Political Connections and Tariff Evasion Evidence from Tunisia

Are politically connected entrepreneurs more likely to evade tariffs? At issue are not only inequity and fiscal losses but also inefficiency since tariff evasion endows perpetrators with a cost advantage over those who are compliant that is not based on performance. The question is especially relevant for developing countries, as they tend to be disproportionately reliant on revenues collected by customs to finance public expenditures (Jean and Mitaritonna 2010),¹ are characterized by a greater prevalence of problematic state-business relationships (Faccio 2006), and often have weaker tax collection capacity (Slemrod and Yithzaki 1999).

Using a unique dataset in which importing firms owned by former president Ben Ali and his family confiscated in the aftermath of the Jasmin Revolution are identified, this paper examines whether politically connected enterprises were more likely to evade tariffs during Ben Ali's tenure. Their behavior is compared with that of public firms and other private sector firms, which can be categorized into two types, notably “onshore” firms and so-called “offshore” firms, which are exempted from having to pay tariffs used in the production of exported output (or output sold to other offshore firms) and consequently have less incentive to evade tariffs. Such “offshore” firms can sell up to 30% of their output in the domestic market. If they chose to do so, they have to pay import tariffs over the share of production sold domestically.

More specifically, politically connected enterprises are identified in firm-product-source country customs data spanning the universe of import transactions. These are merged with UNCTAD data on HS6 exports to Tunisia by country and year to compute evasion gaps (Fisman and Wei 2004), defined as the discrepancy between exports to Tunisia reported by partner countries minus imports of the same product from that source country reported in Tunisia. Such evasion gaps are a useful proxy for the amount of imports that are underreported (or misreported) and thus not taxed (appropriately) and hence have become a standard indicator of tariff evasion (Fisman et al. 2008; Jean and Maritonna 2010). If connected firms are more prone to evade tariffs, evasion gaps should increase with the share of imports accounted for by connected firms. In addition, the correlation between the import share of connected firms and evasion gaps should strengthen with the tariff rate, since evasion is more lucrative when taxes are high. Moreover, gaps can be expected to decrease in product-source lines in which connected firms were operating after they lose such connections as a result of being confiscated.

The data also enable us to examine whether the elasticities of connected firms' reported import values, quantities, and prices, with respect to tariffs, are different from those of nonconnected firms, which is our second test for tariff evasion. If Ben Ali firms are more likely to evade tariffs, one would expect their reported imports to decrease disproportionately faster with tariff increases than those of other firms. Comparing the responsiveness of reported unit prices and import quantities across different groups of firms helps assess to what extent evasion occurs through underreporting of prices and mis- or underreporting of quantities. In addition, a difference-in-difference strategy comparing the import declarations of firms privatized to the Ben Ali family with those of firms privatized to non–Ben Ali family members is deployed to identify the impact of becoming connected on reported unit prices.

Tunisia, a small open economy at the forefront of the Arab Spring, provides an interesting case study of which firms are most likely to engage in tariff evasion for several reasons. To start, the Ben Ali family had extensive business interests and several of its members have been convicted for (ab)using their political power for personal gain, limiting competition in the process (Rijkers et al. 2014b). Establishing leading positions in the import of key consumer products including cars and electronics appears to have been an important strategy by which the family reaped rents (Beau et Graciet 2009; World Bank 2014a). Second, Tunisia has been one of the most successful exporters in Northern Africa and is rather reliant on imports, which amount to roughly half of its GDP, with customs revenues accounting for 9% of fiscal revenues. Third and related, its export success is to a large extent due to tax regulations that stipulate that the so-called offshore firms do not have to pay import duties on goods that they (use to produce goods that they) export. As alluded to above, this diminishes their incentives to engage in tariff evasion. Fourth, Tunisian customs authorities are considered among the most corrupted of all government institutions by Tunisian citizens and companies (ATCP 2015; ITCEQ 2012). While the Tunisian customs code is consistent with best practices defined by the World Customs Organization,² its implementation is discretionary (World Bank 2014b).³ The combination of a bewildering complexity of import regimes allowing for suspension of import duties and very weak administrative controls, including a severely defunct IT system, render effective enforcement challenging. Last but not least, Tunisia has great administrative data and authorities willing to share those, enabling us to unambiguously identify politically connected firms as those who were confiscated in the aftermath of the Jasmin Revolution.

By providing evidence suggesting that politically connected firms are more likely to evade tariffs, this paper contributes to and combines different strands of literature. To start, a large literature, pioneered by Bhagwati (1964, 1967) and popularized by Fisman and Wei (2004), has used discrepancies between trade flows reported by trading partners to show how tariff evasion varies with product characteristics, tariff rates (Javorcik and Narcisko 2008; Fisman and Wei 2009), enforcement (Mishra et al. 2008), customs organization, and country characteristics such as level of corruption or bureaucracy efficiency (Jean and Mitaritonna 2010; Carrère and Grigoriou 2015). However, there is still no research that the authors are aware of that examines which type of entrepreneurs are most likely to evade import taxation.⁴

Second, by unveiling an additional mechanism by which firms may benefit from political connections, the paper helps explain why political connections tend to be valued highly (Fisman 2001; Faccio 2006; Faccio et al. 2006; Johnson and Mitten 2003). Though quantifying the costs associated with tariff evasion is challenging, a highly conservative back-of-the-envelope calculation presented in section V suggests that between 2002 and 2009, underreporting of unit prices alone enabled Ben Ali–owned firms to evade 1.2 billion USD worth of import taxes more than other private firms would have; this estimate does not consider other types of tax fraud, such as smuggling or underreporting of quantities. It also does not consider the indirect costs of this type of fraud, in terms of a lack of transparency and market distortions limiting incentives to invest and hampering efficiency. Our findings also resonate with earlier studies on trade-related corruption by Mobaraq and Purbasari (2008) and Khandelwal et al. (2013), which demonstrated that politically connected firms were prone to firm-specific preferential treatment in being granted exclusive and inefficient import licenses.

Third, by showing evidence suggestive of abuse of power by the ruling elite, our results also contribute to the literature on state-business relationships in the Middle East and Northern Africa (Acemoglu et al. 2014; Diwan et al. 2014) and (indirectly) the economics of the Arab Spring (Campante and Chor 2012; Malik and Awadallah 2013).

The remainder of this paper is organized as follows. The next section briefly reviews related literature and discusses why firms might differ in their propensity to evade tariffs. Testing strategies are presented in section two. Data and descriptive statistics are presented in section three. Product-level regressions are presented in section four, while firm-level regressions are presented in section five. Section six concludes.

I. Why Do Firms Differ in Their Propensity to Evade Tariffs?

Models of tax compliance predict tax evasion, the circumvention of taxes through illegal practices, to increase with the tax rate, and to decrease with the probability of detection, penalties for evasion, risk aversion, and opportunities to avoid taxes (through legal means) (see Alm 1999; Andreoni et al. 1998; Slemrod 2007; and Slemrod and Yithzaki 2002 for reviews of the literature). These factors are likely to vary across different types of firms.

Starting with punishment, detection, and risk-aversion, connected firms faced both a lower risk of being caught and lower penalties conditional on being caught and might have been less risk averse as connected entrepreneurs were on average wealthier than nonconnected ones. Customs officials who had been working in the risk management unit during the Ben Ali era told us that fraudulent behavior by Ben Ali firms was less likely to be reported in part because of career concerns and fear of retaliation from the family. Ben Ali entrepreneurs also appear to have been very well informed of customs risk management practices and control criteria. According to customs officials we interviewed, they “continuously adapted their tactics in response to newly introduced [anti-corruption] measures.”

Connected firms may also have enjoyed greater opportunities for tax avoidance (through legal means); anecdotal evidence suggests connected firms may have had privileged access to duty exempted import regimes.⁵ Tax exemptions to promote exports were also very important for offshore firms; since they do not have to pay import tariffs for goods used to manufacture exports (or sold to other offshore firms), their incentives to evade are limited compared to those faced by onshore firms. Moreover, such tariff exemptions may make detecting evasion by offshore firms relatively more challenging than detecting fraud by onshore firms.

State-owned firms might have had weaker incentives to evade tariffs because they have softer budget constraints and may not be purely profit-oriented and because the compensation of public sector firms does not covary with firm profits to the same extent as is the case in private sector firms (Brockmeyer et al. 2015).⁶ Moreover, financial reporting is typically weak in Tunisian SOEs and overinvoicing imports is often used to reduce possible taxable profits, which can in turn help generate extra funding for the SOE (Banque Mondiale 2014). At the same time, the relative inefficiency of SOEs may incentivize evasion to stay cost-competitive. In sum, managers of public sector firms face mixed incentives.

Since connected entrepreneurs arguably have some sway over policy making, one may wonder why they do not simply exempt themselves from having to pay tariffs at all, or use their political clout to remove (or at least lower) tariffs. In practice, Ben Ali firms did not on average face lower tariffs, as is demonstrated in section III. One possible explanation is that they benefitted to some extent from tariffs, as these reduce foreign competition (Grossman and Helpman 1994; Goldberg and Maggi 1999). This explanation is consistent with evidence suggesting that sectors in which connected firms were active were more likely to be subjected to new restrictions on foreign investment (Rijkers et al. 2014b), which enhanced the market power of connected firms. Moreover, evasion is all the more advantageous when competitors are forced to pay higher taxes. Reducing tariffs would not only help connected firms but also their competitors. Another possible explanation is that the scope for influencing tariff setting might have been limited by Tunisia's WTO membership and international trade agreements, which predated the aggressive expansion of the Ben Ali business empire after the turn of the millennium.

In short, connected entrepreneurs may be more likely to evade tariffs because they face a lower risk of being caught and lower penalties conditional on being caught and because they might be less risk averse. At the same time, they might also be more successful at lobbying for tax breaks, which would diminish their incentives to evade tariffs. Offshore firms are able to avoid taxes when they export and thus have weaker incentives for evasion, while public sector firms face mixed incentives.

II. Econometric Strategy

Two complementary strategies are deployed to test whether connected firms are more likely to evade taxes. The first, product-level, approach relates trade evasion gaps to the relative importance of Ben Ali owned importers and examines how such gaps changed in the aftermath of the Jasmin Revolution. The second, firm-level approach assesses whether the value, quantity, and price of connected firms' imports decline more rapidly with tariffs than those of nonconnected firms. A difference-in-difference strategy comparing privatizations to the Ben Ali family with other privatizations is deployed to isolate the impact of becoming connected on reported unit prices.

Do Evasion Gaps Increase with the Presence of Connected Firms?

Four different proxies for the import shares of different types of firms are used, notably: (i) the aggregate share of the value of all reported imports in a given HS6-country-year cell, (ii) the aggregate share of the total reported quantity imported in that cell, and (iii) the share of all firms that report importing product p from country s at time t. Neither of these proxies is ideal; the latter implicitly assumes homogeneity across importers within an HS6-country pair. The first two measures arguably better account for the relative size of different types of firms, yet they may themselves be affected by differential underreporting and/or misclassification. Indeed a problem with this identification strategy is that underreporting or even nonreporting of imports can be very difficult to detect. In the extreme case in which Ben Ali firms imported goods but simply did not report them at all, they would not appear in the data altogether. To remedy this problem, (iv) the predicted import share of the different types of firms is used as an alternative proxy, which is constructed using a combination of tax and firm census data and an input-output table that does not rely on reported imports but rather on production data (see the supplemental appendix or the working paper version of this article (Rijkers et al. 2015) for details and results using these alternative proxies).

Since the last year for which NTB data are available is 2010, the values for 2011, 2012, and 2013 are all imputed using the 2010 value. If connected firms were more likely to engage in tariff evasion, this effect should diminish after the Jasmin Revolution, especially in product lines subject to high tariffs, where evasion is expected to be greatest; in this case $βPTBA<0$⁠.

Do Connected Firms Report Lower Import Values, Quantities, and Prices (When Tariffs are Higher)?

The identifying assumption underpinning this strategy is that once their output, labor usage, age, and sector are accounted for, there is no reason why Ben Ali firms would import less of goods that are subject to higher tariffs than other firms importing the same product from the same source country in the same year would other than their proclivity to evade taxes.¹⁰ This assumption might be flawed, for instance if Ben Ali firms are better negotiators and more successful at bargaining for lower prices for products subject to high tariffs. Alternatively, if it were easier for Ben Ali firms to substitute away from using high-tariff imports (perhaps because they are more likely to obtain import licenses) than for other firms, then a negative coefficient β_T might be misinterpreted as evidence for tariff evasion. The strategy obviously also does not detect pure smuggling, though it helps detect difference due to misclassification and underinvoicing of imports conditional on reporting.

III. Data and Descriptive Statistics

In the aftermath of the Tunisian revolution, assets of the Ben Ali clan were confiscated. The confiscation process, which is still ongoing, affects 114 individuals, including Ben Ali himself, his relatives, and his in-laws, and concerns the period from 1987 until the outbreak of the revolution.

We obtained from the Tunisian authorities a list of 662 firms that were owned by the Ben Ali clan and confiscated in the aftermath of the revolution (before December 2014) and were able to identify 206 of these firms as importers by merging the business register, the Repertoire National des Enterprises (RNE), with annual firm-HS6 product-origin data on import transactions for the period 2000–2009 from Tunisian customs. The RNE contains information on the age, sector, and employment of all registered nonagricultural firms operating in Tunisia, including for firms not employing any salaried workers, that is, the self-employed (see Rijkers et al. 2014a). Moreover, it has information on firms' tax status and whether or not firms are publicly or privately owned. These data are complemented with information on output declared to the Tunisian tax authorities from the Tunisian Ministry of Finance.

Thus, not all Ben Ali–owned importers are identified. However, the vast majority are included in our sample, which is most likely skewed towards the largest and economically most relevant firms since these are easier to identify (and hence also easier to confiscate).

In order to calculate evasion gaps and assess how they relate to tariffs, the Tunisian HS6-product-origin import data are merged with bilateral tariff data by product from WITS, which is available for 2002–2009, though missing for 2007 and 2009, for which tariff data from 2006 and 2008, respectively, are used instead; data on nontariff measures by product are available for the period from 2000 to 2010 and information on imports and exports to Tunisia by HS6 product and year from COMTRADE for the period from 2002 to 2013. To ensure the results reflect systematic mismatches, rather than erratically reported incidental transactions, the sample is confined to (i) products which account for more than 0.01 percentage points of cumulative total exports to Tunisia reported by partner or more than 0.01 percentage points of cumulative imports reported in Tunisia over this period.¹¹ In addition, (ii) the focus is on the top fifteen source countries in terms of total import value reported in Tunisia or total export value declared in source countries¹² and (iii) HS6-source country-year combinations for which both reported imports in Tunisia and reported exports by partner countries are positive.¹³ The resulting sample comprises 1,386 products and sixteen countries,¹⁴ which cover 69.75% of all exports to and 61.03% of all imports declared in Tunisia. In addition, product-level information on nontariff measures from the World Bank (Malouche et al. 2013) is used.

Table 1 presents descriptive statistics for different types of firms. The 206 connected importing firms are on average larger and more diversified than other private firms; while they comprise only 0.7% of all importing firms, they account for 2.3% of all imports over the period considered. Even more striking, 124 public firms (0.44% of all firms in our sample) together account for more than a quarter of all import value over the period. By contrast, private “onshore” importers, which represent nearly three-quarters of all importing firms, tend to be the smallest and the least diversified, accounting for 38% of reported exports. “Offshore” importers that specialize in exports are comparatively large. Note also that connected firms do not, on average, face lower tariffs or fewer nontariff measures.

Table 2 presents descriptive statistics on average evasion gaps at the source-country-year level for the entire sample and by dominant importer type, by tariff level. It discriminates between, respectively, Ben Ali, offshore, onshore, and public sector–dominated products, depending on which type of firm is the dominant importer based on aggregate import value; that is, goods for which Ben Ali (public/onshore/offshore) firms account for more than 50% of the value of all reported imports from a given country in a given year are classified as Ben Ali (public/onshore/offshore) dominated. Goods for which there is not a single dominant importer are classified into a residual “mixed” category.

Average log evasion gaps in terms of import value are very small. The value of imports recorded in Tunisia is on average 0.1 percentage points higher than the export value reported in partner countries. Arguably more informative are differences in evasion gaps between goods subjects to high tariff vis-à-vis gaps goods subject to low tariffs. Average evasion gaps for goods subject to high tariffs, that is, subject to a tariff rate of at least 36 percentage points, are positive and approximately 9.9 percentage points. By contrast, gaps for goods subject to low tariffs are minus 10.4 percentage points. Thus, goods subject to higher tariffs seem more prone to tax evasion, and such evasion is likely taking place through misclassification of goods.

More striking are the differences across dominant importers. Log evasion gaps for goods for products for which onshore firms are the dominant importer are −0.04 on average, but 0.09 for goods subject to high tariffs. Log evasion gaps for goods for which offshore firms are the dominant importer are around 0.07 and do not seem to vary much with tariffs. By contrast, log gaps for Ben Ali–dominated products are on average approximately 0.36 and a striking 0.80 for goods subject to high tariffs. Gaps are consistently negative for goods for which public firms are the most prominent importers, which is consistent with overinvoicing of imports. Thus, prima facie, the results are suggestive of evasion of tariffs by politically connected firms, as well as overreporting of imports by public firms.

Average log evasion gaps in terms of quantities and prices, presented in panels B and C, respectively, are also small on average, notably 0.02. Quantity gaps are on average somewhat higher for goods subject to high tariffs (0.08) and negative for goods subject to low tariffs (−0.11), which hints at misclassification. The difference in average evasion price gaps between goods subject to low and high tariffs is very small. The standard deviation of price gaps is much lower than that of quantity gaps.

Evasion strategies seem to vary by firm type; while all firm types appear to misclassify goods to some extent (as is evidenced by the fact that across the different dominant importer types evasion gaps are consistently higher for goods subject to high tariffs than for goods subject to low tariffs), price underreporting is most egregious in Ben Ali–dominated product lines subject to high tariffs, for which gaps are as high as 0.47.¹⁵

Can differences between connected and other firms operating in the same five-digit industry and importing the same product from the same country in the same year be detected? Table 3 presents information on average firm-level import values, quantities and unit prices, normalized by the product-source-industry-year average (which is normalized to be equal to 1), and documents descriptive statistics consistent with the product-level patterns; the declared value of Ben Ali firms' imports exceeds that of the average firm by 18%, and their declared import quantities are 21% higher than the average. Yet, their reported unit prices are on average 4.8% lower than those reported by a representative firm. For goods subject to low tariffs, Ben Ali firms' import prices are on a par with those of other firms, whereas for goods subject to high tariffs, their reported prices are 8.1% lower than the average. Onshore firms on average report lower import values and quantities, but their reported prices are very close to average prices. Public firms pay unit prices, which are on average 7.4% higher than other firms that simultaneously import the same HS6 product from the same country.

To sum up, exploratory descriptive statistics are indicative of considerable tariff evasion. They also suggest that connected firms are more likely to evade tariffs than other firms and that they were more likely to use undervaluation of prices as an evasion strategy than other firms. By contrast, underreporting and/or misclassification of import quantities seems to have been an evasion strategy that all types of firms engaged in. The next sections test these hypotheses more rigorously by estimating the models discussed in section II.

IV. Results: Evasion Gaps

This section first presents the main results, before examining to what extent tariff evasion was driven by misrepresenting quantities or prices. The section ends with an analysis of the evolution of evasion gaps in the aftermath of the Revolution.

Basic Results

Table 4 examines the determinants of log evasion gaps using two different models; in the first, simplistic model (presented in columns 1–3), the evasion gap is modeled as a function of the tariff rate and the share of imports accounted for by, respectively, Ben Ali firms, offshore firms, and public enterprises, with onshore firms being the reference group. The second, and preferred, model (referred to as the “interacted” model, presented in columns 4–6) adds interaction terms between the tariff and the value share of Ben Ali importers, offshore importers, and public importers. The coefficient on the tariff can thus (loosely)¹⁶ be interpreted as providing a crude approximation to the evasion elasticity of onshore firms. Standard errors are clustered at the product level. Progressively more elaborate sets of dummies are added when moving from the left side of the table to the right; columns 1 and 4 include country-year effects, columns 2 and 5 add product fixed effects, while columns 3 and 6 control for both country-year and country-product fixed effects. Although the specification in column 6 is in principle our preferred specification as it offers the most rigorous test for differences in evasion across firms, it is important to bear in mind that including both country-year and country-product fixed effects absorbs a lot of the variation of interest.

The results presented in column 1 are consistent with substantial tariff evasion; the tariff rate is a strongly significant predictor of the evasion gap, and the estimated evasion elasticity is 0.058. Once product and country-product dummies are included (columns 2 and 3), the coefficient on the tariffs drops and loses statistical significance, which is presumably at least in part due to the fact that tariffs do not vary dramatically across countries and over time and that out of necessity it was assumed that they were equal to tariffs in the preceding years for two years for which tariff data were missing altogether (see the appendix). The ability to nonetheless identify significant interactions between the tariff rate and the import shares accounted for by different firms (columns 4–6) is due to variability in these import shares (rather than the tariffs themselves) over time.

Turning to the main result, connected firms are more likely to evade tariffs. To start with, evasion gaps are strongly positively correlated with the share of import value accounted for by Ben Ali firms in the simple specification (column 1). This association is robust to controlling for product fixed effects (column 1) but not to country-product fixed effects (column 3). More importantly the interaction between the Ben Ali proxy and the tariff measure is consistently positive and significant in the preferred interactive specifications (columns 4–6), consistent with the hypothesis that connected firms are more likely to evade tariffs. This result is robust to controlling for product (column 5) and even country-product fixed effects (column 6). The regressions thus strongly reject the null hypothesis that connected firms do not differ in their evasion propensity from other firms and are instead consistent with connected firms evading more.

By contrast, offshore firms seem less likely to engage in tariff evasion; once product and product-source dummies are conditioned, the coefficient on offshore importers is negative and statistically significant in the simple specification and the interaction between the tariff and the import share of offshore firms is significantly negative in the interacted specification. Evasion gaps are also significantly negatively correlated with the share of imports accounted for by public firms in the simple specification without interaction terms, pointing towards possible overinvoicing of imports by such firms.

Misrepresentation of Quantities or Prices?

To assess whether the documented evasions gaps are due to (i) underreporting of misclassification of import quantities or (ii) underreporting of prices, table 5 presents estimates of the same regressions using as dependent variable log evasion gaps in weights (columns 1–4) and unit prices (columns 5–8). It replicates the models that only condition on country-year dummies (presented in columns 1, 3, 5 and 7), as well as the models that condition on country-year as well as country-product dummies (presented in columns 2, 4, 6 and 8).