Magic Mirror in My Hand…. How Trade Mirror Statistics Can Help Us Detect Illegal Financial Flows

Gara, Mario; Giammatteo, Michele; Tosti, Enrico

doi:10.2139/ssrn.3212626

Cited by 4 publications

(5 citation statements)

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“…Muhammad and Countryman (2019) analyse the impact of fraudulent behavior on Chinese wine imports by combing information on traded quantities and prices at the 6-digits product classification and on fraud mentions in the media. Gara et al (2019) study inconsistencies in the mirror statistics at the 6-digits product classification between two partner countries to create an indicator of the potential risk of observing an illegal transaction.…”

Section: Literature Reviewmentioning

confidence: 99%

“…For each record, we observe the trade flow type, that is import or export 2 , and the two partner countries. In presence of mirroring trade flows, we average between the reported values (for more details on mirror statistics using Comtrade data, see Hamanaka, 2012 andGara et al, 2019). We remove all intra-EU trade flows and consider the EU as a unique trade partner.…”

Section: Datamentioning

confidence: 99%

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Detecting Anti-dumping Circumvention: A Network Approach

Barbaglia

Croux

Wilms³

2022

SSRN Journal

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Section: Literature Reviewmentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Detecting Anti-dumping Circumvention: A Network Approach

Barbaglia

Croux

Wilms³

2022

SSRN Journal

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“…Gara et al (2018) analysed the mirrored data of Italy’s external trade from 2010 to 2013 at 6-digit level of goods classification and found robust correlations between trade gaps and differential tariff and income tax rates, and trade openness.…”

Section: Survey Of Literaturementioning

confidence: 99%

Illicit Financial Flows through Trade Mis-Invoicing in India: An Empirical Analysis of the Major Commodities Involved in Mis-Invoicing

Tiwari

Akhter

Chattopadhyay

2022

South Asian Journal of Macroeconomics and Public Finance

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This article identifies, based on reported trade data between India and its 19 trading partners, the major commodities exhibiting mis-invoicing during 2000–2018, the extent of mis-invoicing, major trade partners and the associated ports of trade in India. The computed differences in the trade values are too large to be explained by accounting or classification errors, presenting strong evidence of mis-invoicing; however, only a small percentage of commodities account for bulk of mis-invoicing consistently over the years. There is also evidence of the same commodities exhibiting under-invoicing (UI) in trade with some countries and over-invoicing (OI) in trade with others. The tariff rates seem to influence the type of import mis-invoicing—OI being mainly in commodities with higher tariff and UI in commodities with lower tariff. The article contributes to the existing literature by identifying the specific commodities with their 6-digit HS codes, and commodity groups prone to mis-invoicing, which can provide a robust framework for further investigation of transaction level data that may help pinpoint the parties involved in mis-invoicing and associated illicit flows. The findings of the article provide inputs for policies to mitigate the impact of illicit financial flows through trade mis-invoicing. JEL Classification: F13, F14, C32, H26

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“…As an alternative, literature focused on PCM employed an aggregated trade data by partner-HS6 level, sourced from UNCOMTRADE. While the aggregation process may offset the magnitude of under-and over-valuation, the literature (Berger & Nisch, 2008;Carrere & Grigorious, 2014;Fisman & Wei, 2004;Gara, Giammatteo & Tosti, 2018;Kellenberg & Levinson, 2016) evidenced the correlation between trade gaps and the attributes of trade transactions such as tariff rate and corruption of trading countries, suggesting that PCM at the partner-HS6 level is still useful and informative in assessing the risk of trade mis-invoicing.…”

Section: Overviewmentioning

confidence: 99%

Identifying Trade Mis-Invoicing Through Customs Data Analysis

Soo Choi

2019

World Customs Journal

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This paper outlines a methodology for identifying trade transactions where undervaluation or over-valuation is highly suspected. As a first step, the methodology identifies trade transactions with an abnormal unit price. Secondly, it identifies trade transactions with values different from those noted in the records of trading partners. Finally, it presents the trade transactions that were commonly selected from the previous steps. The logic underlying the methodology is that if a trade transaction has an abnormal unit price as well as irreconcilable differences in the trade value ascribed by the trading partner, it would be reasonable to suspect under-valuation or over-valuation in the transaction. In a simulation using actual customs data, this methodology proved effective in detecting fraudulent imports. Of the imports suspected of under-valuation using this methodology, 18 per cent had been penalised and obliged to pay fines, more taxes or duties following customs interventions. This figure is much higher than the share of illicit imports in the test data (4.5%) and the targeting accuracy of the physical inspection of the country (12%). When this methodology was verified using only the imports that had been selected for physical inspection, the targeting accuracy increased to 36 per cent. The result suggests that this methodology could contribute to enhancing the targeting accuracy of existing Customs risk management tools.

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Magic Mirror in My Hand…. How Trade Mirror Statistics Can Help Us Detect Illegal Financial Flows

Cited by 4 publications

References 0 publications

Detecting Anti-dumping Circumvention: A Network Approach

Detecting Anti-dumping Circumvention: A Network Approach

Illicit Financial Flows through Trade Mis-Invoicing in India: An Empirical Analysis of the Major Commodities Involved in Mis-Invoicing

Identifying Trade Mis-Invoicing Through Customs Data Analysis

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