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We model the demolition market, an integral part of the international shipping industry. It is shown through the implementation of a Vector Autoregressive (VAR) model that international steel-scrap prices contribute decisively towards price discovery in the ship-demolition industry. Our finding is explained and attributed to the fact that the growth models of Southeast Asian countries, where the ship-demolition market is primarily located, rely on scrap metal imports. These are mainly obtained from the developed economies rather than the recycling of vessels. We then proceed to test the forecasting ability of our model and use it for price prediction in the ship-demolition market. We establish that it provides the decision-makers with a useful prediction tool which enables all stakeholders involved, the ship owner, the recycler and the cash buyer alike, to gain valuable insights of the underlying trend in the sector.

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Marine transport has grown rapidly as the result of globalization and sustainable world growth rates.Shipping market risks and uncertainty have also grown and need to be mitigated with the development of a more reliable procedure to predict changes in freight rates. In this paper, we propose a new forecasting model and apply it to the Baltic Dry Index (BDI). Such a model compresses, in an optimal way, information from the past in order to predict freight rates. To develop the forecasting model, we deploy a basic set of predictors, add lags of the BDI and introduce additional variables, in applying Bayesian Compressed Regression (BCR), with two important innovations. First, we include transition functions in the predictive set to capture both smooth and abrupt changes in the time path of BDI; second, we do not estimate the parameters of the transition functions, but rather embed them in the random search procedure inherent in BCR. This allows all coefficients to evolve in a time-varying manner, while searching for the best predictors within the historical set of data. The new procedures predict the Baltic Dry Index with considerable success.

This paper develops an equilibrium model for the Greek housing market that incorporates both macroeconomic as well as country-specific variables that affect demand for and supply of houses. In the overall uprising phase of the 23-year period examined (1985Q1-2008Q1), our investigation of short-term fluctuations in real house prices and stock prices confirms the inverse relationship between movements in the housing price index and the stock exchange general index, identifies the direction of causality as running from the financial sector to the real sector, and finds that, following an exogenous shock, reversion to the long-run equilibrium is a rather slow process. Furthermore, we identify a fundamental shift in the behaviour of Greek homeowners, who appear to be moving away from the treatment of housing as consumption good, towards treating house purchases as investment.