To carry out their various missions (collecting revenue, facilitating trade, and ensuring security), many customs administrations have established a risk management unit. In developing countries, however, because of the lack of dedicated human and material resources, intelligence and risk analysis remain insufficiently developed. In view of the lack of resources, this paper proposes a simple methodology aiming at detecting risky import operations. The mirror analysis first helps to identify and target products or sectors with the greatest risk.

Based on the examination of customs declarations patterns (data mining), it is possible to identify and target higher risk economic operators (importers and customs brokers). When implemented in Madagascar, this method has helped to reveal probable fraud cases in the present context of customs reform. Estimates suggest that, in 2014, customs fraud reduced non-oil customs revenues (duties and import value-added tax) by at least 30 percent.

Introduction

With a per capita gross domestic product (GDP) of US$449 (2014), Madagascar is one of the five poorest countries in the world. To finance the country’s development, there must be a significant increase in the state budget. With this end in view, the tax revenue ratio, which is one of the lowest in Africa (around 10% of GDP), should increase.

In order to increase domestic revenue mobilization, Madagascar revenue collection authorities (i.e., tax and customs administrations) should notably combat fraud more effectively. The fight against tax evasion involves that revenue collection authorities should detect more to deter more. To this end, the analysis of discrepancies in international statistics may be very helpful. Zucman (2013) uses the differences between international assets and liabilities to evaluate the degree of tax evasion by households. Based on Bhagwati (1964), Raballand et al. (2012) use discrepancies in trade statistics to identify and assess customs frauds. In a perfect scenario, any statistical anomaly—that is, any difference between the declared export value (price, volume, weight) and the declared import value for the same trade flow, is suspect. When exports are not taxed, the exporting company has no incentive to make a non-compliant declaration. In such a situation, assuming that the gap is due to the importer is therefore a reasonable assumption.

Using original customs data, this paper aims to identify, in Madagascar, some high-risk products and high-risk operators (importers and brokers). The proposed method is complementary to risk analysis methods based on compliance (see e.g. Geourjon and Laporte (2012)). A two-step procedure is adopted. Based on discrepancies in trade statistics (mirror statistics), the paper presents products or sectors in which customs fraud is deemed to be significant. A quantification exercise of customs losses is provided. Then, through the use of highly disaggregated customs data, high-risk operators (importers and brokers) are identified.

Despite the fact the methodology is straightforward, to our knowledge there is hardly any paper using this approach (at the importer/broker level) due to the fact that it is usually difficult to get access to such information. The paper demonstrates how useful such detailed customs data can be and should convince the Head of Customs and/or Ministers of Finance to give access to them to researchers, since they can be used for an operational use. For researchers, it enables to identify some fraud techniques and collusive practices.

The use of export data provided by exporting countries allows us to compute for each sector/product the mirror gap. The mirror gap is, for each product/sector, defined as the difference between export X to Madagascar reported by the exporting country and import M from the exporting country as reported by Madagascar customs. Export data are downloaded via the United Nations platform COMTRADE. Notice that, in view of the time lag in uploads to COMTRADE, by the national institutes of statistics, a wait period of a few months should be observed before downloading the most recent annual bilateral trade data. Due to this time lag, the mirror analysis cannot identify new trends in customs fraud in Madagascar.

Based on mirror gaps, we are then able to identify some sectors/products for which noncompliance seems common. Estimates suggest that undervaluation and misclassification in 2014 accounted for a loss of revenue of US$53.7 and US$42.4 million, respectively.

Total estimated losses (96 million of US$ or MGA 232 billion) represented 30 percent of total non-oil revenues collected by customs. The analysis indicates that clothing (textile, footwear and leather goods) and high tech products (telephones, digital cameras) seemed to be substantially undervalued in 2014. Undervaluation of clothing products and telephones (and digital cameras) are, respectively, estimated at US$25.4 million and US$13.6 million.

Regarding misclassification, the paper highlights that, in Madagascar, some customs tariff headings not subject to duties and value-added tax (VAT) were probably used, in 2014, for tax evasion purposes. Considering that abnormal statistics (e.g. inconsistent unit values) are indicative of fraud, there is reasonable evidence that some high-taxed goods were declared as zero-taxed products, notably fertilizers and rice. The declared unit value of imports of rice and fertilizers (products exempt from duties and VAT) largely exceeded corresponding world prices. Based on discrepancies in trade statistics, we estimate losses in VAT revenues at US$12 million. Despite the fact that rice imports were almost systematically physically inspected, i.e., directed through the red channel, very few infractions had been reported. This figure suggests that there were probably collusion agreements between some economic operators and some customs agents. As the number of reported cases of fraud sharply increased in 2015, such bad practices seem to have declined.