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.     

A truly global crisis? Evidence from contagion dependence across international REIT markets

This study examines the global nature of the recent crisis under bivariate Markov-switching models for pre- and post-crisis periods using the breakpoint of August 9, 2007. It quantifies international synchronization of boom-bust regime switches to investigate contagion-type dynamic comovements of Real Estate Investment Trusts (REITs). Global REIT markets display persistent bust regimes from September 2008 to May 2009, whereas the regime-switching patterns are not significant in the pre-crisis period. The results provide new evidence for global REIT contagion phenomena and suggest greater difficulties in diversifying risks across global REIT markets during the post-crisis period.     

Is it still economic to build a new coal-fired power plant in the U.S.? A real option analysis

In the U.S., virtually no new coal-fired power plants have been built in recent years. Both industry experts and academics seem to believe that no rational firm will build a new coal-fired plant. Will such a trend continue in the future? To provide insights into this question, we investigate the optimal decision of an electricity company with an irreversible and deferrable opportunity to build either a new coal-fired or natural gas-fired power plant as its new base-load resource. According to our real option analysis, the optimal decision depends on the location. In the case of the eastern U.S., it is optimal to choose a natural gas plant if a firm is given a choice among a new natural gas plant, a new coal plant and deferring the investment. However, contrary to the common sentiment in the industry and academia, building a new coal plant in the western U.S. is still more economical than building a new natural gas plant in the absence of emission pricing. Furthermore, introducing carbon pricing to western U.S. states, as California did, can substantially increase the probability that a firm will optimally choose a natural gas plant over a coal plant.     

Volatility spillovers between WTI and Brent spot crude oil prices: an analysis of granger causality in variance patterns over time

There has been an increase in price volatility in oil prices during and since the global financial crisis (GFC). This study investigates the Granger causality patterns in volatility spillovers between West Texas International (WTI) and Brent crude oil spot prices using daily data. We use Hafner and Herwartz’s (2006) test and employ a rolling sample approach to investigate the changes in the dynamics of volatility spillovers between WTI and Brent oil prices over time. Volatility spillovers from Brent to WTI prices are found to be more pronounced at the beginning of the analysis period, around the GFC, and more recently in 2020. Between 2015 and 2019, the direction of volatility spillovers runs unidirectionally from WTI to Brent oil prices. In 2020, however, a Granger-causal feedback relation between the volatility of WTI and Brent crude oil prices is again detected. This is due to the uncertainty surrounding how the COVID-19 pandemic will evolve and how long the economies and financial markets will be affected. In this uncertain environment, commodities markets participants could be reacting to prices and volatility signals on both WTI and Brent, leading to the detection of a feedback relation.     

Do Energy Prices Affect U.S. Investor Sentiment?

The current literature has examined the effect of investor sentiment on energy prices, but no study ever has explored the validity of the reverse question. Therefore, this article explore whether energy prices (i.e., crude oil and natural gas prices) affect U.S. investor sentiment, using the methodology of quantile regression. The empirical results document that controlling for a number of U.S. macroeconomic and financial factors, there exists a statistically significant association between oil and natural gas prices and investor sentiment. However, only natural gas prices appear to retain their statistical significance over the majority of quantiles. These findings received robust support under alternative measures of the investor sentiment index.     

Impact of an urban growth boundary across the entire house price spectrum: The two-stage quantile spatial regression approach

This study provides evidence for the impact of an urban growth boundary (UGB) on house prices. The study employs a two-stage quantile spatial regression method on a dataset that inventories sales transactions of single-family houses within two miles of either side of the eastern boundary of the primary UGB in King County, Washington. The results show that while the UGB decreases house prices across the entire house price spectrum, the impact is uneven; it is most pronounced for houses in the 5th to 8th decile of prices. These findings should encourage policy makers to adopt sub-housing-market-level policy approaches to address UGB and other urban and regional development policies’ potential impacts on house prices.     

Investment decision-making under economic policy uncertainty

It is widely established that economic policy uncertainty (EPU) affects investment decisions and performance, yet research in this area has overlooked the direct property investment market. This article seeks to rectify this and proposes a multistage multilevel analytical framework to offer new insights and a richness of findings. Using a news-based measure of EPU in the United Kingdom, and controlling for economic conditions, a national-level analysis reveals some evidence of Granger-Causality between EPU and total returns, indicating that pricing is responsive to uncertainty. These findings suggest that EPU is an important risk factor for direct property investments, with pricing implications. Differences in data and performance measure are important, however, with income returns unresponsive. A micro-level investigation begins to reveal some of the asset-pricing decisions underpinning the national results, indicating investors’ concerns for income streams are consistently high, regardless of varying EPU. Pricing can also cause changes in EPU, such as in the retail and industrial markets (increasingly linked through logistics) reflecting sector-specific stakeholder groups and newsworthy issues. This evidence highlights how important it is for policy-makers to understand the complex and bi-directional relationship, that indecision can undermine investment confidence and cause investment market volatility, in turn raising EPU.     

Characteristics and implications of Chinese macroeconomic data revisions

The research examining macroeconomic data for developed economies suggests that an understanding of the nature of data revisions is important both for the production of accurate macroeconomic forecasts and for forecast evaluation. This paper focuses on Chinese data, for which there has been substantial debate about data quality for some time. The key finding in this paper is that, while it is true that the Chinese macroeconomic data revisions are not well-behaved, they are not very different from similarly-timed U.S. macroeconomic data revisions. The positive bias in Chinese real GDP revisions is a result of the fast-growing service sector, which is notably hard to measure in real time. A better understanding of the revisions process is particularly helpful for studies of the forecast errors from surveys of forecasters, where the choice of the vintage for outcomes may have an impact on the estimated forecast errors.     

What’s in a price? The American raw cotton market in Liverpool and the Anglo-American War

This article argues that an embryonic futures market was present in Liverpool during the Anglo-American War. The analysis of a previously unseen data-set of printed Prices Currents has facilitated not only a price series of raw cotton prices, but an in-depth analysis of the ‘construction’ of those raw cotton prices. By positing a definition of an embryonic futures market and then analysing each of the features of a such a market in turn, this study demonstrates the existence of an embryonic futures market in early nineteenth-century Liverpool.     

Optimal forecast evaluation: fertilizer prices

High fertilizer price volatility makes production planning and inventory management difficult, so accurate fertilizer price forecasts would be beneficial. This article evaluates commercial forecasts for urea and diammonium phosphate (DAP) prices based on forecast accuracy and optimal forecast properties. Most forecasts pass the tests, but forecasts for the US New Orleans urea and the US Gulf DAP markets, in particular, do not and thus show potential to be improved.