Sinem Celik Girgin

This paper aims to develop an adaptation of the Tobin Q investment model for the shipping asset management in order to monitor valuation mismatch and bubble pricing of shipping assets. In this circumstance, the market prices of various shipping assets (e.g., Capesize or Panamax dry bulk carriers in different age profiles) are compared to the measured long-term asset value with second-hand ship prices. The mark-to-market prices of shipping assets are led by current market trends and freight rates, while the long-term asset value is estimated by using past data under certain assumptions (mean reversion, trend reversion). The discrepancy between market prices and the long-term nominal value of a shipping asset reflects any mispricing, which in turn sheds light on investment timing and market entry-exit decision.

The maritime industry is one of those rare industries that are both highly international integrated to international trade and also highly capital intensive dependent on substantial investment amount. In the literature, ship investments have not been widely examined through the firm-level investment theories to explore the link between investment level and asset price valuation. The general trend in the literature of ship investments is to analyse the relationship among the shipping markets (newbuilding, second-hand, freight rate and scrap) and their impact on asset price valuation, the timing of investments and market entry and exit conditions. In this paper, we extensively reviewed the literature of firm-level investment theories and ship investments. We showed that the application of firm-level investment theories to the ship investments is confined to the basic investment valuation models, such as Net Present Value and Real Option Analysis. Ship investments need to be examined by firm-level investment theories to define firm/industry value maximization level within the approach of the solid investment theories.

A growing body of theoretical and empirical literature analyses the relationship between finance and economic growth. The relationship has been strongly supported by many empirical analyses. However, the 2008 Global Financial Crisis (GFC) and the significantly improved econometric techniques made scholars to revisit this relationship. The main motivation of this paper is to empirically revisit the relationship between financial development and economic growth, especially one under the effect of the world's greatest financial crisis since the Great Depression. In this study, both fixed effect and dynamic panel data analysis are conducted by using 147 countries over the period of 2000-2013. The analysis results prove the destructive effect of the GFC on the relationship between financial development and economic growth. Also, the finding showed that the effect of traditional financial development proxies has reduced after the crisis.