iv: integration of goods markets lecture 11: empirical tests of ppp (purchasing power parity)...
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IV: INTEGRATION OF GOODS MARKETS
LECTURE 11: EMPIRICAL TESTS OF PPP(PURCHASING POWER PARITY)
Motivating questions:
How integrated are goods markets internationally?
How rapidly do prices adjust?
PPP: ALTERNATIVE DEFINTIONS
Absolute PPP : P ≡ price of a basket of goods in domestic currency
(e.g., from the Penn World Tables or the UN’s International Comparison Program).
• RER = 1, where real exchange rate RER ≡ E
• P = E P*• E =
• In logs: e = p - p*.=
Prof. Jeffrey Frankel, Harvard Kennedy School
PPP: ALTERNATIVE DEFINTIONS (continued)
Relative PPP CPI ≡ is a price index, expressed relative to an arbitrary base year
e.g., “CPI2000 ≡ 100.0” (from national agencies).
Define real exchange rate Q ≡ E .• Q is constant (at ),
• CPI (E)(CPI*) . • In logs, Δe = Δ cpi – Δ cpi* (relative to some base year).
• Annual depreciation = π - π* .
or E =
API120 - Prof. J.Frankel
PPP: EMPIRICAL QUESTIONS
• Does PPP hold:
• What is the estimated speed of adjustment to the LR?
• Are PPP deviations: • related to variation in nominal exchange rates?
- Can one infer causality?
• related to geography?- To distance? To borders?
• Does the Law of One Price hold better in some sectors than others?
In the long run? Maybe.In the short run? No.
API120 - Prof. J.Frankel
PPP holds well in hyperinflations (a sort of long run):
The cumulative change in E corresponds to the cumulative change in CPI.
API120 - Prof. J.Frankel
Three useful kinds of evidence:• (1) The pattern of movement in real exchange rates:
• band or threshold• Random Walk• trend• AR .
• (2) Effects of exchange rate regime on variability in Q.• (3) Tests of Law of One Price for narrowly defined goods.
PPP fails badly in the short run. Why? ΔE with sticky prices? So ΔE => ΔQ ? Or does the same exogenous real ΔQ
– coming from productivity or terms-of-trade shocks –show up as ΔE or ΔP, depending if on floating vs. fixed?
(1) Four patterns ofdeviation from PPP
and their likely origins:
a) Band <= barriers to trade
b) Random walk <= shifts in terms of trade
c) Trend <= Balassa-Samuelson effect
d) Autoregression <= sticky prices.
Band Random Walk
Trend
Autoregression
Q
Q ≡
Q ≡
Q ≡
Q ≡
Q ≡
API120 - Prof. J.Frankel
•
•
Specification of PPP test as an AutoRegressive process
δ ≡ AR coefficient; (1-δ) ≡ speed of adjustment.
H0 : δ = 1 (random walk, or unit root)
H1 : δ = 0 (full adjustment to PPP)
HAlt : 0 < δ <1 (gradual adjustment to PPP).
Common finding in tests of 1980s: can’t reject H0 .
True problem: Insufficient power in the tests, due to insufficient data.Since 1990, studies have sought more data.
API120 - Prof. J.Frankel
where q ≡ log of real exchange rate; ut ≡ random disturbance with E(ut) = 0.
q t = k + δ q t-1 + u t
API120 - Prof. J.Frankel
With 100 or 200 years of datait is not hard to reject a random walk, i.e., to detect regression to the mean.
qt
API120 - Prof. J.Frankel
Studies with long time series:
Time Period
Estmt.δ
Speed of Adjustment
Half-life(years)
JF (1990) 1869-1987 .84 .16 4
Updated WTP (2007) 1791-2005 .88 .12(s.e.=.05)
4
Lothian & M. Taylor (1996) 2 centuries 3-5
Alan Taylor (2002)19 currencies 1870-1996 .79 .21
(s.e.=.01)3.4 – 4.1
Papell & Prodan (2005) 1870-1998 1-2
Cross-country Number of panel data studies: countries
Frankel & Rose (1995) 150 4Wei & Parsley (1998) 14 4-5Choi, Mark & Sul (2004) 21 5.5
API120 - Prof. J.Frankel
Taylor spliced together 100+ years of data for 20 currencies: 1870-1996
One lesson:reversionto LR Q
Some have trends.
(2) Var(et) and Var (qt) are correlated across regimes.
Is it coincidence? No, it can’t be: Every time a regime switch raises variability of nominal exchange rates, it also raises variability of real exchange rates.
· Pre- and post-1973 (Fig. 19.4)
· Inter-war period (Eichengreen, 1988): 1922-26 float vs. 1927-31 fix
· Post-war regimes (Mussa, 1986): Canadian float in the 1950s
· A century of PPP (A.Taylor, 2002): 1870-1914 Gold standard 1914-45 Interwar 1946-71 Bretton Woods 1971-96 Float
When nominal exchange rate
variability (¥/$) went upwith floating,
real exchange rate variability
went upin tandem.
Coincidence?
Figure 19.4
Nominal & real exchange rates both became more volatile after 1973.
Monthly Changes in Real Japanese Yen /Dollar Rate
-15
-10
-5
0
5
10
15
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
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1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
percent change
Monthly Changes in Nominal Japanese Yen /Dollar Rate
-15
-10
-5
0
5
10
15
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
percent change
1973
API120 - Prof. J.Frankel
The final nail in the coffin:Exchange rate variability across a century of regimes
Variability of real exchange rate
Variability of nominal exchange rate
Again, each time a more flexible regime raises nominal variability, it raises real variability too.
1870-1996
Each observation is a country-regime. (Adapted from A.Taylor, 2002)
API-120, Prof.J.Frankel
(3) Tests of the Law of One Price (LoOP)
1. NonTraded Goods & Services, e.g., haircuts & housing have little scope for arbitrage.
2. Commodities – oil, minerals, & agriculture. -- where arbitrage can potentially work very well.
3. Disaggregated manufactures
4. Retail: In reality, even TGs have a NTG component(distribution & marketing), & vice versa.
5. Pass-through of import prices.
• McDonalds hamburgers. The Economist Parsley & Wei (2003).
• Some models make the TG/NTG line endogenous: Bergin (2003); Ghironi & Melitz (2004)
Professor Jeffrey Frankel,
Prices of nontraded services vary widely.Notice that they are lower in poorer (low-wage) countriesthan in high-wage countries.
1. NTGs
Arbitrage equalizes prices for a homogenous metal such as gold => The Law of One Price holds.
G.Alessandria & J.Kaboski, 2008, “Why are Goods So Cheap in Some Countries?”
Business Review Q2 (Fed,Res,Bank of Philadelphia), Table 2.
Note: India has tariffs & quotas on gold imports.{
ITF-220 Prof.J.Frankel
2. Commodities
Professor Jeffrey Frankel, Harvard University
Even in a manu-facturing sectoras disaggregatedand seeminglystandardized asball bearings, the relative price in Japan varies(1) widely, and (2) in correlation with the ¥/$ exchange rate.
Giovannini, JIE, 1988 3. Manufactures
ITF-220 Prof.J.Frankel
Big Macs are partly traded (ingredients) & partly nontraded (cooking & retail).Their price varies widely across countries.
Jan.22, 2014Why was the price of Big Macs…
so high in Norway?
than in Japan?
higher in Brazil
Low in India & S.Africa?
4. Big Macs
It tends to be higher in rich countries and in countries with overvalued currencies.
Import prices in Turkey show much more pass-through from depreciation than in the US.
With standard error bands
Gita Gopinath, 2015, “The International Price System,” NBER Working Paper, No. 21646, Oct.
A 10% depreciation of the Turkish Lira results in its import prices in Lira rising by 9.3% one quarter after the shock and by 10.0% eight quarters after the shock [full pass-through]... In the case of the U.S. (thick dashed line) the numbers are much lower at 3.4% and 4.4%.
5. Pass-through to import prices
Exchange Rate Passthrough to Domestic Prices
0.2
0.4
0.6
at the dock imported goodprices
localcompetitor
prices
consumer priceindex
pa
ssth
rou
gh
co
effi
cien
t
76 developing and other countries, 1990-2001
Source: Frankel, Parsley & Wei (2012)
Exchange rate pass-through to domestic prices
• Pass-through coefficient ≡ % change in local price resulting from a given % change in exchange rate.
• Pass-through is greatest for imported goods at dock, but less for prices of the same goods at retail level.
• Reason: local distribution & retail costs. • The pass-through to prices of local substitutes is again less;
and is still less to the CPI.
Passthrough coefficientsfor less developed countries > for rich, historically.
Source: Frankel, Parsley & Wei (2012)
Passthrough and Income (Average 1990-2001)
(Country Grouping Based on World Bank Classification)
12 countries
36 countries
28 countries
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Low Income Middle Income High Income
pass
thro
ugh
coef
fici
ent
Looking ahead
Barriers to International Integration-- Transportation costs-- Tariffs & non-tariff trade barriers -- Border frictions -- Currencies
Non-Traded Goods -- The Balassa-Samuelson Effect