Download Exchange rate movements and export prices An empirical analysis

Augustin Cournot Doctoral Days
Strasbourg
April 06th - 08th 2005
Exchange rate movements
and export prices
An empirical analysis
Isabelle Méjean ∗
∗ CREST and EUREQua, University of Paris I. Email: [email protected]
MOTIVATIONS
A new generation of “Incomplete pass-through”
models...
Following Betts and Devereux (1996)
Incomplete pass-through of exchange rate movements
into import prices
Results : Link between the extent of the exchange rate
pass-through and the expenditure switching effect ⇒
Impact on the international monetary transmission
and the exchange rate determination
... Constructed on a set of stylized facts :
Large and persistent deviations from the LPU, even
for traded goods (Engel, 1999)
Weak sensitivity of import prices to exchange rate
movements (Goldberg and Knetter, 1997)
Pricing-to-Market behaviours observed on disaggregated prices (Knetter, 1989, 1993)
LIMITS
Theoretically :
No unified microfounded explanation of the incomplete pass-through phenomenon
⇒ Nominal price rigidities in local currency vs optimal pricing-to-market behaviours
Empirically :
Aggregate estimates ⇒ Composition and/or endogeneity biases (Imbs and al., 2002)
Lack of microeconomic results confirming the influence of market structures and the elasticity of
demand (see Bacchetta and van Wincoop, 2005)
OBJECTIVE
Robust Exchange Rate Pass-Through Estimates
Estimations on disaggregated data to limit the risk of
composition bias
Supply-sided approach
Estimations on export prices with a low frequency,
allowing an interpretation in terms of strategic behaviours
Macroeconomic Interpretation
Estimations on a large sample of industries, to evaluate the global consequences of those strategies
⇒ Main results
Large pass-through of exchange rate movements into
export prices.
High heterogeneity across industries.
MODEL
A basic model of profit maximization...
Price decisions of a monopolist from country i in a
given industry k, producing goods sold in N separated
markets (j = 1...N ) under constant returns :
M ax
ijk
ijk
ijk
ijk ij
ijk
Πijk
=
M
ax
[P
−M
C
]
D
(P
S
,Z
t
t
t
t
t
t
t )
...Leading to a non structural theoretical relation
pijk
t
= (1 +
β ijk )mcijk
t
εηZ ijk ijk
+ η β zt + β ijk sij
t
εP S
with :
β ijk
εηP S
= − ijk
η − 1 + εηP S
εηP S
=
εηZ
∂ ln ηtijk
∂ ln(Ptijk Stij )
=
∂ ln ηtijk
∂ ln(Ztijk )
EMPIRICAL METHOD
Estimated equation
For each exporting industry located in a given country
(for a each (i,k)) :
pjt = αt + γ j + β j sjt + εjt
Method
Panel model with time and individual fixed effects
Test on the fixed vs random effect hypotheses
Within transformation
⇒ White correction for heteroscedasticity and autocorrelation of the error term
Homogeneity assumption : β j = β, ∀ j
DATA
OECD’s International Trade by Commodities Statistics Database
6 Exporting countries : Germany, the USA, France,
Italy, Japan, the UK
Importing countries restricted to OECD’s
Around 2000 5-digit SITC industries, restricted to the
500 largest ones to increase the accuracy of results
Period 1988-1998 (annual frequency)
F.O.B. export unit-values
Nominal bilateral exchange rates
52
53
-0.25;0.23
-0.30;0.33
41
59
-0.29;0.19
-0.38;0.30
-0.20;0.10
-0.18;0.08
76
65
-0.28;0.18
-0.24;0.10
67
51
(b) Range of the estimated coefficients ignoring the tails (10% of the coefficients ignored)
(a) Fraction of estimated coefficients that are significantly different from 0 at the 5% level
standard error
Share of significant coefficients
(%)(a)
Share of negative
significant coefficients (%)
Interquartile
range
of
coefficients(b)
Interquartile
range of significant coefficients
-0.89;0.23
-0.59;0.13
69
52
-0.38;0.32
-0.31;0.22
62
57
Tab. 1 – Averaged statistics on the distribution of the sector-based nominal
exchange rate pass-through (restricted to the 500 largest industries)
USA
UK
DEU
FRA
ITA
JAP
Mean estimated
0.030
0.041
0.020
0.026
0.046
0.034
Exporter-specific kernel estimates of the distribution of estimated long-run
pass-throughs (Normal kernel function with bandwidth=0.8)
Why is the estimated pass-through so
high?
Hypotheses :
Differences in the estimated pass-through obtained
from export and import prices
Upward composition bias when using aggregate prices
rather than sectorial data
Sensitivity of the results to the sample of importing
countries
Substitution across goods
Benchmark
USA
Euro Zone
High Volatility
Large Partners
Large Shares
-.25;.22
-.24;.15
-.23;.19
-.76;.68
-.24;.23
-.29;.31
-.28;.19
.
-.18;.17
-.85;.48
-.28;.25
-.26;.27
-.24;.13
-.19;.06
-.51;.50
-.19;.08
-.18;.06
-.18;.08
DEU
j
j
j
j
-.95;0,26
-.69;.19
-.98;.08
-.58;.19
-.57;.13
-.59;.13
ITA
-.38;.23
-.34;.21
-.71;.50
-.35;.19
-.30;.16
-.31;.22
JAP
where DGS is a dummy variable computed so that it equals 1 when the observation concerns an importing country of
the studied group. The composition of groups is the following :
1. the United States,
2. Euro Zone, i.e. Austria, Belgium, Finland, France, Germany, Ireland, Italy, the Netherlands, Portugal and Spain,
3. “Volatile” countries, i.e. Greece, Hungary, North Korea, Mexico, Poland and Turkey,
4. the 5 largest partners (in terms of exported value) of each industry- and exporter-specific sample,
5. importing countries in which the share of the exporter in the total imported value is large (with respect to the
mean market share of the studied exporter in the sample of destination markets).
pt = αt + γ + βst + βGS DGS st + υt
j
-.29;.17
-.24;.11
-.62;.47
-.25;.10
-.24;.07
-.24;.10
FRA
of the common pass-through coefficients (β)
UK
(a)
(a) 90% of the total distribution of coefficients taken into
account.
Except for the “benchmark” estimation, estimations are based using (5) :
0.
1.
2.
3.
4.
5.
USA
Tab. 2 – Interquartile ranges