MODELING TRANSNATIONAL SURFACE FREIGHT FLOW AND BORDER CROSSING IMPROVEMENT DISSERTATION. the Degree Doctor of Philosophy in the Graduate

Transcription

1 MODELING TRANSNATIONAL SURFACE FREIGHT FLOW AND BORDER CROSSING IMPROVEMENT DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Timothy C. Matisziw ***** The Ohio State University 2005 Dissertation Committee: Professor Morton O Kelly, Adviser Professor Alan Murray Professor Mark McCord Approved by Adviser Geography Graduate Program

2 Copyright by Timothy C. Matisziw 2005

3 ABSTRACT Transportation costs are known to significantly impact the level of trade between regions. This is especially true for international truck-based movements requiring passage through border crossings. Movement through border crossings often involves assessment of additional costs such as tolls and transshipment fees, as well as the time consumed by the many operational and procedural difficulties encountered at these locations. The costs associated with negotiating international borders are relatively well known and many agencies and organizations are actively working to reduce them. Various solutions exist for effective improvement, involving both physical and policy related changes. Traditionally, improvements to border crossings have been justified based on their impact to a localized area of interest. However, this type of planning fails to consider how a facility s improvement might affect the transportation system as a whole. This dissertation addresses the impact that border crossing improvement may have on existing patterns of truck activity. Of particular interest is how improvements to crossings can initiate changes to flow patterns observed throughout the transportation system. To facilitate trade among regions, the primary goal for border improvement is to minimize the total transport cost associated with all international freight movements. ii

4 Given this goal, an optimization model, the Transshipment Facility Improvement Problem (TFIP), is proposed as a tool for modeling the effects of border crossing improvement on trucking between countries. In order to evaluate the impact of crossing improvement on the cost of systemwide truck transportation, the TFIP is applied to the case of North American (United States, Mexico, and Canada) trucking. This application consists of two challenges: (1) obtaining and modeling current trade volumes moved by motor carriers between countries, and (2) modeling the effects of border facility improvement on the cost of moving these volumes. A methodology is developed for meeting each of these goals. Application of these methodologies allows for current activity patterns to be modeled and analyzed, and the simulated impacts of various crossing improvement schemes on North American truck transport to be investigated. iii

5 To Kristin and The Mo iv

6 ACKNOWLEDGMENTS I would like to thank the Department of Geography at The Ohio State University for the support necessary to complete this dissertation. In particular I thank Morton O Kelly and Alan Murray for their guidance and encouragement as well as Mark McCord and Frank Croft for their valuable feedback on this document. Gratitude is also owed to the many family and friends who provided support during this process. v

7 VITA 1997 B.A. Geography, University of Missouri-Columbia 2000 M.A. Geography, University of Missouri-Columbia PUBLICATIONS Research Publications 1. O Kelly, M., T.C. Matisziw, R. Li, C. Merry, X. Niu Identifying Truck Correspondence in Multi-frame Imagery. Transportation Research Part C. 13, Matisziw, T. C. and J. D. Hipple Spatial Clustering and State/ County Legislation: The Case of Hog Production in Missouri. Regional Studies. 35(8), Major Field: Geography FIELDS OF STUDY vi

8 TABLE OF CONTENTS Page Abstract.. ii Dedication..iv Acknowledgments...v Vita...vi List of Tables.ix List of Figures...xii Chapters: 1. Introduction Problem Statement Modeling Assumptions/Limitations Organization of Dissertation 5 2. Issues in International Freight Movement Border Crossing as a Component of Transportation Cost NAFTA Trucking and Freight Transportation Regulatory and Institutional Obstacles to Trade Improvement Strategies and Potential Impacts Modeling Freight Movement Transshipment Modeling Trade Corridor Assessment Commodity Flow Analysis (CFA) Modeling Approaches to CFA Applied CFA General Flow Analysis Data Uncertainty and Estimation of Missing Data vii

9 4. Transshipment Facility Improvement The Need for Border Improvement Model Formulation Transshipment Facility Improvement Problem Reducing the Cost of Border Crossing Relationship to Other Models Problem Size Reduction Assessing Inter-border and O/D-border Movement North American Trucking Application Problem Scenario Flow Data Acquisition, Conversion, and Processing Transborder Surface Freight Database North America Trucking O-D Generation for Commodity Value Conversion of Commodity Value Flows to Truckloads Final North American O-D Summary Results Model Implementation North American Highway Network Modeling Existing Network Conditions Other Model Parameters Solving the Transshipment Facility Improvement Problem Application Results and Discussion Evaluation of Existing Conditions Examination of Crossing Improvement Scenarios Assessment of an Improvement Strategy Discussion Conclusion Summary of Work Future Directions.169 Appendix 172 Bibliography viii

10 LIST OF TABLES Table Page 2.1 Commodity value moved between: a.) The U.S. and Canada, b.) Canada and Mexico, and c.) Mexico and the U.S. ( ) Top ranked U.S.-Canada crossings for commodity flow (in dollars) Top ranked U.S.-Mexico crossings for commodity flow (in dollars) Number of trucks crossing U.S.-Canada border Number of trucks crossing U.S.-Mexico border Typical Transportation Problem input Modified input data to account for transshipment locations in TP model Inter-border Activity Matrix Summary of available North American surface freight data and O-D Dimension Summary of flow distribution models and parameters used on the 2003 North American commodity flow data Dimensions of final commodity value O-D matrix inbound loaded trucks crossing at U.S. border entry/exit locations Sample records from the U.S. imports from Canada dataset Sample average truck values for major Canadian border crossings computed from Canada flows to the U.S. and Mexico Percentage of total commodity value accounted for in the conversion to truckloads process ix

11 5.8 a.) Original and b.) Post-processed commodity flow values among NAFTA countries (in millions of dollars) Key to state/province abbreviations U.S. value and truck flows to Canada and Mexico Canada and Mexico value and truck flows to the U.S Mexico value and truck flows to the U.S. and Canada U.S. and Canada value and truck flows to Mexico Canadian value and truck flows to the U.S. and Mexico U.S. and Mexican value and truck flows to Canada Key to 67 border crossings used in the TFIP Summarized activity matrix for U.S.-Canadian border-with-canadian province truck movement (Top 25 crossings) Summarized activity matrix for U.S.-Mexican border-with-mexican state truck movement (Top 11 Mexican states) Summarized activity matrix for U.S.-Mexican border-with-u.s. state truck movement (Top 15 U.S. states) Summarized activity matrix for U.S.-Canada border-with-u.s. state truck movement (top 15 U.S. states, top 25 crossings) Summarized activity matrix for U.S.-Canada border-with-u.s.-mexico border truck movement TFIP objective values for 169 border improvement strategies TFIP solution times (in minutes) for 169 border improvement strategies Crossings along both borders selected for improvement Comparison of crossing selection order and crossing size (observed truck counts capacity ) at both borders. 148 x

12 6.10 Activity difference between the improved solution (p = 4 for both borders) and unimproved solution for activity between Canada and the Canadian border Activity difference between the improved solution (p = 4 for both borders) and unimproved solution for activity between Mexico and the Mexican border Activity difference between the improved solution (p = 4 for both borders) and unimproved solution for activity between U.S. and the Mexican border 160 xi

13 LIST OF FIGURES Figure Page 2.1 Typically series of border crossing procedures for U.S.-Mexico crossings Modal shares for: a.) U.S.-Canada trade, b.) Mexico-Canada trade, and c.) U.S.- Mexico trade ( ) Location of North American Highway Border Crossings Classifications of commodity flow analysis Transportation cost discounting example Destination-specific decay parameters for U.S. imports from Canada Destination-specific distance decay parameters for U.S. exports to Canada Origin-specific distance decay parameters for U.S. imports from Canada Conversion of commodity flow values into equivalent truckloads Converting commodity value into truckloads Components of cross-border flow Commodity value to truck conversion process Initial routing of the 2003 North American truck flows TFIP objective values for 169 border improvement strategies Routing and improvement solutions for p=4 at both borders Difference in truck flows = (improved truck flow - initial truck flows) xii

14 6.5 Difference in Canada-to-U.S. truck flows = (improved truck flow - initial truck flows) Difference in Mexico-to-U.S. truck flows = (improved truck flow - initial truck flows) Difference in U.S.-to-Mexico truck flows = (improved truck flow - initial truck flows) A.1 The Canadian Provinces.173 A.2 The United States A.3 The Mexican States A.4 Northeastern U.S.-Canada border crossings A.5 Midwestern U.S.-Canada border crossings A.6 Western U.S.-Canada border crossings..178 A.7 Western U.S.-Mexico border crossings. 179 A.8 Eastern U.S.-Mexico border crossings A.9 U.S.-to-Canada truck flow. 181 A.10 U.S.-to-Mexico truck flow. 182 A.11 Canada-to-U.S. truck flow A.12 Canada-to-Mexico truck flow A.13 Mexico-to-Canada truck flow A.14 Mexico-to-U.S. truck flow. 186 xiii

15 CHAPTER 1 INTRODUCTION Moving commodities across national borders can add significant costs to freight shipments between countries. These high transportation costs result from procedural, infrastructural, and political difficulties often encountered in the border clearance process (Beilock et al., 1996; Anderson and van Wincoop, 2001). Costs associated with passing through border gateways include congestion and transit delays that stem from the processing capacity of crossing checkpoints, increased security inspections, customs clearance, and drayage 1 (Beilock et al., 1996; Volpe Center, 2000; Lin and Lin, 2001). Many examples of this phenomenon can be readily identified world-wide (Ojala and Queiroz, 2003). The cost of moving across borders can significantly impact interaction between a country and its trading partners. As borders become a greater barrier to trade, affected nations are more likely to increase intranational trade at the expense of cross-border trade or to seek alternative trading partners (Helliwell, 1998; Hillberry, 1998, 2002; Coughlin and Wall, 2003; Fox et al., 2003; Coughlin, 2004). This is especially true when shipments must traverse multiple national borders when moving from an origin to destination. A prime example of such a situation is the case of surface freight movement 1 Drayage refers to the specialized movement of freight over short distances by local carriers as a portion of the total movement from an origin to a destination. 1

16 between Canada and Mexico. As countries enter into multinational trade relationships such as the North American Free Trade Agreement (NAFTA), an increasing amount of strategic planning is necessary to ensure that trade is facilitated as much as possible between the nations involved. One way of facilitating such interaction is to decrease the cost of transportation associated with moving between generators and recipients of freight. Reduction of these costs can help stimulate and increase trade between the countries involved (Fox et al., 2003; Haralambides and Londoño-Kent, 2004). As major sources of transit costs, border crossings are prime candidates for improvement and transport cost reduction (OFMO, 2002b). Improving the efficiency of border crossings to facilitate shipments of freight is not a simple task, especially when crossings handle freight shipments emanating from multiple countries. This problem gains greater significance when trade agreements mandate that all countries involved act cooperatively in decisions related to transnational transportation corridor planning and management. However, issues relating to the disbursement of funds to facilitate cross-border movement and the effect resulting plans may have on trade are complicated by the interest of the parties involved (Schneider, 2000). Thus, the tendency has been toward piecemeal planning efforts related to infrastructure improvement issues (Volpe Center, 2000; NYS DOT, 2003). A more integrative, strategic planning approach is certainly warranted. This is a vital concern especially for regional trading partnerships in which all participants should have adequate access to border gateways even if they lack the monetary resources necessary for their improvement and maintenance (Volpe Center, 2000). 2

17 1.1 Problem Statement Of interest in this dissertation is the development of a model to guide decisions on the allocation of border crossing improvements to facilitate transnational freight flows. In particular, the effect of border crossing improvement on the routing of truck movements passing through international borders is explored. Here, truck-based freight shipments between a set of countries separated by at most two border crossings are considered. Two national borders may need to be traversed in instances where truckbased trade between two countries must pass through a third country to complete a freight shipment. A scenario is assumed in which a limited number of capital improvement projects may be selected to improve a discrete number of border crossings on each border considered. Given these limitations and observed freight flows between the countries involved, the goal is to identify a set of crossings that, if improved, would best reduce total transportation costs within the transportation system. That is, improvements should be allocated to minimize the total transportation cost of all truck-based freight movements between all countries involved. An improvement to a crossing would translate into a transportation cost reduction benefiting any trip incorporating that crossing. The developed model is applied to the case of NAFTA trade between the United States (U.S.), Mexico, and Canada. This is a relevant application since there are many border crossings along the U.S.-Canada and U.S.-Mexico border that are candidates for substantial investment in facility improvement (NYS DOT, 2003). Investment in modifications to improve the performance and efficiency of crossings is not cheap, hence these investments must be prioritized (OFMO, 2002a). Any improvements to these 3

18 crossings will impact the transit prospects for all three countries. The model results show that improvements made to a set of facilities have consequences for all portions of the transportation network in terms of transportation cost, facility usage, and corridor choice. Since one goal of NAFTA is to promote interaction between these three nations, improvements need to be strategically allocated in order to minimize transit cost and foster trade. This application also presents an opportunity to evaluate the effects of crossing improvements on transit cost for shipments traversing multiple borders (Canada- Mexico) or a single border (Canada-U.S. or Mexico-U.S.) trade. 1.2 Modeling Assumptions/Limitations In the development of this planning model, there are a number of assumptions that must be made. First, it is assumed that all countries involved in planning for transnational surface trade are interested in cooperating to achieve an outcome that benefits the group as a whole. In this case, the desired outcome is to minimize the total transportation cost of transnational trade. This assumption requires that budgetary resources for border crossing and/or infrastructural improvements be used in ways that benefit everyone. Realistically, local, regional, and national political interests play a large role in dictating these types of decisions, especially when large investments are under consideration. Aside from these realities, the methods presented in this dissertation are consistent with strategic planning efforts underway (see Volpe Center, 2000; White House, 2002) and represent one way of viewing the problem at hand. Additionally, it is assumed that transportation flows between the countries involved in trade are known. Often countries are concerned with keeping detailed records on intranational trade and are less prepared to track the specifics of international 4

19 trade at the same level of detail. This problem stems from the fact that there is little standardization in how countries record their trade data. This is an issue with NAFTA trade data used in this dissertation, but every effort is made to ensure that data used are as commensurate as possible. Data are acquired as reported by various international agencies and appropriate estimation techniques are employed to resolve differences and missing data. 1.3 Organization of Dissertation This dissertation is organized as follows. Literature related to international freight movements and how they may be modeled is reviewed in Chapter 2 and 3. Of interest in Chapter 2 is the basic context for transnational flow analysis, the impacts of national borders on transportation costs, and the peculiarities of North American freight movement and trucking. Chapter 3 then reviews types of models useful in representing the role of border crossings in transportation networks as well as issues related to the modeling of freight flow. Chapter 4 focuses on planning issues in border facility improvement and details the motivation and purpose of this research. A network optimization model for assessing the impact of border crossing improvements on truck routing is also proposed. In Chapter 5 an application of the developed model to North American trucking is presented along with issues related to data acquisition and processing as well as commodity flow modeling. Application results are presented and discussed in Chapter 6. Finally, in Chapter 7 conclusions are drawn and future research directions are outlined. 5

20 CHAPTER 2 ISSUES IN INTERNATIONAL FREIGHT MOVEMENT 2.1 Border Crossing as a Component of Transportation Cost Though many factors are certainly responsible for the level of trade that occurs between two locations, national borders represent a considerable obstacle for international trade. Barriers to trade imposed by national borders include tariffs, added transportation costs, differentials in policy, institutional practice, regulations and laws, as well as those related to cultural differences such as language and customary practices (Wigle, 1992; Anderson and van Wincoop, 2001; Fox et al., 2003; Haralambides and Londoño-Kent, 2004). Anderson and van Wincoop (2001) estimate that the in the case of U.S.-Canadian trade, border related barriers can be equated to a tariff of 50% and if such barriers are removed, a trade increase of up to 79% could result. 2 For freight shipments, issues involved in crossing international borders translate into increased transportation costs. As stated in Boyer (1997), Fox et al. (2003), and Haralambides and Londoño-Kent (2004), given the shipping/handling fees paid at border crossings, a very small span of road can economically become the geographic equivalent of several hundred miles, and considering the time consuming delays encountered, a 2 There is much research aimed at quantifying the effects of borders on international trade. For example, McCallum (1995), Helliwell (1998), and Hillberry (1998, 2002) attempt to assess the impact the Canadian- U.S. border has on trade between Canadian provinces and U.S. states. 6

21 geographic equivalent of thousands of miles. This section examines how borders can contribute so significantly to freight transportation costs in greater depth. The first type of costs relate to the physical infrastructure surrounding border crossing locations. The major issue here is that international truck shipments are required to pass through crossings capable of handling the procedural aspects of customs, inspections, security, toll paying, etc. (and these are limited in number). As demand for international goods increases, more strain is placed on these facilities, each of which has physical limitations on the amount of traffic that can be efficiently handled. The act of moving freight across a border often consists of many separate steps. As is true with many types of network-based facilities, the volume of flow that can move through a crossing is dictated by the crossing function having the least capacity (Barton- Aschman and La Empresa, 1998b). Figure 2.1 list the steps that commercial traffic must complete when moving through the U.S.-Mexico border. Each of these stages has a capacity to process vehicles and a failure at any stage can result in a tremendous increase in the processing queue (Barton-Aschman and La Empresa, 1998b). Given there are relatively few crossing locations along national borders, they represent severe bottlenecks and chokepoints for freight traffic, resulting in much congestion and added trip delay (Volpe Center, 2000; Haralambides and Londoño-Kent, 2004). Some of the physical factors thought to contribute to congestion and delay at border crossings are the design and layout of the checkpoints, lack of adequate facilities to handle intermodal cargo transfers, number of open inspection and processing stations, limited capacity of road lanes on the approach (and departure) to the crossings, and inadequate capacity to process vehicles (Barton-Aschman and La Empresa, 1998b; Volpe 7

22 Center, 2000; Lin and Lin, 2001; Texas Transportation Institute et al., 2002; University of Arizona Office of Economic Development, 2003; Taylor et al., 2003; Haralambides and Londoño-Kent, 2004). Additionally, the topographic conditions surrounding border crossings can affect their ability to handle traffic effectively. For example, canyons surrounding the Nogales, Arizona crossing are known to hinder truck movements through the area (University of Arizona Office of Economic Development, 2003). These types of physical limitations can exacerbate traffic problems depending on the time of day (peaks in traffic flow) and existing operating conditions (Barton-Aschman and La Empresa, 1998b; Lin and Lin, 2001). 8

23 Southbound Process Regional Highways Northbound Process Regional Highways Local Access Roads Local Access Roads Export Declaration State DOT Inspection Export Inspection Exit Inspection Toll Collection Canine Inspection Physical Border Crossing Federal DOT Inspection Document Inspection Scales Primary Inspection Hazmat Inspection Secondary Selection X-ray Inspection Secondary Inspection Canine Inspection Exit Inspection Secondary Inspection Local Access Roads Primary Inspection Regional Highways Canine Block Inspection Physical Border Crossing Toll Collection Exit Inspection Secondary Inspection Secondary Selection Primary Inspection Document Inspection Compound Fee Booth Local Access Roads Regional Highways Figure 2.1: Typical series of border crossing procedures for U.S.-Mexico crossings* * Adapted from: Barton-Aschman and La Empresa (1998b) 9

24 Contributing to these infrastructural issues are those related to procedural aspects of border crossing. For instance, trucks must pass though customs and security inspections and processing of related documents and paperwork is time consuming. These times vary based on the level of traffic at the crossing, the type of cargo being processed, and the shipper moving the freight (Nozick et al., 1998). Compounding processing times are the often overlapping and redundant efforts of authorities at the border (Volpe Center, 2000; Ojala and Queiroz, 2003; University of Arizona Office of Economic Development, 2003; Haralambides and Londoño-Kent, 2004). It has been suggested that much of this problem can be attributed to poor interagency cooperation and inadequate information sharing (OFMO, 2002; University of Arizona Office of Economic Development, 2003). Other issues include insufficient hours of operation for brokerage services, improperly completed documentation, and multiply consigned loads that often require very time consuming secondary inspections (Taylor et al., 2003). In addition to these process related issues, poor staffing of facilities and a large emphasis on drug interdiction contribute to delays (Arizona-Mexico Commission, 1999; Taylor et al., 2003). It has been suggested that inefficiencies in crossing procedures stem from the fact that speed of shipping is not a priority of many of the agencies controlling the border (Barton-Aschman and La Empresa, 1998b; Johnson and Thomas, 2001). The U.S.-Mexico border is notorious for its many infrastructural and procedural difficulties. Haralambides and Londoño-Kent (2004) investigate truck-based movements between the U.S. (Chicago) and Mexico (Monterrey) through interviews conducted with individuals involved in shipping and trucking. Their results identify a staggering array of fixed costs and delays related to transborder movement. Aside from portions of the trip 10

25 not related to border crossing, they find that for southbound crossings, total costs for warehousing, inspection, classification, and verification of the freight, any unloading/ reloading, as well as drayage, can range between $287 to $636 and require 12.1 to 83.3 hours to complete. For northbound shipments, they find that the process can cost $150- $300 and involve hours to complete. Movement into the U.S. has proven more time consuming due to intensive searches for illegal substances and immigrants (OFMO, 2002b; Texas Transportation Institute et al., 2002). Fox et al. (2003) estimate that inefficiencies at the Mexico-U.S. border are comparable to a % tariff on the goods being shipped. The Office of Freight Management and Operations [OFMO] (2002a) estimates that costs due to delays amount to $40 million dollars per year at the Blaine, Washington border facility alone. Given an average per mile cost of trucking of one dollar per mile, these high border costs can be viewed as substantially increasing the geographic separation between two nations (Boyer, 1997; Fox et al., 2003; Haralambides and Londoño-Kent, 2004). In an evaluation of crossing facilities on the U.S.-Canada and U.S.-Mexico borders, the Texas Transportation Institute et al. (2002) found delays at the border average 16 minutes for inbound trips into the U.S. and around 8.1 minutes for outbound trips. Given the variability associated these delays, buffer time was computed to indicate the time that should be incorporated into a trucker s travel plan to keep them on schedule. It was determined that 23.3 minutes of buffer time should be incorporated into travel plans for trips exiting the U.S., while 43.3 minutes of buffer time should be incorporated for inbound trips. These time delays appear negligible to those indicated in Haralambides and Londoño-Kent (2004), but the difference is related to their 11

26 measurement. In the Texas Transportation Institute et al. (2002) study, delays were calculated for the total time involved in moving through the first inspection station in the importing country. Additionally, delays were measured for low flow volume conditions. Even in typical flow conditions, Taylor et al. (2003) show that a single problem in the crossing process can, in less than an hour, trigger a truck queue more than a mile long. Such a queue can often take almost four times as long to clear up as it took to develop. As shown in Haralambides and Londoño-Kent (2004), a bulk of the time contributing to transit delays comes from less obvious sources such as warehousing and transshipment. As previously shown, substantial variability in the time and cost incurred in passing through an international border can exist. This variability is difficult to predict and represents considerable risk to shippers when timely delivery of goods is a critical component of remaining competitive. The risk associated with the variable nature of border costs forces shippers to build extra time and cost into their shipping plans. Doing so involves needlessly tying up equipment and driving up freight cost (OFMO, 2002b; Fox et al., 2003; Taylor et al., 2003). Taylor et al. (2003) find that many shipping companies crossing the U.S.-Canadian border typically allocate one to two hours of time (four to six hours for time sensitive deliveries) when planning for cross border trips, regardless of current crossing conditions. Assuming an hourly cost of $150 for planned freight transit, the authors estimate that around two billion dollars per year is lost for planned border delays. Unplanned delays undoubtedly result in significantly higher costs. Overall, they find that uncertainty in the border crossing process costs carriers approximately $1.8 billion per year and costs the manufacturing industry nearly $2 billion per year. 12

27 The uncertainty in cross-border travel is especially concerning since increased transit time, inspections, unloading, and reloading, all increase the likelihood that the freight will become damaged or lost (Haralambides and Londoño-Kent, 2004). The costs associated with this uncertainty can cause freight rates to be considerably higher for international versus domestic shipments. Taylor et al. (2003) have found that shippers estimate U.S.-Canadian shipments can cost 10-35% higher than domestic shipments. Some of these costs can be attributed to market conditions in the trucking industry as well as traditional shipping practices, but Taylor et al. (2003) find variation in border wait times and costs are primary drivers of this rate differential. Removal or reduction of these border-induced transport costs has a high potential for increasing bilateral trade. Using the General Trade Analysis Project (GTAP) model and equating border inefficiencies to tariffs, Fox et al. (2003) show that abolishing or decreasing border barriers could increase NAFTA trade by over a billion dollars per year for the U.S. and over six billion dollars per year for Mexico. Recently, a software program known as Border Wizard has been developed by the General Services Administration (GSA), Customs and Border Protection, and the Immigration and Customs Enforcement agencies. The aim of this software is to simulate conditions at the nation s border crossings and to estimate the impact of changes (operational, infrastructural, procedural) on the performance of the crossing. So far, this software has only been applied as a justification tool for separate crossings and not for evaluation of the relationship between transportation activities at different crossings (Federal Highway Administration, 2004). 13

28 Increases in trade are particularly vital for countries whose economies depend heavily on trade with a single country (e.g., Mexico s trade with the U.S.). Hummels (2001) has shown for ocean freight, each additional day of shipping decreases the probability that the importer will trade with the exporter by one percent for all goods and by 1.5 percent for manufactured goods. A similar effect may indeed occur in the trucking industry, but this remains to be explored. Decreasing border related costs will undoubtedly reduce uncertainty encountered at the border and should act to facilitate trade, especially that depending on just-in-time delivery of merchandise (Fox et al., 2003). In the belief that reduction of costs associated with these border barriers is possible, this dissertation seeks to develop a means of modeling the effects of border improvement projects on transnational freight flow. Of particular interest is the case of North American trucking involving the United States, Mexico, and Canada. Here, two borders are present, one separating the U.S. and Mexico and the other separating the U.S. and Canada. The particularities of these trading relationships are discussed next. 2.2 NAFTA Trucking and Freight Transportation Since the North American Free Trade Agreement (NAFTA) began its implementation process in 1994, truck-based trade between Canada, Mexico, and the U.S. has steadily increased. Tables 2.1a-c detail the valuation of commodity trade among these three countries. The data presented in these tables are reflective of differences in how countries record their international trade statistics (see technical documentation in U.S. DOT et al., 2004). Regardless of these differences, it is clear that the U.S. imports greater commodity value from the other two countries than they do from their NAFTA 14

29 partners. In fact, for the period considered, the U.S was observed to import almost 30% more on average from Canada than Canada imported from the U.S. (Table 2.1a). Canada s imports from Mexico were nearly 55% greater than Mexico s imports from Canada, while U.S. imports from Mexico are approximately 10% higher than Mexico imports from U.S. Though these are the general trends, there have been a few years (e.g., ) where trade differentials have been minimal (Table 2.1b-c). From 1995 to 2003, the overall value of U.S.-Mexico and Mexico-Canada trade has more than doubled. The already strong trade between the U.S. and Canada also increased approximately 45%. The amount of commodity value transported by truck between the U.S. and Mexico has more than doubled over the eight year period analyzed while U.S.-Canada truck activity has increased almost 31%. The largest increase in commodity value transported was in Canada-Mexico trade where nearly a 263% increase was felt. Although this increase appears spectacular, overall commodity value moved by truck between these two countries only represents roughly five percent of U.S.-Mexican trade and less than four percent of U.S.-Canadian trade (U.S. DOT et al., 2004). Though the trading value between Mexico and Canada is low compared to their trade with the U.S., further increases are likely to be realized as refinements to NAFTA are made. Commodity movement by truck is the dominant mode of transit between Canada, Mexico, and the U.S. Tables 2.1a-c and Figures 2.2a-c illustrate the modal shares for commercial freight. In all three relationships detailed in these tables and figures, truck and rail based shipments account for the majority of the commodity value shipped with truck movements always remaining dominant. For Canada-U.S. trade (Figure 2.2a), all 15

30 four modes maintained a low level of variability from with water transit accounting for the lowest modal share and lowest variability. Trucking has maintained an average share of 67% while rail accounts for an 18% share throughout the period. It is interesting to note that in 1998, a slight upswing in rail s share can be observed coinciding with a noticeable decrease in the trucking share. Similar modal stability can be found in the case of U.S.-Mexico trade (Figure 2.2 c); however, with trucking accounting for 69% of the share on average while rail is responsible for transporting approximately 11% of the commodity value. It is important to note that in this case, water transport always accounts for a greater modal share than air for all of the years listed. The modal relationships in Canada-Mexico trade are also quite interesting (Figure 2.2b). In this trading situation, a pronounced spike in the trucking share is observed from 1995 to 1998 with a corresponding decrease in the rail share. After 1998, the rail share begins to increase, accounting for over 20% of the value moved between the two countries. The considerable decline of rail observed around 1998 and its subsequent upswing (also observable in Figures a and c), can likely be explained by mergers and marketing agreements between railways in the three nations occurring between 1997 and 1998 (Brooks, 2001). 16

31 Canada-U.S. Annual Trade Values Imports from U.S. "total in millions" 109, , , , , , , , ,903 Imports from U.S. "% truck" U.S. imports from Canada "total in millions" 145, , , , , , , , ,166 U.S. imports from Canada "% truck" Percent total value moved by truck Percent total value moved by air Percent total value moved by water Percent total value moved by rail a.) Canada-Mexico Annual Trade Values Imports from Mexico "total in millions" 3,900 4,426 5,071 5,178 6,419 8,125 7,827 8,108 8,688 Imports from Mexico "% truck" Mexico imports from Canada "total in millions" 1,374 1,744 1,968 2,290 2,949 4,017 4,235 4,480 4,121 Mexico imports from Canada "% truck" Percent total value moved by truck Percent total value moved by air Percent total value moved by water Percent total value moved by rail b.) Mexico-U.S. Annual Trade Values Imports from U.S. "total in millions" 53,806 67,437 82,001 93, , , , , ,363 Imports from U.S. "% truck" U.S. imports from Mexico "total in millions" 61,705 72,963 85,872 94, , , , , ,073 U.S. imports from Mexico "% truck" Percent total value moved by truck Percent total value moved by air Percent total value moved by water Percent total value moved by rail c.) Table 2.1: Commodity value moved between: a.) The U.S. and Canada, b.) Canada and Mexico, and c.) Mexico and the U.S. ( ) Source data: U.S. DOT et al. (2004) and BTS (2005a) 17

32 Modal Share Truck Air Water Rail Year a.) Modal Share Truck Air Water Rail Year b.) Modal Share Truck Air Water Rail Year c.) Figure 2.2: Modal shares for: a.) U.S.-Canada trade, b.) Mexico-Canada trade, and c.) U.S. - Mexico trade ( ) Source data: U.S. DOT et al. (2004) and BTS (2005a) 18

33 The massive amount of trade shipped via motor carrier between the three NAFTA countries does, however, have one thing in common, that freight must be moved through at least one border crossing located on the U.S.-Canada or U.S.-Mexico border. There are approximately 24 crossings on the U.S.-Mexico border and 79 on the U.S.-Canada border capable of handling commercial truck freight (BTS, 2005b). Figure 2.3 details all highway border crossing situated along the northern and southern borders of the U.S.. Higher resolution maps are available in the Appendix. As reported in the following tables, only a small minority of these crossings are actually utilized in the bulk of freight movement between NAFTA nations. Tables 2.2 and 2.3 list some of the top U.S.-Canadian and U.S.-Mexican border crossings ranked by commodity value moved through the crossing in 2002 (BTS, 2005a). Table 2.2 shows that trade at the U.S.-Canada border flows predominantly through seven facilities located in New York, Michigan, Washington, and North Dakota. However, notable exceptions are located in Montana, Maine, and Vermont. These high value crossings appear to be located in close proximity to larger Canadian metropolitan areas and represent logical choices for transshipment to neighboring U.S. urban areas. In 2002, the set of crossings reported in Table 2.2 accounted for approximately 57% of all crossborder North American trade. 19

34 Figure 2.3: Location of North American Highway Border Crossings Source data: Caliper Corporation (2002) 20

35 U.S.-Canada Crossing DETROIT, MI 85,467,798,515 79,761,907,359 85,062,396,228 BUFFALO-NIAGARA FALLS, NY 54,659,191,321 47,196,114,858 43,732,264,429 PORT HURON, MI 32,770,366,860 29,954,660,140 32,876,211,329 CHAMPLAIN, NY 15,326,229,720 14,271,253,312 13,254,819,948 ALEXANDRIA BAY, NY 11,980,953,478 10,615,147,714 10,686,707,111 BLAINE, WA 10,691,583,973 9,914,378,330 9,724,795,626 PEMBINA, ND 9,660,728,356 8,252,311,303 8,275,499,394 SWEETGRASS, MT 6,446,132,799 6,887,982,352 6,192,081,004 HIGHGATE SPRINGS, VT 6,968,045,788 4,989,115,011 4,298,970,427 PORTAL, ND 4,375,507,534 4,426,307,472 3,646,584,407 HOULTON, ME 1,848,567,298 1,765,905,884 2,085,282,934 CALAIS, ME 2,261,979,183 2,127,325,569 1,993,360,041 DERBY LINE, VT 2,034,062,027 1,955,105,607 1,934,423,305 SUMAS, WA 1,195,195,121 1,239,660,710 1,297,223,171 SAULT STE. MARIE, MI 1,315,563,499 1,325,539,199 1,296,898,362 % of Total N.A. Transborder Value Table 2.2: Top ranked U.S.-Canada crossings for commodity flow (in dollars) Source data: BTS (2005a) Table 2.3 shows that at the U.S.-Mexican border, seven border crossings account for the majority of cross-border commodity movements. Four of these are located in Texas, two in California, and one in Arizona. Other smaller crossing facilities exist in these states, though the commodity value involving them is considerably less. In sum, all thirty border crossings listed in Tables 2.2 and 2.3 account for nearly 97% of all value shipped across both borders via motor carrier. However, the top seven crossings along each border single handedly account of almost 90% of the total transnational commodity value movements. 21

36 U.S.-Mexico Crossing LAREDO, TX 60,046,648,803 55,298,351,032 55,801,348,663 EL PASO, TX 36,007,672,923 34,697,347,987 35,093,583,193 OTAY MESA STATION, CA 18,759,879,210 19,384,772,659 20,367,624,663 HILDAGO, TX 12,444,297,405 12,210,864,394 12,184,735,176 BROWNSVILLE-CAMERON, TX 11,307,208,193 10,138,558,613 9,455,249,911 NOGALES, AZ 11,046,139,242 9,963,888,935 8,750,090,264 CALEXICO-EAST, CA 8,237,902,729 7,207,360,138 8,278,428,327 EAGLE PASS, TX 4,134,910,638 3,599,087,641 3,560,212,224 DEL RIO, TX 2,386,699,160 2,375,056,035 2,669,692,753 SAN LUIS, AZ 1,225,634, ,126, ,243,904 TECATE, CA 920,176, ,093, ,062,252 DOUGLAS, AZ 934,398, ,294, ,828,181 PRESIDIO, TX 264,809, ,228, ,216,337 RIO GRANDE CITY, TX 234,900, ,318, ,631,527 ROMA, TX 108,253, ,981, ,253,817 % of Total N.A. Transborder Value Table 2.3: Top ranked U.S.-Mexico crossings for commodity flow (in dollars) Source data: BTS (2005a) Though the amount of commodity value moving through North American borders tends to provide a good indication of a crossing s utilization, it is also important to consider the number of trucks actually moving through border facilities. This is critical since commodity value and density vary across commodities making it difficult to assess actual border truck traffic based on estimates of overall commodity value alone (Figliozzi et al., 2001). Tables 2.4 and 2.5 show the number of trucks passing over the U.S.-Canadian and U.S.-Mexican border annually between 2000 and Also shown is the percentage of empty trucks involved in these tabulations. As presented, the data are ranked by total number of crossings observed in

37 For the U.S.-Canada border (Table 2.4), albeit ranked for a different year than Table 2.2, the ordering for the top seven crossings is somewhat comparable. That is, these crossings account for the most truck traffic. An exception to this ranking is Blaine, Washington which has a greater number of trucks passing over the border than Alexandria Bay, New York, but accounts for a lower total commodity value. Some insight to this shift can be gained through the evaluation of empty truck counts. Nearly 30% of all of the trucks moving through the Blaine crossing in 2003 were empty, which is far above the 11% empty truck average for all listed crossings. A similar observation may be made for Sumas, Washington. This is to say that although truck traffic is high at these crossings, there are also a high proportion of trucks not transporting anything of value. Perhaps the large proportion of empty vehicles observed at these locations is a result of backhauling or other fleet redeployment practices. Highgate Springs, VT, Sweet Grass, MT, Sault Ste. Marie, MI, and Portal, ND have the lowest numbers of truck crossings of those locations listed but have a comparatively high commodity value usage, indicating the smaller number of trucks transport relatively high value commodities. The relationship between truck activity and commodity value moved serves to illustrate how the mix of commodities shipped varies between crossings and the affect this has on their usage. Table 2.4 show that the fifteen crossings detailed account for between 87-90% of all commercial truck traffic at the U.S.-Canada border in the period reported. The top seven crossings on the U.S.-Mexico border (Table 2.5) also account for the majority of the truck traffic. At each crossing, it is obvious that an enormous number of empty trucks move across the border. In fact, on average, 36% of all of truck traffic at each crossing consists of empty trucks. This large proportion of empty trucks can likely 23

38 be attributed (in part) to drayage practices (discussed shortly) as well as trade imbalances between the U.S. and Mexico. These empty return trips are the most pronounced at Otay Mesa, CA, El Paso, TX, Brownsville, TX, and Tecate, CA. The fifteen crossings reported here account for over 98% of all cross-border truck trips at the Mexican border. 24

39 U.S.-Canada Crossing Total % Empty Total % Empty Total % Empty Total % Empty DETROIT, MI 1,654, ,722, ,668, ,588, BUFFALO-NIAGARA FALLS, NY 1,187, ,123, ,208, ,162, PORT HURON, MI 767, , , , CHAMPLAIN, NY 470, , , , BLAINE, WA 313, , , , ALEXANDRIA BAY, NY 200, , , , PEMBINA, ND 211, , , , SUMAS, WA 80, , , , CALAIS, ME 153, , , , DERBY LINE, VT 75, , , , HOULTON, ME 78, , , , HIGHGATE SPRINGS, VT 124, , , , SWEETGRASS, MT 145, , , , SAULT STE. MARIE, MI 49, , , , PORTAL, ND 65, , , , Total 5,577, ,048 5,902, ,243 5,999, ,181 5,763, ,519 % of all border crossings Table 2.4: Number of trucks crossing U.S.-Canada border Source data: BTS (2005b)

40 U.S.-Mexico Crossing Total % Empty Total % Empty Total % Empty Total % Empty LAREDO, TX 1,351, ,404, ,437, ,345, OTAY MESA STATION, CA 681, , , , EL PASO, TX 688, , , , HILDAGO, TX 332, , , , CALEXICO-EAST, CA 191, , , , NOGALES, AZ 254, , , , BROWNSVILLE-CAMERON, TX 299, , , , EAGLE PASS, TX 106, , , , DEL RIO, TX 61, , , , TECATE, CA 63, , , , SAN LUIS, AZ 30, , , , RIO GRANDE CITY, TX 21, , , , DOUGLAS, AZ 29, , , , ROMA, TX 12, , , , PRESIDIO, TX 8, , , , Total 4,134,589 1,823,258 4,223,126 1,883,025 4,369,679 1,878,004 4,232,987 1,664,123 % of all border crossings Table 2.5: Number of trucks crossing U.S.-Mexico border Source data: BTS (2005b)