In this thesis we study three basic issues related to international black tea markets: Are black tea markets integrated? Where is the price of black tea discovered? Are there leaders and followers in black tea markets? We use two statistical techniques as engines of analysis. First, we use time series methods to capture regularities in time lags among price series. Second, we use directed acyclic graphs to discover how surprises (innovations) in prices from each market are communicated to other markets in contemporaneous time.
Weekly time series data on black tea prices from seven markets around the world are studied using time series methods. The study follows two paths. We study these prices in a common currency, the US dollar. We also study prices in each country's local currency. Results from unit root tests suggest that prices from three Indian markets are not generated through random walk-like behavior. We conclude that the Indian markets are not weak form efficient. However, prices from all non-Indian markets cannot be distinguished from random walk-like behavior. These latter markets are weak form efficient. Further analysis on these latter markets is conducted to determine whether information among the markets is shared. Vector Autoregressions (VARs) on the non-Indian markets are studied using directed acyclic graphs, impulse response functions and forecast error decomposition analyses. In both local currencies and dollar-converted series, the Sri Lankan and Indonesian markets are price leaders in contemporaneous time. Kenya is an information sink. It is endogenous in current time. Malawi is an exogenous price leader in dollar terms, but it is endogenous in local currency in contemporaneous time.
In the long run, Sri Lanka, Indonesia and Malawi are price leaders in US dollar terms. In local currency series, Indonesia, Kenya and Malawi are price leaders in the long run. We use Theil's U-statistic to test the forecasting ability of the VAR models. We find for most markets in either dollars or on local currencies that a random walk forecast outperforms the VAR generated forecasts. This last result suggests the non-Indian markets are both weak form and semi-strong form efficient
