Smuggling illegal versus legal goods across the U.S.-Mexico border: a structural equations model approach.

• Author: Buehn, Andreas

1. Introduction

   In this article, we study smuggling across the U.S.-Mexico border from 1975 to 2004. We contribute to the literature in the following ways: First, we treat smuggling as an unobservable variable. Using a Multiple Indicators Multiple Causes (MIMIC) model we capture the latent nature of smuggling and identify its determinants and long run trends.1 Secondly, we argue that the analysis of smuggling has been incomplete so far; existing studies merely analyze the causes of trade misinvoicing--illegal trade or smuggling of legal goods--which represent only a fraction of total illegal trade. To improve the understanding of illegal trade, we distinguish between smuggling illegal goods versus smuggling legal goods.

   The types of smuggling differ with respect to the goods being smuggled, the agents involved in smuggling, the smuggling incentive, and the intensity of law enforcement. Trade misinvoicing occurs when entrepreneurs misreport the value of legal exports or imports to evade tariffs and taxes and is commonly considered a peccadillo: Smugglers usually bribe officials or are fined a fee. Smuggling illegal "freight" such as illicit drugs and illegal immigrants, however, often involves dangerous criminals who commit serious offenses and who, if caught, face severe punishment. As a result, their incentive to smuggle is related to the intensity of law enforcement rather than tax or tariff evasion.

   Studying the U.S.-Mexican case is appropriate, as most illegal drugs and immigrants enter the United States via the Mexican border. The large income disparity between the two nations may explain the high U.S. demand for illegal goods, which relatively poor Mexicans are willing to meet despite the risks involved. We examine whether the Clinton and Bush Administrations succeeded in reducing smuggling across the border through intensified border enforcement.

   Using a simple microeconomic framework, we determine which microeconomic incentives affect the two types of smuggling. The hypotheses are then tested in a MIMIC model that studies the impact of observed causes (the microeconomic incentives to smuggle) on the latent phenomenon, smuggling, as indicated by observable macroeconomic variables. Applying the benchmarking procedure promoted by Dell'Anno and Schneider (2006) and Dell'Anno (2007), we calculate a time series for each type of smuggling. We find that smuggling in illegal goods from Mexico to the United States decreases when Mexican labor market conditions improve and U.S. border enforcement is intensified. The Mexican recessions in 1982-1983 and 1995 led to large temporary increases in smuggling to $113 billion and $87 billion, respectively. Smuggling in illegal goods decreased overall, however, from $116 billion in 1984 to $27 billion in 2004; this reduction can be attributed to stricter U.S. border enforcement and better Mexican job prospects.

   Smuggling legal goods is driven by real exchange rates and tariff and tax evasion. Export misinvoicing fluctuated between underinvoicing values of $0.2 billion and overinvoicing values of $0.7 billion, while import misinvoicing switched from underinvoicing, peaking at $1.6 billion in 1983, to recent overinvoicing--up to $3.8 billion in 2002. This pattern can be attributed to substantial tariff reductions in accordance with the GATT in 1987 and the North American Free Trade Agreement (NAFTA) in 1994.

   The rest of the article is organized as follows. Section 2 reviews the smuggling literature. Section 3 considers the incentives driving the two types of smuggling in a microeconomic framework. Section 4 explains the empirical methodology. Section 5 describes the indicators of smuggling. Section 6 presents the estimation results and long-term trends for the smuggling of illegal and legal goods. Section 7 concludes.

2. Literature

   The existing smuggling literature focuses on trade misinvoicing, that is, the false declaration of legal imports and exports. One strand of the theoretical literature analyzes the welfare effects of trade misinvoicing. Bhagwati and Hansen (1973) show that despite the classic view, smuggling can distort welfare, as legal traders are squeezed out by smugglers who operate at inferior terms of trade but profit by circumventing tariffs. Pitt (1981) shows that the welfare consequences of smuggling are ambiguous. He argues that legal trade and smuggling coexist as firms camouflage their smuggling activities by also conducting legal trade.

   Another strand of the theoretical literature, initiated by Pitt (1981), analyzes the determinants of trade misinvoicing. Pitt argues that smuggling is positively correlated with the price disparity, defined as the difference between the actual domestic price and the tariff-inclusive world market price. If, for example, the domestic price of an exportable good exceeds its world market price, it can only be exported legally at a loss, indicating that most of the actual exports are traded illegally. Martin and Panagariya (1984) and Norton (1988) consider the costs of smuggling. They find that stricter law enforcement serves as a deterrent to smuggling. Pitt (1984) analyzes the black market premium (BMP) for foreign exchange as a determinant of smuggling. He finds that the black market equilibrates the supply of foreign exchange from illegal exports and its demand to purchase illegal imports. Biswas and Marjit (2007) find that export (import) underinvoicing is positively (negatively) correlated with the BMP, since the foreign exchange from the unreported transaction is sold (paid) on the black market.

   The empirical literature studies the determinants of trade misinvoicing using data on trade discrepancy. These studies conclude that if the import figures of the importing country fall short of (exceed) the export figures of the corresponding exporting country, import underinvoicing (overinvoicing) must be taking place in the importing country.2 As the empirical literature is vast, Table 1 provides a comprehensive overview and summarizes the findings of previous studies.

   Bhagwati (1964) analyzes trade data for Turkey and its major trading partners. He finds import underinvoicing for transport equipment and machinery. Both product categories feature high tariffs that by far exceed the BMP and thus motivate import underinvoicing. McDonald (1985) finds that export underinvoicing is positively correlated with export taxes and BMP. Pohit and Taneja (2003) conclude that informal trade between India and Bangladesh results in avoidance of administrative burden. Fisman and Wei (2007) find that misinvoicing for cultural properties is highly correlated with the extent of corruption in the exporting country. Berger and Nitsch (2008) confirm this finding for an extended set of product categories. Beja (2008) estimates the amount of China's unreported trade between 2000 and 2005 to be $1.4 trillion. Farzanegan (2008) estimates export and import misinvoicing in Iran using a MIMIC approach and finds that the smuggling of legal goods in Iran accounted for 6-25% of total trade between 1970 and 2002.

3. Micro-Foundations of Smuggling Incentives

   We argue that smugglers of illegal goods respond to different incentives than do smugglers of legal goods. The following uses a simple microeconomic approach to determine the expected impact of different determinants on both types of smuggling.3

   Determinants of Illegal Goods Smuggling

   The representative risk-neutral Mexican smuggler maximizes her expected profit with respect to the amount of illegal goods or persons to be smuggled into the United States, [S.sup.ill]. Equation 1 outlines the revenue from smuggling illegal goods, R([S.sup.ill]):

   R ([S.sup.ill] = (1 + v)e[p.sup.US] [S.sup.ill]. (1)

   The smuggler sells Sm illegal Mexican goods at price [p.sup.US] in the United States and converts the dollar-denominated proceeds on the black market to Mexican pesos, earning BMP v over the official exchange rate e.4 The expected costs of smuggling, E[C([S.sup.ill])], arise from the risk of being caught by U.S. Border and Customs Protection,5 as outlined in Equation 2:

   E[C([S.sup.ill])] = prob([S.sup.ill], H)F,

   with

   [partial derivative]prob([S.sup.ill],H)/[partial derivative][S.sup.ill] > 0, [[partial derivative].sup.2]prob] [([S.sup.ill]).sup.2] > 0, [partial derivative]prob([S.sup.ill],H)/[partial derivative]H > 0. (2)

   The smuggler is apprehended with probability prob([S.sup.ill], H) and faces the punishment cost F. We assume that the probability of apprehension is a convex function of the amount of illegal goods being smuggled and depends positively on the exogenous border enforcement, H; that is, the more officers patrolling the U.S.-Mexico border, the more likely smugglers are to be caught. If the smuggler is apprehended, she will be sentenced to prison. The cost of punishment F therefore represents the opportunity cost of lost labor income, (1 - u)w, during imprisonment. The higher the Mexican wages, w, and the lower the Mexican unemployment rate, u, the higher the cost of punishment, F:

   F = f[(1 - uw], with [partial derivative]f[(1 - u)w]/[partial derivative]u 0. (3)

   Using Equations 1-3, the expected nominal profit from smuggling illegal goods E([[pi].sup.ill]) is

   E ([[pi].sup.ill]) = (1 + v)[ep.sup.US] [s.sup.ill ] - prob ([S.sup.ill,] H)f[(1 - u)w]. (4.1)

   To study the determinants of smuggling illegal goods in real terms, we denominate the expected profit in Mexican goods by dividing Equation 4.1 by the Mexican price index, [p.sup.MEX]. Equation 4.2 shows the expected real profit from smuggling, whereby the real exchange rate is defined as e = [ep.sup.US]/[p.sup.MEX]:

   [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII](4.2)

   Real profit optimization with respect to the amount of smuggling, [S.sup.ill], yields the result that the marginal revenue from smuggling equals the marginal cost of smuggling:

   [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (5)

   Equation 5 determines how the optimal...