metadata: authors: 0: author: Majune,Socrates Kraido
1: author: Montfaucon,Angella Faith Lapukeni
count: Indonesia
docna: 0: docna: Trade Policies and Sea and Air freight : The
            Impact of COVID-19 Lockdowns on Imports and Exports
docty: Policy Research Working Paper
abstracts: cdata!: This study analyzes how
            Indonesia&#x2019;s international trade was affected by
            its own lockdown policies (domestic) and those of its
            trading partners (external) in response to COVID-19. The
            study differentiates between sea freight and air freight, as
            well as products affected by specific non-tariff measures.
            Event-study results show that the decline in imports (which
            were more negatively affected than exports) was mainly
            attributed to external lockdowns, the impacts of which were
            more pronounced and persistent for imports entering
            Indonesia by air (due to restrictions to international
            travel) and imports subject to port-related non-tariff
            measures. Domestic lockdowns adversely affected intermediate
            imports subject to non-tariff measures requiring physical
            inspection, testing, and approval processes. External
            lockdowns, which also had a larger impact on exports
            relative to domestic policies, affected sea and air exports
            evenly. Demand factors (specifically, workplace closures and
            stay-at-home orders) in the partner countries were the
            drivers of the decline in exports. Enhancing trade
            facilitation to keep goods moving as smoothly as possible,
            reforming specific non-tariff measures, and improving
            customs and other procedures would ensure fewer disruptions
            from shocks in a globally integrated world.
display_title: Trade Policies and Sea and Air
            freight : The Impact of COVID-19 Lockdowns on Imports and Exports
listing_relative_url: /research/2023/01/33974187/trade-policies-sea-air-freight-impact-covid-19-lockdowns-imports-exports
topicv3: Private Sector Development m1326060 1921,Transport m1326661 135,Trade m1326924 698
publishtoextweb_dt: 2023-01-09T00:00:00Z
dois: 10.1596/1813-9450-10271
origu: Off of Sr VP Dev Econ/Chief Econ (DECVP)
author_keys: 0: author_key: 1688118
1: author_key: 1819671
model_extractions: Policy Research Working Paper 10271 Trade Policies and Sea and Air freight The Impact of COVID-19 Lockdowns on Imports and Exports _Socrates Majune Angella Faith Montfaucon_ Macroeconomics, Trade and Investment Global Practice January 2023
Policy Research Working Paper 10271

# **Abstract**

This study analyzes how Indonesia’s international trade was affected by its own lockdown policies (domestic) and those of its trading partners (external) in response to COVID-19. The study differentiates between sea freight and air freight, as well as products affected by specific non-tariff measures. Event-study results show that the decline in imports (which were more negatively affected than exports) was mainly attributed to external lockdowns, the impacts of which were more pronounced and persistent for imports entering Indonesia by air (due to restrictions to international travel) and imports subject to port-related non-tariff measures. Domestic lockdowns adversely affected intermediate imports subject to non-tariff measures requiring physical inspection, testing, and approval processes. External lockdowns, which also had a larger impact on exports relative to domestic policies, affected sea and air exports evenly. Demand factors (specifically, workplace closures and stayat-home orders) in the partner countries were the drivers of the decline in exports. Enhancing trade facilitation to keep goods moving as smoothly as possible, reforming specific non-tariff measures, and improving customs and other procedures would ensure fewer disruptions from shocks in a globally integrated world.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at amontfaucon@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# Trade Policies and Sea and Air freight: The Impact of COVID-19 Lockdowns on Imports and Exports<sup>∗</sup>

Socrates Majune<sup>†</sup> and Angella Faith Montfaucon<sup>‡</sup> _JEL Classification_ : F10, F13, F14, O53 _Keywords_ : Lockdown policies, Indonesia, COVID-19, Sea cargo, Air cargo, Non-tariff Measures

> ∗The authors would like to thank Devaki Ghose and Csilla Lakatos for helpful comments, Bayu Agnimaruto for updating the Indonesia non-tariff measures data and Bradley Robert Larson for the COVID-19 data update. This paper has partially benefited from financial support from the Umbrella Facility for Trade trust fund, financed by the governments of the Netherlands, Norway, Sweden, Switzerland and the United Kingdom. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors and do not necessarily represent the views of the World Bank and its affiliated organizations, or those of the Executive Directors or the countries they represent. All errors are our responsibility.

> †World Trade Organization and University of Nairobi skmajune@uonbi.ac.ke

> ‡World Bank amontfaucon@worldbank.org, corresponding author
# **1 Introduction**

While coronavirus (COVID-19) is primarily a health crisis, its ramifications extend to social and economic aspects of countries. Trade collapsed and demand and supply shocks became widespread after pandemic-induced measures were imposed globally to contain transmissions. Supply-side shocks on exports arose from COVID-19 related deaths and infections, and lockdown policies such as border closures, slow clearance of goods and workplace closures that reduced labor participation resulted in a slump in overall firm and country production capacity. Demand shocks then compounded the supply shocks from declines in aggregate demand due to job redundancies, business closures, cautionary spending and investments. These shocks were in turn transmitted and augmented through disruptions in the global supply chains (Hayakawa and Mukunoki, 2021a; Hayakawa and Mukunoki, 2021b).

In this context, this paper assesses the trade effect of the pandemic on the largest economy in Southeast Asia, Indonesia. The study investigates the broad effects of lockdown measures (domestic, i.e., imposed by Indonesia, and external, i.e., imposed by Indonesia’s trading partners) on Indonesia’s imports and exports, including the survival of products in import and export markets. Then, we differentiate between sea and air trade as well as assess the role of specific non-tariff measures (NTMs) on the effect of lockdown measures on trade performance in Indonesia. Additional analyses are also conducted to establish the sensitivity of our results to the type of lockdown policy and the effect of lockdowns on export and import prices. Lockdown is a binary composite indicator variable where one indicates the month any of the following measures were imposed by Indonesia and its trading partners: workplace closure, the closure of public transport, stay-at-home requirements, restrictions on internal movement, and international travel controls. This is done using a monthly series of productby-country data for the period 20 months before and 20 months after January 2020, i.e., May 2018 to August 2021, in survival analysis and event-study designs. For imports, domestic lockdowns represent demand factors and external lockdowns represent supply factors. For exports, the inverse applies.

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Results from the product-country relationship survival analysis show that the failure rate of exports and imports increased during both domestic and external lockdowns, but differences between sea and air freight trade were minimal. Notably, imports subject to NTMs had lower survival rates during both domestic and external lockdowns, especially those subject to port of entry restrictions and import approvals. Event-study results show that overall, imports were more negatively affected by lockdown policies than exports, which recovered during the sample period, unlike imports. The decline in imports was mainly attributed to lockdown policies by Indonesia’s trade partners. These affected imports entering Indonesia by air more than those entering by sea, mainly attributed to restrictions on international travel which limited the availability of air cargo during the pandemic. Imports subject to port of entry restrictions and pre-shipment inspections were also more negatively affected, which seem to have worsened the supply side factors for imports.

On the other hand, Indonesia’s lockdown policies on imports mainly negatively affected intermediate imports subject to NTMs, especially measures requiring physical inspection and testing (such as certification with Indonesian product standards or _Standar Nasional Indonesia_ (SNI)) and import approval processes. As for exports, domestic lockdowns had a mixed and large impact on air exports, but not sea exports, while external lockdowns affected sea and air exports relatively evenly.

These results suggest that supply factors had a larger role in the impact of external lockdowns on imports than demand factors related to the COVID-19 shock. However, NTMs on Indonesia’s imports exacerbated the impact of demand factors for imports. Meanwhile, demand factors (specifically workplace closures which imply lower or no income, and stay at home orders) in the partner countries were the drivers for the slump in exports. Enhanced – trade facilitation to keep goods moving as smoothly as possible including reforming burdensome non-tariff measures, improving customs and other procedures - would ensure fewer disruptions from shocks in a globally integrated world. These would also ensure that port inspections and procedures that necessitate port of entry restrictions are conducted more 2
efficiently and avoid backlogs and port delays. In this regard, Indonesia has taken several steps to remove some regulations related to measures such as pre-shipment inspections, and introduce a more integrated risk management system in 2021. The impacts of these remain to be seen. Additionally, procedures that require physical inspections of goods and testing and certification and their processes could be improved.

Studies providing evidence of the impact of COVID-19 on international trade have been on the increase. They have so far examined the effect of the virus on global value chains (Javorcik, 2020; Vidya and Prabheesh, 2020; Egger and Zhu, 2021; Casta ̃neda-Navarrete et al., 2020; Espitia et al., 2021; Che et al., 2021; Hayakawa and Mukunoki, 2021a), trade policies (Baldwin and Evenett, 2020; Evenett, 2020; Mendoza, 2021; Brenton et al., 2022), export and import flows (Maliszewska et al., 2020; B ̈uchel et al., 2020; Zhao et al., 2021; Minondo, 2021; Hayakawa and Mukunoki, 2021b; Rose et al., 2021;Fang et al., 2022) and COVID-19 lockdown measures (Majune and Addisu, 2021; Hayakawa and Mukunoki, 2021b; Pei et al., 2021; Arenas et al., 2022). These studies have mainly been cross-country aggregate analyses with few exceptions, employing various approaches in their analysis (descriptive statistics, regression model, gravity model, computable general equilibrium model, differencein-differences, propensity score matching, logistic regression and event-study methodology). Monthly data is prevalent among papers except for Majune and Addisu (2021) who applied weekly-level data.

Majune and Addisu (2021) and Arenas et al. (2022) are closely related to our work because they employed an event-study methodology in their analysis. Majune and Addisu (2021) found that COVID-19 had an asymmetric effect on Kenya’s international trade: exports increased by an average of 13% while imports dropped by an average of 23% between July 1, 2019, and June 30, 2020.<sup>1</sup> The introduction of lockdown measures by trading partners of the Philippines affected its imports more than exports, leading to 7% and 56%

> 1The fall in imports was triggered by the disruption in sea cargo trade with countries that imposed lockdown controls. Furthermore, the authors find that lockdowns imposed by Kenya also boosted the country’s exports and dampened imports.

3
monthly average drops in export and import values, respectively, according to Arenas et al. (2022). We closely follow the two studies with a focus on Indonesia and in turn make three contributions to this literature.

Our first contribution is that our paper incorporates non-tariff measures (NTMs) in the analysis, allowing the paper more policy relevance. This is highly relevant for Indonesia, as NTM incidence is among the highest in the region, and their use was prevalent in the pre-COVID period (Cal`ı & Montfaucon, 2021). The novel feature of this contribution is the use of the most updated time-varying data on non-tariff measures, an area in trade policy that has not received much attention in this literature, especially due to the lack of reliable data on NTMs. This allows us to link to the timeline of the pandemic and assess how various lockdown policies differently affected import trade of products subject to specific NTMs.

Our second contribution is methodological. We employ an event-study in our study. This approach is preferred over impact-evaluation estimators such as the difference-in-differences (DiD) and Propensity Score Matching (PSM), and a gravity-model. The event-study approach addresses concerns of lockdown anticipation. Since East Asia was the first epicenter of COVID-19, most countries in the region started imposing restrictions earlier than the rest of the world (Arenas et al., 2022), which could have triggered the reaction of exporters and importers in Indonesia in anticipation of the imposition of lockdowns in partner countries. The event study also enables us to observe the reaction of international trade to lockdown policies at high frequency (months), which often changed depending on the spread/wave of the virus in a country.

Finally, we add to the literature on COVID-19’s impact on trade in a country case study by using more recent and more detailed trade data in a comprehensive analysis of trade for Indonesia, separating impacts of domestic and external lockdowns on trade. This is unlike other studies on Indonesia such as Eschachasthi (2022), Ing and Vadila (2022), and Olivia et al. (2020). Also existing studies on Indonesia, we assess lockdowns in the context of trade by sea and air. Lockdowns disrupted both maritime shipping, which is the main mode 4
of transportation in international trade, and air freight services. With canceled sailings and flights, port delays, and container shortages, COVID-19 measures may have differences in trade transported by sea or air to an archipelago country like Indonesia (see Majune and Addisu, 2021), with implications for trade facilitation measures.

The reminder of this paper is organized as follows. The data is described in section 2. The methodology is presented in section 3 with the results discussed in section 4. Finally, section 5 concludes our study.

# **2 Data**

## **2.1 Lockdown data**

Lockdown is a binary variable, a composite indicator where one indicates the month any of the following measures were in place: workplace closure, the closure of public transport, stay at home requirements, restrictions on internal movement, and international travel controls. Lockdown is twofold: external and domestic. External lockdown refers to when the indicator refers to lockdown policies by Indonesia’s trading partners and domestic lockdown is a dummy where any of the above-mentioned indicators are applied by Indonesia in a particular month. This definition of lockdowns has been adopted from Majune and Addisu (2021) and differs from country to country for the external lockdown since lockdowns were in place at different times. Data for these indicators is from the Oxford COVID-19 Government Response Tracker (Hale et al., 2021).

To explain the pattern of lockdown measures, we display the trend of Indonesia’s lockdown Stringency Index and that of selected countries (Papua New Guinea, India, Thailand, Malaysia, Australia, Singapore, the Philippines and Vietnam) between January 1, 2020, and August 31 2021 in Figure 1. The index is constructed by re-scaling the maximum ordinal values of nine indicators (one health measure and eight closures and containment policies) to range between 0 and 100. The scores are then averaged to get a composite index for each 5
country. A score of 0 indicates no restrictions while 100 signals severe implementation of lockdown policies in a country (Hale et al., 2021).

The first lockdown measure in Indonesia was on January 18, 2020, when COVID-19 screening of international travelers was introduced. This was followed by the ban on arrivals from some regions on February 5, 2020. Closure of workplaces, total border closure, closure of public transport, restrictions on internal movement and stay-at-home requirements followed in that order from March 15 and they were all operational by April 1. This is depicted by the consistent rise in the stringency index which remained above 70 until May 20, 2020, when the closure of public transport was temporarily lifted. The index has since fluctuated depending on the severity of the COVID-19 wave. Indonesia had the second highest index among the countries in Figure 1, after Australia, by the end of 2020. All the lockdown measures were in operation in 2021 and the index was relatively stable at around 72. Indonesia had the third highest index, after Vietnam and the Philippines, at the end of the sample period on August 31, 2021.

Among the neighboring countries, Singapore was the first to impose lockdown measures (January 2), followed by Vietnam (January 25), India (January 26), Papua New Guinea (January 27), Malaysia (January 30), the Philippines (January 31), Australia (February 1) and Thailand (March 6). All the countries started with international travel controls and progressively introduced domestic measures. Singapore’s stringency index was the lowest of all Indonesia’s neighbors at the end of August 2021 because of the relaxation of the conditions on internal movements and public transport. The Philippines, Vietnam and Australia had the highest stringency indices by the end of August 2021, respectively.

# **2.2 Trade data**

Our export and import data is a monthly product-country data series obtained from the Indonesia Statistics Authority (BPS _Badan Pusat Statistik_ ). The data ranges from May 2018 to August 2021. Products are classified at the 8-digit Harmonized System (HS) level.

6
<!-- Start of picture text --> Stringency index for Indonesia and neighbouring countries<br>100<br>x 80 oa Thea) eee meta - 57s 3<br>@ tai ‘ f a cs]<br>' Hb Yituls “sath eal my ~<br>om 40 ' teeeeeet OS<br>£'u<br>®20 —H;<br>fe) a i<br>rr a a, a i i a a |<br>oONoO OoNOo oOoNoO oONoO oONoO OoNOo -N- -N- -N- =-=-N -N=<br>Y ay ay 2 Y ay Y Y hy y Y<br>5 5&8 € & g§ & 5&5 5 © 8 &<br>Date<br>— Australia India — Indonesia -—-- Malaysia<br>---. Papua New Guinea —— Philippines Singapore -—- Thailand<br>Vietnam<br><!-- End of picture text -->
<!-- Start of picture text --> Growth of exports and imports<br>140 | 6t al<br>120 | 18<br>&<br>r= g!<br>12>) x=<br>= 2| |<br>long . .<br>8 80 S<br>a SIY38M)<br>60 3S “a<br>2S| IVI<br>40 S<br>>Ss a22> 4 5 SuorwrtesrteyF SP seeete ys Sse<br>ses 5S oO ose SF TS oOoEos ST SHO FCeSkT Ss OD<br>=o PF RFS RAP ZL FSSRPZPF=SLHPM<br>SseFSFese8E2seseFS2N8R8SRRRHKAKSEAH<br>rot] NNNN G&G NNNN GY NNNN GY N<br>Month<br>——*—— _ Exports ————__ Imports 2018-May=100<br><!-- End of picture text -->
# **2.3 NTM data**

We use an updated version of a novel comprehensive NTM database for Indonesia<sup>3</sup> built by the World Bank. The data is hand collected through extensive regulatory checks. It has the most disaggregated NTM classification available, i.e., 3-digit MAST level, and the highest frequency available, monthly series. This classification is the most appropriate for policy analysis as it identifies individual measures introduced or modified by each agency. There are over 600 regulations spanning 13 government ministries and agencies. A total of over 60 3-digit NTMs are available in the data set, each with values coded between 0 and 1 to signify when they were in effect on the corresponding products, that is, the data varies at the month-product pair. The starting point of this database is data collection by the Economic Research Institute for ASEAN and East Asia (ERIA) in collaboration with UNCTAD. Then the regulations are traced forward and backward from 2015 and coded accordingly, using various other sources, primarily through government repositories. This data is the most up-to-date data on NTMs and at a high-level of frequency, both of which make the data most relevant for the aim of this paper.

As non-tariff measures usually serve a public policy objective, extensive evaluation needs to be made to identify those that may require reform. We focus on four measures in this analysis that previous research has found to be more restrictive to trade than necessary and requiring elimination or reform (see Cal`ı et al. (2022) and Cal`ı and Montfaucon (2021) based on data up to 2018). These measures are pre-shipment inspections (PSI, MAST code C1), mandatory certification with Indonesian product standards or _Standar Nasional Indonesia_ (SNI, MAST code B7), port of entry restrictions (PoE, MAST code C3), and import approvals (IA, MAST code B14). Additionally, three of these measures have been found to have higher tariff ad valorem equivalents compared to similar measures in other countries in ASEAN (Montfaucon et al., 2022).

> 3Cali et al. (2021), Cal`ı et al. (2022), and Cal`ı and Montfaucon (2021) also use an older version of this data set.

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<!-- Start of picture text --> 30%<br>25%<br>20%<br>15%<br>10%<br>5%<br>0%<br>BESCOS EFTASES ZFSVSL SAPSRLS SEESSTIISSMOURESTFS SS RSSSERSSTIISSMOUEEESEERSSTFSSSRPSZIIAZFZSMELBSS<br>2018 2019 2020 2021<br>-®=C1=Pre shipment Inspection<br><!-- End of picture text --> <!-- Start of picture text --> 7%<br>6%<br>5%<br>4%<br>3%<br>2%<br>1%<br>0% S USSESTSSISSTRSSSSTSTFB Z OSES OS TESASPSLBSS SASISSSR STERTSSIVSSTLERERTSSVSSSESIA ZHKSSESLSZIZAZGSZSB<br>2018 2019 2020 2021<br>-©=87- SNI (National Standards)<br><!-- End of picture text --> <!-- Start of picture text --> 25%<br>20%<br>15%<br>10%<br>5%<br>0%<br>BESTESTSSESTSSPSUSLSESESTSSPSLSLSSESTSSPSLSLSESESTSSAHOZASE TASS A HOZASE TASS AHOZAS ETE SL AHOZSPSUS<br>2018 2019 2020 2021<br>——C3-Port of entry restrictions<br><!-- End of picture text --> <!-- Start of picture text --> 45%<br>40%<br>35%<br>30%<br>25%<br>20%<br>15%<br>10%<br>5%<br>0% SUSSSESTSSISTFB Z OSES OS TESASPSLBSS SSSASI S R ERTSSIVSSTLERERTSSVSSSESTTRSSSSTSSIA ZHKSSESLSZIZAZGSZSB<br>2018 2019 2020 2021<br>-©814- Import Approval<br><!-- End of picture text -->
<!-- Start of picture text --> Overall export and import survival under external and domestic lockdowns<br>= a: External lockdown-Exports = b: Domestic lockdown-Exports<br>22<br>8100% ———No Lockown 8 100% ——No Lockown<br>6 75% — — Lockdown 6 75% — — Lockdown<br>$$<br>=50% = 50%<br>| =a<br>w w<br>oa 25% a 25%<br>x x —<br>E 0% ed eed ee ee E 0% Sd ed ee ee el<br>i Oo 2 4 6 8 10 12 14 16 18 20 uo oO 2 4 6 8 10 12 14 16 18 20<br>Survival time (months) Survival time (months)<br>= c: External lockdown-Imports = d: Domestic lockdown-Imports<br>33<br>s100% ——No Lockown s 100% ——No Lockown<br>5 75% — — Lockdown 5 75% — — Lockdown<br>oO oO<br>= 50% = 50%<br>aa<br>a25% a 25%<br># =— £ =<br>E 0% LTS SoS E 0% Clis tS<br>ui 0 2 4 6 8 10 12 14 16 18 20 i Oo 2 4 6 8 10 12 14 16 18 20<br>Survival time (months) Survival time (months)<br><!-- End of picture text -->
<!-- Start of picture text --> Sea and Air export and import survival under external and domestic lockdowns<br>= a: External lockdown-Exports = b: Domestic lockdown-Exports<br>33<br>a<br>Sy 75% —Sea aS 75% »—Sea<br>= 50% 5S 50%<br>a a<br>oa 25% oa 25%<br>22<br>E0% £ 0%<br>iri} 0 2 4 6 8 10 12 14 16 18 20 iri} 0 2 4 6 8 10 12 14 16 18 20<br>Survival time (months) Survival time (months)<br>= c: External lockdowns-Imports = d: Domestic lockdowns-Imports<br>3gs 100% Air 3sg 100% Air<br>2 °, — —Sea 2 ° — + —Sea<br>S 75% & 75%<br>ss<br>S50% e 50%<br>3E 25%0% 3E 25%0% .<br>iri] 0 2 4 6 8 10 12 14 16 18 20 Ww Oo 2 4 6 8 10 12 14 16 18 20<br>Survival time (months) Survival time (months)<br><!-- End of picture text -->
<!-- Start of picture text --> Import survival by exposure to NTMs under external and domestic lockdowns<br>a: PSI External lockdown b: PSI Domestic lockdown a: PoE External lockdown b: PoE Domestic lockdown<br>2! 00% 2100% 200% no bok 00% No Por<br>5B SB 5 — - -PoE SB — = -PoE<br>o oO oO ©<br>8 75% 975% 8 75% 975%<br>Qa a a Qa<br>s 3 ro rd<br>= 50% 550% 50% 550%<br>aaaa<br>=325% 325% 3= 25% 3225%<br>EE"E7£<br>i0% \i4 0% a0% = a0% =———_<br>0 4 8 12 16 20 0 4 8 12 16 20 0 4 8 12 16 20 0 4 8 12 16 20<br>Survival time (months) Survival time (months) Survival time (months) Survival time (months)<br>a: SNI External lockdown b: SNI Domestic lockdown a: IA External lockdown b: IA Domestic lockdown<br>2100% 100% No SNI = 100% NolA 2100%<br>5B BS — = -SNI 3B —-lA 3B<br>oO oO oO oO<br>§ 75% 875% S 75% 8 75%<br>aaaa<br>gg g g<br>5 50% 550% S 50% 5 50%<br>a” a]” |” |n<br>Zz Z a=] ZZ<br>2 25% 225% 2 25% 2 25%<br>ri}E 0% iE 0% : aE 0% . aE 0% :<br>0 4 8 12 16 20 0 4 8 #12 16 20 0 4 8 12 16 20 0 4 8 12 16 20<br>Survival time (months) Survival time (months) Survival time (months) Survival time (months)<br><!-- End of picture text -->
of the event-study approach is that it addresses concerns of lockdown anticipation. Since East Asia was the first epicenter of COVID-19, most countries started imposing restrictions earlier than the rest of the world, which could have triggered the reaction of exporters and importers in Indonesia in anticipation of the imposition of lockdowns in partner countries. The event-study also enables us to observe the reaction of international trade to lockdown policies at high frequency (months), which often changed depending on the spread/wave of the virus in a country. The event-study model for the effect of external lockdowns is specified as follows: where the dependent variable, _Yipgt_ , is a natural logarithm of bilateral export and import trade (values/quantities) between Indonesia ( _p_ ) and its trading partners ( _g_ ) across products ( _i_ ) and time in months ( _t_ ). Seasonality patterns are controlled for by month-time fixed effects ( _αt_ ) and product-month fixed effects ( _αit_ ). _αt_ captures any secular variation in exports and imports during a month while _αit_ controls for seasonality and inventory stocking patterns associated with high frequency data such as monthly (Bricongne et al., 2012). _αig_ is the product-partner fixed effects that captures any product and partner characteristics that are correlated with lockdowns and trade flows. In general, the three fixed-effects address the problem of endogeneity, particularly unobserved heterogeneity arising from characteristics of partner countries, product characteristics and seasonality of trade. _βj_ is the coefficient indicating the magnitude of the effect of the lockdown on an export or import trade outcome _j_ months before and after it was implemented. _tdiffg_ is the number of months until and after the lockdown was imposed in a partner country. The period _j_ = _−_ 1 is a month prior to the lockdown. It is used as the reference category when interpreting coefficients for other periods.

14
All periods _j < −_ 1 are utilized as leads to show the anticipatory effect of the lockdown after the start of the pandemic. Countries imposed lockdowns at different times in our sample following the first case of the virus in China. Hence, there is a possibility of anticipatory effects and failure to account for these effects can understate the effect of the lockdown policies (Majune & Addisu, 2021). All periods _j > −_ 1 are considered as lags. Although the maximum period of our data is 40 months, we allow our leads to run up to 24 months since some countries delayed imposing lockdown measures (not all countries imposed lockdowns in January 2020, which could have made leads to be 20 months). On the other hand, the maximum lag period is 19 months since the earliest lockdown event for trading partners of Indonesia was in January 2020. _γipt_ is included to control for the effect of domestic lockdowns on the performance of trade. It contains dummies for the months the lockdown was active in Indonesia and zero for the months the lockdown was absent. _ε_ is the error term. _ipgt_ The event-study model for the domestic lockdown is as follows: Definitions of most terms in Equation 2 resemble those of Equation 1 except for _tdiffp_ which is a number of months until and after the lockdown was imposed in Indonesia. It is a binary variable with one indicating months when Indonesia strictly imposed restrictions (from January 2020) and zero otherwise. Therefore, the number of months until and after the lockdown was imposed is uniform across observations. The maximum period of lags, in this case, is 19 months (February 2020-August 2021) and 20 months for the lead period (May 2018-December 2019). _γigt_ is included in Equation 2 to control for the effect of external lockdowns on export and import flows and is coded as 1 for the months when lockdowns were active in Indonesia’s partners and zero for the months when lockdowns were absent.

Event-study coefficients of monthly dummies before and after lockdown policies were either imposed by Indonesia or its trading partners from Equation 2 and Equation 1, re15
spectively, are plotted in the results section. The coefficients are interpreted as percentage changes having been transformed into elasticities. Coefficients _βj_ were transformed into elasticities as follows _βj_ =(exp _βj_ -1)*100 (see Ullah et al. (2021) and Clarke and Tapia-Schythe (2021) for a guide on conducting event-study analysis in Stata). All regressions are done in sub-samples of imports and exports for: overall trade, type of product, type of transportation and products affected by specific non-tariff measures. We later conduct additional analysis to establish the sensitivity of our results to the type of lockdown policy and the effect of lockdowns on export and import prices.

# **4 Results**

## **4.1 Imports**

### **Overall imports**

We do not find that domestic lockdown policies affected import values and quantities (Figure 7 a) except for the second month following their implementation. Values declined by 171% while quantities slumped by 102% two months after Indonesia put in place lockdown measures. All other changes in import values and quantities cannot be attributed to domestic lockdowns as the coefficients are not statistically significant. Part b of Figure 7 shows that due to external lockdowns, imports dropped persistently, by 11% a month into the lockdown, and continued to deteriorate, reaching a drop of 30% in the twelfth month and 37% by the nineteenth month. Similarly, the quantity of imports fell by 11% a month into external lockdowns, followed by a 36% drop in the twelfth month and 43% decline by the nineteenth month. The average monthly drops in import quantities and values upon imposition of external lockdowns were 32% and 26%, respectively.

The results suggest that containment measures by Indonesia’s trading partners had a larger effect on the country’s imports than its own COVID-19 restrictions (given that all the 16
<!-- Start of picture text --> Effect of domestic lockdown on imports<br>Import Value<br>2 2000<br>$&8 1000<br>is}<br>z 0<br>=§ 5000-1000<br>17 -15 -13 -11 9 7 5S -3 41 1 3 5 7 9 1°13 15 17<br>Months Relative to Lockdown<br>Import Quantity<br>© 2000<br>S8 1000<br>sy<br>F -10000<br>= 5000<br>7 -15 13-11-99 FT 5S 3 A 1 3 5 7 9 1° =13° 15 17<br>Months Relative to Lockdown<br>* Point Estimate —— 95% Cl<br><!-- End of picture text --> <!-- Start of picture text --> Effect of external lockdowns on imports<br>Import Value<br>@ 200<br>s3 100<br>oo<br>z petesiuueee wwawaass<br>258 -100-200 }<br>-22 -20 -18 -16 -14 -12 -10 8 6 4 2 0 2 4 6 8 10 12 14 16 18 20<br>Months Relative to Lockdown<br>Import Quantity<br>@ 200<br>gEa 100<br>oo<br>5 -100 peeeaturers WHEESEETSTTTT T TS<br>&§ -200 }<br>-22 -20 -18 -16 -14 -12 -10 8 6 4 2 0 2 4 6 8 10 12 14 16 18 20<br>Months Relative to Lockdown<br>* Point Estimate —— 95% Cl<br><!-- End of picture text -->
imports also contracted from the fourth month, and lasted up to the tenth month, with a monthly average of 23%. One of the underlying factors may have been that the cancellation of passenger flights due to travel bans limited the availability of air cargo, resulting in increases in the price of air cargo (OECD, 2020). In subsection 4.3, we formally test which specific lockdown measures were the driver in the effects of imports and exports.

We find that Indonesia’s lockdown policies did not significantly affect values and quantities of imports by sea cargo (Figure 9 part a). A month into the external lockdowns, however, import value declined by 6% (part b). This was followed by a 12% and 16% decline in the fourth and sixth months, respectively. The value of sea imports seem to have since recovered but these changes are not attributable to the external lockdowns. The lower panel shows that import quantities significantly declined in the first 11 months of the external lockdown by a monthly average of 22%. The coefficients are not statistically significant for the period that follows.

In general, we do not find evidence that domestic lockdown policies by Indonesia affected either the country’s sea or air imports, but external lockdowns affected air imports more negatively than sea imports. This may be due to restrictions on international travel, which mainly take place by air, and were prevalent.

Overall, domestic lockdowns mainly affected Indonesia’s intermediate goods affected by NTMs. External lockdowns mainly led to the decline of imports.

# **Intermediate imports exposed to NTMs**

We focus this section on intermediate goods imports, as these play a critical role in the access of input varieties. Imported inputs raise productivity, through greater complementarity of inputs and technology/quality transfer (Bas & Strauss-Kahn, 2014). While lockdown policies may have limited imports generally, non-tariff measures on intermediate products may have further worsened the impact of the COVID-19 shock on goods subject to such measures. For instance, limits on mobility of people may have affected processes 18
<!-- Start of picture text --> Effect of domestic lockdown on air imports<br>=5&&= 2000 30001000 Import Value<br>g 0<br>a 1000<br>44° 42 40 8 6 4 2 0 2 4 6 8 10<br>Months Relative to Lockdown<br>Import Quantity<br>&»2= 20003000<br>S5 1000<br>3 0<br>* 4000<br>-14 12 -10 8 6 Months4 Relative2 to Lockdowni) 2 4 6 8 10<br>© Point Estimate ——+ 95% Cl<br><!-- End of picture text --> <!-- Start of picture text --> Effect of domestic lockdown on sea imports<br>Import Value<br>2 500<br>& 0<br>&= -500<br>&8 -1000<br>-1500<br>17 -15 -13 -11 9 7 5 3.) -1 1 3 5 7 9 11°0613°«15 «17<br>Months Relative to Lockdown<br>Import Quantity<br>2 500<br>&=<br>&8 -1000-500<br>-1500<br>7 15 13-17 9 FT 5 3 A 1 3 5 7 9 1°0°13°0«15 17<br>Months Relative to Lockdown<br><!-- End of picture text --> <!-- Start of picture text --> Effect of external lockdowns on air imports<br>400 Import Value<br>2 8 o048 &<br>z5 4<br>8 200<br>& -400<br>19-47-15 13-11 9 7 5 3 4 1 3°55 7 9 1 13 15 17 19<br>Months Relative to Lockdown<br>Import Quantity<br>>25 400200 z :<br>222 0<br>8 200<br>= 400<br>19 -17 -15 13 -11 9 7 Months5 3 Relative-14 to1 Lockdown3.5 7 9 1 #13 15 17 «19<br>© Point Estimate ——1 95% Cl<br><!-- End of picture text --> <!-- Start of picture text --> Effect of external lockdowns on sea imports<br>Import Value<br>200<br>8<br>s 100<br>So=<br>85 ~100<br>& -200<br>-21 -19 17 -15 13 -11 9 7 5 3 1.1 3 5 7 9 11 13 15 17 19<br>Months Relative to Lockdown<br>Import Quantity<br>°2200<br>Soo<br>z8 -100 t Wess<br>& -200<br>-21 -19 17 -15 13 -11 9 7 5 3 1.1 3 5 7 9 11 13 15 17 19<br>Months Relative to Lockdown<br><!-- End of picture text -->
<!-- Start of picture text --> Effect of domestic lockdown on intermediate imports exposed to NTMs<br>Import Value<br>2 1000<br>25 -1000¢5 0. e se é fb tay<br>&8 -2000-3000 ry<br>1 9 7 5 Months-3 Relative-1 to1Lockdown3 5 7 9 an<br>1000 Import Quantity<br>Fio29 © 3<br>= 1000 ey eee<br>5 -2000<br>-3000<br>11 9 T 5 Months-3 Relative-1 to1Lockdown3 5 7 9 aa<br><!-- End of picture text --> <!-- Start of picture text --> Effect of external lockdowns on intermediate imports exposed to NTMs<br>Import Value<br>Zo5g2224020 beet? $ ,<br>@8 4060<br>14 12 -10 8 6 Months4 Relative2 to LockdownoO 2 4 6 8 10<br>40 Import Quantity<br>ZoOo=2 2020 betett?<br>5 -40<br>60<br>-14 12 -10 8 6 Months4 Relative2 to LockdownoO 2 4 6 8 10<br><!-- End of picture text -->
<!-- Start of picture text --> Effect of domestic lockdown on imports<br>Import Value<br>22 60008000<br>&g 40002000 t t t t t<br>eo<br>-2000<br>A745 13-1109 7 5 3 4°43 °5 7 9 1 13 15 47<br>Months Relative to Lockdown<br>© Point Estimate —+ 95% Cl<br>Import Quantity<br>22 60008000<br>2& 4000<br>= 2000<br>-2000<br>A745 13-409 7 5 3 4 4 3°05 7 9 1 13 15 17<br>Months Relative to Lockdown<br>© Point Estimate 95% Cl<br><!-- End of picture text --> <!-- Start of picture text --> Effect of external lockdowns on imports<br>Import Value<br>g2 100<br>53 -1000<br>é<br>-200<br>2119-47 15-43-41 -9 7-5 3-4 1 3°55 7 9 11 13:15 17 19<br>Months Relative to Lockdown<br>© Point Estimate + 95% Cl<br>Import Quantity<br>22 100<br>2& 06 Fy<br>= -100<br>-200<br>2119-47 15-43-19 7 5 3-4 1 3°55 7 9 11 13:15 17 19<br>Months Relative to Lockdown<br>® Point Estimate + 95% Cl<br><!-- End of picture text -->
eleventh months of the lockdown, and we do not find any evidence that SNI and import approvals significantly affected intermediate imports during the external lockdown. This suggests that port-related measures were more relevant in the supply side of imports.

Figure 13 shows that products which were not exposed to port of entry restrictions were not significantly affected by the domestic lockdown. There is evidence that absence of PSI and SNI, though sporadic, positively affected intermediate imports during the domestic lockdown. For instance, products which were not exposed to SNI grew by 183% in the first month and later by an average of 319% between the seventh and tenth months of the domestic lockdown. Products which were not exposed to import approval significantly declined during the first three months of the domestic lockdown, a much shorter period than for products subject to import approvals.

Consistent with the overall impact of external lockdowns on imports, products which were not exposed to import approvals significantly declined for the entire period of external lockdowns, by a monthly average of 31%. Those that were not exposed to PoE and SNI also declined significantly during the external lockdown except for the second month: the monthly average (third-eleventh month) drop for imports that were not subject to PoE and SNI was 31% and 34%, respectively. Imports which were not exposed to PSI contracted in the first and fourth months by 11% and 23%, respectively.

These results suggest that while overall imports were not severely affected by domestic lockdowns by Indonesia, NTMs exacerbated demand-side factors on imports. This was especially the case for imports subject to product certification and approval procedures (i.e., import approval and certification of SNI), which require more physical presence. For instance, compliance with national standards (SNI) is mandatory in Indonesia for thousands of goods, including also domestically produced ones. As certification requires a visit to the factory premises by an Indonesian certifying agency, the cost is considerably higher for imported goods and travel was especially difficult during lockdowns. Only a few agencies, mandated by the Ministry of Industry, can certify a specific product, so producers in need 22
<!-- Start of picture text --> Effects of external and domestic lockdowns on intermediate imports that were exposed to NTMs<br><!-- End of picture text -->

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# Effects of external and domestic lockdowns on intermediate imports that were not exposed to NTMs

|)<br>Non-PSI-External<br>@<br>5-100|)<br>Non-PSI-Domestic <br>© 1000<br>§-1000||5<br>Non-PoE-External<br>S<br>100<br>8-100|
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takes place at the port before products are exported to Indonesia), thus making lockdowns in the exporting countries more relevant.

# **4.2 Exports**

## **Overall exports**

The effect of domestic and external lockdown policies on Indonesia’s export trade is presented in Figure 14. In general, exports were more affected by external lockdowns than the domestic lockdown policy, but recovered after the eighth month. As shown in the upper panel of part a, domestic lockdowns did not have a significant effect on export values except in the fifteenth month (a 64% growth). The lower panel depicts several instances where the domestic lockdown significantly affected export quantities: they grew by 244% in the third month and by a monthly average of 82% between the twelfth and fifteenth months. The discrepancy between values and quantities signifies the price/exchange rate effect on exports.

Part b of Figure 14 shows that export values and quantities significantly declined by 7.5% and 5.7% between the third and eighth months respectively, but recovered from a contraction after the first eight months of the implementation of lockdown policies in destination markets. The initial drop in exports is consistent with Pimenta et al. (2021), who find that lockdown stringency in destination markets reduced exports at the onset of COVID-19 for firms in Portugal. Exports later grew by 9% (for values) and 11% (for quantities) between the tenth and eighteenth months, suggesting some level of adaptation.

## **Effect of Lockdowns on Sea and Air Exports**

The value of air exports initially improved by a monthly average of 241% in the first five months of the domestic lockdown (Figure 15). This was followed by periods of contraction, particularly after the thirteenth month, when coefficients were statistically significant, with a monthly average of -240%. The effect of the domestic lockdown was not statistically 25
<!-- Start of picture text --> Effect of domestic lockdown on exports<br>Export Value<br>&8 500<br>iS)=8-000<br>=-1000<br>20-18 16-14-12 40 8 6 4 2 0 2 4 6 8 10 12 14 16 18 20<br>Months Relative to Lockdown<br>Export Quantity<br>&8 500<br>& °<br>8-500<br>*“4000<br>-20 -18 -16 -14 -12 10 8 6 4 2 0 2 4 6 8 10 12 14 16 18 20<br>Months Relative to Lockdown<br><!-- End of picture text --> <!-- Start of picture text --> Effect of external lockdowns on exports<br>Export Value<br>2 203 A res333<br>FS5z20 pease<br>8 40<br>a -60<br>24 22-20-18 16-14-12 -10 8 6 4 2 0.2 4 6 8 10 12 14 16 18<br>Months Relative to Lockdown<br>Export Quantity<br>532 20204 ppetet z z BagsPeres Eststs z PeEeEEES!<br>8 -40<br>& 604}<br>-24 -22 -20 -18 -16 -14 -12 -10 -8 6 4 2 0 2 4 6 8 10 12 14 16 18<br>Months Relative to Lockdown<br><!-- End of picture text -->
<!-- Start of picture text --> Effect of domestic lockdown on air exports<br>Export Value Value<br>g 500 ‘ F<br>233 5 8000000 ¢ } t<br>& -1000<br>-20 18 16 -14 12-10 8 6 4.2 0 2 4 6 8 10 12 14 16 18<br>Months Relative to Lockdown<br>Export Quantity<br>@ 500<br>2 3<br>©is}is} z 855 -500anan '<br>& -4000<br>-20 -18 -16 -14 -12 -10 8 6 4 2 0 2 4 6 8 10 12 14 16 18<br>Months Relative to Lockdown<br>© Point Estimate ——+ 95% Cl<br><!-- End of picture text --> <!-- Start of picture text --> Effect of external lockdowns on air exports<br>Export Value Value<br>a 100.<br>55z=g55z=g5z=g5=g550*4 50*4 tt ttt} } } t t f f {<br>-24 -22 -20 -18 -16 -14 12-10 -8 6 4 2 0 2 4 6 8 10 12 14 16 18<br>Months Relative to Lockdown<br>Export Quantity<br>2 100<br>2<br>_ = eagdttththt<br>58 0 FY<br>* 60 t<br>-24 -22 -20 -18 -16 -14 -12 10 8 6 -4 2 0 2 4 6 8 10 12 14 16 18<br>Months Relative to Lockdown<br>e Point Estimate +1 95% Cl<br><!-- End of picture text --> <!-- Start of picture text --> Effect of domestic lockdown on air exports Effect of external lockdowns on air exports<br>Export Value Value Export Value Value<br>g 500 ‘ F a 100.<br>233 0 } } } t t f f {<br>5 8000000 ¢ } t g55 *44 tt ttt}<br>& -1000 55z=g55z=g5z=g5=g550*4<br>-20 18 16 -14 12-10 8 6 4.2 0 2 4 6 8 10 12 14 16 18 -24 -22 -20 -18 -16 -14 12-10 -8 6 4 2 0 2 4 6 8 10 12 14 16 18<br>Months Relative to Lockdown Months Relative to Lockdown<br>Export Quantity Export Quantity<br>@ 500 2 100<br>2 3 2<br>©is}is} z 855 -500anan ' _ = 858 0 FY eagdttththt<br>& -4000 * 60 t<br>-20 -18 -16 -14 -12 -10 8 6 4 2 0 2 4 6 8 10 12 14 16 18 -24 -22 -20 -18 -16 -14 -12 10 8 6 -4 2 0 2 4 6 8 10 12 14 16 18<br>Months Relative to Lockdown Months Relative to Lockdown<br>© Point Estimate ——+ 95% Cl e Point Estimate +1 95% Cl<br>Effect of domestic domestic lockdown on sea exports Effect of external lockdowns on sea exports<br>Export Value Export Value<br>2 1000 40<br>2 500 Fy<br>& 0 5§§ 2044 eget eee tte<br>% -500 : E<br>5 -1000 E 20<br>-1500, -40<br>-20 18 16 -14 -12 10 8 6 4.2 0 2 4 6 8 10 12 14 16 18 -24 -22 -20 18 16 14-12-10 8 6 4 2 0 2 4 6 8 10 12 14 16 18<br>Months Relative to Lockdown Months Relative to Lockdown<br>1000 Export Quantity Quantity 40 Export Quantity Quantity<br>22 500 F)22 33<br>Booo 3”oo558588 0 geeet teas<br>§5§5§§ -1000-500-500 558588 200 tyesbpeeget iessssste®bpeeget iessssste®et iessssste® iessssste®<br>* 4500 * 40<br>-20 -18 -16 -14 -12 -10 8 6 4 2 0 2 4 6 8 10 12 14 16 18 -24 -22 -20 -18 -16 -14 -12 -10 -8 6 4 2 0 2 4 6 8 10 12 14 16 18<br>Months Relative to Lockdown Months Relative to Lockdown<br>© Point Estimate ——+ 95% Cl © Point Estimate + 95% Cl<br><!-- End of picture text --> <!-- Start of picture text --> Effect of domestic domestic lockdown on sea exports<br>Export Value<br>2 1000<br>2 500<br>& 0<br>% -500<br>5 -1000<br>-1500,<br>-20 18 16 -14 -12 10 8 6 4.2 0 2 4 6 8 10 12 14 16 18<br>Months Relative to Lockdown<br>1000 Export Quantity Quantity<br>222 500<br>Booo<br>§5§5§§ -1000-500-500<br>* 4500<br>-20 -18 -16 -14 -12 -10 8 6 4 2 0 2 4 6 8 10 12 14 16 18<br>Months Relative to Lockdown<br>© Point Estimate ——+ 95% Cl<br><!-- End of picture text --> <!-- Start of picture text --> Effect of external lockdowns on sea exports<br>Export Value<br>40<br>Fy<br>5§§ 2044 eget eee tte<br>: E<br>E 20<br>-40<br>-24 -22 -20 18 16 14-12-10 8 6 4 2 0 2 4 6 8 10 12 14 16 18<br>Months Relative to Lockdown<br>40 Export Quantity Quantity<br>F)22 33<br>3”oo558588 200 tyesbpeeget iessssste®bpeeget iessssste®et iessssste® iessssste® geeet teas<br>* 40<br>-24 -22 -20 -18 -16 -14 -12 -10 -8 6 4 2 0 2 4 6 8 10 12 14 16 18<br>Months Relative to Lockdown<br>© Point Estimate + 95% Cl<br><!-- End of picture text -->
test the sensitivity of our results to the different types of measures put in place by Indonesia’s trade partners. We assume that different measures adequately capture the severity of the impact of the lockdown restrictions on trade flows as opposed to a compound indicator. To do this, we test the effect of workplace closure, stay-at-home requirements, restrictions on internal movement, and international travel controls on Indonesia’s bilateral export and import values. Each indicator is a dummy variable for the months that it was active in a partner country. We assess the average effect of lockdown indicators for all the months that they were active (overall) and at intervals of 1-4 months, 5-8 months, 9-12 months, 13-16 months and 17-19 months. This gives a glimpse of their effects over time.

The top panel of Table 1 indicates that the closure of workplaces had the most severe effect on exports: the overall effect was -3.6%, which is the average over the study period. Since this is the closure of workplaces in Indonesia’s trading partners, it suggests that a slump in demand in partner countries - potentially from unemployment - was the cause for low demand of products from Indonesia. The negative effect was acute in the first four months and from the 17-19<sup>th</sup> months. Stay-at-home requirements by Indonesia’s partners also reduced Indonesia’s exports: the average monthly drop was 1.6%, mainly driven by the first 12 months when the measures were in place. The overall effect of restrictions on internal movements and international travel on exports is positive although they were negative in the first eight months of trading.

The lower panel shows that the overall effect of all lockdown measures on imports was negative, signaling supply-side disruptions. Restrictions on international travel by trading partners by far had the largest negative impact on Indonesia’s imports, with an overall effect of -23%, and continued to worsen over time. Cancellation of passenger flights linked to travel restriction limited the availability of air cargo during the pandemic (OECD, 2020), and this result is consistent with imports by air being more affected by external lockdowns compared to sea cargo. The overall effects of workplace closure and stay-at-home requirements are -9.6% and -8.8%, respectively. Furthermore, the coefficients are large for the first 12 months, 28
implying that disruptions in production reduced imports from countries which had these measures early on during the pandemic.

**Table 1: Average event-study coefficients for Indonesia’s exports and imports of by external lockdown indicators**

|||**Exports**|||
|---|---|---|---|---|
|**Period**|**Workplace**|**Stay-at-home**|**Internal movement**|**International travel**|
|Overall|-5.613|-1.872|3.889|2.697|
|1-4 months|-5.688|-5.778|-5.142|-7.227|
|5-8 months|-4.379|-4.872||-6.794|
|9-12 months|-4.180|-4.087|8.793|6.267|
|13-16 months|-5.015|7.250|8.016|10.617|
|17-19 months|-8.805|x|x|10.624|
|||**Imports**|||
|Overall|-9.974|-8.683|-2.812|-24.005|
|1-4 months|-18.906|-21.535|-16.768|-9.567|
|5-8 months|-22.226|-18.412|-18.033|-20.651|
|9-12 months|-13.876|-13.134|-11.706|-25.121|
|13-16 months|-8.222|-8.688|9.039|-28.598|
|17-19 months|13.360|18.353|23.409|-36.088|

Note: All coefficients are significant at 10% level. x indicates that all coefficients are not significant in a specific period. Source: Authors’ compilation

# **Import and export prices**

The second mechanism we test entails establishing the effects of domestic and external lockdowns on export and import prices. This will further attempt to show differences in quantities and values that some results may have shown. Prices are calculated as the ratio of value to quantity at the product-partner-month level for both exports and imports. As before, coefficients are transformed into elasticities.

Effects of the domestic lockdowns on import prices are shown in the fourth column of Table A2 (only coefficients for lags are presented due to space constraint). Import prices significantly declined from the third month to the eighteenth month by a monthly average of 316% due to Indonesia’s lockdown policies. As we did not find that domestic lockdowns 29
**Table 2: Average event-study coefficients for Indonesia’s exports and imports of by domestic lockdown indicators**

|||**Exports**|||
|---|---|---|---|---|
|**Period**|**Workplace**|**Stay-at-home**|**Internal movement**|**International travel**|
|Overall|84.930|143.418|x|11.173|
|1-4 months|x|189.100|x|x|
|5-8 months|x|145.008|x|x|
|9-12 months|x|96.147|x|x|
|13-16 months|84.930|x|x|11.173|
|17th month|x|x|x|x|
|||**Imports**|||
|Overall|-0.577|-15.350|-0.494|-0.480|
|1-4 months|-21.042|-31.525|-20.965|-20.965|
|5-8 months|-10.889|-18.486|-10.751|-10.750|
|9-12 months|4.524|-8.269|4.561|4.643|
|13-16 months|13.407|-3.121|13.501|13.484|
|17th month|11.112|x|11.184|11.189|

Note: All coefficients are significant at 10% level. x indicates that all coefficients are not significant in a specific period. Source: Authors’ compilation significantly affected import trade except for intermediate goods imports subject to NTMs, this may signal that lower demand for imports may have led to lower prices. The external lockdown led to an increase in import prices, specifically between the third and tenth months when prices significantly increased by a monthly average of 6.2%. This suggests that lower supply from the origin countries due to lockdowns may have led to higher prices. We find no evidence of external lockdowns affecting import prices after the tenth month.

As displayed in Table A2, the third column shows that export prices contracted immediately after Indonesia imposed lockdown measures and this effect consistently lasted for the first 12 months of the lockdown. The effect started with a 392% decline in the first month and consistently remained negative until the twelfth month (the average monthly contraction in export prices between the first and twelfth months was 249%). Export prices also shrunk in the fourteenth month by 61%. The second column shows that export prices significantly declined by an average of 2.3% in the fourth and fifth months following external lockdowns.

30
This was followed by a 2.2% drop in the seventh month and later by a monthly average of -3.8% between the tenth and sixteenth months. In general, export prices decreased more due to domestic than external lockdowns in the first 12 months, going by the magnitude of the coefficient and starting period of the effect. Nonetheless, the effect of external lockdowns on export prices was long-lived as shown by the 4% decline in the nineteenth month. The decrease in export prices due to external lockdowns may also signal that lower demand may have led to lower price setting by Indonesian exporters.

# **5 Conclusion**

This study sought to analyze how Indonesia’s international trade was affected by its own lockdown policies (domestic) and those of its trading partners (external) in response to COVID-19, differentiating between sea and airports as well as imports affected by non-tariff measures (NTMs). We employed survival analysis and event-study approaches on monthlyproduct-country export and import data ranging from May 2018 to August 2021.

Results from the survival analysis show that the failure rate of exports and imports increased during both domestic and external lockdowns, but sea exports had higher survival than air exports, while air had higher import survival rates. Imports subject to NTMs also had lower survival rates during both domestic and external lockdowns, especially those subject to port of entry restrictions and import approvals. Event-study results show that overall, imports were more negatively affected by lockdown policies than exports, which recovered during the sample period, unlike imports. The decline in imports was mainly attributed to lockdown policies by Indonesia’s trade partners, which affected all imports. The impact of external lockdowns was more pronounced and persistent for imports entering Indonesia by air, while imports by sea recovered relatively faster. We find no impact of Indonesia’s lockdown policies on imports, except for negatively affecting intermediate imports subject to non-tariff measures.

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While external lockdowns also had a larger impact on exports than domestic policies, exports recovered past the eighth month of both domestic and external lockdowns. Domestic lockdowns had a mixed and large impact on air exports, but not sea imports, while external lockdowns affected sea and air exports relatively evenly. The result implies that supply factors (specifically restrictions on international travel, workplace closures, stay-at-home orders and internal movement restrictions, in that order) had a larger role on the impact on imports than demand factors related to the COVID-19 shock. However NTMs exacerbated the impact of demand factors for imports. Meanwhile, demand factors (specifically workplace closures and stay-at-home orders) in the partner countries were responsible for the slump in exports.

– Enhanced trade facilitation to keep goods moving as smoothly as possible including identifying unnecessary non-tariff measures, customs procedures with limited human intervention such as integrated risk management, and improving processes on necessary non-tariff measures of specific goods, would ensure fewer disruptions from shocks in a globally integrated world. These would also ensure that port inspections and procedures that necessitate port of entry restrictions are conducted more efficiently and avoid backlogs and port delays.

In this regard, Indonesia has removed several regulations on measures such as preshipment inspections,<sup>4</sup> to only apply to a limited number of products; and introduced regulations to improve risk management between customs and the Ministry of Trade.<sup>5</sup> Nevertheless, procedures on import approval and port of entry requirements still affect a large share of imports, and certification for national standards (SNI), while affecting a smaller share of goods, remains quite costly and may warrant further reform. These procedures also require physical inspections of goods and testing and certification and their processes could be improved.

> 4In 2021, Indonesia revoked over 20 regulations on PSI

> 5In 2021, Indonesia enacted a law to improve information sharing, including procedures that would enable traders with priority status with customs to also be recognized by Ministry of Trade.

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