Maritime Econometrics: Models of Dry Cargo Ships and Tankers, 1996-2005 Survey

Alexandros M Goulielmos

doi:10.4236/me.2018.912136

Abstract

We reviewed the most representative papers belonging to “maritime econometrics” published between 1996 and 2005: a scientific branch in-the-making, we believe. The papers covered the econometrics of the dry-cargo and liquid-cargo ships. We also mentioned a number of papers selected from a paper of Prof. Button in 2005. We traced the progress of “general econometrics” (since the “ARCH model” in 1982) in connection with its application to Maritime Markets (1996). We saw that the progress was made through doctoral theses of maritime economists (since 1996), who applied general econometrics to shipping markets. We also traced the evolution of this applied branch of economics from 1967 to 2005. Maritime economists during this period committed certain mistakes: 1) they relied on “spurious regressions”; 2) they did not apply any tests for stationarity, and 3) they took “co-integration” as a sufficient condition for Random Walk-RW. However, they—unfairly, we believe—have been criticized (by Button) for: 1) using only short run models or, even worse, sticking to Marshall’s “market period”; 2) ignoring “institutional economics”; 3) copying their models from others, producing nothing new and original... They were also criticized for using almost exclusively GARCH model, and for being deceived in their conclusions by data, because longer data in calendar time supports RW, and data in days, weeks reject the existence of random walk, even belonging to same period and market…

Highlights

This decade, 1996-2005, was dominated by papers coming mostly from—let us say—“English School”—a personal classification
We saw that the progress was made through doctoral theses of maritime economists, who applied general econometrics to shipping markets
Maritime economists during this period committed certain mistakes: 1) they relied on “spurious regressions”; 2) they did not apply any tests for stationarity, and 3) they took “co-integration” as a sufficient condition for Random Walk-RW

Summary

Introduction

This decade, 1996-2005, was dominated by papers coming mostly from—let us say—“English School”—a personal classification. All 24 regressions, showed autocorrelation, cured by using the “Durbin”s two-step 1976 estimators” They concluded that “BIFFEX prices” can predict movements of the dry bulk shipping market, up to 6 months maximum prior to a real happening in the physical market, with accuracy from 90% for 1-month lag and 23% for a 6-month lag. Grammenos and Marcoulis [4]) examined whether the “return performance” of 19 companies related to company’s beta7 = β, or to: 1) stock exchange price, 2) leverage, 3) average fleet age and 4) level of dividends (1989-1993) They used OLS, and a cross-section regression (due to Fama and MacBeth in 1973). Co-integration theory helped “time-series” econometrics, and advanced greatly by the empirical success of ECM; the EC term was frequently made up of “co-integrated non-stationary” variables

The GARCH Model in 1986

Further Information on Above Models

Further Research

Findings

Concluding Remarks