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countries. Froot and Rogoff (1994) has mentioned that if the non-traded goods sector is more labour intensive, a even balanced growth in both sectors will result in an appreciation of relative tradable price. Empirical results from Ragoff (1996) also supported this claim as they found a positive relationship between income and price levels, with the richer countries having the greatest distinction.

Other factors that might impact the PPP from holding includes; differences in exchange rate regime, import and export restrictions, travel costs, perishable goods and location amid others. These will impact the price of similar goods sold in different countries as well as the general price level in the respective countries, resulting in the violation of the law of one price and the convergence to PPP in the long and long run.

2.5 Innovations in the test of PPP

Most early studies on PPP based on the simple PPP hypothesis or test for existence of unit root and random walk have produced disappointing results that does not support the relevance of the PPP theory. Subsequently, researchers started to implement more sophisticated econometric techniques, in hope of getting favourable results. Two of the more notable techniques employed by them are the Co-integration test and Fractional integration.

2.5.1 Co-integration

Engle and Granger (1987) concluded that if two non-stationary variables are integrated of the same order and put into a regression, the two variables will possess a relationship, if the residual is stationary. Therefore, Co-integration test could be used to detect the presence of a weak relationship for time-series that are otherwise rejected under strong PPP criterion. Test for “strong” or stringent form PPP test could be determined through the values for of α and β under a regression. For a “strong” PPP to hold, the value for α and β should be 0 and 1. But in co-integration, even if the variables does not conform to these conditions, there might still exist a relationship in a weaker form if the residual of two non-stationary variables, is found to be stationary.

Testing for co-integration basically involves a three step procedure. First, is to use the Dickey-Fuller test to determine whether the respective time series (Exchange rates and price levels for the countries) have unit roots and whether they can be differenced to the same integer order. Following on, the “co-integrating” equation is regressed using OLS and residual is determined. The last step involves subjecting the OLS residuals to the Dickey-Fuller unit root test so as to determine its stationarity. Hence, the variables will be co-integrated when the residual is stationary. Corbar and Ouliaris (1988), Taylor (1988), Kim (1990) applied co-integration techniques but most found that the null hypothesis of non co-integration cannot be rejected in most cases. Rogoff and Froot (1994) compared the 3 techniques used to determine PPP and concluded that although the co-integration test have been more successful in rejecting the null hypothesis, it is unclear whether this technique produces a benefit over the simple PPP hypothesis or random walk test. Though the results have not been satisfactory, these studies have revealed common characteristics of the test and data. First, rejection of the null hypothesis of no-cointegration occurs more often under fixed than floating exchange rate regime