00074910012331338893
Bulletin of Indonesian Economic Studies
ISSN: 0007-4918 (Print) 1472-7234 (Online) Journal homepage: http://www.tandfonline.com/loi/cbie20
Indonesia's Non-Oil Export Performance During
the Economic Crisis: Distinguishing Price Trends
from Quantity Trends
L. Peter Rosner
To cite this article: L. Peter Rosner (2000) Indonesia's Non-Oil Export Performance During
the Economic Crisis: Distinguishing Price Trends from Quantity Trends, Bulletin of Indonesian
Economic Studies, 36:2, 61-95, DOI: 10.1080/00074910012331338893
To link to this article: http://dx.doi.org/10.1080/00074910012331338893
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Date: 19 January 2016, At: 22:05
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Bulletin of Indonesian Economic Studies
Vol 36 No 2, August 2000, pp. 61–95
INDONESIA’S NON-OIL EXPORT
PERFORMANCE DURING THE ECONOMIC
CRISIS: DISTINGUISHING PRICE TRENDS
FROM QUANTITY TRENDS
L. Peter Rosner*
Harvard Institute for International Development (HIID)
Despite an enormous currency depreciation, the growth rate of Indonesia’s
non-oil exports, measured in dollars, did not accelerate during the first
two years of the Asian crisis. In fact, during the second year of the crisis
non-oil export value dropped sharply. This paper demonstrates that the
main reason for the decline in the dollar value of non-oil exports was a
collapse of export prices. Non-oil export dollar prices fell 26% between
the second quarter of 1997 and the second quarter of 1999. Measured at
constant prices, non-oil exports grew 24% and manufactured exports 31%
during this period. Non-oil import prices fell by roughly the same amount
as non-oil export prices during the crisis, with little change in the non-oil
terms of trade. The decline in the price of traded goods significantly
reduced the magnitude of the real exchange rate depreciation experienced
by Indonesia.
INTRODUCTION
During the first year of the Asian economic crisis the Indonesian rupiah
lost more than 80% of its nominal value relative to the dollar. Although
some of this loss was subsequently recovered, the inflation-adjusted value
of the rupiah at the end of 1999 was still more than 30% lower than it had
been before the crisis began. A depreciation of this magnitude might have
been expected to result in strong export growth. Indonesia’s own past
experience indicated a close link between devaluations and export
performance. For example, when the rupiah was devalued by 28% in
early 1983, the growth rate of non-oil export value rose from –13% in
1982 to +27% in 1983 and to +17% in 1984. When the rupiah was again
devalued by 31% in September 1986, the growth rate of non-oil exports
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
62
L. Peter Rosner
rose from 0% in 1985 to 11% in 1986, 31% in 1987 and 34% in 1988. Past
econometric research also found a strong link between the real exchange
rate and export growth in Indonesia. For example, using quarterly data
from 1985–94, Radelet (1996) estimated a price elasticity of supply for
non-oil exports of 0.778, implying that a 10% depreciation of the real
exchange rate would lead to a 7.78% rise in non-oil exports. Before the
onset of the East Asian currency crisis, therefore, Indonesia’s experience
with exchange rate depreciations had been relatively straightforward:
large depreciations (or devaluations) were followed by large increases in
the growth rate of non-oil export value, sustained over several years.
Indonesia’s experience during the recent crisis has been very different.
Despite a massive depreciation of the currency, non-oil export value
growth fell from +10% in 1997 to –2% in 1998 and to –6% in 1999. Far
from stimulating export growth, the 1997–98 depreciation appeared to
result in an unprecedented collapse of non-oil exports.
Several explanations for this surprising development have been
popularised. The most common is that the collapse of the domestic
banking system made trade finance unavailable to exporters. According
to this explanation, export firms were unable to finance imports of raw
materials and components, and did not have access to working capital
for day-to-day operations, preventing them from taking advantage of
the depreciation (Pardede 1999; FEER, 14/1/99; JP, 19/10/99). Reduced
demand in importing countries, particularly in East Asia, has also been
blamed for the export slowdown. A third argument sometimes heard is
that Indonesia’s export industries are too dependent on imported inputs.
With the collapse of the rupiah, according to proponents of this view,
imported inputs have become too expensive. Policy makers have therefore
drawn the conclusion that import-dependent export industries are
unreliable and that future export promotion efforts should focus on
industries that process domestic raw materials.1 A fourth explanation is
that social and political instability in Indonesia in 1998 and 1999 caused
international buyers of manufactured products to shift orders to other
countries, particularly in the wake of the May 1998 riots in Jakarta.
Little noticed in this discussion of factors responsible for the non-oil
export slowdown is the fact that Indonesia suffered a massive
deterioration in export prices between 1997 and 1999. Observers of export
trends have focused exclusively on the dollar value of Indonesia’s exports,
for the simple reason that this is the only information readily available.
But if export prices decline, export value and export volume can move in
opposite directions. A large share of Indonesia’s non-oil exports is
composed of primary commodities such as rubber, copper, coal, plywood
and palm oil. World market prices for primary commodities have fallen
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
Indonesia’s Non-oil Export Performance during the Economic Crisis
63
steadily since the onset of the regional economic crisis. For example, the
World Bank’s index of non-energy commodity prices for low and middle
income developing countries declined from 126.0 in the second quarter
of 1997 to 87.8 in the second quarter of 1999 and to 85.8 by July 1999
(World Bank, Global Commodity Markets, table A1, various issues). This
represents a decline of 32% over a two-year period.2
Prices for Indonesia’s major non-oil export commodities have
followed a similar trend. As can be seen in table 1, prices for 20 of
Indonesia’s most important non-oil export commodities, comprising 42%
of non-oil export value in 1997, fell by an average of 25% between the
first half of 1997 and the first half of 1999. World market prices for many
other items such as garments and footwear also fell. One of the prime
reasons for the poor performance of Indonesia’s non-oil exports over the
past two years is this sharp drop in export prices. Any analysis of recent
export performance must therefore distinguish between price movements
and quantity movements. There is no reason to expect, and economic
theory does not postulate, that export value will rise following a currency
depreciation—only a rise in export quantity should be expected.3
Some observers have recognised that Indonesian export prices
declined during the crisis, causing a divergence between trends in export
value and export volume. For example, James (2000) notes that if
Indonesian non-oil export values are deflated using an import price index
for the United States, non-oil exports in constant dollar prices rose 1.58%
in 1998, although they fell by 2% when measured in current dollars.
However, the composition of US imports and Indonesian non-oil exports
is quite different, so the US import price index is at best a rough proxy
for export prices faced by Indonesia.
Unfortunately, a satisfactory aggregate measure of either non-oil
export volume or export price does not yet exist for Indonesia. The central
statistics agency (BPS) publishes quantity data in kilograms for individual
export items, but does not publish an aggregate volume index. It does
publish a rupiah-based wholesale price index (WPI) for exports, but the
non-oil component of the index includes only 43 items, of which less
than 20 are manufactured products, and the index is therefore not
representative of overall non-oil exports (BPS 2000).4 The International
Monetary Fund (IMF) publishes a monthly export volume index, but the
IMF’s index is an unweighted average (or simple sum) of export tonnage.5
Since exports of sand account for more than one-half of non-oil export
tonnage, sand dominates the IMF’s index even though it accounts for
less than 0.2% of non-oil export value, making this index a fairly
meaningless measure of export performance.
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
64
L. Peter Rosner
This paper addresses the lack of an appropriate measure of non-oil
export volume by using unit values (export value in dollars divided by
export quantity in kilograms) to construct an aggregate measure of
monthly non-oil exports at constant prices. If we hold prices fixed,
movements in export value can only be due to quantity changes. This is
equivalent to measuring export volume by constructing a weighted
average of export quantity indices, with the weights being the value share
of each item in total non-oil exports. Once a volume index has been
constructed, an implicit export price index can be derived simply by
dividing export value by export volume.
To measure non-oil exports at constant prices, the data are first cleaned
for extreme quantity outliers, and a base time period is selected for
deriving constant export prices from export unit values. The analysis is
conducted at the Harmonised System (HS) nine-digit level so as to
minimise aggregation problems inherent in the use of unit values as a
measure of export prices. After describing the methodology, we present
findings for non-oil exports as a whole and for selected subsectors over
the 69-month period April 1994 through December 1999.
MEASURING NON-OIL EXPORT VOLUME: METHODOLOGY
Our measure of non-oil export volume can be expressed as follows:
n
∑ Pi 0 Qit
Vt =
i =1
n
x 100
(1)
∑ Pi 0 Qi 0
i =1
where: Vt is the index of non-oil export volume at time period t;
Pi0 is the price of item i in time period 0;
Qi0 is the quantity of item i exported in time period 0; and
Qit is the quantity of item i exported in time period t.
This is equivalent to measuring non-oil export volume as a weighted
average of quantity indices for each item, i.e.:
n
∑ Pi 0 Qit
Vt =
i =1
n
∑ Pi 0 Qi 0
i =1
n
x 100 = ∑ wi 0
i =1
Qit
x 100
Qi 0
(2)
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Indonesia’s Non-oil Export Performance during the Economic Crisis
65
TABLE 1 World Market Prices for Indonesia’s Major Non-oil Export Commodities
World Market Prices
1997
Export
Value
Commodity ($ million) Unit
Plywood
Coal
Rubber
Copper
Palm oil
Shrimp
Paper
Textile fabric
(mmf)
Textile fibre
& yarn
Coffee
Fish
Wood pulp
Cocoa
Coconut oil
Fertiliser
Aluminium
Tin
Gold
Nickel
Tea
3,742 ¢/sheet
1,694 $/mt
1,501
¢/kg
1,497 $/mt
1,446 $/mt
1,046
$/kg
925 $/mt
854
$/kg
% Price
Change
Jan– Jan–Jun
Jun
1997 to
1999 Jan–Jun
1999
JanJun
1997
July–
Dec
1997
Jan–
Jun
1998
July–
Dec
1998
500
37.7
116.0
2,463
559
9.35
573
6.86
474
32.7
85.8
2,090
532
10.47
461
6.92
384
29.3
73.2
1,716
663
7.63
482
5.51
372
26.8
68.7
1,592
681
5.97
510
4.70
423
24.0
62.7
1,438
511
7.30
469
4.10
–15
–36
–46
–42
–9
–22
–18
–40
763
$/kg
2.90
2.63
2.21
1.85
1.74
–40
529
492
490
408
402
311
303
275
224
210
89
¢/kg
$/kg
$/mt
¢/kg
$/mt
$/mt
$/mt
¢/kg
$/toz
$/mt
$/kg
177
1.14
376
153
712
183
1,590
578
348
7,427
1.27
170
1.11
441
171
601
123
1,608
537
315
6,428
1.52
188
1.19
419
171
616
107
1,413
558
297
5,194
1.90
177
0.89
414
164
701
107
1,302
550
291
4,065
1.48
161
0.94
343
127
784
96
1,251
534
280
4,934
1.07
–9
–17
–9
–17
+10
–48
–21
–8
–19
–34
–16
100
92
84
79
75
–25
Sum
17,201
Weighted average
price index
Source: Prices for plywood, rubber, copper, palm oil, coconut oil, coffee (robusta),
aluminum, tin, gold and nickel are from World Bank, Global Commodity Markets
(various issues). Prices for coal, shrimp, paper, textile fabric from man-made fibre
(mmf), textile yarn and fibre, fish, wood pulp, fertiliser and tea are calculated
from BPS export data by dividing export value in dollars by export tonnage.
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
66
L. Peter Rosner
where wi is the value share for item i in the base time period, or:
wi0 =
Pi 0 Qi 0
n
∑ Pi 0 Qi 0
(3)
i =1
Export prices (the Pis) are derived from export unit values, measured
as export value divided by export quantity. A weakness in using unit
values to measure export prices is that changes in unit values can reflect
either true price changes or a change in the mix of items exported under
a given export line. For relatively homogeneous items such as minerals
and agricultural products it is reasonable to assume that a given export
line will track the same item over time. But for manufactured goods the
mix of items in a single export line frequently changes over time. For
example, an export line identified as ‘colour TV sets’ might contain
14-inch sets one month and 19-inch sets the next. Moreover, export
quantity is generally measured in kilograms, and kilograms are clearly a
crude measure of quantity for manufactured goods.6
To avoid the aggregation problem inherent in the use of unit values,
it would be necessary to have direct price observations for individual
export items. Given the heterogeneity of manufactured exports this is
not possible. A typical garment export firm, for example, frequently
exports 100 or more different types of garments. Even a narrowly defined
item such as ‘men’s cotton dress shirts’ could contain items of vastly
different quality. In fact, for brand name garments each order is unique,
so that even with the most detailed data imaginable it would not be
possible to construct a perfect time series of the price of ‘men’s cotton
dress shirts’. Given this inherent measurement problem and the
limitations of Indonesian trade data, any measure of export volume or
price that is representative of overall exports must rely on unit values.
Since changes in the mix of items within a given export line can create
significant aggregation bias in the measurement of export volume, it is
essential to minimise this bias by identifying export items in as much
detail as possible. To minimise aggregation bias, the analysis is conducted
at the most detailed level possible with Indonesian export data, by using
nine-digit HS codes, which allow non-oil exports to be separated into
more than 7,000 individual export lines. Even at this level of detail,
aggregation bias is still a major problem in the data. Analysis of individual
HS nine-digit lines indicates that many lines contain a mix of
heterogeneous items. However, because the data are disaggregated to
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Indonesia’s Non-oil Export Performance during the Economic Crisis
67
the HS nine-digit level, the measure of non-oil export volume presented
below is less influenced by aggregation bias than other measures of nonoil export volume that use a higher level of aggregation.
Data Source
The data for this analysis are BPS monthly export data for the period
April 1994 through December 1999. BPS trade data record exports by
both HS and SITC (Standard International Trade Classification) nine-digit
codes. Since exporters record only the HS code on the export declaration
form they submit to customs, and since the mapping from HS codes to
SITC codes is subject to error, the HS codes are more reliable. The two
key variables available in the monthly data for each HS line are the value
of exports in dollars and the quantity of exports measured in kilograms.
Cleaning the Data
Unfortunately, BPS export data contain significant errors, particularly in
the quantity variable. For example, exports of gold (HS line 7108.12.100)
in January 1998 were recorded as 831.3 tonnes. This was more than 100
times greater than any previous or subsequent monthly quantity of gold
exports, and implied that Indonesia sold gold for $71 per tonne in January
1998, as against a minimum price of more than $5,000 for any other month.
Similarly, exports of unbleached cotton fabric (HS line 5208.12.900) were
recorded at 102,999 tonnes in December 1998, exceeding any previous or
subsequent quantity by a factor of 48 and implying that cotton fabric
was sold for 12¢ per kilogram in December 1998 as against a minimum
price of $3.24 for any other month.
Because of these large data errors, any quantity index constructed
from uncleaned data produces unreliable results. This can be seen in
figure 1, which applies equation (1) to raw BPS export data. The index is
highly volatile, particularly in 1997 and 1998, with month-to-month
changes in excess of 20% that bear little relationship to changes in export
value. The uncleaned quantity index is particularly volatile in mid 1998,
with volume growth of 57% recorded between May and July, followed
by a decline of 22% in August.
To respond to the data error problem, we developed a simple data
cleaning algorithm. Our algorithm assumes that the export values for each
HS line in each month are correct and that all problems lie in the quantity
variable.7 Any excessive change in the unit value (value divided by
quantity) for a particular HS line between one month and the next is
assumed to reflect a mistake in the quantity variable. In the event of an
excessive month-to-month change in the unit value, we assume that the
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
68
L. Peter Rosner
unit value in the previous non-zero month is the correct unit value, and
we define a new ‘cleaned’ quantity by dividing the current month’s unit
value by the previous month’s unit value. In other words, our cleaning
algorithm can be expressed as follows:
if (Pit/Pit–1) > x or (Pit/Pit–1) < (1/x) then Qit* = Yit/Pit–1 and Pit = Pit–1
(4)
where x is the cleaning factor, Yit is the dollar value of item i exported in
time t, Pit–1 is the unit value of item i in the previous (non-zero) time
period and Qit* is the cleaned quantity. The cleaned Qit* are then used to
construct new unit values for the calculation of fixed base-period export
prices, and are also used in equation (1) above.8
The decision about what constitutes an ‘excessive’ month-to-month
change in the unit value for a particular export item is subjective. We
decided that anything greater than a fivefold change was definitely
excessive and anything less than a twofold change was within the bounds
of the possible. We then experimented with various cleaning factors (x
values in equation (4)). The results for x = 2, x = 3, x = 4 and x = 5 are
discussed in more detail in the appendix.
Choice of a Base Time Period for Calculating Constant Prices
The choice of time period for constructing constant prices is not clearly
determined by economic theory, and yet can have an impact on the
resulting measure of export volume. Measuring 1994–99 non-oil exports
at constant 1994 prices produces different results from those obtained
using constant 1996 prices or constant 1998 prices. In broad terms, the
choice is between using current prices and projecting them back or using
past prices and projecting them forward—the difference between a
Paasche and a Laspeyres index. Ideally the difference between these two
indices would not be large, but in practice it turns out to be significant.
This is because the fixed prices are essentially weights, as was shown in
equation (2) above, and the weights change significantly over time as
export value shares change.
A potential solution to this problem would be to use a chain-linked
index. However, the analysis uses monthly data over a 69-month period
(April 1994 to December 1999) and calculating an index with 68 links is a
tedious task. More importantly, no cleaning technique is perfect and
remaining errors in the data for any particular month can be large. This
would tend to make a monthly chain-linked index excessively volatile.
Over longer periods of time data errors average out. Mistakes in a
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
Indonesia’s Non-oil Export Performance during the Economic Crisis
69
FIGURE 1 Non-oil Export Value, Volume and Price before Cleaninga
(monthly index April 1994 to December 1999; April 1994 = 100)
230
Value
Volume
190
Implicit Price
150
110
70
Jan-94
Jan-95
Jan-96
Jan-97
Jan-98
Jan-99
Jan-00
a
The export volume index uses constant average 1994–99 prices. The export quantity for gold in January 1998 has been cleaned. If the published number of 831
tonnes is used, the volume index rises to more than 500 in January 1998.
particular HS line in a single month could have a major impact on the
volume index if data from that month alone were used to create the fixed
price for each item, but if the fixed prices for each item are calculated
from many months of data the sensitivity of the results to outliers is
reduced. This consideration argues for using a period of at least 12 months,
and perhaps longer, for calculating the fixed price for each item.
Experiments with the data indicated that even calculating the fixed
prices from annual data produced significantly different results
depending on which year was chosen. Measuring exports at constant
1996 prices, for example, resulted in higher 1998 volume growth than
measuring them at constant 1997 prices, and using constant 1998 prices
produced the lowest measure of export volume growth in 1998. These
differences are presented and discussed in the appendix. To avoid having
to select a single year’s export prices as the ‘correct’ prices, it was decided
to use the average price for each item over the entire 69-month time period
for which data were available.
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
70
L. Peter Rosner
The methodology ultimately selected for measuring non-oil export
volume therefore uses a modified version of equation (1), which can be
expressed as:
n
∑ Pi Qit*
Vt =
i =1
n
∑
x 100
Pi Qi*0
(5)
i =1
69
∑ Yit
P =
where i
t =1
69
*
∑ Qit
t =1
Yit is the dollar export value of item i in time t, and Qit* are the cleaned
quantity data.
FINDINGS: EXPORT VOLUME AND PRICES
BEFORE AND DURING THE CRISIS
Figure 2 presents the results of applying the methodology described above
to monthly BPS export data over the period April 1994 to December 1999.
Non-oil export volume is measured at constant average 1994–99 prices
with a cleaning factor of x = 3, meaning that any month-to-month change
in the unit value within a particular HS line that exceeds a factor of 3 is
assumed to reflect a mistake in the quantity data, and a new quantity
variable is then created using the previous month’s unit value and the
current month’s value. The cleaned volume index is less volatile than the
uncleaned index shown in figure 1, and bears a stronger resemblance to
the non-oil export value index.
Figure 2 shows that the average price of non-oil exports rose in 1994
and 1995 and then fell very slightly from early 1996 through mid 1997. In
mid 1997 non-oil export prices began a steep decline that continued
through early 1999. By the second quarter of 1999 they had dropped by
26% relative to the same period two years earlier.
Corresponding to this drop in prices, the growth rate of non-oil export
volume began to accelerate in mid 1997. This is best seen in table 2, which
shows quarterly non-oil exports measured both at current prices and at
constant average 1994–99 prices, along with the implicit export price index
and year-on-year growth rates.
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
Indonesia’s Non-oil Export Performance during the Economic Crisis
71
TABLE 2 Quarterly Non-oil Exports: Value, Volume and Price, 1994–1999
Volume
Year-on-Year Growth
(constant
Implicit
(%)
average
Price
1994–99 prices;
Index
Implicit
$ million) (1994 Q2 = 100) Value
Volume
Price
Year and
Quarter
Value
(current
prices;
$ million)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
1994 Q2
Q3
Q4
1995 Q1
Q2
Q3
Q4
1996 Q1
Q2
Q3
Q4
1997 Q1
Q2
Q3
Q4
1998 Q1
Q2
Q3
Q4
1999 Q1
Q2
Q3
Q4
7,589
8,154
8,339
7,583
8,395
9,165
9,811
8,462
9,593
9,891
10,147
9,151
10,411
11,311
10,997
10,242
10,272
10,804
9,657
8,296
9,634
10,555
10,387
7,502
7,772
7,919
6,945
7,574
8,235
8,684
7,487
8,507
8,993
9,166
8,239
9,354
10,637
10,779
10,901
11,455
12,470
11,188
9,687
11,573
12,613
12,060
100
104
104
108
110
110
112
112
111
109
109
110
110
105
101
93
89
86
85
85
82
83
85
11
12
18
12
14
8
3
8
9
14
8
12
–1
–4
–12
–19
–6
–2
8
1
6
10
8
12
9
6
10
10
18
18
32
22
17
4
–11
1
1
8
10
6
7
4
2
–1
–2
–2
–1
–3
–8
–15
–19
–19
–15
–9
–7
–3
0
–7
24
–26
Growth 1997 Q2 to 1999 Q2
Source: Calculated from BPS trade data.
As can be seen in the sixth column of the table, export volume growth
was lower than export value growth from 1995 through the first half of
1996, and very slightly above it from mid 1996 until mid 1997, but in the
third quarter of 1997 export volume growth accelerated sharply. Yearon-year volume growth peaked at 32% in the first quarter of 1998 and
then declined during the second and third quarters of 1998, but remained
well above historical levels. By contrast, export value growth turned
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
72
L. Peter Rosner
FIGURE 2 Non-oil Export Value, Volume and Price, Using Cleaned Quantity Data
(monthly index April 1994 to December 1999; April 1994 = 100)
230
Value
190
Volume
Implicit Price
150
110
70
Jan-94
Jan-95
Jan-96
Jan-97
Jan-98
Jan-99
Jan-00
negative after the first quarter of 1998. In the final quarter of 1998 volume
growth slowed and then became negative in the first quarter of 1999, but
it remained much higher than value growth. In the second quarter of
1999 volume growth recovered to plus 1%, and reached 8% by the fourth
quarter, even though value growth remained negative through the third
quarter.9
Figure 2 shows that most of the growth in non-oil export volume
took place during the first year of the economic crisis. Although volume
was still 17% higher during the third quarter of 1998 than it had been a
year earlier, on a month-to-month basis it began declining in August 1998
and continued to drop sharply through early 1999. During January and
February 1999, non-oil export volume fell to its lowest level in three years.
It recovered in March 1999 and continued to grow through August 1999,
but during the period March–August 1999 it was still 2% lower than it
had been during the same period in 1998.
The apparent slowdown in the growth of non-oil export volume after
mid 1998 may have been caused partly by the civil unrest that
accompanied the political transition occurring at that time. It may also
have been due to the fact that export volumes had reached a very high
level in the first half of 1998, with much of the growth caused by one-off
export activities that were not sustainable. During the first half of 1998
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
Indonesia’s Non-oil Export Performance during the Economic Crisis
73
the value of the rupiah dropped at an unprecedented rate, falling from
Rp 4,650/$ at the end of 1997 to more than Rp 15,000/$ by mid 1998. The
magnitude and speed of the depreciation created opportunities for
windfall profits from trade, as local prices did not always adjust up as
rapidly as the rupiah was falling. A large quantity of merchandise appears
to have been exported during an ‘arbitrage window’ in the first half of
1998, as traders took advantage of the speed of the rupiah depreciation
to purchase existing stocks of goods in Indonesia and ship them abroad.
Toward the end of the third quarter of 1998, as the rupiah began to
strengthen and local prices caught up with international prices, this
window may have begun to close, contributing to a decline in these ‘oneoff’ exports.
Evidence of ‘one-off’ export activity can be seen in the pattern of
jewellery exports. Between January and March 1998, monthly jewellery
exports rose from less than $50 million to a record level of $337 million.
During the first half of 1998 the value of jewellery exports reached $1.3
billion, three times greater than a year earlier, and jewellery accounted
for more than one-third of the growth of non-oil export value over this
period. In August 1998 jewellery exports suddenly collapsed and by the
end of 1998 were below pre-crisis levels. The pattern seen in figure 3
strongly suggests a depreciation-induced boom motivated by pure
trading opportunities, followed by a bust as the arbitrage window
closed.10 A similar pattern can be seen in wood pulp exports, which grew
enormously during the period January–July 1998 and then dropped
suddenly toward the end of 1998. With jewellery and wood pulp
excluded, non-oil export volume grew by 9% during the second quarter
of 1999 relative to the same period in the previous year.
If the enormous growth of non-oil export volume during the first
half of 1998 was partly driven by factors that were not sustainable, a
better indication of the impact of the depreciation of the rupiah on export
activity might be obtained by comparing export levels in 1999 with levels
two years earlier. Although year-on-year volume growth was low in
1999, volume levels remain very high relative to levels before the crisis.
During the second quarter of 1999, for example, non-oil export volume
was 24% higher than it had been two years earlier (table 2), even though
it was up only 2% from the previous year. The fact that Indonesian
exporters were able to maintain the very high export volume levels
reached during the first half of 1998 suggests that problems such as trade
financing and political instability may not have been crippling Indonesia’s
exports. If exporters could not import raw materials owing to a lack of
trade finance, or if manufacturers could not find foreign buyers willing
to place orders in Indonesia, it is unlikely that such high export volume
levels could have been sustained.
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
74
L. Peter Rosner
FIGURE 3 Monthly Exports of Jewellery, January 1992 to December 1999
($ million)
350
300
250
200
150
100
50
0
Jan-92 Jan-93
Jan-94 Jan-95 Jan-96 Jan-97 Jan-98
Jan-99 Jan-00
Source: BPS.
Toward the latter part of 1999 export prices began to recover
(figure 2). The monthly index of non-oil export prices, calculated as the
ratio of export value to export volume, increased from 82 in September
1999 to 87 in December 1999. This upturn coincided with a recovery in
world market prices for commodities as recorded in international data
sources. For example, the World Bank’s ‘Pink Sheet’ series shows that
prices of copper, nickel, aluminium, gold, steel and wood pulp all turned
up strongly in the second half of 1999, and plywood prices were 32%
higher in the fourth quarter of 1999 than they had been in the third quarter
of 1998.11 The stabilisation and partial recovery of export prices in late
1999 allowed the relatively strong growth of non-oil export volume during
the crisis to show up as higher dollar revenue, and was probably the
main factor behind the 29.6% year-on-year rise in non-oil export value
reported during the first quarter of 2000.
THE SOURCES OF NON-OIL EXPORT GROWTH:
SECTORAL ANALYSIS
The preceding analysis has shown that non-oil export volume continued
to grow strongly during the economic crisis and that the drop in export
revenue, measured in dollars, was caused mainly by declining export
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
Indonesia’s Non-oil Export Performance during the Economic Crisis
75
prices. The strong growth of non-oil export volume was interpreted as
an indication that trade finance problems did not prevent exporters from
taking advantage of the enormous increase in competitiveness caused
by the depreciation of the rupiah.
However, not all of Indonesia’s non-oil exports require significant
quantities of imported inputs. Almost one-half of non-oil exports consist
of primary commodities and semi-processed resource-based products
with low import content, such as coal, rubber, palm oil and plywood.
Since exporters of these products generally do not need to open letters of
credit for imported inputs before each export shipment, it is possible
that even a very serious trade finance problem would not greatly affect
them. If the growth of export volume during the crisis has been driven
mainly by exports of primary commodities and semi-processed products,
and if manufactured exports have stagnated or declined, this would
suggest that trade finance problems might be having more of an impact
than would be assumed from the aggregate export volume data alone. It
is therefore important to look at the source of non-oil export volume
growth by sector.
To investigate the source of non-oil export volume growth, non-oil
exports were divided into four broad categories: (1) agriculture and
related semi-processed products; (2) forestry products (including
plywood, pulp, paper and semi-processed forestry products); (3) mining
and mineral products; and (4) manufactured goods.12 The results of this
analysis are shown in table 3. As can be seen in the last row of the table,
manufactured exports did better during the crisis than any of the other
three categories, in both value and volume terms. Measured in dollars,
manufacturing was the only category to experience growth between the
second quarter of 1997 and the second quarter of 1999. Export value for
the other three categories contracted sharply. Measured by volume, all
four categories experienced growth over this two-year period, but
manufacturing experienced by far the strongest growth.
In 1999, export volume of manufactured goods stagnated, rising only
0.3% relative to the previous year, but the volume level was still very
high. As was discussed above, much of the apparent slowdown was due
to the impact of ‘one-off’ exports during the first half of 1998, particularly
jewellery exports. The impact of jewellery on total exports of
manufactured products can be seen in figure 4. With jewellery removed
from the export volume index, it is apparent that exports of manufactured
products were considerably higher in 1999 than in 1998. In fact, if we
exclude jewellery, exports of manufactured goods grew 10% in real terms
in 1999. This was slower than the 1998 growth rate of 12%, but over the
two-year period 1997–99 exports of manufactured products (excluding
jewellery) increased by a very healthy 23%, measured at constant prices.
Quarter
Value (Current Prices)
Agric.
Forestry
1994 Q2
1,411
1,471
Q3
1,840
1,470
Q4
1,764
1,500
1995 Q1
1,411
1,444
Q2
1,627
1,629
Q3
1,777
1,687
Q4
1,919
1,712
1996 Q1
1,619
1,401
Q2
1,748
1,688
Q3
1,945
1,671
Q4
1,892
1,782
1997 Q1
1,634
1,513
Q2
1,856
1,778
Q3
2,072
1,482
Q4
1,848
1,376
1998 Q1
1,349
1,286
Q2
1,411
1,083
Q3
1,826
1,545
Q4
1,611
1,123
1999 Q1
1,349
1,145
Q2
1,553
1,534
Q3
1,859
1,731
Q4
1,616
1,653
Growth 1997 Q2 to 1999 Q2
–16%
–14%
Volume (Constant 1994–99 Prices)
Mining
Manuf.
600
747
752
836
819
1,061
1,085
944
1,113
986
1,005
935
1,256
1,225
1,033
997
930
903
1,128
912
926
947
1,141
4,107
4,098
4,324
3,892
4,321
4,641
5,095
4,498
5,044
5,289
5,467
5,069
5,522
4,340
3,116
4,646
4,961
5,077
3,549
3,849
5,579
6,003
5,975
1,508
1,672
1,574
1,131
1,266
1,521
1,707
1,394
1,534
1,812
1,779
1,496
1,730
2,150
2,115
1,557
1,729
2,356
2,111
1,639
1,924
2,482
2,088
–26%
1%
11%
Agric.
Forestry
Implicit Price Index
Mining
Manuf.
Agric.
1,375
1,414
1,477
1,409
1,508
1,499
1,492
1,277
1,467
1,433
1,524
1,301
1,551
1,520
1,927
1,848
1,880
2,337
2,141
1,643
1,835
1,970
1,882
623
742
705
719
706
875
881
794
947
917
917
845
1,073
1,147
1,003
1,084
1,056
1,063
1,325
1,142
1,240
1,181
1,296
3,995
3,944
4,163
3,686
4,094
4,341
4,605
4,023
4,559
4,830
4,947
4,597
5,000
5,826
5,761
6,427
6,800
6,700
5,591
5,254
6,574
6,980
6,794
100
118
120
133
137
125
120
124
122
115
114
117
115
112
110
105
96
88
92
93
86
80
83
100
97
95
96
101
105
107
103
108
109
109
109
107
107
96
85
73
74
69
76
79
82
82
100
105
111
121
120
126
128
123
122
112
114
115
122
111
107
95
91
88
88
83
78
83
91
100
101
101
103
103
104
108
109
108
107
108
107
107
102
98
91
90
89
89
85
83
84
86
18%
16%
31%
–25%
–27%
–36%
–23%
Forestry
Mining
Manuf.
Source: Calculated from BPS HS nine-digit monthly export data, April 1994 to December 1999. Classifications are based on three-digit SITC codes. See
table 4 for a more detailed description of the items in each category.
L. Peter Rosner
im Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUA
Year and
76
TABLE 3 Quarterly Non-oil Exports by Sector, Q2 1994 to Q4 1999: Value, Volume and Implicit Price (value and volume: $ million)
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
Indonesia’s Non-oil Export Performance during the Economic Crisis
77
FIGURE 4 Export Volume of Manufactured Goods Excluding Jewellery
(monthly index April 1994 to December 1999; April 1994 = 100)
240
210
All manufacturing
Manufacturing without jewellery
180
150
120
90
Jan-94
Jan-95
Jan-96
Jan-97
Jan-98
Jan-99
Jan-00
Source: Calculated from BPS trade data.
Figure 4 also shows that exports of manufactured goods declined
sharply during the second half of 1998. This decline began roughly three
months after the May 1998 riots. Many manufactured export products,
such as garments and footwear, typically have a lag of about three months
between the time orders are placed and the time merchandise is shipped
out of the country. The timing of the sharp drop in manufactured exports
in the second half of 1998 is consistent with the assertion that international
buyers shifted orders to other countries in response to the May 1998 riots
and the continued political instability in Indonesia in 1998. Interviews
with textile, garment and footwear manufacturers conducted by the
author in the second half of 1998 confirmed that many companies suffered
a severe cutback in orders following the riots. However, the strong
recovery of manufactured exports after February 1999 indicates that this
impact was largely temporary.
Looking at export price trends by sector, table 3 shows that all four
non-oil export sectors suffered from sharply falling dollar prices in 1997–
99. Prices for manufactured products declined the least, dropping by 23%
between the second quarter of 1997 and the second quarter of 1999, but
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
78
L. Peter Rosner
TABLE 4 Non-oil Exports by Sector: Value Growth, Volume Growth and Price
Change, April–July 1997 to April–July 1999
(%)
Sector
(based on
SITC 3-digit
classification)
Value
Growth
Implicit Comparable
ContriVolume
Price International bution to
Growtha Change
Price
Volume
Changeb
Growth
Agriculture
Fresh fish & shrimp
Rubber
Vegetable oils
Coffee
Cocoa
Processed food
Fish
Vegetables & fruit
Other processed food
Fresh fruit & vegetables
Animal feed
Tea
Spices
Other agricultural products
–20
–12
–46
–27
–26
2
42
4
82
40
18
–40
–1
0
–18
8
11
6
–10
–4
48
64
43
89
61
56
–11
32
14
–6
–26
–20
–49
–19
–23
–31
–14
–27
–4
–13
–24
–33
–25
–12
–12
Mining & mineral products
Copper
Coal
Nickel
Aluminum
Tin
Gold
Other mining products
–24
–30
–20
–5
–64
–16
–8
8
16
9
33
33
–52
–11
48
45
–34
–36
–40
–29
–25
–6
–38
–26
Forestry products
Plywood
Pulp & paper
Sawnwood
Other forestry products
–12
–32
34
–6
–5
21
–5
68
18
39
–27
–29
–21
–20
–32
–38
–44
–21
–22
–30
–28
–39
–26
–25
–16
–4
–21
–18
–40
7
2
1
–2
0
2
3
0
1
2
1
0
0
0
0
8
1
5
1
–2
0
1
1
14
–2
12
1
4
this decline was only slightly less than the 25% drop in the average price
of agricultural exports. Average export prices fell by 27% for forestry
products and by 36% for mining and mineral products.
A more detailed analysis of the source of non-oil export growth during
the economic crisis is provided in table 4, which disaggregates non-oil
exports into 45 items and subsectors. For each item or subsector, the table
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
Indonesia’s Non-oil Export Performance during the Economic Crisis
79
TABLE 4 (continued) Non-oil Exports by Sector: Value Growth, Volume Growth and
Price Change, April–July 1997 to April–July 1999
(%)
Sector
(based on
SITC 3-digit
classification)
Manufactured products
Textiles, garments & footwear
Fibre & yarn
Fabric
Garments
Footwear
Electronics & computers
Chemicals
Furniture
Machinery
Toys
Jewellery
Iron & steel
Household articles
Motorcycles & bicycles
Other transport equipment
Downstream plastics
Construction materials
Fertiliser
Tobacco products
Tyres
Total Non-oil
Value
Growth
Implicit Comparable
ContriVolume
Price International bution to
Growtha Change
Price
Volume
Changeb
Growth
1
10
23
–7
20
1
–8
19
34
39
8
–85
30
6
11
29
54
68
–40
–26
10
31
40
82
36
45
12
12
64
71
51
87
–67
79
43
46
37
77
141
12
51
48
–23
–22
–32
–32
–17
–10
–18
–28
–22
–8
–42
–56
–27
–26
–24
–6
–13
–30
–46
–51
–26
–8
24
–25
–26
–48
71
37
9
8
18
3
5
12
7
3
2
–4
3
1
1
1
2
4
0
1
1
100
a
Calculated using constant average unit values over the period January 1996 to
September 1999.
b
Comparable international prices taken from World Bank, Global Commodity Markets, various issues.
shows the growth rate of export value and volume and the change in the
implicit export price between the four-month period April–July 1997 and
the same period in 1999.13 The table also shows price changes for similar
items from international data sources, where available.
Table 4 shows that average export prices declined for every one of
the 45 items and subsectors over this two-year period, with the largest
price decline in the mining sector and the smallest in the manufacturing
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
80
L. Peter Rosner
sector. The price changes calculated from Indonesian trade data are
generally similar to price changes reported in international publications,
although for some items Indonesian export prices changed more, and
for others less, than reported world market prices.
The last column of table 4 shows the contribution of each item to
non-oil export volume growth between April–July 1997 and April–July
1999. Manufacturing accounted for 71% of volume growth over this
period, even though it represented less than 55% of non-oil export volume
(and value) at the start of the period. The item that made the greatest
contribution was garments, which accounted for 18% of all non-oil export
volume growth over this period. Chemicals and pulp and paper each
accounted for 12% of volume growth, fibre and yarn for 9%, fabric for
8%, and furniture for 7%, while coal and electronics each accounted for
5% of volume growth. The volume growth data indicate that export
sectors that are heavily dependent on imported inputs, such as garments,
textiles, chemicals, toys, and transport equipment, experienced rapid
export volume growth during the economic crisis.14 On the other hand,
so did some sectors that are dependent on domestic natural resources,
such as pulp and paper, furniture, processed food and coal.
COMPARISON WITH OTHER REGIONAL ECONOMIES
Indonesia’s experience with sharply falling export prices during the
regional economic crisis was apparently not unique. Data from Thailand
and Korea indicate that both of these countries also experienced a sharp
decline in export prices between 1997 and 1999. Export price indices for
Indonesia, Korea and Thailand are shown in figure 5 (re-based so that
July 1997 equals 100 to facilitate comparison). As can be seen in the figure,
export prices declined by at least 20% in all three countries during the
crisis. Relative to July 1997 Indonesia suffered the sharpest decline, but
export prices for Korea had been declining since mid 1995, and by mid
1999 had fallen more than 30% in four years. Export prices for Thailand
began to decline in early 1997 and by late 1999 had fallen by as much as
Indonesian non-oil export prices.
Korea and Thailand are mainly exporters of manufactured goods:
more than 90% of Korea’s exports and more than 70% of Thailand’s
exports consist of manufactured products. The fact that the average price
of exports from these two countries declined by almost as much as that
of Indonesia’s non-oil exports lends further support to the finding that
the collapse in export prices during the crisis was not confined to primary
commodities.
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
Indonesia’s Non-oil Export Performance during the Economic Crisis
81
FIGURE 5 Export Price Indices, Indonesia, Korea and Thailand
(July 1997 = 100)
120
110
100
90
80
Thailand (export unit value)
Korea (export price)
Indonesia (implicit non-oil
export price)
70
Jan-94
Jan-95
Jan-96
Jan-97
Jan-98
Jan-99
Jan-00
Sources: Indonesia: calculated from BPS export data using HS nine-digit unit values.
Korea: IMF, International Financial Statistics.
Thailand: Bank of Thailand homepage (www.bot.or.th/bothomepage/
databank).
Although their export prices declined to a similar extent, other
regional economies did not suffer as drastic a fall in export values as did
Indonesia. During the first year of the crisis Indonesia’s non-oil exports
(measured in dollars) grew considerably faster than total dollar exports
from Korea or Thailand. However, during the second year Indonesia’s
non-oil export value declined by 12.2%, whereas total Korean export value
declined by 2.4% and total Thai export value by 3.4% (table 5). Moreover,
Korean and Thai export values recovered strongly in 1999 and had
surpassed pre-crisis levels by the end of the year, whereas Indonesian
non-oil export values remained well below pre-crisis levels in 1999. This
suggests that Indonesian exports suffered from more than just a drop in
prices, at least during the second year of the crisis. It is possible that the
slowdown in non-oil export volume growth between August 1998 and
February 1999 was a very delayed reaction to the trade finance problem
that started in late 1997. However, given that the slowdown began three
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
82
L. Peter Rosner
TABLE 5 Annual Growth of Export Value, Indonesia, Thailand and Korea
(%)
Perioda
Year-on-Year Export Growth
Indonesia (non-oil)
Thailand
Korea
1994/95 to 1995/96
13.8
9.2
15.4
1995/96 to 1996/97
7.8
–2.0
1.0
——————————————————— start of crisis ——————————
1996/97 to 1997/98
7.3
2.0
3.0
1997/98 to 1998/99
–12.2
–3.4
–2.4
a
Each time period starts in August so as to coincide with the floating of the Indonesian rupiah. Thus ‘1994/95’ refers to the 12-month period August 1994 to July
1995. The first two rows are therefore pre-crisis growth rates.
Source: Korea and Thailand: IMF, International Financial Statistics; Indonesia: BPS.
months after the May 1998 riots, and given that non-oil export volume
recovered strongly in mid 1999 even though trade finance problems
continued, it seems likely that the August 1998 – February 1999 drop in
non-oil exports was due mainly to the impact of social and political
instability on international demand for Indonesian manufactured
products.
TERMS OF TRADE AND THE REAL EXCHANGE RATE
The finding that non-oil export prices declined by around 26% in dollar
terms during the crisis suggests a massive deterioration in Indonesia’s
terms of trade. This raises the possibility that a major correction in the
exchange rate might have been required to maintain Indonesia’s
ISSN: 0007-4918 (Print) 1472-7234 (Online) Journal homepage: http://www.tandfonline.com/loi/cbie20
Indonesia's Non-Oil Export Performance During
the Economic Crisis: Distinguishing Price Trends
from Quantity Trends
L. Peter Rosner
To cite this article: L. Peter Rosner (2000) Indonesia's Non-Oil Export Performance During
the Economic Crisis: Distinguishing Price Trends from Quantity Trends, Bulletin of Indonesian
Economic Studies, 36:2, 61-95, DOI: 10.1080/00074910012331338893
To link to this article: http://dx.doi.org/10.1080/00074910012331338893
Published online: 18 Aug 2006.
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Bulletin of Indonesian Economic Studies
Vol 36 No 2, August 2000, pp. 61–95
INDONESIA’S NON-OIL EXPORT
PERFORMANCE DURING THE ECONOMIC
CRISIS: DISTINGUISHING PRICE TRENDS
FROM QUANTITY TRENDS
L. Peter Rosner*
Harvard Institute for International Development (HIID)
Despite an enormous currency depreciation, the growth rate of Indonesia’s
non-oil exports, measured in dollars, did not accelerate during the first
two years of the Asian crisis. In fact, during the second year of the crisis
non-oil export value dropped sharply. This paper demonstrates that the
main reason for the decline in the dollar value of non-oil exports was a
collapse of export prices. Non-oil export dollar prices fell 26% between
the second quarter of 1997 and the second quarter of 1999. Measured at
constant prices, non-oil exports grew 24% and manufactured exports 31%
during this period. Non-oil import prices fell by roughly the same amount
as non-oil export prices during the crisis, with little change in the non-oil
terms of trade. The decline in the price of traded goods significantly
reduced the magnitude of the real exchange rate depreciation experienced
by Indonesia.
INTRODUCTION
During the first year of the Asian economic crisis the Indonesian rupiah
lost more than 80% of its nominal value relative to the dollar. Although
some of this loss was subsequently recovered, the inflation-adjusted value
of the rupiah at the end of 1999 was still more than 30% lower than it had
been before the crisis began. A depreciation of this magnitude might have
been expected to result in strong export growth. Indonesia’s own past
experience indicated a close link between devaluations and export
performance. For example, when the rupiah was devalued by 28% in
early 1983, the growth rate of non-oil export value rose from –13% in
1982 to +27% in 1983 and to +17% in 1984. When the rupiah was again
devalued by 31% in September 1986, the growth rate of non-oil exports
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62
L. Peter Rosner
rose from 0% in 1985 to 11% in 1986, 31% in 1987 and 34% in 1988. Past
econometric research also found a strong link between the real exchange
rate and export growth in Indonesia. For example, using quarterly data
from 1985–94, Radelet (1996) estimated a price elasticity of supply for
non-oil exports of 0.778, implying that a 10% depreciation of the real
exchange rate would lead to a 7.78% rise in non-oil exports. Before the
onset of the East Asian currency crisis, therefore, Indonesia’s experience
with exchange rate depreciations had been relatively straightforward:
large depreciations (or devaluations) were followed by large increases in
the growth rate of non-oil export value, sustained over several years.
Indonesia’s experience during the recent crisis has been very different.
Despite a massive depreciation of the currency, non-oil export value
growth fell from +10% in 1997 to –2% in 1998 and to –6% in 1999. Far
from stimulating export growth, the 1997–98 depreciation appeared to
result in an unprecedented collapse of non-oil exports.
Several explanations for this surprising development have been
popularised. The most common is that the collapse of the domestic
banking system made trade finance unavailable to exporters. According
to this explanation, export firms were unable to finance imports of raw
materials and components, and did not have access to working capital
for day-to-day operations, preventing them from taking advantage of
the depreciation (Pardede 1999; FEER, 14/1/99; JP, 19/10/99). Reduced
demand in importing countries, particularly in East Asia, has also been
blamed for the export slowdown. A third argument sometimes heard is
that Indonesia’s export industries are too dependent on imported inputs.
With the collapse of the rupiah, according to proponents of this view,
imported inputs have become too expensive. Policy makers have therefore
drawn the conclusion that import-dependent export industries are
unreliable and that future export promotion efforts should focus on
industries that process domestic raw materials.1 A fourth explanation is
that social and political instability in Indonesia in 1998 and 1999 caused
international buyers of manufactured products to shift orders to other
countries, particularly in the wake of the May 1998 riots in Jakarta.
Little noticed in this discussion of factors responsible for the non-oil
export slowdown is the fact that Indonesia suffered a massive
deterioration in export prices between 1997 and 1999. Observers of export
trends have focused exclusively on the dollar value of Indonesia’s exports,
for the simple reason that this is the only information readily available.
But if export prices decline, export value and export volume can move in
opposite directions. A large share of Indonesia’s non-oil exports is
composed of primary commodities such as rubber, copper, coal, plywood
and palm oil. World market prices for primary commodities have fallen
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Indonesia’s Non-oil Export Performance during the Economic Crisis
63
steadily since the onset of the regional economic crisis. For example, the
World Bank’s index of non-energy commodity prices for low and middle
income developing countries declined from 126.0 in the second quarter
of 1997 to 87.8 in the second quarter of 1999 and to 85.8 by July 1999
(World Bank, Global Commodity Markets, table A1, various issues). This
represents a decline of 32% over a two-year period.2
Prices for Indonesia’s major non-oil export commodities have
followed a similar trend. As can be seen in table 1, prices for 20 of
Indonesia’s most important non-oil export commodities, comprising 42%
of non-oil export value in 1997, fell by an average of 25% between the
first half of 1997 and the first half of 1999. World market prices for many
other items such as garments and footwear also fell. One of the prime
reasons for the poor performance of Indonesia’s non-oil exports over the
past two years is this sharp drop in export prices. Any analysis of recent
export performance must therefore distinguish between price movements
and quantity movements. There is no reason to expect, and economic
theory does not postulate, that export value will rise following a currency
depreciation—only a rise in export quantity should be expected.3
Some observers have recognised that Indonesian export prices
declined during the crisis, causing a divergence between trends in export
value and export volume. For example, James (2000) notes that if
Indonesian non-oil export values are deflated using an import price index
for the United States, non-oil exports in constant dollar prices rose 1.58%
in 1998, although they fell by 2% when measured in current dollars.
However, the composition of US imports and Indonesian non-oil exports
is quite different, so the US import price index is at best a rough proxy
for export prices faced by Indonesia.
Unfortunately, a satisfactory aggregate measure of either non-oil
export volume or export price does not yet exist for Indonesia. The central
statistics agency (BPS) publishes quantity data in kilograms for individual
export items, but does not publish an aggregate volume index. It does
publish a rupiah-based wholesale price index (WPI) for exports, but the
non-oil component of the index includes only 43 items, of which less
than 20 are manufactured products, and the index is therefore not
representative of overall non-oil exports (BPS 2000).4 The International
Monetary Fund (IMF) publishes a monthly export volume index, but the
IMF’s index is an unweighted average (or simple sum) of export tonnage.5
Since exports of sand account for more than one-half of non-oil export
tonnage, sand dominates the IMF’s index even though it accounts for
less than 0.2% of non-oil export value, making this index a fairly
meaningless measure of export performance.
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64
L. Peter Rosner
This paper addresses the lack of an appropriate measure of non-oil
export volume by using unit values (export value in dollars divided by
export quantity in kilograms) to construct an aggregate measure of
monthly non-oil exports at constant prices. If we hold prices fixed,
movements in export value can only be due to quantity changes. This is
equivalent to measuring export volume by constructing a weighted
average of export quantity indices, with the weights being the value share
of each item in total non-oil exports. Once a volume index has been
constructed, an implicit export price index can be derived simply by
dividing export value by export volume.
To measure non-oil exports at constant prices, the data are first cleaned
for extreme quantity outliers, and a base time period is selected for
deriving constant export prices from export unit values. The analysis is
conducted at the Harmonised System (HS) nine-digit level so as to
minimise aggregation problems inherent in the use of unit values as a
measure of export prices. After describing the methodology, we present
findings for non-oil exports as a whole and for selected subsectors over
the 69-month period April 1994 through December 1999.
MEASURING NON-OIL EXPORT VOLUME: METHODOLOGY
Our measure of non-oil export volume can be expressed as follows:
n
∑ Pi 0 Qit
Vt =
i =1
n
x 100
(1)
∑ Pi 0 Qi 0
i =1
where: Vt is the index of non-oil export volume at time period t;
Pi0 is the price of item i in time period 0;
Qi0 is the quantity of item i exported in time period 0; and
Qit is the quantity of item i exported in time period t.
This is equivalent to measuring non-oil export volume as a weighted
average of quantity indices for each item, i.e.:
n
∑ Pi 0 Qit
Vt =
i =1
n
∑ Pi 0 Qi 0
i =1
n
x 100 = ∑ wi 0
i =1
Qit
x 100
Qi 0
(2)
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Indonesia’s Non-oil Export Performance during the Economic Crisis
65
TABLE 1 World Market Prices for Indonesia’s Major Non-oil Export Commodities
World Market Prices
1997
Export
Value
Commodity ($ million) Unit
Plywood
Coal
Rubber
Copper
Palm oil
Shrimp
Paper
Textile fabric
(mmf)
Textile fibre
& yarn
Coffee
Fish
Wood pulp
Cocoa
Coconut oil
Fertiliser
Aluminium
Tin
Gold
Nickel
Tea
3,742 ¢/sheet
1,694 $/mt
1,501
¢/kg
1,497 $/mt
1,446 $/mt
1,046
$/kg
925 $/mt
854
$/kg
% Price
Change
Jan– Jan–Jun
Jun
1997 to
1999 Jan–Jun
1999
JanJun
1997
July–
Dec
1997
Jan–
Jun
1998
July–
Dec
1998
500
37.7
116.0
2,463
559
9.35
573
6.86
474
32.7
85.8
2,090
532
10.47
461
6.92
384
29.3
73.2
1,716
663
7.63
482
5.51
372
26.8
68.7
1,592
681
5.97
510
4.70
423
24.0
62.7
1,438
511
7.30
469
4.10
–15
–36
–46
–42
–9
–22
–18
–40
763
$/kg
2.90
2.63
2.21
1.85
1.74
–40
529
492
490
408
402
311
303
275
224
210
89
¢/kg
$/kg
$/mt
¢/kg
$/mt
$/mt
$/mt
¢/kg
$/toz
$/mt
$/kg
177
1.14
376
153
712
183
1,590
578
348
7,427
1.27
170
1.11
441
171
601
123
1,608
537
315
6,428
1.52
188
1.19
419
171
616
107
1,413
558
297
5,194
1.90
177
0.89
414
164
701
107
1,302
550
291
4,065
1.48
161
0.94
343
127
784
96
1,251
534
280
4,934
1.07
–9
–17
–9
–17
+10
–48
–21
–8
–19
–34
–16
100
92
84
79
75
–25
Sum
17,201
Weighted average
price index
Source: Prices for plywood, rubber, copper, palm oil, coconut oil, coffee (robusta),
aluminum, tin, gold and nickel are from World Bank, Global Commodity Markets
(various issues). Prices for coal, shrimp, paper, textile fabric from man-made fibre
(mmf), textile yarn and fibre, fish, wood pulp, fertiliser and tea are calculated
from BPS export data by dividing export value in dollars by export tonnage.
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66
L. Peter Rosner
where wi is the value share for item i in the base time period, or:
wi0 =
Pi 0 Qi 0
n
∑ Pi 0 Qi 0
(3)
i =1
Export prices (the Pis) are derived from export unit values, measured
as export value divided by export quantity. A weakness in using unit
values to measure export prices is that changes in unit values can reflect
either true price changes or a change in the mix of items exported under
a given export line. For relatively homogeneous items such as minerals
and agricultural products it is reasonable to assume that a given export
line will track the same item over time. But for manufactured goods the
mix of items in a single export line frequently changes over time. For
example, an export line identified as ‘colour TV sets’ might contain
14-inch sets one month and 19-inch sets the next. Moreover, export
quantity is generally measured in kilograms, and kilograms are clearly a
crude measure of quantity for manufactured goods.6
To avoid the aggregation problem inherent in the use of unit values,
it would be necessary to have direct price observations for individual
export items. Given the heterogeneity of manufactured exports this is
not possible. A typical garment export firm, for example, frequently
exports 100 or more different types of garments. Even a narrowly defined
item such as ‘men’s cotton dress shirts’ could contain items of vastly
different quality. In fact, for brand name garments each order is unique,
so that even with the most detailed data imaginable it would not be
possible to construct a perfect time series of the price of ‘men’s cotton
dress shirts’. Given this inherent measurement problem and the
limitations of Indonesian trade data, any measure of export volume or
price that is representative of overall exports must rely on unit values.
Since changes in the mix of items within a given export line can create
significant aggregation bias in the measurement of export volume, it is
essential to minimise this bias by identifying export items in as much
detail as possible. To minimise aggregation bias, the analysis is conducted
at the most detailed level possible with Indonesian export data, by using
nine-digit HS codes, which allow non-oil exports to be separated into
more than 7,000 individual export lines. Even at this level of detail,
aggregation bias is still a major problem in the data. Analysis of individual
HS nine-digit lines indicates that many lines contain a mix of
heterogeneous items. However, because the data are disaggregated to
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Indonesia’s Non-oil Export Performance during the Economic Crisis
67
the HS nine-digit level, the measure of non-oil export volume presented
below is less influenced by aggregation bias than other measures of nonoil export volume that use a higher level of aggregation.
Data Source
The data for this analysis are BPS monthly export data for the period
April 1994 through December 1999. BPS trade data record exports by
both HS and SITC (Standard International Trade Classification) nine-digit
codes. Since exporters record only the HS code on the export declaration
form they submit to customs, and since the mapping from HS codes to
SITC codes is subject to error, the HS codes are more reliable. The two
key variables available in the monthly data for each HS line are the value
of exports in dollars and the quantity of exports measured in kilograms.
Cleaning the Data
Unfortunately, BPS export data contain significant errors, particularly in
the quantity variable. For example, exports of gold (HS line 7108.12.100)
in January 1998 were recorded as 831.3 tonnes. This was more than 100
times greater than any previous or subsequent monthly quantity of gold
exports, and implied that Indonesia sold gold for $71 per tonne in January
1998, as against a minimum price of more than $5,000 for any other month.
Similarly, exports of unbleached cotton fabric (HS line 5208.12.900) were
recorded at 102,999 tonnes in December 1998, exceeding any previous or
subsequent quantity by a factor of 48 and implying that cotton fabric
was sold for 12¢ per kilogram in December 1998 as against a minimum
price of $3.24 for any other month.
Because of these large data errors, any quantity index constructed
from uncleaned data produces unreliable results. This can be seen in
figure 1, which applies equation (1) to raw BPS export data. The index is
highly volatile, particularly in 1997 and 1998, with month-to-month
changes in excess of 20% that bear little relationship to changes in export
value. The uncleaned quantity index is particularly volatile in mid 1998,
with volume growth of 57% recorded between May and July, followed
by a decline of 22% in August.
To respond to the data error problem, we developed a simple data
cleaning algorithm. Our algorithm assumes that the export values for each
HS line in each month are correct and that all problems lie in the quantity
variable.7 Any excessive change in the unit value (value divided by
quantity) for a particular HS line between one month and the next is
assumed to reflect a mistake in the quantity variable. In the event of an
excessive month-to-month change in the unit value, we assume that the
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68
L. Peter Rosner
unit value in the previous non-zero month is the correct unit value, and
we define a new ‘cleaned’ quantity by dividing the current month’s unit
value by the previous month’s unit value. In other words, our cleaning
algorithm can be expressed as follows:
if (Pit/Pit–1) > x or (Pit/Pit–1) < (1/x) then Qit* = Yit/Pit–1 and Pit = Pit–1
(4)
where x is the cleaning factor, Yit is the dollar value of item i exported in
time t, Pit–1 is the unit value of item i in the previous (non-zero) time
period and Qit* is the cleaned quantity. The cleaned Qit* are then used to
construct new unit values for the calculation of fixed base-period export
prices, and are also used in equation (1) above.8
The decision about what constitutes an ‘excessive’ month-to-month
change in the unit value for a particular export item is subjective. We
decided that anything greater than a fivefold change was definitely
excessive and anything less than a twofold change was within the bounds
of the possible. We then experimented with various cleaning factors (x
values in equation (4)). The results for x = 2, x = 3, x = 4 and x = 5 are
discussed in more detail in the appendix.
Choice of a Base Time Period for Calculating Constant Prices
The choice of time period for constructing constant prices is not clearly
determined by economic theory, and yet can have an impact on the
resulting measure of export volume. Measuring 1994–99 non-oil exports
at constant 1994 prices produces different results from those obtained
using constant 1996 prices or constant 1998 prices. In broad terms, the
choice is between using current prices and projecting them back or using
past prices and projecting them forward—the difference between a
Paasche and a Laspeyres index. Ideally the difference between these two
indices would not be large, but in practice it turns out to be significant.
This is because the fixed prices are essentially weights, as was shown in
equation (2) above, and the weights change significantly over time as
export value shares change.
A potential solution to this problem would be to use a chain-linked
index. However, the analysis uses monthly data over a 69-month period
(April 1994 to December 1999) and calculating an index with 68 links is a
tedious task. More importantly, no cleaning technique is perfect and
remaining errors in the data for any particular month can be large. This
would tend to make a monthly chain-linked index excessively volatile.
Over longer periods of time data errors average out. Mistakes in a
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Indonesia’s Non-oil Export Performance during the Economic Crisis
69
FIGURE 1 Non-oil Export Value, Volume and Price before Cleaninga
(monthly index April 1994 to December 1999; April 1994 = 100)
230
Value
Volume
190
Implicit Price
150
110
70
Jan-94
Jan-95
Jan-96
Jan-97
Jan-98
Jan-99
Jan-00
a
The export volume index uses constant average 1994–99 prices. The export quantity for gold in January 1998 has been cleaned. If the published number of 831
tonnes is used, the volume index rises to more than 500 in January 1998.
particular HS line in a single month could have a major impact on the
volume index if data from that month alone were used to create the fixed
price for each item, but if the fixed prices for each item are calculated
from many months of data the sensitivity of the results to outliers is
reduced. This consideration argues for using a period of at least 12 months,
and perhaps longer, for calculating the fixed price for each item.
Experiments with the data indicated that even calculating the fixed
prices from annual data produced significantly different results
depending on which year was chosen. Measuring exports at constant
1996 prices, for example, resulted in higher 1998 volume growth than
measuring them at constant 1997 prices, and using constant 1998 prices
produced the lowest measure of export volume growth in 1998. These
differences are presented and discussed in the appendix. To avoid having
to select a single year’s export prices as the ‘correct’ prices, it was decided
to use the average price for each item over the entire 69-month time period
for which data were available.
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70
L. Peter Rosner
The methodology ultimately selected for measuring non-oil export
volume therefore uses a modified version of equation (1), which can be
expressed as:
n
∑ Pi Qit*
Vt =
i =1
n
∑
x 100
Pi Qi*0
(5)
i =1
69
∑ Yit
P =
where i
t =1
69
*
∑ Qit
t =1
Yit is the dollar export value of item i in time t, and Qit* are the cleaned
quantity data.
FINDINGS: EXPORT VOLUME AND PRICES
BEFORE AND DURING THE CRISIS
Figure 2 presents the results of applying the methodology described above
to monthly BPS export data over the period April 1994 to December 1999.
Non-oil export volume is measured at constant average 1994–99 prices
with a cleaning factor of x = 3, meaning that any month-to-month change
in the unit value within a particular HS line that exceeds a factor of 3 is
assumed to reflect a mistake in the quantity data, and a new quantity
variable is then created using the previous month’s unit value and the
current month’s value. The cleaned volume index is less volatile than the
uncleaned index shown in figure 1, and bears a stronger resemblance to
the non-oil export value index.
Figure 2 shows that the average price of non-oil exports rose in 1994
and 1995 and then fell very slightly from early 1996 through mid 1997. In
mid 1997 non-oil export prices began a steep decline that continued
through early 1999. By the second quarter of 1999 they had dropped by
26% relative to the same period two years earlier.
Corresponding to this drop in prices, the growth rate of non-oil export
volume began to accelerate in mid 1997. This is best seen in table 2, which
shows quarterly non-oil exports measured both at current prices and at
constant average 1994–99 prices, along with the implicit export price index
and year-on-year growth rates.
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Indonesia’s Non-oil Export Performance during the Economic Crisis
71
TABLE 2 Quarterly Non-oil Exports: Value, Volume and Price, 1994–1999
Volume
Year-on-Year Growth
(constant
Implicit
(%)
average
Price
1994–99 prices;
Index
Implicit
$ million) (1994 Q2 = 100) Value
Volume
Price
Year and
Quarter
Value
(current
prices;
$ million)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
1994 Q2
Q3
Q4
1995 Q1
Q2
Q3
Q4
1996 Q1
Q2
Q3
Q4
1997 Q1
Q2
Q3
Q4
1998 Q1
Q2
Q3
Q4
1999 Q1
Q2
Q3
Q4
7,589
8,154
8,339
7,583
8,395
9,165
9,811
8,462
9,593
9,891
10,147
9,151
10,411
11,311
10,997
10,242
10,272
10,804
9,657
8,296
9,634
10,555
10,387
7,502
7,772
7,919
6,945
7,574
8,235
8,684
7,487
8,507
8,993
9,166
8,239
9,354
10,637
10,779
10,901
11,455
12,470
11,188
9,687
11,573
12,613
12,060
100
104
104
108
110
110
112
112
111
109
109
110
110
105
101
93
89
86
85
85
82
83
85
11
12
18
12
14
8
3
8
9
14
8
12
–1
–4
–12
–19
–6
–2
8
1
6
10
8
12
9
6
10
10
18
18
32
22
17
4
–11
1
1
8
10
6
7
4
2
–1
–2
–2
–1
–3
–8
–15
–19
–19
–15
–9
–7
–3
0
–7
24
–26
Growth 1997 Q2 to 1999 Q2
Source: Calculated from BPS trade data.
As can be seen in the sixth column of the table, export volume growth
was lower than export value growth from 1995 through the first half of
1996, and very slightly above it from mid 1996 until mid 1997, but in the
third quarter of 1997 export volume growth accelerated sharply. Yearon-year volume growth peaked at 32% in the first quarter of 1998 and
then declined during the second and third quarters of 1998, but remained
well above historical levels. By contrast, export value growth turned
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72
L. Peter Rosner
FIGURE 2 Non-oil Export Value, Volume and Price, Using Cleaned Quantity Data
(monthly index April 1994 to December 1999; April 1994 = 100)
230
Value
190
Volume
Implicit Price
150
110
70
Jan-94
Jan-95
Jan-96
Jan-97
Jan-98
Jan-99
Jan-00
negative after the first quarter of 1998. In the final quarter of 1998 volume
growth slowed and then became negative in the first quarter of 1999, but
it remained much higher than value growth. In the second quarter of
1999 volume growth recovered to plus 1%, and reached 8% by the fourth
quarter, even though value growth remained negative through the third
quarter.9
Figure 2 shows that most of the growth in non-oil export volume
took place during the first year of the economic crisis. Although volume
was still 17% higher during the third quarter of 1998 than it had been a
year earlier, on a month-to-month basis it began declining in August 1998
and continued to drop sharply through early 1999. During January and
February 1999, non-oil export volume fell to its lowest level in three years.
It recovered in March 1999 and continued to grow through August 1999,
but during the period March–August 1999 it was still 2% lower than it
had been during the same period in 1998.
The apparent slowdown in the growth of non-oil export volume after
mid 1998 may have been caused partly by the civil unrest that
accompanied the political transition occurring at that time. It may also
have been due to the fact that export volumes had reached a very high
level in the first half of 1998, with much of the growth caused by one-off
export activities that were not sustainable. During the first half of 1998
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Indonesia’s Non-oil Export Performance during the Economic Crisis
73
the value of the rupiah dropped at an unprecedented rate, falling from
Rp 4,650/$ at the end of 1997 to more than Rp 15,000/$ by mid 1998. The
magnitude and speed of the depreciation created opportunities for
windfall profits from trade, as local prices did not always adjust up as
rapidly as the rupiah was falling. A large quantity of merchandise appears
to have been exported during an ‘arbitrage window’ in the first half of
1998, as traders took advantage of the speed of the rupiah depreciation
to purchase existing stocks of goods in Indonesia and ship them abroad.
Toward the end of the third quarter of 1998, as the rupiah began to
strengthen and local prices caught up with international prices, this
window may have begun to close, contributing to a decline in these ‘oneoff’ exports.
Evidence of ‘one-off’ export activity can be seen in the pattern of
jewellery exports. Between January and March 1998, monthly jewellery
exports rose from less than $50 million to a record level of $337 million.
During the first half of 1998 the value of jewellery exports reached $1.3
billion, three times greater than a year earlier, and jewellery accounted
for more than one-third of the growth of non-oil export value over this
period. In August 1998 jewellery exports suddenly collapsed and by the
end of 1998 were below pre-crisis levels. The pattern seen in figure 3
strongly suggests a depreciation-induced boom motivated by pure
trading opportunities, followed by a bust as the arbitrage window
closed.10 A similar pattern can be seen in wood pulp exports, which grew
enormously during the period January–July 1998 and then dropped
suddenly toward the end of 1998. With jewellery and wood pulp
excluded, non-oil export volume grew by 9% during the second quarter
of 1999 relative to the same period in the previous year.
If the enormous growth of non-oil export volume during the first
half of 1998 was partly driven by factors that were not sustainable, a
better indication of the impact of the depreciation of the rupiah on export
activity might be obtained by comparing export levels in 1999 with levels
two years earlier. Although year-on-year volume growth was low in
1999, volume levels remain very high relative to levels before the crisis.
During the second quarter of 1999, for example, non-oil export volume
was 24% higher than it had been two years earlier (table 2), even though
it was up only 2% from the previous year. The fact that Indonesian
exporters were able to maintain the very high export volume levels
reached during the first half of 1998 suggests that problems such as trade
financing and political instability may not have been crippling Indonesia’s
exports. If exporters could not import raw materials owing to a lack of
trade finance, or if manufacturers could not find foreign buyers willing
to place orders in Indonesia, it is unlikely that such high export volume
levels could have been sustained.
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
74
L. Peter Rosner
FIGURE 3 Monthly Exports of Jewellery, January 1992 to December 1999
($ million)
350
300
250
200
150
100
50
0
Jan-92 Jan-93
Jan-94 Jan-95 Jan-96 Jan-97 Jan-98
Jan-99 Jan-00
Source: BPS.
Toward the latter part of 1999 export prices began to recover
(figure 2). The monthly index of non-oil export prices, calculated as the
ratio of export value to export volume, increased from 82 in September
1999 to 87 in December 1999. This upturn coincided with a recovery in
world market prices for commodities as recorded in international data
sources. For example, the World Bank’s ‘Pink Sheet’ series shows that
prices of copper, nickel, aluminium, gold, steel and wood pulp all turned
up strongly in the second half of 1999, and plywood prices were 32%
higher in the fourth quarter of 1999 than they had been in the third quarter
of 1998.11 The stabilisation and partial recovery of export prices in late
1999 allowed the relatively strong growth of non-oil export volume during
the crisis to show up as higher dollar revenue, and was probably the
main factor behind the 29.6% year-on-year rise in non-oil export value
reported during the first quarter of 2000.
THE SOURCES OF NON-OIL EXPORT GROWTH:
SECTORAL ANALYSIS
The preceding analysis has shown that non-oil export volume continued
to grow strongly during the economic crisis and that the drop in export
revenue, measured in dollars, was caused mainly by declining export
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
Indonesia’s Non-oil Export Performance during the Economic Crisis
75
prices. The strong growth of non-oil export volume was interpreted as
an indication that trade finance problems did not prevent exporters from
taking advantage of the enormous increase in competitiveness caused
by the depreciation of the rupiah.
However, not all of Indonesia’s non-oil exports require significant
quantities of imported inputs. Almost one-half of non-oil exports consist
of primary commodities and semi-processed resource-based products
with low import content, such as coal, rubber, palm oil and plywood.
Since exporters of these products generally do not need to open letters of
credit for imported inputs before each export shipment, it is possible
that even a very serious trade finance problem would not greatly affect
them. If the growth of export volume during the crisis has been driven
mainly by exports of primary commodities and semi-processed products,
and if manufactured exports have stagnated or declined, this would
suggest that trade finance problems might be having more of an impact
than would be assumed from the aggregate export volume data alone. It
is therefore important to look at the source of non-oil export volume
growth by sector.
To investigate the source of non-oil export volume growth, non-oil
exports were divided into four broad categories: (1) agriculture and
related semi-processed products; (2) forestry products (including
plywood, pulp, paper and semi-processed forestry products); (3) mining
and mineral products; and (4) manufactured goods.12 The results of this
analysis are shown in table 3. As can be seen in the last row of the table,
manufactured exports did better during the crisis than any of the other
three categories, in both value and volume terms. Measured in dollars,
manufacturing was the only category to experience growth between the
second quarter of 1997 and the second quarter of 1999. Export value for
the other three categories contracted sharply. Measured by volume, all
four categories experienced growth over this two-year period, but
manufacturing experienced by far the strongest growth.
In 1999, export volume of manufactured goods stagnated, rising only
0.3% relative to the previous year, but the volume level was still very
high. As was discussed above, much of the apparent slowdown was due
to the impact of ‘one-off’ exports during the first half of 1998, particularly
jewellery exports. The impact of jewellery on total exports of
manufactured products can be seen in figure 4. With jewellery removed
from the export volume index, it is apparent that exports of manufactured
products were considerably higher in 1999 than in 1998. In fact, if we
exclude jewellery, exports of manufactured goods grew 10% in real terms
in 1999. This was slower than the 1998 growth rate of 12%, but over the
two-year period 1997–99 exports of manufactured products (excluding
jewellery) increased by a very healthy 23%, measured at constant prices.
Quarter
Value (Current Prices)
Agric.
Forestry
1994 Q2
1,411
1,471
Q3
1,840
1,470
Q4
1,764
1,500
1995 Q1
1,411
1,444
Q2
1,627
1,629
Q3
1,777
1,687
Q4
1,919
1,712
1996 Q1
1,619
1,401
Q2
1,748
1,688
Q3
1,945
1,671
Q4
1,892
1,782
1997 Q1
1,634
1,513
Q2
1,856
1,778
Q3
2,072
1,482
Q4
1,848
1,376
1998 Q1
1,349
1,286
Q2
1,411
1,083
Q3
1,826
1,545
Q4
1,611
1,123
1999 Q1
1,349
1,145
Q2
1,553
1,534
Q3
1,859
1,731
Q4
1,616
1,653
Growth 1997 Q2 to 1999 Q2
–16%
–14%
Volume (Constant 1994–99 Prices)
Mining
Manuf.
600
747
752
836
819
1,061
1,085
944
1,113
986
1,005
935
1,256
1,225
1,033
997
930
903
1,128
912
926
947
1,141
4,107
4,098
4,324
3,892
4,321
4,641
5,095
4,498
5,044
5,289
5,467
5,069
5,522
4,340
3,116
4,646
4,961
5,077
3,549
3,849
5,579
6,003
5,975
1,508
1,672
1,574
1,131
1,266
1,521
1,707
1,394
1,534
1,812
1,779
1,496
1,730
2,150
2,115
1,557
1,729
2,356
2,111
1,639
1,924
2,482
2,088
–26%
1%
11%
Agric.
Forestry
Implicit Price Index
Mining
Manuf.
Agric.
1,375
1,414
1,477
1,409
1,508
1,499
1,492
1,277
1,467
1,433
1,524
1,301
1,551
1,520
1,927
1,848
1,880
2,337
2,141
1,643
1,835
1,970
1,882
623
742
705
719
706
875
881
794
947
917
917
845
1,073
1,147
1,003
1,084
1,056
1,063
1,325
1,142
1,240
1,181
1,296
3,995
3,944
4,163
3,686
4,094
4,341
4,605
4,023
4,559
4,830
4,947
4,597
5,000
5,826
5,761
6,427
6,800
6,700
5,591
5,254
6,574
6,980
6,794
100
118
120
133
137
125
120
124
122
115
114
117
115
112
110
105
96
88
92
93
86
80
83
100
97
95
96
101
105
107
103
108
109
109
109
107
107
96
85
73
74
69
76
79
82
82
100
105
111
121
120
126
128
123
122
112
114
115
122
111
107
95
91
88
88
83
78
83
91
100
101
101
103
103
104
108
109
108
107
108
107
107
102
98
91
90
89
89
85
83
84
86
18%
16%
31%
–25%
–27%
–36%
–23%
Forestry
Mining
Manuf.
Source: Calculated from BPS HS nine-digit monthly export data, April 1994 to December 1999. Classifications are based on three-digit SITC codes. See
table 4 for a more detailed description of the items in each category.
L. Peter Rosner
im Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUA
Year and
76
TABLE 3 Quarterly Non-oil Exports by Sector, Q2 1994 to Q4 1999: Value, Volume and Implicit Price (value and volume: $ million)
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
Indonesia’s Non-oil Export Performance during the Economic Crisis
77
FIGURE 4 Export Volume of Manufactured Goods Excluding Jewellery
(monthly index April 1994 to December 1999; April 1994 = 100)
240
210
All manufacturing
Manufacturing without jewellery
180
150
120
90
Jan-94
Jan-95
Jan-96
Jan-97
Jan-98
Jan-99
Jan-00
Source: Calculated from BPS trade data.
Figure 4 also shows that exports of manufactured goods declined
sharply during the second half of 1998. This decline began roughly three
months after the May 1998 riots. Many manufactured export products,
such as garments and footwear, typically have a lag of about three months
between the time orders are placed and the time merchandise is shipped
out of the country. The timing of the sharp drop in manufactured exports
in the second half of 1998 is consistent with the assertion that international
buyers shifted orders to other countries in response to the May 1998 riots
and the continued political instability in Indonesia in 1998. Interviews
with textile, garment and footwear manufacturers conducted by the
author in the second half of 1998 confirmed that many companies suffered
a severe cutback in orders following the riots. However, the strong
recovery of manufactured exports after February 1999 indicates that this
impact was largely temporary.
Looking at export price trends by sector, table 3 shows that all four
non-oil export sectors suffered from sharply falling dollar prices in 1997–
99. Prices for manufactured products declined the least, dropping by 23%
between the second quarter of 1997 and the second quarter of 1999, but
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
78
L. Peter Rosner
TABLE 4 Non-oil Exports by Sector: Value Growth, Volume Growth and Price
Change, April–July 1997 to April–July 1999
(%)
Sector
(based on
SITC 3-digit
classification)
Value
Growth
Implicit Comparable
ContriVolume
Price International bution to
Growtha Change
Price
Volume
Changeb
Growth
Agriculture
Fresh fish & shrimp
Rubber
Vegetable oils
Coffee
Cocoa
Processed food
Fish
Vegetables & fruit
Other processed food
Fresh fruit & vegetables
Animal feed
Tea
Spices
Other agricultural products
–20
–12
–46
–27
–26
2
42
4
82
40
18
–40
–1
0
–18
8
11
6
–10
–4
48
64
43
89
61
56
–11
32
14
–6
–26
–20
–49
–19
–23
–31
–14
–27
–4
–13
–24
–33
–25
–12
–12
Mining & mineral products
Copper
Coal
Nickel
Aluminum
Tin
Gold
Other mining products
–24
–30
–20
–5
–64
–16
–8
8
16
9
33
33
–52
–11
48
45
–34
–36
–40
–29
–25
–6
–38
–26
Forestry products
Plywood
Pulp & paper
Sawnwood
Other forestry products
–12
–32
34
–6
–5
21
–5
68
18
39
–27
–29
–21
–20
–32
–38
–44
–21
–22
–30
–28
–39
–26
–25
–16
–4
–21
–18
–40
7
2
1
–2
0
2
3
0
1
2
1
0
0
0
0
8
1
5
1
–2
0
1
1
14
–2
12
1
4
this decline was only slightly less than the 25% drop in the average price
of agricultural exports. Average export prices fell by 27% for forestry
products and by 36% for mining and mineral products.
A more detailed analysis of the source of non-oil export growth during
the economic crisis is provided in table 4, which disaggregates non-oil
exports into 45 items and subsectors. For each item or subsector, the table
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
Indonesia’s Non-oil Export Performance during the Economic Crisis
79
TABLE 4 (continued) Non-oil Exports by Sector: Value Growth, Volume Growth and
Price Change, April–July 1997 to April–July 1999
(%)
Sector
(based on
SITC 3-digit
classification)
Manufactured products
Textiles, garments & footwear
Fibre & yarn
Fabric
Garments
Footwear
Electronics & computers
Chemicals
Furniture
Machinery
Toys
Jewellery
Iron & steel
Household articles
Motorcycles & bicycles
Other transport equipment
Downstream plastics
Construction materials
Fertiliser
Tobacco products
Tyres
Total Non-oil
Value
Growth
Implicit Comparable
ContriVolume
Price International bution to
Growtha Change
Price
Volume
Changeb
Growth
1
10
23
–7
20
1
–8
19
34
39
8
–85
30
6
11
29
54
68
–40
–26
10
31
40
82
36
45
12
12
64
71
51
87
–67
79
43
46
37
77
141
12
51
48
–23
–22
–32
–32
–17
–10
–18
–28
–22
–8
–42
–56
–27
–26
–24
–6
–13
–30
–46
–51
–26
–8
24
–25
–26
–48
71
37
9
8
18
3
5
12
7
3
2
–4
3
1
1
1
2
4
0
1
1
100
a
Calculated using constant average unit values over the period January 1996 to
September 1999.
b
Comparable international prices taken from World Bank, Global Commodity Markets, various issues.
shows the growth rate of export value and volume and the change in the
implicit export price between the four-month period April–July 1997 and
the same period in 1999.13 The table also shows price changes for similar
items from international data sources, where available.
Table 4 shows that average export prices declined for every one of
the 45 items and subsectors over this two-year period, with the largest
price decline in the mining sector and the smallest in the manufacturing
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
80
L. Peter Rosner
sector. The price changes calculated from Indonesian trade data are
generally similar to price changes reported in international publications,
although for some items Indonesian export prices changed more, and
for others less, than reported world market prices.
The last column of table 4 shows the contribution of each item to
non-oil export volume growth between April–July 1997 and April–July
1999. Manufacturing accounted for 71% of volume growth over this
period, even though it represented less than 55% of non-oil export volume
(and value) at the start of the period. The item that made the greatest
contribution was garments, which accounted for 18% of all non-oil export
volume growth over this period. Chemicals and pulp and paper each
accounted for 12% of volume growth, fibre and yarn for 9%, fabric for
8%, and furniture for 7%, while coal and electronics each accounted for
5% of volume growth. The volume growth data indicate that export
sectors that are heavily dependent on imported inputs, such as garments,
textiles, chemicals, toys, and transport equipment, experienced rapid
export volume growth during the economic crisis.14 On the other hand,
so did some sectors that are dependent on domestic natural resources,
such as pulp and paper, furniture, processed food and coal.
COMPARISON WITH OTHER REGIONAL ECONOMIES
Indonesia’s experience with sharply falling export prices during the
regional economic crisis was apparently not unique. Data from Thailand
and Korea indicate that both of these countries also experienced a sharp
decline in export prices between 1997 and 1999. Export price indices for
Indonesia, Korea and Thailand are shown in figure 5 (re-based so that
July 1997 equals 100 to facilitate comparison). As can be seen in the figure,
export prices declined by at least 20% in all three countries during the
crisis. Relative to July 1997 Indonesia suffered the sharpest decline, but
export prices for Korea had been declining since mid 1995, and by mid
1999 had fallen more than 30% in four years. Export prices for Thailand
began to decline in early 1997 and by late 1999 had fallen by as much as
Indonesian non-oil export prices.
Korea and Thailand are mainly exporters of manufactured goods:
more than 90% of Korea’s exports and more than 70% of Thailand’s
exports consist of manufactured products. The fact that the average price
of exports from these two countries declined by almost as much as that
of Indonesia’s non-oil exports lends further support to the finding that
the collapse in export prices during the crisis was not confined to primary
commodities.
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
Indonesia’s Non-oil Export Performance during the Economic Crisis
81
FIGURE 5 Export Price Indices, Indonesia, Korea and Thailand
(July 1997 = 100)
120
110
100
90
80
Thailand (export unit value)
Korea (export price)
Indonesia (implicit non-oil
export price)
70
Jan-94
Jan-95
Jan-96
Jan-97
Jan-98
Jan-99
Jan-00
Sources: Indonesia: calculated from BPS export data using HS nine-digit unit values.
Korea: IMF, International Financial Statistics.
Thailand: Bank of Thailand homepage (www.bot.or.th/bothomepage/
databank).
Although their export prices declined to a similar extent, other
regional economies did not suffer as drastic a fall in export values as did
Indonesia. During the first year of the crisis Indonesia’s non-oil exports
(measured in dollars) grew considerably faster than total dollar exports
from Korea or Thailand. However, during the second year Indonesia’s
non-oil export value declined by 12.2%, whereas total Korean export value
declined by 2.4% and total Thai export value by 3.4% (table 5). Moreover,
Korean and Thai export values recovered strongly in 1999 and had
surpassed pre-crisis levels by the end of the year, whereas Indonesian
non-oil export values remained well below pre-crisis levels in 1999. This
suggests that Indonesian exports suffered from more than just a drop in
prices, at least during the second year of the crisis. It is possible that the
slowdown in non-oil export volume growth between August 1998 and
February 1999 was a very delayed reaction to the trade finance problem
that started in late 1997. However, given that the slowdown began three
y [Universitas Maritim Raja Ali Haji], [UNIVERSITAS MARITIM RAJA ALI HAJI TANJUNGPINANG, KEPULAUAN RIAU] at 22:05 19
82
L. Peter Rosner
TABLE 5 Annual Growth of Export Value, Indonesia, Thailand and Korea
(%)
Perioda
Year-on-Year Export Growth
Indonesia (non-oil)
Thailand
Korea
1994/95 to 1995/96
13.8
9.2
15.4
1995/96 to 1996/97
7.8
–2.0
1.0
——————————————————— start of crisis ——————————
1996/97 to 1997/98
7.3
2.0
3.0
1997/98 to 1998/99
–12.2
–3.4
–2.4
a
Each time period starts in August so as to coincide with the floating of the Indonesian rupiah. Thus ‘1994/95’ refers to the 12-month period August 1994 to July
1995. The first two rows are therefore pre-crisis growth rates.
Source: Korea and Thailand: IMF, International Financial Statistics; Indonesia: BPS.
months after the May 1998 riots, and given that non-oil export volume
recovered strongly in mid 1999 even though trade finance problems
continued, it seems likely that the August 1998 – February 1999 drop in
non-oil exports was due mainly to the impact of social and political
instability on international demand for Indonesian manufactured
products.
TERMS OF TRADE AND THE REAL EXCHANGE RATE
The finding that non-oil export prices declined by around 26% in dollar
terms during the crisis suggests a massive deterioration in Indonesia’s
terms of trade. This raises the possibility that a major correction in the
exchange rate might have been required to maintain Indonesia’s