetric properties with shock-inflicted persistence, which appear not to converge over the simulation period. Moreover, in terms of the location of the burden of the pandemic impact, we find a food product divide.

Panel Cointegration Modelling of COVID-19 Monthly Infected Cases and Deaths

In this paper, the cointegration relationships between COVID-19 new infection cases and the number of deaths due to COVID-19 in all 37 districts of Tamil Nadu state, India, during the period from July 3, 2020 to March 31, 2021 are investigated based on a panel regression Fully Modified Least Squares method and the Granger causality test © 2022. Natural Sciences Publishing Cor

Commentary on a method for testing resistance to shocks.

This note tours the Narayan (2020a: Has COVID-19 Changed Exchange Rate Resistance to Shocks?) approach to testing for resistance of a time-series variable to shocks. We take a step-by-step account of this approach and demonstrate its applicability with respect to the crude oil price.•The approach entails steps (1) to (8), as outline in the paper.•Future researchers will find this method useful in evaluating the resistance of variables to not only COVID-19 shocks but to any shock which has had a sufficiently long life.