We show that house prices from Aberdeen in the UK improve in- and out-of-sample oil price forecasts. The improvements are of a similar magnitude to those attained using macroeconomic indicators. We explain these forecast improvements with the dominant role of the oil industry in Aberdeen. House...

In this paper we show that the MSCI ACWI Metals and Mining Index has the ability to predict base metal prices. We use both in-sample and out-of-sample exercises to conduct such examination. The theoretical underpinning of these results relies on the present-value model for stock-price...

In this paper we show that the exchange rates of some commodity exporter countries have the ability to predict the price of spot and future contracts of aluminum. This is shown with both insample and out-of-sample analyses. The theoretical underpinning of these results relies on the...

Shared equity homeownership is a form of subsidised, resale-restricted housing through which lower-income households can sustain their affordability. This paper aims to distinguish two types of affordability within shared equity homeownership: “entry affordability” indicates how affordable...

This paper proposes a framework for monitoring vulnerabilities related to the residential real estate sector in a cross-country context. The framework might be useful for complementing or cross-checking signals available from existing approaches. It takes into account three dimensions of real...

This paper presents an estimate of the costs of reducing CO2 emissions as agreed in Kyoto by Annex 1 countries. Unlike most of the existing literature, this paper uses an Almost Ideal Demand System model for energy products to estimate the role of each country within the Annex 1 market. A major...

We evaluate the performance of inflation forecasts based on the open-economy Phillips curve by exploiting the spatial pattern of international propagation of inflation. We model these spatial linkages using global inflation and either domestic slack or oil price fluctuations, motivated by a...

We propose a tool to predict risks to economic growth and international business cycles spillovers: the GDP-Network CoVaR. Our methodology to assess Growth-at-Risk is composed by two building blocks. First, we apply the network-based NETS methodology by Barigozzi and Brownlees to identify...

We augment the existing literature using the Log-Periodic Power Law Singular (LPPLS) structures in the log-price dynamics to diagnose financial bubbles by providing three main innovations. First, we introduce the quantile regression to the LPPLS detection problem. This allows us to disentangle...