An econometric model of the world shipping markets
This thesis presents an aggregated econometric model of the world shipping markets. The model distinguishes between dry cargo and tankers and also between the a) freight market, b) second hand market for ships, C) shipbuilding market, d) scrap market. Chapters 1,2 of the thesis examine the history of shipping in the last 100 years or so, analyse the cyclical behaviour of the industry, and consider past theoretical attempts at modelling the shipping markets. It is argued that the structure of existing models of the shipping industry is theoretically flawed In its treatment of the demand for new and second hand ships as well as in the treatment of expectations. Chapter 3 presents a 'new' theoretical model of the behaviour of shipping markets that attempts to remedy these defects. Novel features of this theory are the assumption of 'rational expectations' in shipping markets as well as the treatment of new and second-hand ships as assets, the portfolio demand for which varies with the own expected return relative to the return on other assets. Econometric versions of the theoretical model are estimated from post World War II annual data, separately for the dry cargo and tanker sectors In chapters 4, S. The two models are linked In chapter 6 and the models are used In order to simulate the dynamic response of the shipping markets to anticipated and unanticipated external shocks. A crucial role in the adjustment process is played by the forward looking speculative positions of investors in the second hand and newbuilding markets. Chapter 7 tests the assumption of the rational expectations hypothesis in the shipping markets by examining the evidence from the freight futures, time charter and new building markets. The stochastic behaviour of these variables is examined and statistical tests are performed in order to Investigate the extent to which this Is considered to be consistent -with the efficient markets / rational expectations hypothesis. The results are somewhat mixed. Chapter 8 illustrates how the model can be used for real world forecasting purposes and scenario planning.