Effect of Energy Prices on Economic Growth in the ECOWAS Sub-Region: Investigating the Channels Using Panel Data

The article empirically examines the effect of energy prices on economic growth within the Economic Community of West African States sub-region by acknowledging that the effect of energy prices on growth is quintessentially indirect and hence can be tracked through some channels. Exploiting the System Generalized Methods of Moments estimation technique for the period spanning 2002–2015, the results indicate that the overall effect of energy prices on economic growth is significantly negative. This effect propagates mainly through government consumption expenditure and investment, albeit its effect through real interest rate is positive. However, its negative effects on government consumption, investment, and exchange rate significantly overwhelm the positive effect from real interest rate.     

Hedonic pricing and the spatial structure of housing data – an application to Berlin

Housing prices are largely determined by physical location. By applying the outsample prediction accuracy of rental prices as evaluation criteria, we examine whether the choice of the hedonic model additionally depends on the spatial structure of housing data, i.e. accounting for locational effects by either district fixed effects or spatial econometric modelling. Our results show that a generalised spatio-temporal model outperforms a district fixed effects model only if the spatial density – the weighted mean distance to nearest neighbours – is relatively small. Moreover, we use the required density thresholds to deduce a pseudo indifference curve, thereby showing that the ratio of the weighted spatial distance-to-the mean district diameter increases with the mean sample size per district. This emphasises the role of data structure and district choices for model selection. Differences in data can thereby serve as an explanation for contradictory findings in literature, whether spatial econometric methods or simple district fixed effects are used.     

Forecasting Bordeaux wine prices using state-space methods

Generic Bordeaux red wine (basic claret) can be regarded as being similar to an agricultural commodity. Production volumes are substantial, they are traded at high frequency and the quality of the product is relatively homogeneous. Unlike other commodities and the top-end wines (which represent only 3% of the traded volume), there is no futures market for generic Bordeaux wine. Reliable forecasts of prices can to large extent replace this information deficiency and improve the functioning of the market. We use state-space methods with monthly data to obtain a univariate forecasting model for the average price. The estimates highlight the stochastic trend and the seasonality present in the evolution of the price over the period 1999 to 2016. The model predicts the path of wine prices out of sample reasonably well, suggesting that this approach is useful for making reasonably accurate forecasts of future price movements.     

Oil prices and economic activity: evidence for G-7 economies based on a wavelet approach

This study examines the relationship between oil prices and economic activity in the G-7 economies during the period 1960M1–2014M07 using a wavelet approach. The results show significant differences in the relationship between these two variables depending on the frequencies. Furthermore, we find that oil price shocks affect economic activity at low frequencies (long run) in all G-7 countries, while the effect at high frequencies (short run) is limited to a few countries.     

Stock market dependence in crisis periods: Evidence from oil price shocks and the Qatar blockade

This paper examines the correlation and the dependence patterns of the Qatar stock market with other markets using copula statistical theory and exploiting new datasets covering the period August 1998 to June 2018. To examine the crisis –specific change in the average degree of dependence we decomposed the data into the time periods before and after oil price shocks and the 2017 political crisis among the Gulf Cooperation Council members (i.e. the Qatari blockade). Our findings from the static copula modelling show that the correlations between the Qatari and the other stock markets significantly change after the oil price and the blockade crisis as well. The degree of change in the correlation is time varying and differs from county-group to another. Moreover, our findings reveals that the 2008 global financial crisis has a stronger impact than the price shocks and political crisis. The findings of the paper are of interest and allow for formulating a reliable and dynamic portfolio design framework for investors and risk managers.     

Oil price and Gulf Corporation Council stock indices: New evidence from time-varying copula models

Using a time-varying GJR copula approach, we determine the conditional dependence of the GCC stock indices on oil price between 2007 and 2016. We show how to improve the forecasting accuracy of the co-movement of energy and stock prices in an equally weighted portfolio. Contrary to prior findings, we demonstrate that due to the different co-movements across the GCC stock indices, portfolios of oil assets and several GCC stocks are less likely to be affected by systemic risk. The different co-movements across several stock indices over time provide different entry and exit points for stock investors. This approach is in line with the ‘buy low/sell high’ adage.     

Estimating the duration of different seasons and their impact on hotel room prices

The purpose of the study is to accurately measure the span of different seasons and its effect on the fluctuation of the occupancy rate and the average room rates in the hospitality sector. While prior studies have concentrated on measuring seasonality using calendar months, this study takes a different approach by measuring seasons in terms of the date count so that the exact starting and ending date of a season can be identified. This step involves adopting a non-parametric methodology that split the time scale into several small parts to obtain a better fit of the relationship and that can detect the starting and end of the season when given specific dates.     

Permit markets,carbon prices and the creation of innovation clusters

Innovation clusters combining public and private effort to develop breakthrough technologies promise greater technological advances to slow down climate change. We use a multi-country model with an emission trading system to examine whether and how international climate policy can incentivize countries to create such innovation clusters. We find that a minimal carbon price is needed to attract applied research firms, but countries may nevertheless fail to invest in complementary research infrastructure. We construct a mechanism that leads to innovation clusters when emissions targets are set before uncertainty surrounding technological developments is resolved. It is a combination of low permit endowments for the country with the lowest costs to build the needed infrastructure, compensation for this country by profits from permit trade, and maximal possible permit endowments for the remaining countries. We outline how the EU-ETS can be further refined according to this mechanism.     

Time-varying inter-urban housing price spillovers in China: Causes and consequences

The spatial spillovers of housing prices across regions are well documented by a large body of previous studies. This paper tries to investigate the dynamic (time-varying) evolution of spatial interactions and their underlying driving factors intensively. Using a recently developed Generalized Autoregressive Score (GAS) model, this paper examines the time-varying spatial spillovers of housing prices in 70 major and median cities of China from 2006 to 2019. We find that the GAS model can well capture the impact of time-varying critical events of Chinese real estate market on the whole. However, different regions display heterogeneous variation patterns over time. Further investigation shows that inter-regional labor mobility and trades are two major channels, accounting for 1.25% and 2.58% of the monthly standard deviations of spatial spillover effects from one city to another, respectively. We also characterize and distinguish between three time-varying patterns of spatial spillovers within different regions of China. Our results shed lights on the understanding of spatial spillovers across regional real estate markets across different city network structures within China.     

A new assessment of economic integration in East Asia: Application of an industry-specific G-PPP model

It is well known that intra-industry trade and cross-border production networks have promoted economic growth and regional integration in East Asia. However, regional supply and production chains may have been formed differently across industries, reflecting different degrees and a different scope of regional economic linkages at an industry level. This paper makes a threefold contribution. First, to assess industry-level differences, this study adopts the generalized purchasing power parity (G-PPP) model using industry-specific producer prices. Second, the momentum threshold autoregressive (M-TAR) model is employed to allow for possible nonlinearity arising from the dynamic nature of regional economic growth and development. Third, the Granger causality test is also conducted to assess whether regional economies have autonomously integrated. The empirical results reveal that economic integration has progressed more autonomously in the electrical industry, as well as in the transportation equipment industry, as China and the ASEAN countries have become the final destination markets for finished products in these two industries.