Services trade

and the Indonesian third unbundling

Krisna Gupta & Dhany Ratana

CIPS, Politeknik APP Jakarta

July 25, 2024

Indonesian services

Indonesia has always been a net importer of trade. Export services is dominated by tourism, while import services is dominated by logistics and business services.

Indonesian government often concerned with deficit trade, but trade in services has often neglected in the discussion.

But more!

About the chapter

  • The state of trade in services in Indonesia

  • Services as manufacturing inputs

    • using Input-Output.

    • services import-manufacturing export cointegration.

  • Preliminary conclusions

The third unbundling

  • Unbundling: how much part of the supply chain of production can be traded across border increase the use of comparative advantage (Baldwin 2016; Kimura 2018).

    • trade cost: 1st, communication costs: 2nd, face-to-face costs: 3rd.
  • 3 development paths: step-by-step, leap-frogging, feedback (Kimura 2018)

  • The last two makes services ever more important:

    • leap-frog to supplying part of a services tasks, or;

    • Feedback, using services to improve manufacturing.

Services in manufacturing

  • Melitz (2003): non-trivial trade cost makes small-margin firms lose.

  • Services can lower this cost: brigde information gap on the market, business customs and regulations in other countries, especially for new firms entering export market (Lodefalk 2014)

  • In Sweden, firms with higher services embeded in its final products increases its intensity of export (Lodefalk 2014)

  • In Indonesia, 10 per cent increase in service intensity of a firm increase its productivity by 7 to 8 per cent (Hing and Thangavelu 2023)

Services trade in Indonesia

  • Trade in services is complicated amid 4 modes (Magiera 2011):

    • mode 2 & 4 \(\rightarrow\) Visa and KITAS regulations

    • mode 3 \(\rightarrow\) investment and operational.

  • Magiera (2011): complicated authorities, unlike goods. Makes it hard to discuss Deep Trade Agreements (Syahputri and Gupta 2024).

  • IJEPA: no evidence it improves services trade (Syahputri and Gupta 2024)

Data: BaTIS

  • First launched in 2017 by OECD and WTO (Liberatore and Wettstein 2021),

  • Balanced data from two trading partners.

  • Not very good outside of rich countries.

  • used to build other databases like TiVA.

Table 1: Services classification in BaTIS
Code Category description
SA Manufacturing services on physical inputs owned by others
SB Maintenance and repair services n.i.e.
SC Transport
SD Travel
SE Construction
SF Insurance and pension services
SG Financial services
SH Charges for the use of intellectual property n.i.e.
SI Telecommunications, computer, and information services
SJ Other business services
SK Personal, cultural and recreational services
SL Government goods and services n.i.e.

Trade by partner,2021

Figure 1: Indonesia’s exports by partner, 2021
Figure 2: Indonesia’s imports by partner, 2021

Singapore is the most important partner in trade in services for Indonesia. China, on the other hand, is the main buyer of Indonesia’s services export

Trade by sector, 2021

Figure 3: Indonesia’s exports by sector, 2021
Figure 4: Indonesia’s imports by sector, 2021

Indonesia’s imports dominates exports in all categories bar travel (SD). Additionally, the highest traded services in Indonesia are transport (SC) and business services (SJ)

Top services: travel

Figure 5: Indonesia’s travel export, top 6 partners
Figure 6: Indonesia’s travel import, top 6 partners

The only net export got punished by the pandemic. China+Australia important export destination,

Top services: transport

Figure 7: Indonesia’s travel export, top 6 partners
Figure 8: Indonesia’s travel import, top 6 partners

Singapore’s dominance is apparent here. Very important for manufactures trade.

Top services: ICT services

Figure 9: Indonesia’s ICT service export, top 6 partners
Figure 10: Indonesia’s ICT service import, top 6 partners

Perhaps the most relevant services to leap-frogging and feedback. Also the highest beneficiary of the pandemic.

Top services: biz services

Figure 11: Indonesia’s ICT service export, top 6 partners
Figure 12: Indonesia’s ICT service import, top 6 partners

Other business services includes consulting management, research and development, and trade-related services (Liberatore et al. 2021)

All in all

  • Singapore is important for Indonesia

  • Travel carry the trade balance. Most travel exports comes mainly from tourism, which is bad since the pandemic punishes it disproportionately.

  • Trade agreements play a huge role in improving trade in services.

  • Measures that affects movement of natural persons (e.g., qualification harmonization), and other non-tariff measures like computing requirement and investment list are crucial as trade in services can be done in 4 different modes that got affected by these rules.

Manufacturing feedback

  • We look at the role of imported services to Indonesian manufacturing, a sector Indonesian government tries to revive for a long time.

  • Two approaches: input-output table and ARDL cointegration.

  • Input-Output utilises ICIO data (OECD 2023), the ARDL uses Indonesian Central Bank data (Bank Indonesia, n.d.)

ICIO

Let there be a nest of product from some degree of substitutable services input:

\[ Y_{it}=f(AS^D_{it},AS^F_{it}) \]

for all \(i=\) manufacturing sectors and \(t=year\). A is the nest multiplier, \(S^D_i\) and \(S^F_i\) are total services purchased by industry \(i\), domestically and imported respectively.

Assuming a Cobb-Douglass relationship, a log-linearized version thus

\[ y_{it}=a+\beta_d s^D_{it}+\beta_f s^F_{it}+\varepsilon_{it} \]

ICIO

To construct the dataset for the regression, we aggregate non-factor inputs from each manufacuring sectors, separated by whether it is from Indonesia or from other countries. All inputs from foreign countries are aggregated into foreign.

For comparison purpose, we also do the same for 4 countries in the region, namely Singapore, Malaysia, Thailand and Vietnam. Data from these 5 countries are then concatenated to add one more dimension, countries. Summary statistics on the data is shown in Table 2.

Summary

Table 2: Summary Statistics from ICIO, million USD, 2002-2021.
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all IDN
Mean SD Histogram Mean SD Histogram
value added 4181.70 6845.40 ▇▁ 8150.56 12191.95 ▇▁
output 15930.67 21741.55 ▇▁ 21529.33 29317.48 ▇▁▁
domestic services 2804.36 3889.86 ▇▂▁ 3735.21 4176.07 ▇▅▁
foreign services 845.74 1730.29 420.05 339.95 ▇▆▄▃▂▁
domestic goods 5213.09 9008.54 ▇▁ 7123.05 12296.21 ▇▁
foreign goods 7057.46 9172.47 ▇▁▁ 10240.63 12983.59 ▇▁▁
for. services share 5.76 3.70 ▃▇▃▁ 2.45 1.34 ▇▆▆▇▄▃▂▂▁
dom. services share 18.02 6.73 ▂▇▇▇▅▃▁▁ 18.55 5.41 ▂▆▇▇▅▄▅▃▁
for. goods share 47.62 11.39 ▁▂▂▅▇▆▄▂▁ 50.30 11.98 ▁▁▃▇▅▇▅▁▂▁
dom. goods share 28.37 11.11 ▃▄▇▇▄▂ 28.60 8.57 ▁▂▂▃▅▇▅▄▂▁

ICIO

Table 3: Panel regression of log manufacturing value added
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all IDN SGP VNM THA MYS
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
lfs 0.159 -0.207 0.172 0.358** -0.175* 0.082
(0.159) (0.283) (0.170) (0.094) (0.062) (0.264)
lds 0.708*** 0.735* 0.587* 0.479*** 1.112*** 0.808***
(0.157) (0.280) (0.209) (0.086) (0.066) (0.173)
Num.Obs. 1520 304 304 304 304 304
R2 0.825 0.863 0.984 0.993 0.992 0.945
R2 Within 0.658 0.423 0.780 0.984 0.952 0.727

all has country and sector dummy, while country regressions only has sector dummy.

For value added, log foreign services (lfs) do not seem to be significant bar Vietnam, while log domestic services (lds) generally significant.

OLS

Table 4: Panel regression of log manufacturing output
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all IDN SGP VNM THA MYS
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
lfs 0.221+ -0.070 0.179 0.471** 0.112+ 0.155
(0.105) (0.141) (0.138) (0.135) (0.062) (0.166)
lds 0.745*** 0.910*** 0.640** 0.547*** 0.865*** 0.745***
(0.103) (0.129) (0.166) (0.123) (0.062) (0.103)
Num.Obs. 1520 304 304 304 304 304
R2 0.962 0.954 0.993 0.995 0.996 0.987
R2 Within 0.921 0.880 0.914 0.990 0.973 0.891

For output, log foreign services (lfs) do not seem to be significant bar Vietnam, while log domestic services (lds) generally significant.

Indonesia’s low share of foreign services seem to be the reason why it has no correlation with both output and value added.

ARDL

We complement previous analysis with ARDL cointegration analysis by using aggregate export and import data from the central bank (selo?)

\[\begin{align} exM_t&=\alpha_0+\alpha_1 exM_{t-1}+\alpha_2 imM_t+\alpha_3 imSev_t+\nu_i \\ exM_t&=\gamma_0+\gamma_1 exM_{t-1}+\gamma_2 imM_t+\gamma_3 imSev_t+ \gamma_4 imM_{t-1}+\gamma_5 imSev_{t-1}+\upsilon_i \\ pdb_t&=\delta_0+\delta_1 pdb_{t-1}+\delta_2 imM_t+\delta_3 imSev_t+\omega_i \\ pdb_t&=\theta_0+\theta_1 pdb_{t-1}+\theta_2 imM_t+\theta_3 imSev_t+ \theta_4 imM_{t-1}+\theta_5 imSev_{t-1}+\eta_i \end{align}\]

where \(exM\) is log manufacturing exports, \(pdb\) is log manufacturing GDP, \(imM\) is log manufacturing imports and \(imSev\) is log services imports, all for Indonesian level in time \(t\), where \(t\) is from 2005 to 2023.

Specifications that we run are ARDL(1,0,0), the least restrictive, and ARDL(1,1,1) which is considered from AIC, BIC and RMSE (Pesaran and Smith 1995; Natsiopoulos and Tzeremes 2022).

ARDL

Figure 13: Indonesian trade dynamics

ARDL

Table 5: Summary statistics
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Mean Median SD Histogram
log value added 7.62 7.67 1.26 ▁▁▃▅▇▆▃▁
log output 9.01 9.06 1.21 ▁▂▄▆▇▄▂
log foreign services 5.98 6.00 1.21 ▂▄▇▇▄▁
log domestic services 7.23 7.23 1.25 ▁▁▃▅▇▆▄▂▁

ARDL

Table 6: ARDL results on four specifications
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Export 1 Export 2 GDP 1 GDP 2
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
(Intercept) 0.704 1.354+ 0.112 0.243+
(0.724) (0.692) (0.127) (0.128)
L(exM, 1) 0.676** 1.135***
(0.222) (0.177)
imM 0.273 0.307* -0.003 -0.023
(0.184) (0.127) (0.020) (0.022)
imSev -0.106 -0.130 0.098** 0.110***
(0.247) (0.146) (0.029) (0.024)
L(imM, 1) -0.151 0.031
(0.166) (0.023)
L(imSev, 1) -0.485* -0.083*
(0.182) (0.030)
L(pdb, 1) 0.917*** 0.938***
(0.024) (0.022)
Num.Obs. 18 18 18 18
R2 0.881 0.967 0.997 0.998
Log.Lik. 32.291 43.772 70.818 76.085
RMSE 0.04 0.02 0.00 0.00

ARDL

  • Indonesia’s current import service does not seem to contribute much to the country’s manufacturing export.

  • This corroborates findings in ICIO regression.

  • Indonesian firms does not seem to have much in house services to begin with, and those who do are only a small fraction of very productive firms (Hing and Thangavelu 2023).

All in all

  • By itself, Indonesian services export relies on travel. Looks to be net-importing for some time.

  • Services content in manufacturing seems to be an untapped potential: increasing services content may be beneficial for Indonesian manufacturing thus the feedback mechanism a la Kimura (2018).

  • Exports will be needed if manufacturing to increase its services content beyond transport to justify the cost.

Conclusion

  • This chapter arguably met its goal in discussing Indonesia’s service trade.

  • while ICIO is not the best, it remains the best data to look at services content in manufacturing (and services too, in fact i.e., the leap-frog)

  • We may need to fine-tune the discussion, so feedback is welcomed!

References

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