There is a weak link between the theoretical foundations and the empirical validity of the monetary approach to exchange rate determination. The authors use econometric analysis to determine whether fundamentals move together and can be used to forecast exchange rates in the long run.
The authors present support for the monetary model of exchange rate determination. Their work contributes to other studies on the disconnect puzzle between exchange rates and their fundamental determinants. Using the dataset previously used by Engel and West (Journal of Political Economy 2005), the authors find evidence of a long-run relationship between exchange rates and fundamentals in all multivariate and most bivariate equations they test. Moreover, their Granger causality tests provide evidence that fundamentals may be used in predicting short- and long-run movements of exchange rates. These results may imply that in the long run, the monetary approach does provide a useful explanation of the behavior of exchange rates. Nevertheless, this relationship is not very clear in the short run.
How Is This Research Useful to Practitioners?
The issue of the exchange rate disconnect puzzle has been widely discussed in international macroeconomic literature. The authors stipulate that exchange rates are determined by fundamentals in the long run and attempt to prove that thesis using a new econometric technique. The theoretical foundation of the research rests on the flexible-price and sticky-price monetary models of exchange rate determination. The authors assume two conditions that could support the monetary model of exchange rate determination. The first is evidence of co-integration (i.e., long-run co-movement) between exchange rates and their fundamentals, and the second is the proper sign and significance of parameters in the long-run relationship.
The authors find evidence of a long-run relationship between an exchange rate and its fundamentals as well as observe expected behavior of assumed parameters in several cases. The results achieved differ from those of Engel and West. In particular, the authors identify co-integration behavior in most analyzed cases. Moreover, they show that it may be possible to forecast exchange rates using fundamentals in the short run and the long run.
Academics are the primary group that could find the methodology and results interesting. But the results do require further testing, and the methodology itself should be checked against various scenarios to become more useful for practitioners because the monetary model itself can serve only as a benchmark in real-life policy or business decisions.
How Did the Authors Conduct This Research?
The authors use the autoregressive distributed lag (ARDL) approach to co-integration. The key advantage of this method is that it is applicable regardless of whether the underlying variables are stationary or not. The ARDL method selects the order of each variable that is beneficial from an econometric point of view. Furthermore, the authors conduct a number of Granger causality tests.
They use the same dataset as in the seminal paper of Engel and West and compare the results. The data cover the exchange rates of six countries (Canada, France, Germany, Italy, Japan, and the United Kingdom) against the US dollar as well as such fundamentals as money supply, output, interest rate, and consumer price differentials.
The ARDL model is first estimated to study the long-run and short-run relationship between exchange rates and fundamentals. The authors then use the F-statistic procedure to test for the significance of lagged-level variables in a conditional error correction format. They also examine the sign and significance of the lagged error correction term. They examine multivariate equations between the exchange rate and a whole set of fundamentals for each country as well as estimate 24 bivariate equations (four per country) between the exchange rate and every fundamental.
The authors find evidence of co-integration in 20 bivariate relationships between exchange rates in the six countries and each of four fundamentals as opposed to only five in Engel and West’s research. Moreover, the authors find co-integration based on multivariate relationships in all six countries as opposed to almost none in Engel and West. Using Granger causality tests, the authors find evidence that fundamentals may be used for predictions of exchange rates in all six countries in both the short run and the long run. An obvious limitation of the research is the use of an outdated dataset.
The authors contribute new methodology to the subject literature and provide an interesting addition to an ongoing debate. The results are interesting, and I would welcome further analysis that uses the same methodology with a newer dataset, particularly from the period after the financial crisis.