Chapter 2
Practical Applications: The Investment and Policy Insights and Implications Derived From Arbitrage and Mobility
Abstract
We begin to explore the usefulness and empirical validity of the concepts introduced in the first building block. One insight was that absent transportation costs, factor returns will be equalized across economies. That will result in the convergence of the income earned by a factor across the various national borders. This suggests that measures aimed at increasing the degree of integration, such as the EU, result in a convergence of nominal rates of returns. Conversely, disturbances that lead to measures with less integration, such as the breakdown of Bretton Woods, result in a divergence of nominal rates of returns.
Keywords
convergence
divergence of interest rates and inflation
Interest Rate Parity
Law of One Price
Purchasing Power Parity
terms of trade
Purchasing Power Parity (PPP) and Interest Rate Parity (IRP) are our starting point of most of the international economic analysis and countries’ comparisons [1]. As we showed in the previous chapter, both concepts are easily derived once profit maximization, and the absence of transaction costs are assumed. Combined, the two assumptions lead to the conclusion that the price of any commodity, say a ton of steel, be it the Dollar, Euro, or any other currency unit, and has to be the same all over the world. If it was not, the difference in price and the absence of transportation or transaction costs would create a profit opportunity that arbitrageurs would exploit and eventually eliminate.
We made liberal use of equations to illustrate the relationships implied by our assumptions. In addition, we made very explicit and somewhat restrictive assumptions during the specification of the relationships in the equations; this was done to arrive at clear and precise conclusions. Relaxing these assumptions allows us to examine how the model implications would change. The reader is free to do so. Our next step is to assess how robust are the conclusions reached in the previous section. If they are, they provide us with a framework from which one may be able to analyze policy changes and anticipate the new equilibrium conditions.
This is what we affectionately call the Wayne Gretzky approach. When Gretzky was asked why he was such a good player even though he was not a fast skater, his answer was that most people skate to where the puck is. He did not. He said that he skated to where the puck was going to be. That is the investment approach that we hope to derive from the use of the framework outlined in the previous paragraphs. But that is not all. If we know where the puck is going to be, we may also know what drove it there. The analogy here being that our framework may help us understand the impact of the different Policies, and that in turn could be quite useful in designing Policies that will drive the puck where we want it to be. In the process, we may be able to identify and discard the policies that will not drive the puck to the goal.
We also want to make a very important point. It is our belief that the framework is the key to understanding the policies that impact the world. How the global economy reaches a new equilibrium from which one can develop investment and policy insights? How the average person does conduct this analysis? Does it require an advanced knowledge of econometrics and statistics? We contend that these tools are useful but not required. As opposed to a precise and delayed answer provided by such rigorous approach, we believe that what is important is the intuition and the understanding that allows a person to get a good approximation of the correct answer as quickly as possible. To do so we need to have a very good understanding of the framework, and to speed up the process we also need to be able to do back-of-the-envelope calculations that point us in the direction of the precise answer.
With this in mind, we try to avoid regression analysis and other econometric techniques, and attempt to illustrate the relationships graphically and perform a simple qualitative analysis that point us in the right direction in very little time without requiring an advanced degree in statistics and/or econometrics. Common sense and a bit of logic as outlined in the equations presented in the previous chapter can take us a long way.
Is the Law of One Price a Useful Concept?
There is a simple and direct way to answer the question. Let’s put the theory to the test, then look at the data and see if the implications yielded by the framework hold water.
Our first case study is the state economies within the United States. The different states in the union are as large as or larger than many countries in the world. In fact, the state of California often brags that if it was a country it would be the 7th largest economy in the world. We are going to look at the United States as a global economy where member states maintain a fixed exchange rate system, the dollar. Also because of the interstate commerce clause, there are no trade restrictions among the states. Factors are free to move about both within the state as well as across the states. We concede that within the US economy some factors face high transportation costs, with land being the textbook example. Other factors may face some immobility for other reasons such as family ties and so on. Hence in what follows, we assume there is true free trade in goods and services across state lines and partial, if not full, mobility of factors of production.
The Hypothesis: We have shown in the previous chapter that under some general conditions, the free trade in goods combined with mobility leads to the equalization of factor returns across state lines. We also showed that differences in transportation costs lead to nonarbitrageable differences in prices across state lines equal to or smaller than the transportation costs. Also as the states’ economies have a single currency, in effect they have a fixed exchange rate system; therefore arbitrage insures the equality of the prices net of transportation costs as well as of the inflation rates across the different states.
The Data: The US Department of Commerce provides free of charge and easily downloadable data on the states’ gross state product (GSP). The ratio of the constant dollar and current dollar data provided us with an estimate of the states’ deflators, a proxy for the price index. Using the individual states’ data, we calculated several other variables such as each of the states’ real GSP growth rates, the state’s share of the US GSP, the states’ terms of trade, and each state’s inflation rate for each calendar year.
The Inflation Results: Next, we ranked the inflation rate during each of the years from high to low to get a sense of the dispersion among the states’ inflation rates. We then divided each year ranking into quartiles and calculated the average inflation rate for each of the quartiles.
Fig. 2.1 presents information on the average inflation rate for each of the quartiles as well the average inflation rates for all the states, that is the US inflation rate. It uncovers several interesting pieces of information. The first one being that the second and third quartiles are fairly close to the US inflation rate. In fact, visually it is hard to separate one of the series from the other. The first quartile, the lowest inflation quartile, is close to the average with the noticeable exception, the big recession, where it takes a big dip relative to the other series. While not perfect, the data suggests that for at least three of the quartiles, the inflation rate is not that much different than that of the states’ averages. This is precisely the result one would expect under the profit maximization arbitrage conditions we have derived, the Law of One Price or PPP holds. The data suggests that more often than not, it holds. Thus this is a good starting point.
Figure 2.1 States’ inflation rates.
The data presented in Fig. 2.1, in particular quartile 4 shows that some states experience an above-average inflation rate that visually is clearly different from the average of the other quartiles and the US average inflation rate. This result may be interpreted as either a blemish on the Law of One Price or as evidence that we need to expand the framework.
Something we have done in the previous chapter is that we showed that changes in relative prices would lead to deviations in the underlying inflation rate across the state economies’ consumer price index (CPIs). These deviations would accord our view and reflect changes in terms of trade across the different economies. Reversing the process, we are now going to assume that the differences in the inflation rates across states are the result of terms of trade changes that will be discussed later on.
The States’ Growth Rates: According to our framework, mobile factors arbitrage differences in salaries by simply moving to the state with the higher salaries. We also showed that if the number of mobile factors plus traded goods exceeds the total number of factors of production, prices and factor returns would be equalized across state lines. If the states also have a similar mix of factors, one can then stretch the analysis and argue that there will be a tendency for the equalization of the income derived by similar factors in the different localities. There will be a tendency for a state’s GSP, as well as its growth rate to converge to the national average.
Again as before, to test our hypothesis, we ranked the growth rates of the states from high to low each of the years and separated them into four quartiles. The times series generated by these quartiles as well as the US growth rate are reported in Fig. 2.2. Notice that the different series tend to move together. The second and third quartiles appear to be undistinguishable from the average.
Figure 2.2 States’ gross state product growth rate.
Our interpretation of the data and explanation of the results is quite simple; we contend that the differences in growth rates are due to a combination of factor immobility and region-specific shocks. The latter could be natural causes and or man-made such as fiscal policy chocks [2]. The common movement is easy explained in terms of an integrated global/US economy. Under a global economy with free trade and no transportation costs, prices are determined by the global demand and supply of the different commodities. Changes in these prices induce a common response across the different countries’ demand and supply curves, thereby introducing a common effect across the different economies. However, for the factors facing prohibitive moving costs, the market-clearing conditions are determined by the local demand and supply conditions.
A rising local price for a nontraded factor or product results in a higher factor return and a higher output in that locality relative to the rest of the world. The price and output response in each locality will have two different components: the contributions of the mobile factor, which will be common among the localities and the contributions of the local or nontraded factors, which will be specific to the localities. All of this suggests that in the faster growing economies, the immobile factors and product will experience a faster price appreciation, that is a faster inflation rate. The excess inflation and faster growth rates are nothing more than a reflection of the improving terms of trade effect in the locality.
Real GSP Growth and the Terms of Trade: To further test our hypothesis regarding the relationship between the real GSP growth rates, the terms of trade, and the states’ inflation rates, we compared the US growth rate to the average GSP growth rate of the states in the top and bottom inflation quartile (Fig. 2.3). The data shows that the states in the top inflation quartile experience an above-average real GDP growth during periods of economic expansion, while the states in the bottom quartile show a below average growth during these same periods.
Figure 2.3 Average GSP growth rates for the states.
To test the robustness of these results, we reversed the process. Fig. 2.4 reports the average inflation rate for states in the top and bottom quartiles of growth respectively. The data presented in Fig. 2.4 shows that the states in the top real GDP growth experience an above-average inflation rate during periods of economic expansion and a below average inflation rate during periods of economic expansion.
Figure 2.4 Average inflation rates for the states.
No matter how the data is sliced, it uncovers a positive relationship between the local growth rate and the inflation rate. This we have attributed to the terms of trade effect. While the data suggests that is the case, there is a simple way to test this point of view: looking at the data directly. Fig. 2.5A–F shows the relationship between the terms of trade and the states’ share of the US GSP for the following states—Alaska, Indiana, New York, North Dakota, Ohio, and Texas. The results, while not perfect, point to a clear positive correlation between the state’s share of the US GSP and its terms of trade relative to the US economy. Adding more states would not add to the qualitative information, but it would clearly take more space.
Figure 2.5 (A) Alaska’s share of the US GSP; (B) Indiana’s share of the US GSP; (C) New York’s share of the US GSP; (D) North Dakota’s share of the US GSP; (E) Ohio’s share of the US GSP; (F) Texas’ share of the US GSP.
The Investment and Policy Implications: One often hears that certain areas have become very expensive to live, that the affordability index is very low. More often than not, these expensive areas are prosperous areas where there is some fixed or inelastic factor, the quintessential one being real estate. As the mobile factors are attracted to the area, the demand for the inelastic or fixed factor rises, as do prices. The area prices go through the roof and some of the more dilapidated areas get gentrified. That is how the market works. It is no different than investing in the stock market. People want to buy stocks that are undervalued and likely to appreciate. Nobody wants to buy a stock that will become more affordable. The same holds for real estate: as the affordability declines due to a higher demand, price increases. The latter attracts suppliers, be it through new construction or gentrification.
To implement a successful real estate investment strategy, all one needs to do is identify areas that are likely to grow and prosper. In those areas, the fixed factor will appreciate, while areas where the economy is likely to slowdown, the prices and returns to the fixed factor are likely to decline. Good policy that attracts businesses does a lot for the returns of the fixed factor and that reduces the affordability index. But that is not a bad thing. A rising tide lifts all boats. While people complain about the lack of affordability, the jobs will be plentiful in these areas. Think of the Silicon Valley, Manhattan, and Austin in recent years. The easiest way to increase the affordability is to destroy the local economy. Detroit and South Central Los Angeles during the last few decades comes to mind. The investment and policy implications could not be clearer. The same goes for the economic policy recommendations for a state politician: adopt pro-growth policies. These policies attract skilled workers and jobs, as well as producing higher asset prices and higher income, thereby expanding the state tax base.
Convergence: The Implementation of the Euro
The events leading to the implementation of the Euro meant that within the Eurozone all prices would be quoted in the local currency, the Euro. Hence, the price comparison is fairly straightforward. As economies within the Eurozone use the same currency, the exchange rate is by definition fixed. This means that absent transportation costs, arbitrage requires that the underlying inflation rate in each of the Eurozone economies converges to a common underlying inflation rate, presumably set by the European Central Bank (ECB) [3]. That is, the arbitrage process when applied to commodities, leads to the PPP conditions outlined. And when applied to securities, such as bonds, it leads to the IRP. The concept is the same, except that a time span is now involved. Again, if the yield comparisons occur between two countries within the Eurozone, there is no exchange rate fluctuation. Then IRP and arbitrage suggest that, absent transaction and/or transportation costs, the yields of countries in the Eurozone have to converge.
The simple framework shows that profit maximization, perfect mobility, and foresight require the inflation rate to be the same in each of the economies within the Eurozone, that is PPP holds. Now these same assumptions and the fact that PPP holds also tell us that the real rate of return has to be the same in each economy in the region, that is IRP holds. The latter is easy to show. If the real rate of return differs across countries, capital will move to arbitrage these differences. The process will end and equilibrium will be achieved when the rates of return are equalized across national borders.
The framework is relatively simple and its implications are quite insightful. We have used the PPP–IRP approach quite frequently in the past and found the implications derived to be easily implemented in a way that produces above-average returns.
What We Said at the Time: Leading up to the implementation of the euro, we were quite emphatic about who the early winners and losers of the creation of the euro would be. At the time, many pundits argued that Germany would be the big winner. However, we did not share that opinion—at least not in the short run. We argued that the adoption of the euro would result in a convergence of bond yields across the member countries. The investment implication was that the worst countries, that is those with the highest yields, would do well and that the best countries, those with the lowest yields, would underperform. Here is what we said in March of 1998:
The run up to the European Economic and Monetary Union, its electronic start in 1999, and its impact on monetary and fiscal policy afterwards, have important investment implications. To better understand these implications it is useful to draw a parallel between the EMU and our own United States.
Convergence
The proposed monetary union in Europe closely resembles the system already in place in the United States. The union of the states under a federal central bank in 1913 led to the convergence of interest rates across states, which resulted in virtual equality of rates across the nation. But, despite this near equality, growth rates do differ among states. These growth differentials are largely explained by variations in state fiscal policies.
For portfolio managers, this interest-rate convergence and growth-differential paradigm is useful when applied to the European landscape. European Union member nations, like our states, employ various fiscal and monetary policy instruments to meet the Maastricht Treaty convergence criteria. The interest-rate provision of the treaty says that, to be eligible for entrance into EMU, a nation must have an average nominal interest rate on long-term government bonds over the past year of no more than two percentage points above that of the three best-performing member states in terms of price stability. Thus far, the eleven nations vying for admittance - Austria, Belgium, Finland, France, Ireland, Italy, Luxembourg, Netherlands, Germany, Spain and Portugal - have fared relatively well in meeting this provision... As the EMU approaches and interest rates converge, and as they fluctuate within a narrow range after January 1, 1999, the policies employed to meet the Maastricht criteria will dictate growth differentials among the nations. The investment implications are easy to see. We have said previously that the best portfolio strategy for the transition is to buy shares of companies in those countries whose interest rates are higher and most distant from German rates. This convergence insight has served portfolio managers well so far in the transition. The Maastricht Treaty also includes a price stability provision. It states that, for a nation to be admitted, it must have an average rate of consumer price inflation during the year before the examination (this year) that does not exceed by more than 1.5 percentage points that of, at most, the three best performing member states. This provision also has been met with some success... The data shows that Spain’s convergence accelerated late in 1996. The Maastricht conditions have forced a change in policies for aspiring members of the currency union. They have all converged to the German rates, effectively making Germany’s central bank the precursor of the European Central Bank [4].
The Convergence and Postconvergence Euro Environments
The IRP- and PPP-driven insight proved quite useful. As we were arguing that the adoption of the euro would result in a convergence, it meant that the largest risk premium reduction would occur in the weaker countries, mostly the portugal, ireland, italy and greece (PIIGS). One does not need to be a rocket scientist to know that if the highest yields decline the most, the highest yield bonds would produce the largest appreciation. Fig. 2.6A shows that our yield forecast and anticipated convergence did come to pass. Also, a fact that is difficult to discern from the data is that Germany, the strongest economy with sound policies, became the benchmark as far as bond yields is concerned (as we had anticipated). The euro yields are no different than those of the German bond yields.
Figure 2.6 (A–B) Selected Eurozone countries bond yields.
After the initial convergence in bond yields across the Eurozone, IRP was essentially achieved. But, as we have already mentioned, despite the near equality, shortly after the adoption of the euro, growth rates did differ among states. We argued then (and still do) that these growth differentials are largely explained by variations in state fiscal policies. After the transition to the euro, when interest rates and inflation rates convergences were achieved, the relative performances of the economies would be explained by the real exchange rate or terms of trade changes, much like we showed previously with the states’ situation. Again, to reiterate, these terms of trade changes could be explained in terms of fiscal policy changes and other real shocks to the economies in the region, but more on this later.
The convergence produced by the announcement and the measures leading up to the adoption of the euro is clearly visible in Fig. 2.6A. The left portion of Fig. 2.6B provides evidence of the convergence in the context of a longer time period.
The middle of the graph illustrates what we called the pure IRP and PPP, the time period when interest rates and inflation rates had converged, and the differences in return were attributable to the differences in fiscal policies.
Divergence: The Dismantling of Bretton Woods
The Bretton Woods Agreement was developed at the United Nations Monetary and Financial Conference held in Bretton Woods, New Hampshire, from July 1 to July 22, 1944. The landmark system for monetary and exchange rate management was based on a gold exchange rate standard where member countries would fix their exchange rate to that of the US dollar and, in turn, the United States would fix the value of the dollar to the price of an ounce of gold (in a later chapter we discuss in greater detail how this system operated. For now, we will focus on the events surrounding the dismantling of the system).
We contend that during the mid-1960s the United States got increasingly involved in the Vietnam War, the increased involvement contributed to an increase in military spending. Domestically, the Johnson administration was implementing the “Great Society” programs. Both the domestic and defense spending put enormous pressure on the overall spending of the federal government. The President of the United States, Lyndon B. Johnson, used the phrase “guns versus butter” to catch the attention of the national media while reporting on the state of national defense and the economy. Indeed the Johnson administration faced a choice. Given limited resources, it had to decide where to spend the same. The financing choices were also limited. Taxes could not be raised. Doing so would reverse the famous Kennedy-Johnson tax rate cuts. The Vietnam War was unpopular making the issuance of public debt difficult. The one option available to the administration that could be done without any Congressional approval was to print money. In fact, the easy money policy had an added attraction. To the extent that the rest of the world used the dollar as its international reserve, the United States was effectively forcing the rest of the world to share the money financing costs.
As the United States printed money to finance the Vietnam War, the excess money was exported to the rest of the world as a balance of payment deficit. By 1965, the rest of the world began accumulating dollars and some complained. The leader of this group was none other than Charles de Gaulle. He forced the US hand when, in accordance with the Bretton Woods Agreement, he threatened to bring US dollars to the Fed and demanded gold at the official exchange rate. Initially the United States honored the gold exchange commitment. Unfortunately, it also continued printing money, which meant that the US gold reserves would suffer a steady decline. At some point something had to give. Either the United States would run out of gold or the excess money printing would have to stop. Yet the Nixon administration chose neither. Instead, in 1970 and 1971, it took a series of steps in its attempt to defend the dollar and control inflation. It enacted wage and price controls, devalued the dollar and allowed it to float. Milton Friedman had made the case earlier in 1950, but many economists picked up on the theme around that time [5].
President Nixon accepted the now-conventional view that favored a freely floating exchange rate and ultimately the Nixon administration accepted these arguments and the dollar were allowed to float freely in the open market.
The Local Inflation Results
One of the major arguments in favor of the flexible exchange rate was that it would insulate the countries from external monetary/inflationary shocks. The allure was that it would stop inflation and seigniorage tax the United States was imposing on the rest of the world. The implication was that by adopting the flexible exchange rate, the non-US inflation rate would decline. Sadly, as shown in Fig. 2.7, the forecast did not materialize. Contrary to expectations, the inflation rate surged all over the world. It was a disappointment to the proponents of the flexible exchange rate who had promised or forecasted an insulation from external shocks as well as a lower inflation rate. The rise in inflation was not an isolated phenomenon. Not only had the inflation rates increased across the globe, the near double digit inflation continued throughout the decade and didn’t peak until late in 1979 and early 1980, when Paul Volcker changed the operating procedures of the Fed and eventually tamed the inflation beast.
Figure 2.7 Inflation rate.
The unhinging of the Bretton Woods system produced some interesting results. Not only did all the countries inflation rates surge (Fig. 2.7), but when converted to dollars (Fig. 2.8) the inflation rates hovered around that of the United States. The differences in inflation rates we attribute to terms of trade effects.
Figure 2.8 Local inflation rate in US dollars.
The information presented in Figs. 2.9 and 2.10 are quite interesting, and produce qualitatively similar results to those presented in Figs. 2.7 and 2.8. Yet there are significant differences regarding the series. In Figs. 2.9 and 2.10, the time series were constructed as follows: using the full sample of the 189 countries in IMF data base, for each year we ranked the information from high to low, irrespective of the country. We constructed 189 time series, where the first one consisted of the highest inflation rate each year. The 189 series consisted the lowest inflation rate in the world during that year. The series were grouped in quartiles and we calculated the average inflation in each quartile.
Figure 2.9 Worldwide inflation statistics in local currencies.
Figure 2.10 Worldwide inflation statistics in US dollars terms.
The selection process is such that, on average, we would expect to see the second quartile be above-average, and the data shows that is the case. That logic would also lead us to expect the average inflation rate to be below the median, and it is. However, whether the average inflation rate in the third quartile is below or above the US inflation cannot be determined a priori. In theory, the US inflation could rank anywhere. Nevertheless, as a point of reference, the second quartile shows that the countries’ average inflation is not that much different from the US inflation. Taken at face value, these results suggests that the adoption of the floating exchange rate was not successful in isolating the countries form the supposedly undesired inflation of the 1970s, in this case the United States. The data suggests that at best the inflation rate was similar to the United States and, at worst, the local inflation rate deteriorated in both absolute and relative terms (see third quartile information presented in Fig. 2.9). The conclusion is that the floating exchange rate did not deliver the results promised by the people who advocated for the floating exchange rate system.
Does the Law of One Price Still Hold?
Although Figs. 2.7 and 2.9 conclusively show that the floating exchange rate did not deliver the inflation shield that the countries expected from a floating exchange rate, the issue as to whether the Law of One Price still holds is another matter. We have shown that in the absence of transportation costs and of relative price changes, that is terms of trade effects, arbitrage insures that the rate of change of each country’s consumer basket is the same across countries. This is the version of the Law of One Price or PPP that we now examine using the data from the 189 countries. Our first step was to convert the rate of change of the consumer basket in local currency into dollars. That is, we calculated the inflation rate in domestic currencies and subtracted from it the local currency exchange rate depreciation vis-a-vis the US dollar. We call this the countries’ dollar inflation rates.
Our next step was to rank each of the countries’ dollar inflation rates, from high to low for each of the years. Again as before, we constructed 189 time series where the first one consisted of the highest dollar inflation rate each year. The 189 series is made up of the dollar inflation rates for countries with the lowest dollar inflation rate in the world during that year. The series were then grouped into quartiles, and then we calculated the average inflation in each quartile. Fig. 2.10 plots the two quartile series as well as the US inflation rate. There are several interesting features of the two series. The turning points appear to coincide. In effect, the two series appear to be parallel to each other. Needless to say, the second quartile is the higher of the two series. The two series span the US inflation rate.
Next, as we look at Figs. 2.8 and 2.10, it becomes apparent that the exchange rate adjusted inflation series are much closer to the US inflation series. The fact that the difference between the second quartile and the United States has narrowed significantly suggests a few things. First, the exchange rate adjustment brings the two series much closer, just like the Law of One Price would predict. We attribute the divergences to terms of trade effects. Nevertheless, we can safely argue that while not perfect, the Law of One Price framework is a good starting point. A broader and comprehensive approach would incorporate changes in the terms of trade to enhance the explanatory power of our framework. The third observation is the fact that the dollar inflation is lower than the inflation in local currency means that, on average, the rest of the world’s exchange rate depreciated. Hence the unhinging from the dollar with the adoption of a floating exchange rate may have brought about a higher global inflation rate in local currencies. This is nothing more than the so-called divergence effect.
Are the Terms of Trade Constant?
Using worldwide data, we calculated the terms of trade or relative price changes as the local inflation rate less the local exchange rate depreciation against the US dollar, as well as the US inflation rate. A positive number means an improvement in the foreign economy’s terms of trade relative to the United States. That is, it takes more US goods to acquire one unit of the foreign good. A negative number means an improvement in the US terms of trade or a deterioration of the foreign economy’s terms of trade.
We applied the same methodology as before. We ranked the terms of trade changes for each year, constructed 189 series and split them into quartiles. We then calculated the average terms of trade changes for the second and third quartile. The results are reported in Fig. 2.11. The data shows that for most of the turning points, peaks and trough for the two series coincide.
Figure 2.11 Worldwide terms of trade effects relative to the United States.
One interpretation of these results is that the series identify the terms of trade changes. The fact that second quartile series is consistently higher than the third quartile has not escaped us. This result is not unrelated to the fact that the dollar inflation for the third quartile (Fig. 2.9) is lower than that of the third quartile. One possible explanation is measurement errors. If that is the case, then when the measurement errors are corrected, we would observe second and third quartile series converge to each other. And that will bring it all together. The relative price changes or terms of trade impact the different countries’ CPI differently. This suggests that these differences between the inflation rate series may be capturing the terms of trade changes. Once these relative prices are accounted for, the Law of One Price holds.
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