A Primer On Misalignment (You’ll Need It If Peter Navarro Has His Way)

Thursday’s Bloomberg article notes that my one-time coauthor Peter Navarro has pushed to have countervailing duty (CVD) investigations augmented with assessments of currency unvervaluation. A prominent target of CVD investigations has been China.

Figure 1: USD/CNY bilateral nominal exchange rate (blue, left inverted scale), and real trade weighted (broad) value of the CNY (red, right scale). May 2019 observation is for first 20 days. Light orange denotes Trump administration. Source: Federal Reserve via FRED, BIS.

Figure 2: China foreign exchange reserves, in millions of USD, through April 2019 (blue). Source: TradingEconomics.com accessed 5/23.

While the value of the inflation-adjusted CNY in April was the same that it was the month Mr. Trump took office, this is not conclusive evidence either way on the undervaluation question. Foreign exchange reserves (official) are slightly above levels in January 2017 — but far below levels in early 2014 near $4 trn. (See Brad Setser for more.)

Hence, it might be useful to recount the various ways in which different observers define currency “misalignment”. Here I update a primer first posted in 2010 (note that the Treasury’s approach — as discussed most recently in its October 2018 report — incorporates aspects of several approaches).

Currency misalignment can be determined on the basis of the following criteria or models:

  • Relative purchasing power parity (PPP)
  • Absolute purchasing power parity
  • The “Penn Effect”
  • The behavioral equilibrium exchange rate (BEER) approach
  • The macroeconomic balance effect
  • The basic flows approach
  • An equilibrium approach

I have discussed several of these approaches in the past [0] [1], but a review of the approaches bear repeating, if only because there so much confusion regarding what constitutes currency misalignment.

Relative PPP

Relative PPP can be expressed as:

s = μ + p – p*

where lowercase letters denote log values, s is the price of foreign currency, p is the price index, and * denotes a foreign variable, and μ is a constant arising from the fact that p and p* are indices.

Using this criteria, a currency is misaligned if s deviates from the μ + p – p*. One difficulty is that μ has to be estimated. Typically, estimates of μ can vary drastically with sample period. Oftentimes, there is a time trend in q ( which equals s – μ – p + p*), which means that relative PPP cannot literally hold. Then, one might have to allow for a (ad hoc) time trend, which itself has to be estimated. In Chinn (Emerging Markets Review, 2000), I apply this approach to the East Asian currencies, pre-crisis.

In the case of China, presented below is the (log) trade weighted real effective exchange rate of China, (q), using the latest data spliced to an older series incorporating the swap rates pre-1994 per discussion in Chinn, Dooley, Shrestha (JIMF, 1999). Upwards denotes depreciation.


Figure 1: Log trade weighted real effective exchange rate, CPI deflated (blue); and linear trend estimated 1980-2009. Source: IMF, International Financial Statistics, various issues; and author’s calculations.

Using a simple linear trend, one obtains the counter-intuitive result that the RMB is overvalued. This suggests caution.

For more on effective exchange rates, see this survey paper (Open Econs. Review, 2015).

Absolute PPP

Given the drawback of relative PPP, it seems like one could get around the problem of estimating μ by using actual prices of identical bundles of goods across countries, rather than price indices.

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