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14 October 2022 
(22-7750) Page: 1/22 
Committee on Trade Facilitation  Original: English  
 
 
MEASURING TRADE FACILITATION: EVIDENCE FROM INDIA1 
COMMUNICATION FROM INDIA  
The following communication, dated 4 October  2022, is being circulated at the request of the 
delegation of India for Members' information.  
 
_______________  
 
1  SUMMARY  
1.1.  In this paper the authors use the trigger presented by the World Trade Organization 's (WTO 's) 
Trade Facilitation Agreement (TFA) to undertak e a comprehensive review of various publicly 
available studies for India relating to performance measurement of the ecosystem that handles the 
cross-border movement of goods, focusing on the period since 2015.  
1.2.  The paper summarizes the results of six key co mposite performance indicators —namely, 
(1) the Organisation for Economic Co -operation and Development 's (OECD 's) trade facilitation 
indicators (TFIs); (2) the World Bank 's Ease of Doing Business (EODB) Index; (3) the World Bank 's 
Logistics Performance Index (LPI); (4) the World Economic Forum 's (WEF 's) Global Competitiveness 
Index (GCI); (5) the World Bank 's World Governance Indicators (WGIs); and (6) the United Nations ' 
Global Survey on Trade Facilitation and Paperless Trade Implementation (GSTF -PTI). This paper, by 
examining these composite survey -based indicators and the intertemporal trends they exhibit for 
India, reveals that they have not been moving in agreement with each other and that some of the 
trends are evidently counterintuitive . A comparison between delineated subindicators of select 
composite indicators sometimes indicates surprising trends.  
1.3.  Import cargo release times (a performance measurement prescribed by the TFA) for the largest 
containerized port in the country, the Jawaha rlal Nehru Port Trust (JNPT), have been extracted from 
various studies that have relied on the data from the customs automation system; the container 
tracking system, which employs radio -frequency identification (RFID); and survey -based studies, 
including the Trading Across Borders (TAB) component of the World Bank 's EODB Index. These 
import cargo release time studies present a consistent trend of improvement since 2017.  
1.4.  The paper, therefore, highlights the greater robustness of cargo release time trends, b ased 
particularly on technology -enabled data -driven studies as a more meaningful metric for 
measurement of performance of border management agencies and practices vis -à-vis survey or 
perception -based indicators representing "enablers " of trade facilitation . 
2  INTRODUCTION  
2.1.  The World Trade Organization (WTO) Trade Facilitation Agreement (TFA) has placed trade 
facilitation initiatives high on the agenda of the governments of the member economies, including 
India, for meeting the commitments made thereunder. It has also provided a high degree of 
coherence to various components of trade facilitation, as a package through a whole -government 
approach, encouraging a plethora of efforts at performance measurement by different agencies.  
 
 1 Authors: Vijay Singh Chauhan Commissioner of Customs at the Customs Authority for Advance Rulings, 
New Delhi, and Sruti Vijayakumar, Deputy Commissioner of Customs at the Jawaharlal Nehru Custom House, 
Nhava Sheva; 17  May 2021.  This paper was originally published by Carnegie India. The link to the or iginal 
document: https://carnegieindia.org/2021/05/17/measuring -trade -facilitation -evidence -from-india-pub-84456 . G/TFA/W/84  
 
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  2.2.  The TFA entered i nto force on 22 February 2017. This new Multilateral Agreement on Trade 
Facilitation was first raised during the Ninth WTO Ministerial Conference, held in Bali in 
December  2013; subsequently, an amendment protocol to bring the TFA into the WTO's legal 
framework was adopted in November 2014 and members were invited by WTO to complete their 
national process for ratification. India ratified the TFA in April 2016. The efforts toward simplifying 
procedures and processes associated with cross -border movement of g oods and improving ease of 
doing business (EODB) have thus been underway for a longer period, both in India and the world 
over. Therefore, the coming into force of the TFA is viewed as a major landmark, one that has 
provided added impetus and enhanced focu s to the facilitation measures, requiring compliance with 
specific provisions of the TFA in a time -bound manner.  
2.3.  The Government of India has constituted the National Committee on Trade Facilitation (NCTF), 
chaired by the cabinet secretary, the senior -most civil servant, to ensure domestic coordination and 
to drive forward and monitor India's compliance with the provisions of the TFA. The NCTF has put 
together the National Trade Facilitation Action Plan 2017 -2020 (NTFAP), which identifies the lead 
agency res ponsible for each of the provisions of the TFA and prescribes timelines under three broad 
categories: short -term (zero to six months), medium -term (six to eighteen months), and long -term 
(eighteen to thirty -six months).2 
2.4.  The NTFAP, "in order to identify t he key performance indicators and to achieve the objectives 
of TFA," referred to four "global key performance indicators or benchmarks that will provide 
aspirational value" to the government measures.3 These four indicators are (1) the Organisation for 
Economic Co -operation and Development (OECD) trade facilitation indicator's (TFls); (2) World Bank 
Trading Across Borders (TAB), which is a component of the World Bank's EODB Index; (3) the World 
Bank's Logistics Performance Index (LPI); and (4) the World Ec onomic Forum's (WEF) Global 
Competitive Index (GCl).4 The specific performance indicator included in the TFA to measure trade 
facilitation relates to measuring and publishing the average release time of goods, including through 
the conduct of a release ti me study, which "encourages members to measure and publish their 
average release time of goods periodically and in a consistent manner, using tools such as, inter alia, 
the Time Release Study of the World Customs Organization."5 
2.5.  It has been more than three years since the TFA came into force. The WTO has been monitoring 
the "state of play of the TFA" on a daily basis, providing the implementation status for the various 
member countries.6 In addition, details of various performance indicators that are being deployed 
by different agencies and organizations and cargo release times for specific customs formations 
reported by various agencies are available to the public.  
2.6.  In this paper we have undertaken a comprehensive review of the publicly available data on 
trade facilitation and key performance indicators pertaining to India since 2010, or from the time 
they are available  – whichever is later. Toward this objective, we have gone beyond the four key 
performance indicators identified in the NTFAP, since tho se indicators are also found to provide 
similar assessment of the economy in respect to select parameters.  
2.7.  As regards the release time data, we note that besides the World Customs Organization 's 
(WCO 's) Time Release Study (TRS), there are certain other ind icators that also seek to capture data, 
broadly corresponding to release time, often in addition to certain other performance indicators. For 
example, the World Bank 's EODB Index includes the TAB subindicator, which captures respondents ' 
perception about r elease time and cost for import and export cargo, at specified customs formations. 
In the case of India, the two formations that are captured by TAB are the Jawaharlal Nehru Custom 
House (JNCH), catering to the Jawaharlal Nehru Port Trust (JNPT) —the larges t containerized port in 
the country, located in the Raigad District, near Mumbai, and the inland container depot (ICD) at 
Tughlakabad in Delhi —a major customs dry port. The studies relating to cargo release time are often 
 
2 Central Board of  Indirect Taxes and Customs,  National  Trade  Facilitation  Action  Plan 2017–2020 
(Revised  up to August,  2019)  (New Delhi: Central Board of Indirect Taxes and Customs, 
2019),  http://cbic.gov.in/resources/htdocs -cbec/implmntin -trade -facilitation/ntf -action -plan-Revised -upto-
August2019.pdf . 
3 Central Board of Indirect Taxes and Customs,  National  Trade  Facilitation  Action  Plan 2017–2020. 
4 For the World Economic Forum's  Global  Competitiveness  Reports , see World Economic Forum, 
"Reports," web page, n.d.,  https://www.weforum.org/reports . 
5 World Trade Organization, Agreement on Trade  Facilitation, 22  February  2017,  
https://www.wto.org/english/docs_e/legal_e/tfa -nov14_e.htm , subarticle 7.6.1 . 
6 World Trade Organization, "State of Play of th e Trade Facilitation Agreement in 7 Charts," web page, 
accessed 20 March 2021,  https://tfadatabase.org/state -of-play. G/TFA/W/84  
 
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  found to be location specific and seem to have higher utility when so presented. In view of the 
above, and taking into account the happy coincidence of the JNCH producing high -quality annual 
TRSs since 2017, with which the authors were closely associated, this paper seeks to analyze the 
import cargo release time data, with specific reference to the JNCH and JNPT.  
3  THE WORLD TRADE ORGANIZATION 'S TRADE FACILITATION AGREEMENT  
3.1.  The TFA is divided into three sections comprising twenty -four articles. The first twelve articles, 
included in section 1 , cover specific commitments relating to publication and availability of 
information (article 1); opportunity to comment, information before entry into force, and 
consultations (article 2); advance rulings (article 3); procedures for appeal or review (arti cle 4); 
other measures to enhance impartiality, non -discrimination, and transparency (article 5); disciplines 
on fees and charges imposed on or in connection with importation and exportation and penalties 
(article 6); release and clearance of goods (articl e 7); border agency cooperation (article 8); 
movement of goods intended for import under customs control (article 9); formalities connected 
with importation, exportation and transit (article 10); freedom of transit (article 11); and customs 
cooperation (ar ticle 12). Section 2 contains articles 13 –22 and covers the special and differential 
treatment provisions for developing country members and least -developed -country members. 
Section 3 covers articles 23 –24, which relate to institutional arrangements and fi nal provisions.  
3.2.  Article 14 of the TFA provides that there are three categories of provisions: category A contains 
provisions that a developing country member or a least -developed -country member designates for 
implementation upon entry into force of the agr eement, or in the case of a least -developed -country 
member within one year after entry into force, as provided in article 15; category B contains 
provisions that a developing country member or least -developed -country member designates for 
implementation on  a date after a transitional period of time following the entry into force of the TFA, 
as provided in article 16; and category C contains provisions that a developing country member or 
least-developed -country member designates for implementation on a date after a transitional period 
of time following the entry into force of the TFA and requiring the acquisition of implementation 
capacity through the provision of assistance and support for capacity building, as provided in 
article  16. 
3.3.  According to a communic ation dated 18 March 2016, India provided a detailed list of provisions 
within a category A commitment, stating that all other commitments in section 1 were designated 
as category B commitments. These category B commitments need to be implemented by 
Februa ry 2022.  
3.4.  According to the data available as of 22 February 2020, India has completed its designation of 
categories A, B, and C; its implementation status reflects that 72.3 % of provisions have been placed 
under category A, which have been fulfilled. The re maining 27.7 % of provisions are placed under 
category B, for which no separate notification will be filed by India until  30 April 2020.7 
3.5.  India's NCTF published the revised NTFAP in August 2019.8 As initially formulated and 
subsequently revised, the plan includes sixteen specific provisions, which were to be completed 
within the short and medium terms and have been fulfilled. It included nine category B 
commitments, which were to be fulfilled in th e medium term of six to eighteen months. None of the 
provisions were placed in category C.  
3.6.  The NTFAP also included a much longer list of fifty action points, categorized as TFA Plus 
Activities, which were to be completed mostly in the medium term. These ac tion points relate mainly 
to infrastructure developments, including those related to major ports (thirteen points); those 
related to civil aviation (ten points); and those related to land customs stations (three points). The 
NTFAP was subsequently updated to include additional activities pertaining to category  B 
commitments and to integrate eleven additional TFA Plus Activities, cumulatively taking the number 
of activities to ninety -six. 
 
7 World Trade Organization, "Trade Facilitation Agreement Database," webpage, accessed 
20 March  2021,  https://tfadatabase.org/implementation/progress -by-member . 
8 Central Board of Indirect Taxes and Customs,  National  Trade  Facilitation  Action  Plan 2017–2020. G/TFA/W/84  
 
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  3.7.  The list of activities identified by the NCTF, including those covered  by the TFA commitments, 
are expected to improve EODB, facilitate trade, and bring about other perceptible improvements in 
the economic environment of India, acting as "enablers " of trade facilitation.  
4  INDIA 'S PERFORMANCE AS MEASURED BY GLOBAL INDICATORS  
4.1.  In this section we review India 's performance as measured by six global indicators, which are 
conducted by different agencies with varying periodicity. The six indicators selected are the four key 
indicators referred to in the NTFAP, the World Bank 's Govern ance Indicators (WGI), and the 
United  Nation 's Global Survey on Trade Facilitation and Paperless Trade Implementation (GSTF -PTI). 
The additional two indicators have been included since governance and paperless trade are both 
enablers of trade facilitation.  
4.2.  All six indicators covered in this section are composite indicators, since they include a varying 
number of subindicators. These indicators invariably provide economy -wide statistical scores, often 
including economic ranks. In some cases, subindicator sco res and ranks are also available.  
4.3.  In table 1 we summarize the salient features of these composite indicators. Thereafter we 
briefly discuss each of them, presenting their time series rank and score, if available for India.9 
Table 1 The Composite Indicators  
 
Note: The latest study covers 120 economies, of which 99 were covered in the previous two studies as 
well. 
 
9 Investopedia,  What Is a Time Series?,  webpage, last updated 31  March  2020, 
https://www.investopedia.com/terms/t/timeseries.asp . Time series data consist of successive measurement s 
obtained from the same source at specific time intervals, often used to track changes over time.  
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  5  THE ORGANISATION FOR ECONOMIC CO -OPERATION AND DEVELOPMENT 'S TRADE 
FACILITATION INDICATORS  
5.1.  The OECD TFIs, as composite performance indicators, perhaps most closely approximate the 
provisions of the TFA. The OECD itself claims that  to help governments  improve  their border  
procedures,  reduce  trade  costs,  boost  trade flows and reap greater  benefits  from international  trade,  
we have developed  a set of trade  facilitation  indicators  (TFIs)  that identify  areas  for action  and 
enable  the potential  impact  of reforms  to be assessed.  The OECD  TFIs cover  the full spectrum  of 
border  procedures  for more than 160 economies  across  different  income  levels,  geographical  
regions,  and levels  of development.10 
5.2.  The OECD TFIs comprise eleven subindicators, each covering several related variables. Ten of 
these subindicators represent ten specific provisions of the TFA, wi th "governance and impartiality " 
being outside its remit.  
5.3.  The indicator assigns values ranging from 0 to 2 for each of the eleven subindicators, where 
0 represents the worst performance that can be achieved and 2 represents the best. The scores aim 
to refl ect the regulatory framework, along with the implementation status of various trade facilitation 
measures in the country concerned. The indicator also presents the overall combined average trade 
facilitation performance score for each country based on the eleven subindicator scores, assigning 
equal weight to each of the subindicators.  
5.4.  Our primary research of OECD TFIs was based on publicly available data for 2015, 2017, and 
2019 on the OECD 's website. Subsequent to the completion of our primary research, however, we 
noted that at the OECD website there were certain changes in the reported scores for India beyond 
the deletion of data relating to 2015. In order to understand the reasons behind the modifications 
in the data, we wrote to the OECD team. The team has responded, explaining that the OECD revised 
certain scores "in respect of the sub -indicators, for the years 2017 and 2019, based on a fine -tuned 
methodology  with the aim to deepen the a nalysis of various components by inserting additional 
variables that were previously challenging to cover across the different indicators as well as 
introducing some adjustments in the scoring across several components. "11 This revision is in some 
sense re flective of the challenges in performance measurement of trade facilitation measures, both 
across time and economies.  
5.5.  In figure 1 we present India 's scores in respect to each of the eleven subindicators, for the 
three biennial data points covering 2015 –2019, relying on the revised scores for 2017 –2019 and 
using the earlier available score for 2015.  
5.6.  For the OECD TFIs as a whole, we find that India 's average cumulative trade facilitation score 
in 2019 is 1.524, which is well above the global average of 1.15. At the subindicator level, we find 
that in 2015 and 2019, India 's scores improved in respect to seven subindicators, remained the 
same for three (formalities -automation, formalities -procedure, and advance rulings) and marginally 
declined for one (involveme nt of the trade community).  
5.7.  Further, since the revision of the data by OECD has had a significant impact on India 's trade 
facilitation scores, we consider it useful to present a comparative position of the prerevised and 
revised scores for eleven subindica tors for 2017 and 2019, as can be seen in figure 2.  
 
10 Organisation for Economic Co -operation and Development, "Trade Facilitation," web page, 
n.d., https://www.oecd.org/trade/topics/trade -facilitation/ . 
11 Email communication received from OECD to the author on 30  August  2020, in response to the email 
query to the OECD.  G/TFA/W/84  
 
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  Figure 2 TFIs: India's Revised and Prerevised Scores  
 
Source:  Authors' calculations, based on OECD TFls for 2017 and 2019 (Paris: OECD), which can be found at 
"Compare your country: trade facilitation" O ECD, Trade Facilitation, accessed 15 March 2021, 
https://www.oecd.org/trade/topics/trade -facilitation/  and based on data received from OECD vide 
email.  
5.8.  The comparative position shows that, according to the prerevised data, India 's scores were 
reported to have surprisingly declined in respect to all the eleven subindicators, and to have fallen 
even below the 2015 score in respect to nine of the eleven subindicators. Yet, taking in to account 
the revision undertaken by the OECD, India has, during the same period, improved its scores in 
respect to eight subindicators, remained unchanged for one, and declined marginally for the other 
two. We consider the revised scores to be better ali gned with anecdotal evidence regarding 
improvement in trade facilitation measures in India, as well as other performance indicators covered 
in the present paper.  
5.9.  The results noted herein have been arrived at through a methodology that is summarized by 
the OECD: "TFIs are based on a detailed questionnaire, with the aim of ensuring factual information 
that is geographically comparable and consistent over time. Data is collected from three types of 
sources: (a) publicly available information included in the we bsites of Customs and other relevant 
border agencies, official publications such as Customs Codes, annual reports, or public databases; 
(b) direct submissions from countries; and (c) factual information from the private sector  – in 
particular express indus try associations and companies operating worldwide. Discrepancies are 
verified by the OECD, and completed country datasheets are sent to capitals for validation. " Further, 
"Country datasheets are sent for validation with the assistance of WTO Permanent Del egations in 
Geneva, the World Customs Organization (WCO) and the ASEAN Secretariat for economies outside 
the OECD membership. "12 
5.10.   The substantive revision in the country score for India by the OECD, much after the publication 
of earlier scores, suggests, ho wever, that the methodology adopted by the OECD is still in the 
process of evolution and yet to stabilize. On the basis of information available to the public and 
responses from the OECD team, it is not clear whether the revisions can be attributed to the process 
of country data sheet validation included in the OECD 's methodology. Be that as it may, we are of 
the view that the fine -tuning undertaken by the OECD has resulted in evening out various glaring 
inconsistencies in the scores reported for India, wit h the revised data being more aligned with the 
assessment of other major performance indicators.  
6  THE WORLD BANK 'S EASE OF DOING BUSINESS INDEX  
6.1.  The EODB Index is perhaps the most widely known and tracked performance indicator for which 
longer time series da ta regarding wider geographic coverage are available.  
 
12 Organisation for Economic Co -operation and Development,  Introducing  the OECD  Trade  Facilitation  
Indicators  (Paris: Organisation for Economic Co -operation and Development, n.d.), 
https://w ww.oecd.org/trade/topics/trade -facilitation/documents/trade -facilitation -indicators -methodology.pdf . 
G/TFA/W/84  
 
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  6.2.  The EODB Index covers ten "Doing Business " topics comprising forty -one indicators. It presents 
both rank and score, separately for each of the ten topics, as well as at the aggregated level, each 
assigned equal weight. In figure 3 the coverage of EODB is presented, though it should be 
emphasized t hat measurements relating to "employing workers " and "contracting with the 
government " are presently not included in the composite EODB Index.  
Figure 3 What is Measured in Doing Business  
 
Note:  The employing workers and contracting with the government indicator sets are not included in the 
ease of doing -business ranking.  
Source :  World Bank, Doing Business 2020 (Washington, DC: World Bank, 2020), fig. 0.1, 
https://www.doingbusiness.org/en/reports/global -reports/doing -business -2020.  
6.3.  The score combines measures with different units, such as time to start a company or 
procedures to transfer a property or costs involved in the same. (This is explained in g reater detail 
later in this paper, with reference to "Trading Across Borders " [see figure 15]). The score for any 
subindicator for an economy represents the gap between an economy 's current performance and a 
measure of the best regulatory practice for that  subindicator. Prior to the 2019  Doing  Business  
Report , this score was referred to as the "distance to frontier score "; it has since been changed to 
the "ease of doing business score. " The score, therefore, seeks to reflect an economy 's position with 
respe ct to the best regulatory practice. Thus, with respect to a particular regulatory practice, the 
best economy gets a score of 100. For other economies, the higher the score, the better EODB they 
provide. Lower scores show poorer EODB, with the worst perform ance being set at 0. The percentage 
point scores of an economy on the ten different topics are averaged together to obtain the aggregate 
EODB score. The countries are then ranked according to the score for each subindicator and at the 
aggregate level.  
6.4.  In figure 4, India 's composite EODB rank and score since 2014 are presented, when a 
substantive modification in the methodology was carried out.13 It is worth noting that India 's country 
score has been improving consistently during the entire data period, albeit at a significantly faster 
pace since 2018. During the early period of sluggish growth in score, India 's country rank had slipped 
or stagnated, which is attributable to the differing relative performance of other countries with 
similar doing -business scores. But since 2018, India 's rank has improved significantly, making it one 
of the fastest -improving economies in terms of EODB rank.  
 
13 World Bank, "Doing Business: Methodology," web page,  
https://www.doingbusiness.org/en/method ology . 
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  Figure 4 India's EODB Rank and Score  
 
Source:  Authors' calculations, based on World Bank, Doing Business Repo rts for 2014 -2020 (Washington, 
DC: World Bank), which can be found at "Reports," World Bank, Doing Business: Measuring Business 
Regulations, accessed 5 March 2021, https://www.doingbusiness.org/en/reports/global -
reports/doing -business -2020. 
6.5.  Taking into account the scope of the subindicators, we expected that the TAB subindicator of 
EODB would be most closely aligned with OECD TFIs. However, we find that the prerevise d version 
of OECD TFIs was significantly misaligned; and the subsequent fine -tuning by OECD has resulted in 
directional alignment with EODB and its TAB subindicator. This is discussed in greater detail later in 
this paper, in the section "Release Time Data ." 
7  THE WORLD BANK 'S LOGISTICS PERFORMANCE INDEX  
7.1.  In terms of scope, the World Bank 's LPI is seen to be more closely related to issues of trade 
and trade facilitation, measuring rank and score for economies on six dimensions of trade —namely, 
(1) the efficiency of customs and border management clearance; (2) the quality of trade and 
transport infrastructure quality; (3) the ease of arranging international, competitively priced 
shipments; (4) the competence and quality of logistics services (trucking, f orwarding, and customs 
brokerage); (5) the ability to track and trace consignments; and (6) the frequency with which 
shipments reach consignees within scheduled or expected delivery times.  
7.2.  The LPI seeks to present the worldwide view on trade logistics perf ormance across more than 
160 countries, as seen by the logistics professionals. Using a five -point scale for assessment (from  1, 
"very low " to 5, "very high ") in respect to each of the six aforementioned subindicators, it seeks the 
opinion of logistics pro fessionals worldwide about trading with the country, to find how easy or 
difficult it is in these countries to transport general merchandise -typically, manufactured products 
in unitized form. The data used in the rank and score come from a survey of logist ics professionals, 
who are asked questions about the foreign countries in which they operate. In figure 5 we summarize 
the average LPI rank and score for India for 2010 –2018.  
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  Figure 5 India's LPI Rank and Score  
 
Source:  Authors' calculations, based on the  World Bank's LPI data sets for 2010, 2012, 2014, 2016, and 
2018, at World Bank, "Aggregated LPI 2012 -2018," web database, https://lpi.worldbank.org/ . 
7.3.  The 2018 World Bank Report  Connecting  to Compete:  Trade  Logistics  in the Global  
Economy  helpfully includes its "Appendix 1: Aggregated International LPI Results Across Four 
Editions: 2012, 2014, 2016, and 2018, " wherein India, with a mean LPI score of 3.22, has the mean 
LPI rank of forty -second among 160 countr ies. Therefore, notwithstanding the slippage, in 2018, 
India was ranked second after Viet  Nam (whose rank was thirty -ninth) among the top -performing 
lower -middle -income economies.14 
7.4.  In order to understand and identify the reasons for slippage in rank and s core between 2016 
and 2018, we present in figure 6 the time series score in respect to each of the six subindicators.  
Figure 6 India's Score in the Subindicators of the LPI  
 
Source :  Authors' calculations, based on the World Bank's LPI data sets for 2010, 2012, 2014, 2016, and 
2018, at World Bank, "Aggregated LPI 2012 -2018," web database, https://lpi.worldbank.org/ . 
7.5.  It is important to note that India 's score is found to have improved in respect to all 
six subindicators between 2014 and 2016; after that, it declined in respect to all the 
six subindicators. The high degree of positive correlation between the six LPI subindicators is at 
varianc e with the earlier two studies, wherein we found the subindicators to follow divergent trends.  
8  THE WORLD ECONOMIC FORUM 'S GLOBAL COMPETITIVENESS INDEX  
8.1.  In this section we look at India 's GCI rank and score for 2014 –2019, even as we note that the 
latest vers ion of the index, called the GCI 4.0, was introduced in 2018 and covers 141 economies, 
accounting for about 99 % of the world 's gross domestic product. The GCI draws inspiration from the 
 
14 Jean-François Arvis, Lauri Ojala, Christina Wiederer, Ben Shepherd, Anasuya Raj, Karlygash 
Dairabayeva, and Tuomas Kiiski,  Connecting  to Compete  2018:  Trade  Logistics  in the Global  Economy;  The 
Logistics  Performance  Index  and Its Indicators  (Washington, DC: World Bank, 2018).  
G/TFA/W/84  
 
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  growth accounting economic literature. It aims to measure the drivers of total factor productivity, 
the part of economic growth that is not explained by the growth in the factors of production but 
instead how smartly they are combined. Total factor productivity is considered to be the main 
determinant of long -term economic g rowth. The GCI 4.0 is the product of an aggregation of 
103 individual indicators, derived from a combination of data from international organizations, as 
well as from the WEF 's Executive Opinion Survey.15 
8.2.  An economy 's performance on the overall GCI results , as well as each of its components, is 
rated as a progress score on a 0 –100 scale, where 100 represents the "frontier, " an ideal state at 
which an issue ceases to be a constraint to productivity growth.  
8.3.  Under the earlier methodology, we find that for 2014 –2017 (as shown in figure 7), India 's score 
increased consistently, albeit gradually, from 4.21 to 4.59. Under the revised methodology, even as 
India has the best rank of South Asian nations for 2019, at sixty -eighth, it has lost in terms of both 
rank and score over 2018. With a 2019 GCI score of 84.8 out of 100, Singapore is the country closest 
to the frontier of competitiveness.  
Figure 7 India's GCI Rank and Score  
 
Note:  Methodology revision resulted in the scoring change from 2017 to 2018.  
Source:  Authors' calculations, based on World Economic Forum, Global Competitiveness Reports for 
2014-2019 (Geneva: World Economic Forum), at https://www.weforum.org/reports .  
8.4.  India, in the sixty -eighth posi tion in 2019, has lost ground in the ranks of South Asian nations 
despite a relatively stable score, mostly due to faster improvements in several countries previously 
ranked lower. It is followed by Sri Lanka (the most improved country in the region, at ei ghty-fourth), 
Bangladesh (105th), Nepal (108th), and Pakistan (110th). 
9  THE WORLD BANK 'S WORLD GOVERNANCE INDICATORS  
9.1.  The World Bank 's WGIs are composite governance indicators based on over thirty data sources, 
covering six dimensions of governance: (1) voice and accountability; (2) political stability and 
absence of violence/terrorism; (3) government effectiveness; (4) regulatory quality; (5) rule of law; 
and (6) control of corruption. These aggregate indicators combine the views of a lar ge number of 
enterprises, from both citizen and expert survey respondents, in industrial and developing 
countries.  The data sources used for preparation of WGIs are produced by a variety of survey 
institutes, think tanks, non -governmental organizations, in ternational organizations, and 
private -sector firms. The four different types of source data are (1) surveys of households and firms; 
(2) commercial business information providers; (3)  non-governmental organizations;  and 
(4) public -sector organizations.  
9.2.  Though annual data for over 200 countries and territories are available for 1996 –2018, in figure 
8 we present the data for India for 2010 –2018 only. We have noted that during this period the data 
 
15 World Economic Forum, "Shaping the Future of the New Economy and Society," web page, last 
updated 2021,  https://www.weforum.org/platforms/shaping -the-future -of-the-new-economy -and-society . 
G/TFA/W/84  
 
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  sources and methodologies have undergone certain changes. Yet since our intention in this paper is 
to highlight the broad trends suggested by WGIs, we have ignored these changes in the 
methodologies. In doing so, we also concur with the view expressed at the World Bank 's WGI web 
page that "changes in governance over short year -to-year periods are difficult to measure with any 
kind of data, and are typically quite small. "16 We highlight that government effectiveness, control of 
corruption, and regulatory quality, which would have significant correlation with trade faci litation or 
EODB, have shown perceptible improvement since 2015 even as the other dimensions do not show 
such clear improvement, with voice and accountability showing the most negligible results.  
Figure 8 India's WGI Percentile Rank  
 
Source:  Authors' cal culations, based on the World Bank WGls for 20 10-2018, at World Bank, "World 
Governance Indicators," web page, https://info.worldbank.org/governance/wgi/ . 
10  THE UNITED NATIONS REGIONAL COMMISSIONS ' GLOBAL SURVEY ON TRADE 
FACILITATION AND PAPERLESS TRADE IMPLEMENTATION  
10.1.   The last survey report that we consider in this section is the GSTF -PTI, jointly carried out by 
the five United Nations Regional Commissions. The GSTF -PTI covers 120 econom ies from 
eight regions, and we take into account the three data points for 2015 –2019 that are available for 
ninety -nine countries. India is included in the South Asia region, along with Afghanistan, Bangladesh, 
Bhutan, Maldives, Nepal, Pakistan, and Sri La nka. 
10.2.   This indicator focuses on measures related to the WTO 's TFA, as well as to paperless trade 
and the United Nations Framework Agreement on Facilitation of Cross -border Paperless Trade in Asia 
and the Pacific17, through a survey questionnaire covering forty -seven questions under four main 
areas: (1) general trade facilitation measures, with subindicators of transparency, formalities, and 
institutional arrangement and cooperation; (2) paperless trade, through a set of ten questions  
seeking to assess the implementation of innovative, technology -driven measures aimed at enabling 
trade using electronic rather than paper -based data and documentation; (3) transit facilitation; and 
(4) inclusiveness in trade facilitation, with subindicato rs focused on specific trade facilitation 
measures targeted at small - and medium -size enterprises (SMEs), the agricultural sector, and 
women.  
10.3.   Each of the trade facilitation measures included in the survey was scored as "fully 
implemented " (3), "partially i mplemented " (2), "on a pilot basis " (1), or "not implemented " (0) to 
calculate implementation across countries, regions, or categories. The survey follows a three -step 
data collection and validation process. The first step involves data submission by exper ts, collected 
through a questionnaire sent to trade facilitation experts and publicly available online. The second 
step involves data verification by the United Nations Regional Commissions Secretariats. The 
 
16 See Klaus Schwab, "Appendix B: The Executive Opinion Survey: The Voice of the Business 
Community," in  The Global  Competitiveness  Report  2018 (Geneva: World Economic Forum, 
2018),  https://reports.weforum.org/global -competitiveness -report -2018/ . 
17 World Bank, "World Governance Indicators," web page, n.d.,  
https://info.worldbank.org/governance/wgi/Home/Documents . 
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  third step involves data validation by national governments. It has also been stated that the 
feedback from national governments was incorporated to finalize the data set.  
10.4.   In figure 9 we present the time series subindicator score for India, noting the general trend 
of improvement over time. We note that  the government initiatives toward simplification of customs 
procedures, a significant push toward digitization, and a reduction in paper -based processes are 
reflected in improved scores in respect to cross -border paperless trade, formalities, and 
transpar ency.  
Figure 9 India's GSTF -PTI Subindicator S core 
 
Source:  Authors' calculations, based on the GSTF -PTls for 2015, 2017, and 2019, at United Nations Network 
of Experts for Paperless Trade and Transport in Asia and the Pacific, "UN Global Survey on Trade 
Facilitation and Paperless Trade Implementation," web page, 
https://unnext.unescap.org/content/un -global -survey -trade-facilitation -and-paperless­trade -
implementation . 
10.5.   We conclude that for India t he review of the time series rank and score, where available, 
presents a mixed picture for 2015 –2019. The country has shown relatively consistent improvement 
according to some indicators, but in the case of other indicators the trend has been uneven. This 
unevenness becomes more pronounced when we look at the scores at the level of subindicators, 
even as we recognize that the scores may depend on the methodology adopted as much as the 
actual performance of the country on each subindicator. Therefore, if the  null hypothesis is to be 
posited as India 's performance showing consistent improvement in scores reported by the different 
composite indicators, this is not proven. The country rank, where reported, is found to be further 
impacted by the relative performa nce of economies belonging to the same cohort, even as EODB 
has reported consistent improvement in rank since 2016.  
11  COMPARISONS BETWEEN SELECT INDICATORS AND SUBINDICATORS  
11.1.   In the previous section, "India's Performance as Measured by Global Indicators, " we presented 
the scope, methodology and coverage of the six composite performance indicators, highlighting the 
significant differences therein. In view of these differences, it was expected that the intertemporal 
performance measurement reported might not be similar, particularly with reference to the pace of 
reforms, as captured by the changes in scores.  
11.2.   Having observed that it was not just the pace of reform but also its direction that was found 
to vary between the six composite indicators, in this section w e present the results of certain 
comparisons between select indicators and subindicators.  
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  11.3.   In view of the aforementioned differences in scope, methodology, and coverage, including the 
difference in scoring patterns (which were also modified during the study  period in a few cases), we 
recognize that these comparisons should not be viewed with statistical precision but only as broad 
subjective indicators of trends.  
11.4.   Recognizing that the theme of this paper is performance measurement, with TFA at its core, 
we ta ke OECD TFIs as the primary performance measurement indicators. Therefore, the first 
comparison that we make is between OECD TFIs and the EODB since 2015 –2016, thus 
approximating the period after which the TFA gained momentum. During this period India impr oved 
its average EODB score from 54.5 in 2016 to 71.0 in 2020, an improvement of 30.3 %. In line with 
the EODB scores, India 's scores in OECD TFIs, after the revision of the methodology, is found to 
have increased from 1.253 in 2017 to 1.524 in 2019, an imp rovement of 21.6 %. 
11.5.   It can be noted that the GSTF -PTI bears close similarity with the OECD TFIs in terms of scope, 
frequency, and data points. According to the OECD TFIs, India 's composite score improved from 
1.253 in 2015 to 1.534 in 2019; according to the  GSTF-PTI, India 's score has shown an improvement 
from 64.52 % in 2015 to 79.57 % in 2019.  
11.6.   In addition, we find that it is possible to identify and group together performance indicators 
as regards to four subindicators: (1) transparency; (2) formalities; (3)  automation; and (4) 
institutional cooperation and arrangement. The "transparency " indicator of the GSTF -PTI measures 
aspects of publications, stakeholder consultations, notification of new regulations, advance rulings, 
and appeal mechanisms, and this corresponds to the indicators of "information availability, " 
"involvement of the tradi ng community, " "advance rulings, " and "appeal procedures " of the OECD 
TFIs; hence, both can be grouped under "transparency. " The "formalities " indicator of the GSTF -PTI 
is compared with the indicators of "formalities (documents), " "formalities (procedure), " and "fees 
and charges " in the OECD TFIs, and they can all be grouped under "formalities. " The GSTF -PTI 
indicators of "paperless trade " and 'cross-border paperless trade ' are correlated with the OECD TFI 
indicator "formalities (automation), " and can be gr ouped under "automation. " And "institutional 
cooperation and arrangement " in the GSTF -PTI is comparable with the OECD TFIs ' "internal border 
agency cooperation " and "external border agency cooperation " and can be grouped under 
"institutional cooperation an d arrangement. " 
11.7.   In figure 10 we present the comparative performance reported in respect to these combined 
subindicators of the OECD TFIs and the GSTF -PTI. 
Figure 10 India's Performance in OECD TFIs and the GSTF -PTI 
 
Source:  Authors' calculations, based on OECD TFls for 2017 and 2019 (Paris: OECD), which can be found at 
"Compare your country: trade facilitation" OECD, Trade Facilitation, accessed 15 March  2021, 
https://www.oecd.org/trade/topics/trade -facilitation/  and the GSTF -PTls for 2017 and 2079, at 
United Nations Network of Experts for Paperless Trade and Transport in Asia and the Pacific, "UN 
Global Survey on Trade Facilitation and Paperless Trade Imple mentation," web page, 
https://unnext.unescap.org/content/un -global -survey -trade-facilitation -and-paperless -trade-
implementation . 
11.8.   The third comparison we present is between the two indicators prepared by the World Bank: 
the broader and more widely tracked EODB and the more narrowly focused LPI. In addition, we note 
G/TFA/W/84  
 
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  that the TAB subindicator of EODB and the customs subindicator of LPI rela te more directly to 
cross-border movement of goods.  
11.9.   Therefore, in figure 11, we compare the two sets of indicators for 2014, 2016, and 2018; the 
composite EODB score shows consistent improvement, whereas the average LPI score initially 
improves but thereaf ter declines between 2016 and 2018; and the TAB subindicator shows initial 
decline and then improvement, whereas the customs subindicator of the LPI shows initial 
improvement and then decline.  
Figure 11 India's Performance in the World Bank EODB and the Wo rld Bank LPI  
 
Source:  Authors calculations, based on the World Bank's EODB, at 
https://www.doingbusiness.org/en/doingbusiness ; LPI at World Bank, "Aggregated LPI 2012 -2018," 
web database, htt ps://lpi.worldbank.org/; EODB TAB, at 
https://www.doingbusiness.org/en/doingbusiness ; and LPI -Customs data, at World Bank, 
"Aggregated LPI 2012 -2018," web database, https://lpi.worldbank.org/ . 
11.10.   We conclude this section by summarizing the results of the six composite indicators, 
combining the annual rank and score on a line in figure 12, with four indicators showing 
improvements to the right and three showing decline to the left. The indicator on the extreme right 
shows maximum improvement and the one closest to "No Change " shows minimum improvement. 
Analogously, the indicator on the extreme left shows maximum decline. The distance between the 
indicators does not have any quantitative implication. In this figure, we include two versions of the 
OECD TFIs—revised and prerevised —to highlight the substantive shift in the reported performance 
of India, subsequent to the revision by the OECD. Overall we find that the composite indicators 
present an improv ement in India 's performance in EODB, paperless trade, trade facilitation, and 
governance, whereas it shows declining performance in logistics performance and competitiveness.  
Figure 12 Summary of India's Performance  
 
Source:  Authors' presentation.  
12  RELEA SE TIME DATA  
12.1.   Article 7 of the TFA contains specific provisions for facilitating release and clearance of goods, 
including subarticle 7.6.1 for the establishment and publication of average release time, which reads 
as follows: "Members encouraged to measure  and publish their average release time of goods 
periodically and in a consistent manner, using tools such as,  inter alia, the Time Release Study of 
the World Customs Organization. "18 India has made subarticle 7.6.1 a category A commitment.  
 
18 United Nations, Framework Agreement on Facilitation of Cross -border Paperless Trade in Asia and the 
Pacific, 20  December 2020, https://www.unescap.org/resources/framework -agreement -facilitation -cross-
border -paperless -trade -asia-and-pacific . 
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  12.2.   The NTFAP has, accordingly, prescribed the conduct of the TRSs for both import and export 
cargo at all seaports, air cargo complexes, ICDs, integrated check posts, and land customs stations.  
12.3.   The TRS has long been advocated by the WCO as "an internationally accepted strategic tool 
to measure the actual time taken for the release and/or clearance of goods  – from the time of arrival 
until the physical release of cargo  – as well as the effectiveness and efficiency of border procedures 
relating to imports, exports and tra nsit movements of goods. It helps in identifying associated 
bottlenecks objectively, and in addressing them in an efficient and effective manner. "19 
12.4.   In this section we review the literature available on the average release time data, with 
reference to sea cargo imports through the JNPT and cleared through its associated custom house, 
the JNCH.  
12.5.   We first present the intertemporal average import release time, using a bill of entry (a 
statutory import document) as the unit, computed from the time stamps obtaine d from the customs 
automation system. We then present average import release time, using a cargo container as the 
unit, computed by using RFID technology. Finally, we present the average release time culled from 
two survey -based studies —namely, the TAB sub indicator of the EODB Index and  Total Transport  and 
Logistics  Cost (TTLC), published by the Global Alliance for Trade Facilitation (GATF).20 
13  RELEASE TIME BASED ON TIME STAMPS FROM THE CUSTOMS AUTOMATION SYSTEM  
13.1.   Since July 2015 the Central Board of Indirect Taxes and Customs (CBIC) has published 
monthly dwell time data in respect to import cargo through two major seaports (Chennai and the 
JNCH), three air cargo complexes, and one ICD on its website.21 Here, however, we look at the time 
series data since Janua ry 2017, taking note of the methodology revision to factor in the impact of 
prearrival processing, one of the major initiatives to promote EODB and facilitate trade. We further 
note that pursuant to the revision of the methodology, the terms  dwell time and release  time could 
be used interchangeably, seeking to measure, in the case of imports, the time taken between the 
arrival of the cargo at the seaport to the completion of the customs clearance process, enabling the 
importer or its representative to take delivery of the cargo.  
13.2.   CBIC dwell time data have been presented for two categories of imports: green channel cargo 
and red channel cargo.  Green  channel  cargo  refers to the majority of the consignments that are 
allowed clearance on the basis of scrutiny of the details provided under the self -declaration process 
by the information -technology -driven risk management system, without human intervention for 
verification of the details or documents (submitted online) or actual physical examination of th e 
goods. All other consignments that are subjected to examination are put together as  red channel  
cargo . Here we examine aggregate monthly import dwell time for the JNCH, assigning a constant 
60% weight to green channel cargo. This percentage of weight is arrived at from the average share 
of fully facilitated cargo reported by the JNCH TRSs, recognizing that green channel and fully 
facilitated cargo have broadly the same connotation in customs parlance. These dwell time data are 
a simplistic post facto perf ormance indicator, based on the time stamps drawn from the customs 
information technology (IT) system, given that almost 100 % of all cargo clearance processes 
through these customs formations take place through an electronic medium.  
13.3.   Since the signing of th e TFA, the JNCH has led the way among Indian customs formations in 
conducting in -house annual TRS using the WCO guidelines for the purpose. Here we examine the 
results of the four JNCH TRSs, providing the average import release time for all imports made du ring 
the first week of January of each calendar year from 2017 to 2020. These annual TRSs have been 
conducted as a live preannounced study -cum-outreach initiative, urging the stakeholders to put their 
"best foot forward. "22 Therefore, some concerns have be en expressed that this method of 
approaching TRSs may impact the release time for the weekly consignments covered by the annual 
 
19 World Trade Organization, Agreement on Trad e Facilitation, subarticle 7.6.1.  
20 World Customs Organization,  Guide  to Measure  the Time Required  for the Release  of Goods , version 3 
(Brussels: World Customs Organization, 2018),  http://www.wcoomd.org/ -
/media/wco/public/global/pdf/topics/facilitation/instruments -and-tools/tools/time -release -study/trs -
guide_en.pdf?db=web . 
21 Global Alliance for Trade Facilitation,  Total Transport  and Logistics  Cost (TTLC):  Methodological  Note, 
version 1.0 (Paris: Global Alliance for Trade Facilitation, 2020) . 
22 Central Board of Indirect Taxes and Customs, "Dwell Time," web table, last updated January  2021,  
https://www.cbic.gov.in/htdocs -cbec/dwell_time . G/TFA/W/84  
 
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  JNCH TRSs. Here we attempt to ascertain whether these concerns are borne out by the release time 
data obtained from other source s. 
13.4.   CBIC dwell time data provide the monthly average import release time data, based on all 
documents filed during the month, excluding specific categories for clearly stated reasons (for 
example, those interdicted for infringement and delayed on account of  consequent statutory 
procedure). The average release time reported under the JNCH TRSs is based on all documents filed 
during the first week of January of every calendar year since 2017.23 We note that the JNCH TRSs 
are more detailed studies that also inc lude export TRSs. For the purposes of this paper, however, 
we note that the data source for the CBIC dwell time and the JNCH TRSs is the same; thus, the 
methodology adopted for computation of average release time is entirely consistent.  
13.5.   For fuller complian ce with the NTFAP, the CBIC has coordinated the first ever national TRS 
covering fifteen major customs formations, including the JNCH, during the months of August and 
September 2019. The data source and the methodology adopted by the national TRSs are also  
entirely consistent with the JNCH TRSs insofar as they relate to sea cargo import release time. 
Therefore, the average release time data provided in the national TRSs for the JNCH for the 
first week of August 2019 has provided an additional data point, al beit one adversely impacted by 
severe weather conditions: a monsoon deluge during the study period.  
13.6.   The data source for these three studies is the customs automation system, which handles 
100% of the cargo clearance through the JNCH. Further, the digital m ode of working enables tracking 
of each consignment, represented by a bill of entry, and every step in the cargo clearance process 
has a precise time stamp. Based on the time stamp reflecting the arrival of the cargo at the seaport 
and out of charge reflec ting the completion of the cargo clearance process, the precise release time 
is calculated.24 In figure 13 we present the monthly average import release time data for the JNCH 
as obtained from the CBIC dwell time report and superimpose the average release time reported by 
the JNCH on national TRSs.  
Figure 13 Monthly Average Release Time for the JNCH  
 
Source:  Authors' calculations, based on dwell time data, at Central Board of Indirect Taxes and Customs, 
"Dwell Time," web table, last updated January 2021, https://www.cbic.gov.in/ htdocs -cbec/dwell -
time/archived_dwell_time ; the JNCH TRSs for 2017 -2020, at Jawaharlal Nehru Custom House, "Time 
Release Study," web database, http://www.jawaharcustoms.gov.in/in formation.aspx?Page1D=3836 ; 
and the national TRSs.  
13.7.   Our analysis suggests (1) a trend of improving monthly release time; (2) consistent 
improvement in the release time reported by annual TRSs; (3) a pronounced increase in the release 
time of both green and red channel cargo during July -September 2017 coinciding with the 
 
23 Jawaharlal Nehru Custom House,  Time Release  Study  2018,  Foreword p. 9, webpage, 
n.d., http://www.jawaharcustoms.gov.in/pdf/TRS2018 -Jan-June.pdf . 
24 Jawaharlal Nehru Custom House,  Time Release  Study  2017,  webpage, 
n.d., http://jawaharcustoms.gov.in/pdf/TRS2017 -Jan-June.pdf . 
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  introduction of Goods and Services Tax; and (4) better release time during the TRS months, 
attributable perhaps to outreach efforts.  
14  DWELL TIME BASED ON RADIO -FREQUENCY IDENTIFICATION TRACKIN G 
14.1.   The Logistics Data Bank (LDB) analytics reports are products of NICDC Logistics Data Services 
(DLDS), which is a joint venture between the government of India 's National Industrial Corridor 
Development and Implementation Trust and a major Japanese IT con cern, NEC Corporation. Using 
RFID technology, which involves placing a tag or a label on containers, LDB seeks to capture, store, 
and analyze the dwell time of containers through ports, container freight stations (CFSs) and ICDs 
across the country to help improve operational efficiency, compliance across systems, and better 
coordination among different stakeholders.  
14.2.   We extracted the monthly data since April 2017 pertaining to the JNPT as a port, and the 
CFSs pertaining to the same, as a proxy for the cargo that is customs cleared through the JNCH. 
The LDB presents segregated data, for export and import, for the overall JNPT region, port to CFS 
delivery time, and overall CFS dwell time. Adding the time taken under these three categories, it is 
possible to arr ive at the overall import dwell time / release time of the cargo for the JNCH calculated 
on the basis of RFID -based physical tracking of the consignment from the time of its arrival at the 
port to its departure from the JNPT CFS zone.  
14.3.   In figure 14 we super impose the LDB time series data on the graph showing the average 
release time from the customs automation system, wherein a broad consistency in the monthly data 
from the customs automation system and RFID -based tracking is observed.  
Figure 14 Average Rele ase Time from the BCIC and the LDB  
 
Source:  Authors' calculations, based on dwell time data for 2017 -2019, at Central Board of Indirect Taxes 
and Customs, "Dwell Time," web table, last updated January 2021, https://ww w.cbic.gov.in/htdocs -
cbec/dwell -time/archived_dwell_time ; and LDB data for 2017 -2019, at NICDC Logistics Data 
Services, at https://nldsl.in/our_services.aspx?mpgid=10&pgidl=l l&pgidtrail=71 . 
15  AVERAGE RELEASE TIME BASED ON SURVEY STUDIES  
15.1.   In the earlier section, "India's Performance as Measured by Global Indicators, " it was 
mentioned that one of the subindicators covered under the EODB Index is TAB, which takes into 
account the ti me taken and costs incurred in import and export clearance, which can be broken 
down further into border compliance, documentary compliance, and domestic transport. For imports, 
it measures the release time for a standardized shipment of 15 metric tons of containerized auto 
parts from India 's import partner, South Korea. Since 2015, TAB had covered the JNPT, representing 
Mumbai and ICDs; and Tughlakabad, representing Delhi. The TAB Index follows the same EODB 
methodology and presents both country rank and s core. In figure 15 the time series country rank 
and score for TAB is presented. The trend reflects a gradual improvement in India 's rank and score 
since 2016 and a drastic improvement since 2019, coinciding with the period since the TFA efforts 
gained mome ntum.  
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  Figure 15 India's TAB Rank and Score  
 
Source:  Authors' calculations, based on World Bank, Doing Business Reports for 2014 -2020 
(Washington,  DC: World Bank), which can be found at "Data," World Bank, Doing Business accessed 
15 March  2021, https://www.doingbusiness.org/en/custom -query . 
15.2.   In figure 16 we have extracted the time taken under border compliance and documentary 
compliance at the JNCH since the 2015 EODB report (reporting data for 2014). Since it is possible 
and increasingly quite likely for the process of documentary compliance and border compliance to 
proceed simultaneously, it would not be appropriate to add the time taken for the two sets of 
processes. Therefore, we present the time series data for 2015 –2020, reflecting a sudden 
improvement in the time taken in TAB (particularly since 2018), which is more drastic when 
compared with the release time data presented by the dwell time / release time studies.  
Figure 16 EODB: Time Take n for Border Compliance and Documentary Compliance at the 
JNCH  
 
Source:  Authors' calculations, based on World Bank, Doing Business Reports for 2015 -2020 
(Washington,  DC: World Bank), which can be found at "Data," World Bank, Doing Business accessed 
15 March 2021, https://www.doingbusiness.org/en/custom -query . 
15.3.   It is worth noting that the improvements in release time reported by the actual data -based 
studies, which started in 2017, are more gradu al than the survey -based EODB TAB; the latter initially 
failed to report the improvements in 2018, but then saw a marked improvement in 2019. Based on 
our ground -level understanding of the situation, we consider it plausible that the survey respondents 
in 2019 "corrected " their responses, being made aware of the actual release time through the 
data-based studies.  
15.4.   The GATF works to support governments in developing and least -developed countries 
implementing the TFA. From July to December 2018, the Alliance c onducted the  TTLC study in India 
to measure the cost of import and export processes to help target trade facilitation 
reforms.  TTLC measures the total cost of transport and logistics in cross -border trade, broken down 
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  into two components:  direct  costs are those incurred by an importer or exporter to complete an 
import or export process through a given point of entry or exit, excluding duties and taxes;  indirect  
costs are defined as costs related to time, which include the average lead time, delays, and time  
variance in completing an import or export process.  
15.5.   The TTLC diagnostic in India considers imports of full 40 -foot containers by sea and truck 
transport through the three terminals in Nhava Sheva Port near Mumbai and includes four import 
products: chemica ls, electronics, general goods, and auto parts. All products are selected based on 
their trade volume and their dependence on trade facilitation. The study sample includes importers 
located within 700 kilometers of Mumbai. Final results are based on interv iews with twelve importers, 
fourteen clearing and forwarding agents, and one terminal operator.  
15.6.   For this paper we have extracted only the average transit time of imports for border clearance, 
which is 113.6 hours. The report presents average transit times for three different modes of cargo 
clearance: CFS, direct port delivery (DPD), and a combination of the two (DPD -CFS), showing the 
lowest time for DPD clearances, at 80.9 hours, and the highest for DPD -CFS, at 119.4 hours, which 
includes time that the carg o may dwell at the CFS, even after "out of charge " has been granted by 
customs, at the discretion of the importer or the broker.  
15.7.   Our analysis of the JNCH data for the period since 2017 shows that an improvement in release 
time is evident from all three sets of studies: those based on actual clearance data taken from the 
customs automation system, the RFID tracking of the physical movement of the containers, and the 
survey methodology adopted by the EODB Index. Further, the one -off survey data prese nted by the 
GATF are also found to be consistent with other data sets.  
15.8.   We find, however, that the improvement in release time according to TRSs and the LDB are 
more gradual than the survey -based TAB, which shows a distinct break in the trend in 2019  – a 
break that is not noticed in the studies based on data sourced through technology. This leads us to 
wonder whether the launch of live conduct of TRSs at the JNCH, and their findings, resulted in 
significant and sudden improvement in the stakeholder percept ion about the reality of a more 
impressive release time.  
16  CONCLUSION  
16.1.   During the course of our research, we found an impressive amount of data on trade facilitation 
performance indicators  – for India at the country level and the JNCH at the local level  – that is 
available to the public. As is mentioned in the NTFAP, there is a commitment to measure the release 
time of import and export cargo and a need to carefully monitor key composite indicators and 
benchmark India 's goals.  
16.2.   In this paper we have first revie wed India 's performance over a longer period of time and 
stacked up the intertemporal performances reported by the key composite country -level indicators. 
The six key composite indicators covered in the section titled "India's Performance as Measured by 
Global Indicators " aim to present statistical measurement of multiple variables, some of which are 
not readily amenable to such measurement. Given the scope and global coverage, the survey 
methodologies adopted for the purpose would be expected to have their  limitations. Yet even after 
factoring in differences in scope and methodology, we are surprised by the diversity of the results 
regarding India 's performance during the period since the enactment of the TFA. Our studies show 
that these indicators have not  necessarily been moving in agreement with each other, and some of 
the trends are clearly counterintuitive. Determining the reasons for these varying trends or providing 
probable explanations by delving deeper into their respective methodologies, sample si ze, and 
sample selection, has not been attempted in this paper, recognizing these as topics for a separate 
research project.  
16.3.   Further, much caution should be exercised in interpreting these results, since limiting 
availability of time series data to three t o five annual or biennial data points would suggest that one 
must wait for a longer period to reassess the trends reported by these indicators.  
16.4.   We have, however, found significantly more consistent results while looking at the 
performance measurement (the release time of import cargo) that has been specifically 
recommended in the TFA. These findings, covered in the section titled "Release Time Data, " show a 
clear and consistent result for a more precise indicator: import cargo release time for a limited G/TFA/W/84  
 
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  geographic location such as the JNCH. In case of this specific indicator, for which monthly data are 
available from the customs automation system and RFID -based container tracking, we have found 
a high degree of consistency and improved performance. We have a lso noted that the survey -based 
performance measurement results are also aligned with IT -based release time, albeit with a lag.  
16.5.   The findings regarding consistent improvement in the release time trends is limited to 
one seaport, the JNCH, and only for impor t cargo. The simple reason for limiting the scope of our 
study is that similar data are not available for other major customs formations; and even for the 
JNCH, export release time data of equal robustness are still not available for a significant period o f 
time. The conducting of national TRSs initiated by the CBIC is a step in the right direction, as it 
would provide import and export cargo release time data for various customs formations in the 
country, enabling a more comprehensive study of trade facili tation performance measurement, as 
required under the TFA.  
16.6.   We conclude by noting that it is generally recognized that the release time analysis of import 
and export cargo is, by far, the most meaningful metric that encapsulates the performance of border 
management agencies and processes, assuming that the quality of compliance ensured by the border 
agencies is not compromised due to focus on expeditious release. Further, we think that deeper 
adoption of automated processes for customs clearance of goods mak es it possible to quantify this 
metric objectively, both over a period of time and across jurisdictions. In other words, such release 
time measurement need not be influenced by any plausible biases and prejudices that the 
respondents in a survey -based meas urement may have. This paper has established that all three 
release time measures relying on technology -based time stamps —the CBIC dwell time study, the 
LDB dwell time report, and TRSs —produce similar results, at least in terms of trends over a period 
of time, if not the actual time taken (in hours) at a particular point in time. We also find that the 
improvements reported by these three measures find correlation in the survey -based EODB TAB 
(albeit with a lag) and, thereafter, a sharp correction that is al igned with all three measures.  
16.7.   The story is, however, different in the case of indicators that seek to measure the availability 
and implementation of enablers that are meant to assure this improvement in cargo release time. 
The enablers that have been cove red in this paper could be the specific trade facilitation measures 
specified in the TFA, the level of automation, the quality of physical infrastructure at the ports and 
airports, the efficiency of the logistics supply chain dealing with international car go, or the overall 
quality of governance. The measurement of the degree to which these have either been implemented 
(if they are trade facilitation measures) or the extent to which they obtain in the economy (if they 
relate to infrastructure or governance)  is inherently subjective and based on the individual 
assessment or perception of the respondents. Further, the challenges relating to the specific 
methodology of the survey -based studies are evident from the belated "fine-tuning " of the results 
by the OEC D, as discussed in this paper, and the recent decision of the World Bank to conduct "a 
systematic review and assessment of data changes that occurred subsequent to the institutional 
data review process for the last five Doing Business reports " following ce rtain irregularities in the 
reports for 2018 and 2020.25 
16.8.   In summary, we have found some dissonance both in the movement exhibited by the 
composite indicators inter se, as well as between the composite indicators and the release time 
indicators. We have fou nd that composite indicators, with their ambitious objective of measuring the 
performance of enablers of trade facilitation and EODB, among other aspects, are still grappling with 
various methodological and data challenges. The indicators based on technolo gy-driven release time 
data have more modest objectives but present more credible and consistent results. Further, it is 
likely that there is an intertemporal relationship between availability and implementation of such 
enablers as the creation of infrastr ucture and a reduction in formalities and their effect on release 
time. More sophisticated statistical research would need to be undertaken, with data for a longer 
period, to ascertain and quantify such a linkage.  
16.9.   Moving forward, we are of the view that si milar studies for other economies or groups of 
economies will give policymakers and administrators associated with trade facilitation and EODB 
greater insights into the performance of their economies, even as we acknowledge the present 
limitations of such studies. Such studies would also indicate whether the mixed results obtained in 
the case of India are particular to the nation or similar results can be found for other economies. In 
 
25 World Bank, "Doing Business —Data Irregularities Statement," press release, 
27 August  2020,  https://www.worldbank.org/en/news/statement/2020/08/27/doing -business ---data-
irregularities -statement . G/TFA/W/84  
 
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  the event of the latter, it would become imperative to revisit the method ology of the study and 
strengthen the coordination with the concerned nations ' representatives. As noted earlier in this 
paper, both the OECD TFIs and World Bank EODB are being subject to review. We expect these 
issues to be resolved over time with more ro bust methodologies and greater recourse of 
technology -based data sourcing in preference to survey -based analyses.  
 
  G/TFA/W/84  
 
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  ABBREVIATIONS  
CBIC Central Board of Indirect Taxes and Customs  
CFS container freight station  
DFD direct port delivery  
CRAR  Credit Rating Agencies Regulation  
EODB  ease of doing business  
GATF  Global Alliance for Trade Facilitation  
GCI Global Competitiveness Index  
GSTF-PTI Global Survey on Trade Facilitation and Paperless Trade Implementation  
ICD inland container depot  
IT information technology  
JNCH  Jawaharlal Nehru Custom House  
JNPT Jawaharlal Nehru Port Trust  
LDB Logistics Data Bank  
LPI Logistics Performance Index  
NCTF National Committee on Trade Facilitation  
NTFAP  National Trade Facilitation Action Plan 2017–2020 
OECD  Organisation for Economic Co -operation and Development  
RFID radio-frequency identification  
SMEs  small - and medium -size enterprises  
TAB Trading Across Borders  
TFA Trade Facilitation Agreement  
TFI trade facilitation indicator  
TRS Time Release Study  
TTLC Total Transport and Logistics Cost  
WCO World Customs Organization  
WEF World Economic Forum  
WGI World Governance Indicator  
WTO World Trade Organization  
 
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